LIPOPEPTIDE-COATED IRON OXIDE NANOPARTICLES AND ENGINEERED Qβ
VIRUS LIKE PARTICLES AS POTENTIAL GLYCOCONJUGATE-BASED SYNTHETIC
ANTICANCER VACCINES
By
Suttipun Sungsuwan

A DISSERTATION
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of
Chemistry − Doctor of Philosophy
2017

ABSTRACT
LIPOPEPTIDE-COATED IRON OXIDE NANOPARTICLES AND ENGINEERED Qβ
VIRUS LIKE PARTICLES AS POTENTIAL GLYCOCONJUGATE-BASED SYNTHETIC
ANTICANCER VACCINES
By
Suttipun Sungsuwan
Due to genetic and/or epigenetic alteration, glycan markers on tumor cells structurally
differ from those on the normal cells. These unique glycans, termed tumor associated
carbohydrate antigens (TACAs), have been utilized to educate the immune system to specifically
recognize and eliminate cancer cells, a concept known as cancer immunotherapy or anticancer
vaccine. The major challenge of developing an anti-TACA vaccine is the low immunogenicity of
TACAs as they are self-antigens and not sufficiently immunogenic when administered alone.
In chapter 1, iron oxide magnetic nanoparticles (NPs) have been evaluated as carriers for
glycoconjugate-based anticancer vaccines. With their high biocompatibilities and large surface
areas, magnetic NPs were synthesized for TACA delivery. The magnetic NPs were coated with
phospholipid-functionalized

TACA

glycopeptides

through

hydrophobic−hydrophobic

interactions without the need for any covalent linkages. Multiple copies of glycopeptides were
presented on NPs, potentially leading to enhanced interactions with antibody-secreting B cells
through multivalent binding. Mice immunized with the NPs generated strong antibody responses,
and the glycopeptide structures important for high antibody titers were identified. The antibodies
produced were capable of recognizing both mouse and human tumor cells expressing the
glycopeptide, resulting in tumor cell death through complement-mediated cytotoxicities. These
results demonstrate that magnetic NPs can be a new and simple platform for multivalently

displaying TACA and boosting anti-TACA immune responses without the need for a typical
protein carrier.
Besides iron oxide magnetic nanoparticles (NPs), bacteriophage Qβ is another excellent
immunogenic carrier able to break self-tolerance to induce strong antibody response against
TACA. One potential drawback of bacteriophage Qβ is its strong immunogenicity, which also
induces a strong antibody response against itself. This unwanted anti-carrier immune response
can lead to carrier-induced epitopic suppression (CIES), which can limits the full potential of the
Qβ in inducing maximum desired immune response against TACA.
In chapter 2, Qβ viral capsid was engineered to reduce the unwanted immune response
against the carrier protein, thus refocusing the immunity towards generating higher potency of
desired immune response against TACAs. Non-native disulfide bonds were introduced into the
capsid to enhance the stability of the engineered capsids. Our results showed that the new Qβ
mutants can reduce the unwanted anti-carrier immune response, yet enhance the wanted titers of
antibodies against TACA. The approaches presented in this study provide a fundamental
implication for rational design of engineered virus-like-particle-based carrier to maximize the
potency of vaccines targeting TACA expressing cancers as well as other diseases.

To my beloved family
and
His Majesty King Bhumibol Adulyadej.

iv

ACKNOWLEDGEMENTS

The way led to the completion of this dissertation would be more difficult or would have
not been accomplished without the support from many people. I would like to express my respect
and appreciation to these people who guided and helped me along the way. The most influential
person of my dissertation was my advisor, Professor Xuefei Huang, who generously gave me his
invaluable guidance, supports, supervision and kind encouragement throughout this study. Even
though I disappointed him many times to get good results or make experiments work, he never
failed to inspire and challenge me to experience many of new research areas I had never been
exposed to, which drove my perspective and capability in conducting research to another level. I
would also like to thank all my guidance committee members, Dr. Heedeok Hong, for his helpful
suggestions involving molecular biology aspects and his kind permission to let me use
instruments in his lab; Dr. Kevin Walker, for his assistance, good suggestions and kindness, and
Dr. Robert Abramovitch for his helpful suggestions and kind collaboration in anti-M.
tuberculosis vaccine project.
I would like to thank all instrumental specialists who assisted me to run all experiments
involving sophisticate analytical instruments. My special thanks are to Dr. Dan Holmes who
kindly trained me to set up and run all kinds of NMR experiments; Professor Dan Jones, Lijun
Chen, Scott Smith and Tony Schilmiller, who trained me to run high-end mass spectrometers and
assisted me to process all data; Dr. Xudong Fan, who helped me run TEM and made all the
images look fantastic and Dr. Xianshu Jin, who kindly helped me run and analyzed X-ray
crystallography of Qβ VLPs.

v

My great appreciation is also expressed to fellowships from Royal Thai Government,
graduate school and department of chemistry in Michigan State University for opportunities and
all supports throughout my study in doctoral degree.
I am indebted to all of my friends and colleagues from Huang group, especially Dr.
Zhaojun Yin, who patiently spent his time mentoring me to develop my research knowledge and
skills in immunology. I would not come this far without him. Besides, I thank Moe, Hovig,
Herbert, Philip, Jingguang, Xuanjun, Qian, Shuyao and Mehdi for their invaluable assistance in
biological experiments. I also thank Vivian, Bo, Keisuke, Steve, Weizhun, Sherif, Kedar,
Changxin, Peng, Jicheng, Zeren, Jia for introducing me to the beauty of carbohydrate synthesis
and great assistance in my chemical synthesis parts. These people well demonstrated how the
hard work pays off. In addition to research assistance, I have deep appreciation for their warm
friendship and cheering me up when I am discouraged. They helped me expand my perspective
tremendously about their interesting cultures, personalities and positive attitudes.
Finally, I would like to express my deepest gratitude to my family and my beloved
girlfriend, Cho, for their unconditional love, care, understanding and encouragement through the
duration of my research.

Thank you.
Suttipun Sungsuwan

vi

TABLE OF CONTENTS

LIST OF TABLES ...........................................................................................................................x
LIST OF FIGURES ....................................................................................................................... xi
LIST OF SCHEMES ................................................................................................................... xix
KEY TO ABBREVIATIONS .......................................................................................................xx
CHAPTER 1 : Lipopeptide-Coated Iron Oxide Nanoparticles as Potential GlycoconjugateBased Synthetic Anticancer Vaccines1 ............................................................................................1
1.1 Introduction .............................................................................................................................1
1.1.1 Cancer immunotherapy ...............................................................................................1
1.1.2 Mechanism behind immunity .....................................................................................3
1.1.3 Protein post-translation modification by glycosylation ..............................................7
1.1.4 Mucin1 ......................................................................................................................8
1.1.5 Aberrant glycosylation in cancer cells ......................................................................11
1.1.6 Evidences supporting MUC1 based vaccine.............................................................14
1.1.7 Anti-MUC1 vaccine development ............................................................................16
1.1.8 Particulate Vaccine ...................................................................................................18
1.1.9 Physical properties of a particulate vaccine determine the immune response
profile. ....................................................................................................................20
1.1.10 Anti-MUC1 particulate vaccines ..............................................................................21
1.1.11 Superparamagnetic iron oxide nanoparticle: SPION ................................................25
1.1.12 Self-assembly of amphiphilic-molecule coated iron oxide nanoparticles ................26
1.2 Results and discussion ..........................................................................................................27
1.2.1 Synthesis of magnetic NPs coated with MUC1 lipopeptides and lipoglycopeptides ............................................................................................................27
1.2.2 In vitro activation of dendritic cells and detection of NP draining into local
lymph nodes in vivo. .................................................................................................33
1.2.3 Immunization with MUC1 coated NPs elicited strong anti-MUC1 IgG
responses. ..................................................................................................................36
1.2.4 The antibodies from immunized mice showed binding and complement
dependent cytotoxicity against MUC1-expressing tumor cells. ...............................39
1.2.5 Discussion .................................................................................................................41
1.3 Conclusions ...........................................................................................................................43
1.4 Materials and methods ..........................................................................................................45
1.4.1 Materials and instrumentation...................................................................................45
1.4.2 Synthesis of Fmoc-pTn-Thr-OH ...............................................................................46
1.4.3 Synthesis of MUC1 1 and Tn-MUC1 2-4 .................................................................50
1.4.4 Purification and characterization of (glyco)-peptides 1–4 ........................................51
1.4.5 Synthesis of lipo-(Tn)-peptide (DPPE-MUC1 5 and DPPE-Tn-MUC1 6-8) ...........56
1.4.6 Purification and characterization of lipo-(glyco)-peptide 5–8 ..................................56

vii

1.4.7
1.4.8

Preparation of iron oxide NPs (OA-IONPs) .............................................................61
The number of OA-IONP nanoparticle was estimated by TEM and TGA
analysis. ....................................................................................................................61
1.4.9 Preparation of NP5-9 ................................................................................................62
1.4.10 Verification of the glyco-lipopeptide (DSPE-MUC1(Tn) 6, 7 and 8 on the
coated nanoparticles ..................................................................................................63
1.4.11 Quantification of the lipopeptide (DSPE-MUC1) on the coated nanoparticles ........65
1.4.12 The ratio of DPPE-MUC1 and DSPE-PEG coated on each nanoparticle
determined by Malachite Green phosphate assay .....................................................65
1.4.13 Elemental analysis for estimation of the number of DPPE-MUC1 molecules
coated on a single nanoparticle .................................................................................65
1.4.14 Bone marrow derived dendritic cell culture..............................................................66
1.4.15 Flow cytometry of dendritic cellular marker expression ..........................................66
1.4.16 Histology of the NPs in the targeted lymph node .....................................................67
1.4.17 Mouse immunization ................................................................................................67
1.4.18 ELISA ....................................................................................................................67
1.4.19 Cell culture ................................................................................................................68
1.4.20 Flow cytometry analysis ...........................................................................................68
1.4.21 Complement dependent cytotoxicity ........................................................................69
APPENDICES ............................................................................................................................70
APPENDIX A: Quantification of the lipopeptide (DSPE-MUC1) on the coated
nanoparticles .............................................................................................................71
APPENDIX B: NMR spectra................................................................................................75
REFERENCES ...........................................................................................................................81
CHAPTER 2 : Engineered Virus-Like Particle Qβ as a Novel Carrier for TACA-Based
Anticancer Vaccines ......................................................................................................................96
2.1 Introduction ...........................................................................................................................96
2.1.1 Virus-like particle as a vaccine carrier......................................................................96
2.1.2 Bacteriophages ..........................................................................................................97
2.1.3 Bacteriophage Qβ .....................................................................................................97
2.1.4 Bacteriophage Qβ VLP in vaccine applications .....................................................100
2.1.5 Qβ VLP as a carrier for TACA-based anti-cancer vaccines. ..................................108
2.1.6 Carrier-Induced Epitopic Suppression (CIES) in Qβ..............................................116
2.2 Results and discussion ........................................................................................................119
2.2.1 B cell epitope prediction .........................................................................................119
2.2.2 Improve stability of Qβ VLP ..................................................................................129
2.2.3 Immunization study ................................................................................................138
2.2.4 Binding of the elicited antibody against tumor cells ..............................................142
2.2.5 Tumor challenge .....................................................................................................145
2.3 Conclusions .........................................................................................................................150
2.4 Future perspective ...............................................................................................................151
2.5 Materials and methods ........................................................................................................155
2.5.1 Site-directed mutagenesis of Qβ VLPs ...................................................................155
2.5.2 Qβ viral capsid protein expression and purification ...............................................157
2.5.3 Synthesis and characterization of Qβ or mQβ conjugates36 ...................................159

viii

2.5.4
2.5.5
2.5.6

Size exclusion chromatography (SEC) ...................................................................159
Non-denaturing agarose gel ....................................................................................160
Thermal stability measurement of viral capsid by temperature varied UV-Vis
spectroscopy............................................................................................................160
2.5.7 Dynamic light scattering (DLS) and transmission electron microscopy (TEM) ....161
2.5.8 Immunization studies36 ...........................................................................................161
2.5.9 Enzyme-linked immunosorbent assay (ELISA) .....................................................162
2.5.10 Cell cultures ............................................................................................................163
2.5.11 Flow cytometry experiment ....................................................................................163
2.5.12 Anti-tumor immunoprotection (Tumor challenge) .................................................163
2.5.13 Liquid chromatography–mass spectrometry (LCMS) ............................................164
2.5.14 Transmission electron microscopy (TEM) Images .................................................164
2.5.15 Synthesis of Tn1 and Tn2 .......................................................................................165
2.5.16 Synthesis procedure ................................................................................................166
APPENDICES ..........................................................................................................................171
APPENDIX A: Size Exclusion Chromatograms ................................................................172
APPENDIX B: Liquid chromatography–mass spectra .......................................................177
APPENDIX C: NMR spectra..............................................................................................184
REFERENCES .........................................................................................................................219

ix

LIST OF TABLES

Table 1.1: Hydrodynamic diameters and zeta potentials of the NP vaccines in PBS ...................32
Table 2.1: Sequences of Qβ specific peptides used for re-stimulation of splenocytes from
the vaccinated mice.22 ..................................................................................................................103
Table 2.2: Qβ mutants reported that assemble to form the capsid. .............................................123
Table 2.3: Qβ mutants that fail to assemble into the VLP. .........................................................125
Table 2.4: Physical characteristics of Qβ mutants. .....................................................................126
Table 2.5: The average number of Tn1 conjugated on each capsid of Qβ particle and yield
of Qβ-Tn1 conjugate. [% addn Tn = (Tn1/subunitmQβ − Tn1/subunitwtQβ) × 100 /
Tn1/subunitwtQβ] ...........................................................................................................................136
Table 2.6: Physical characteristics of Qβ-Tn1 conjugates. .........................................................137
Table 2.7: Primers used in the construction of mutant Qβ VLPs ...............................................156

x

LIST OF FIGURES

Figure 1.1: A cartoon showing two types of humoral immune activation by a tumor
antigen.Upper panel – T cell-independent B-cell activation: the multivalent antigen
crosslinks B cell receptors without the help from T cells leading to IgM secretion. Lower
panel − T cell-dependent B-cell activation: In addition to B-cell activation by direct antigen
recognition, the antigen can be taken up by antigen presenting cells such as dendritic cells,
which subsequently present the antigen fragment to activate helper T cell (Th cell). The
activated Th cell releases cytokines to induce B cells to undergo Ig-isotype switching from
IgM to IgG. The figure is adapted and reproduced from reference14. .............................................4
Figure 1.2: Illustration showing the process of cell-mediated immunity. a) The antigenpresenting cell uptakes and processes an antigen into a short fragment (CD8+ T-cell
epitope). The digested fragment is loaded onto MHC class I and presented to a CD8+ T
cell. The activated CD8+ T cell then proliferates and becomes cytotoxic T cells, which will
be able to kill the corresponding pathogens or cancer cells. b) The processed antigen
fragments that are loaded onto MHC class II will be presented to CD4+ T cell. The
activated CD4+ T cells will release cytokines in T-cell dependent B cell activation resulting
in IgM-to-IgG isotype switching and the generation of IgG secreting plasma cells and
memory B cells. The figure is reproduced with permission from reference17. ................................6
Figure 1.3: a) C-terminal (MUC1-C) and N-terminal subunit (MUC1-N) are connected by
non-covalent interaction after auto-proteolytic cleavage. b) C-terminal MUC1 (MUC1-C)
are composed of a cytoplasmic domain (CD), a transmembrane domain (TM), and an
extracellular N-terminal domain (ED). N-glycan on Asp-36 can cis-bind to receptor
tyrosine kinases (RTKs) after loss of polarity. c) The N-terminal subunit (MUC1-N) will
dissociate and leave the C-terminal subunit (MUC1-C) due to tumorigenesis on cancer
cells. d) Cellular alteration due to tumorigenesis causes loss of polarity or delocalization of
the remaining C-terminal subunit to entire cell surface, instead of specific presentation on
the apical side. The C-terminal subunits form cis-interactions with receptor tyrosine kinases
(RTKs) causing amplification of the aberrantly overexpression of MUC1 on cancer cells.
This figure is adapted and reproduced with permission from reference25. ......................................9
Figure 1.4: Variable number tandem repeats (VNTR) of twenty amino acids in N-terminal
subunit (MUC1-N). 5 potential amino acids (red letters) are potentially subjected to Oglycosylation. This figure is adapted and reproduced with permissions from references21, 25. .....10
Figure 1.5: The process of O-glycosylation begins with the addition of a GalNAc moiety
onto a serine or threonine residue in a polypeptide. The glycosylation will then be extended
from the starting GalNAc unit by T-synthase to core 1 – core 4 structures. This figure is
adapted and reproduced with permission from reference34b. .........................................................12

xi

Figure 1.6: The glycosylation enzyme T-synthase in cancer cells is malfunctioning due to
improper enzyme folding caused by the absent of Cosmc chaperon in the endoplasmic
reticulum in cancer cells. The malfunctioning T-synthase in cancer cells leads to the
aberrant glycosylation in glycopeptide MUC1. This figure is adapted and reproduced with
permission from reference34b. ........................................................................................................13
Figure 1.7: The structure of TACAs; Tn, T and their sialiated products; α(2-3)ST, α(26)STn..............................................................................................................................................14
Figure 1.8: Representative structures of fully synthetic three-component compounds
composed of B cell epitope from MUC1, Th epitope from polio virus (PV) and TLR1 and 2
agonist, Pam3CysSK4, or TLR2 and 6 agonist, Pam2CysSK4. This figure is adapted and
reproduced with permission from reference75................................................................................23
Figure 1.9: Synthesis of the hydrophobic OA-IONPs by the thermal decomposition
method, and monolayer self-assembly coating of the NPs by phospholipid functionalized
MUC1 or MUC1(Tn) glycopeptide. ..............................................................................................31
Figure 1.10: TEM images and hydrodynamic diameters from DLS a, c) OA-IONPs; b, d)
NP-5. ..............................................................................................................................................31
Figure 1.11: a) MALDI-TOF mass spectrum of NP-5 coated with lipopeptide 5 ([M+H]+ =
2662) and DSPE-PEG (top spectrum); and NP-9 coated with DSPE-PEG only (bottom
spectrum). b) SDS-PAGE of DPPE-MUC1, NP-PEG (NP-9), and NP-MUC1 (NP-5). The
gel was visualized through silver staining. ....................................................................................33
Figure 1.12: a) Flow cytometry results showing the expression of cellular markers of
activation state (CD40, CD80, CD86 and MHCII) of BMDC after incubation with NP-PEG
(NP-9) (red line), or NP-PEG (NP-9) + MPLA (blue line). Confocal images of BMDC
incubated with b) PBS and c) NP-9 (FITC) + MPLA. Histology of sections from d)
axillary (local) lymph nodes, and e) inguins (distant) lymph node, stained by Prussian blue.......35
Figure 1.13: Microscopic images of Prussian blue staining of BMDC after incubation with
NP-9. Left) only dendritic cells; Middle) dendritic cells incubated with NP-9 (50 μg) in
PBS 12 hrs.; Right) dendritic cells incubated with NP-9 (50 μg) and MPLA (2 μg/mL) in
PBS 12 h. .......................................................................................................................................36
Figure 1.14: a) Anti-MUC1 and anti-Tn-MUC1 antibody titers from individual mouse
(n=5), collected on day 35 after immunization with NP-MUC1 (NP-5) and NP-MUC1(Tn)
(NP-6, NP-7 and NP-8) vaccines, compared with soluble MUC1 peptide 1 and lipoMUC1-peptide 5. The anti-MUC1 antibody titers were determined by ELISA coated with
corresponding (glyco)peptides 1-4. b) IgG antibody titer from individual mouse, collected
on day 35 after immunization with NP-MUC1 (NP-5), against MUC1 peptide 1 and NP-9
c) IgM/IgG antibody response determined by ELISA at 3200-fold dilution of serum from
mice immunized with different vaccines. d) IgG isotypes of antibody response determined
by ELISA from mice immunized with various vaccines. ..............................................................38

xii

Figure 1.15: Cross-recognition of various MUC1 glycoforms by sera from mice
immunized with NP-5 – NP-8. ......................................................................................................39
Figure 1.16: Flow cytometric analysis of the binding of antibodies induced by various
constructs to a) MUC1-Ag104 cells and c) MCF-7. MTS assay analysis of complementdependent cytotoxicity of antibodies induced by various vaccines on b) MUC1-Ag104 cells
and d) MCF-7. (** P < 0.05, *** P < 0.005,)................................................................................40
Figure 1.17: Flow cytometry showing the specific binding of anti-MUC1 antibody from
immunized mice a) against wild type Ag104 (Ag104(wt)) and MUC1 transfected Ag104
cells (Ag104(MUC1)); b) against MUC1 transfected Ag104 cells (Ag104(MUC1)) and
endothelial cells (EA.hy926). ........................................................................................................41
Figure 1.18: Synthesis of Fmoc-pTn-Thr-OH. ...........................................................................46
Figure 1.19: HPLC chromatogram and MALDI-TOF mass spectrum of the MUC1 peptide
1, and the MUC1 glycopeptide 2, 3 and 4. ....................................................................................52
Figure 1.20: HPLC chromatogram and MALDI-TOF mass spectrum of the lipopeptide 5,
and lipo-glycopeptide 6, 7 and 8. ...................................................................................................57
Figure 1.21: TGA curve of OA-IONP. .........................................................................................62
Figure 1.22: MALDI-TOF mass spectrum of glyco-lipopeptide coated OAIONP; NP-6,
NP-7, NP-8 indicate the present of the glyco-lipopeptide on each nanoparticle. The
clustered peaks in the base line represent the coating DSPE-PEG. ...............................................63
Figure 1.23: Quantification of the lipo(glyco)peptide on the coated nanoparticles. ....................71
Figure 1.24: 1H NMR spectrum of SI-3. ......................................................................................75
Figure 1:25: 1H NMR spectrum of SI-4. ......................................................................................76
Figure 1.26: 1H NMR spectrum of SI-5. ......................................................................................77
Figure 1.27: 1H NMR spectrum of SI-7. ......................................................................................78
Figure 1.28: 1H NMR spectrum of SI-8. ......................................................................................79
Figure 1.29: 1H NMR spectrum of Fmoc-pTn-Thr-OH. ............................................................80
Figure 2.1: Qβ protein structure (PDB-ID: 1QBE), a.) Qβ subunit protein with secondary
structure domains; b,c) The alignment of the dimer subunit and all lysine residues; d) The
organization of fivefold- and quasi-sixfold units to form icosahedral shape with
triangulation number (T) = 3. The green residues are cysteines at position 74 and 80, which
form an intra-subunit disulfide bond..............................................................................................99

xiii

Figure 2.2: Qβ specific T cell responses were measured from level of cytokines secreted
from splenocytes of HA conjugated Qβ immunized mice with peptide pools spanning Qβ
capsid protein regions. Each bar represents the total cytokine response to each peptide pool
and the colored boxes represent level of each specific cytokine. Each peptide pool is
composed of 5 peptides fragments that have the overlap sequences as listed in Table 2.1.
The figure is reproduced from reference22. ..................................................................................102
Figure 2.3: X-ray crystal structure of Qβ subunit (1qbe). The red and blue colored regions
display the most probable Th epitopes. Red region = Qβ41-71, Blue region = Qβ101-132...............104
Figure 2.4: Top panel: Branched oligomannose glycans were conjugated via CuAAC
reaction on the wild-type Qβ, mutant QβK16M or QβHPG, where the most reactive lysine
at position 16 was replaced by an unnatural amino acid homopropargyl glycine. Bottom
panel: Synthesis of QβHPG glycoconjugates QβHPG-Man8 (11) and QβHPG-Man8/Man9
(12). The figure is reproduced with permission from reference22. ..............................................106
Figure 2.5: Synthesis of Qβ-triazole-Tn via CuAAC reaction. The reaction condition can
be adjusted to provide a variable number of Tns (78, 150 and 340 Tns) attached on the viral
capsid. This figure is adapted and reproduced with permission from reference35. ......................112
Figure 2.6: a) a table showing characteristic details of the vaccine compound with varied
Tn density used in 6 groups to investigate the effect of antigen density on the viral capsid.
b) ELISA results of IgG and c) IgM antibodies from 6 groups of immunized mice at 1/6400
dilution. This figure is adapted and reproduced with permission from reference35.....................113
Figure 2.7: a) Vaccine constructs Qβ-Tn 4 and Qβ-Tn 5. b,c) IgG titers elicited from the
vaccine constructs against Tn or triazole. The increased number of attached Tn induced
lower anti-Tn antibody titers due to suppression from increased anti-triazole immune
response. d) Specific recognition against Tn-expressing cancer cells of the elicited
antibodies from Qβ-Tn 1 and Qβ-Tn 6. e) Vaccine constructs Qβ-Tn 6 where the triazole
linker was replaced with low immunogenic alkyl linker. f) anti-Tn antibody titers elicited
from Qβ-Tn6. The IgG titers became higher compared with those from Qβ-Tn 4 and Qβ-Tn
5. This figure is adapted and reproduced with permission from reference36. ..............................115
Figure 2.8: Antibody titers against D2 peptide (attached antigen) and Qβ VLP (carrier)
elicited from Qβ primed- or naïve mice after 1st, 2nd and 3rd vaccination. The result suggests
that the higher density of D2 on the Qβ helped reduce the suppression from CIES. This
figure is adapted and reproduced with permission from reference37. ..........................................118
Figure 2.9: a) Eight of synthetic 30-amino-acid peptides that overlapped sequence by 15
amino acids covering the entire amino acid sequence of Qβ capsid protein. b) ELISA result
of peptide scanning experiment showing the binding of the peptides fragments with the
anti-wtQβ IgG antibodies. The synthetic peptides were coated on the ELISA plate. The
dilution of serum (1/64000 dilution) from wtQβ-immunized mice was added to test
recognition towards each peptide fragments. Group (-) is a negative control group where
only PBS was used in coating process. ........................................................................................120

xiv

Figure 2.10: Discontinuous B cell epitope prediction by DiscoTope 2.0 server40 showing in
electron cloud surface is overlaid over 3D structure of Qβ capsid protein. The red areas
represent protein fragments that obtain high scores from the prediction.....................................122
Figure 2.11: A graph showing solvent accessible surface area (SASA) of each amino acid
residue in representative chain B of Qβ capsid protein (1qbe). The figure and data were
obtained from VIPERdb (http://viperdb.scripps.edu).41 ..............................................................122
Figure 2.12: Electrophoretic mobility of Qβ whole capsids by native agarose gel. The
samples (~30 μg of each capsid protein) were loaded into 0.7% agarose gel in PBS with
SYBR Safe DNA gel strain as a straining reagent for the encapsulated RNA. The
electrophoresis was performed in TEA buffer at 4°C for 4 hours. Top panel) The
encapsulated RNA strained in the capsids was detected by UV light. Middle panel) The
capsid proteins were detected by Coomassie staining. Bottom panel) Overlaying the two
panels confirms the presence of the encapsulated RNA in the mQβs. ........................................128
Figure 2.13: X-ray crystal structure of wtQβ showing a) distances between β-carbon of
residues involving disulfide formation; b) disulfide bond networks from native disulfide
bonds between C74 and C80 (green residues) in wtQβ and expected non-native disulfide
bonds in mQβ A40C/D102C (yellow residues). ..........................................................................131
Figure 2.14: a) Size exclusion chromatograms of wtQβ (red) and mQβs, A38K(yellow),
A38K/A40C/A102C (green), A40C/D102C (blue); b) TEM images of wtQβ and mQβs. .........131
Figure 2.15: a) SDS-PAGE of the viral capsids in non-reductive (oxidative) condition
(Left) and reductive condition (right). .........................................................................................133
Figure 2.16: Thermal stability of mQβs determined by UV absorption at λ = 310 nm at
increasing temperature. ................................................................................................................134
Figure 2.17: Conjugation reaction between NHS-Tn1 with the various mQβs. ........................136
Figure 2.18: X-ray crystal structure of wtQβ showing the hydrogen bond interaction (solid
blue line) between the carboxyl group on the side chain of D102 and the amino group on
the side chain of K13(distance = 3.145 Ã…). .................................................................................138
Figure 2.19: ELISA results of post-immunized sera (day 35) from groups of mice (n=5)
vaccinated with variant mQβ-Tn1. a and b) Anti-Tn1 titers of the post-immunized sera
presented in linear and log scale, respectively. The statistical significance of differences
between a mQβ and wtQβ was determined by the Student t test (** р < 0.01; *** р < 0.001;
**** р < 0.0001) c) OD450 from the ELISA result of the post-immunized sera at 1/819200
dilution against BSA-Tn1. d) OD450 from the ELISA result of the post-immunized sera at
1/1638400 against the corresponding carrier capsids. The statistical significance of
differences between a mQβ and wtQβ was determined by the Student t test. e) OD450 from
ELISA result at 1/819200 sera dilution of IgG subtypes antibodies (IgG1, IgG2b, IgG2c
and
IgG3)
elicited
by
wtQβ-Tn1,
mQβ(A38K/A40C/D102C)-Tn1
and
mQβ(A40C/D102C)-Tn1 immunization against BSA-Tn1. ........................................................140

xv

Figure 2.20: Competitive ELISA showing reduced anti-wtQβ antibody recognition of
mQβ-Tn conjugates......................................................................................................................142
Figure 2.21: Flow cytometry showing binding of elicited IgG antibodies by Qβ conjugates;
a and b) Histogram showing binding recognition of the elicited antibodies against Jurkat
cells and TA3Ha cells, respectively, c and d) Graph of median fluorescent intensities of the
binding recognition of the elicited antibodies towards Jurkat cells and TA3Ha cells,
respectively. .................................................................................................................................144
Figure 2.22: a) Chemical structures of Tn1 and Tn2. b) MFI of cellular binding against
Jurkat cells of the serum from mice immunized with wtQβ-Tn2 and
mQβ(A38K/A40C/D102C)-Tn2 compared with those from wtQβ-Tn1 and
mQβ(A38K/A40C/D102C)-Tn1. .................................................................................................145
Figure 2.23: OD450 from the ELISA result of the post-immunized sera at 1/819200 dilution
against BSA-Tn2 from mice immunized with wtQβ-Tn2 and mQβ(A38K/A40C/D102C)Tn2. The statistical significance of differences was determined by the Student t test. ...............147
Figure 2.24: Flow cytometry showing binding of elicited IgG antibodies by wtQβ-Tn2 and
mQβ(A38K/A40C/D102C)-Tn2 a) Histogram showing binding recognition of the elicited
antibodies against TA3Ha cells, respectively, b) Graph comparing median fluorescent
intensities of the binding recognition of the elicited antibodies towards TA3Ha cells. ..............149
Figure 2.25: Kaplan-Meier survival curves comparing the protective effect of wtQβ-Tn2
and mQβ(A38K/A40C/D102C)-Tn2: a) after 1st tumor challenge with treatment of CP
(n=10), b) after 2nd tumor challenge without any further treatment (n=5). Statistical analysis
of survival is determined by using the log-rank test in GraphPad Prism software. Note:
Control experiments have been done in reference36. ...................................................................150
Figure 2.26: Chemical structure of tolerogenic CD22 ligand. ....................................................153
Figure 2.27: UV-visible absorption of wtQβ at varied temperature from 25 to 90°C. The
estimated wavelength that provides the most different absorption is 310 nm (dashed line). ......161
Figure 2.28: TEM images of wild-type Qβ and various Qβ mutants. ........................................164
Figure 2.29: Size-exclusion chromatography of wild-type Qβ, varied Qβ mutants and their
Tn1 derivatives.............................................................................................................................172
Figure 2.30: Mass spectra of wild-type Qβ-Tn1 and varied Qβ mutant-Tn1 after applying
MaxEnd1 algorithm. ....................................................................................................................177
Figure 2.31: 1H NMR spectrum of compound SI-11 ..................................................................184
Figure 2.32: 13C NMR spectrum of compound SI-11 ................................................................185
Figure 2.33: 1H-1H COSY NMR spectrum of compound SI-11 ................................................186

xvi

Figure 2.34: gHMQC NMR spectrum of compound SI-11 ........................................................187
Figure 2.35: gHMBC NMR spectrum of compound SI-11 ........................................................188
Figure 2.36: 1H NMR spectrum of compound SI-12..................................................................189
Figure 2.37: 13C NMR spectrum of compound SI-12 ................................................................190
Figure 2.38: 1H-1H COSY NMR spectrum of compound SI-12 ................................................191
Figure 2.39: gHMQC NMR spectrum of compound SI-12 ........................................................192
Figure 2.40: gHMBC NMR spectrum of compound SI-12 ........................................................193
Figure 2.41: 1H NMR spectrum of compound SI-14..................................................................194
Figure 2.42: 13C NMR spectrum of compound SI-14 ................................................................195
Figure 2.43: 1H-1H COSY NMR spectrum of compound SI-14 ................................................196
Figure 2.44: gHMQC NMR spectrum of compound SI-14 ........................................................197
Figure 2.45: gHMBC NMR spectrum of compound SI-14 ........................................................198
Figure 2.46: 1H NMR spectrum of compound Tn1 ....................................................................199
Figure 2.47: 13C NMR spectrum of compound Tn1...................................................................200
Figure 2.48: 1H-1H COSY NMR spectrum of compound Tn1...................................................201
Figure 2.49: gHMQC NMR spectrum of compound Tn1 ..........................................................202
Figure 2.50: gHMBC NMR spectrum of compound Tn1 ..........................................................203
Figure 2.51: 1H NMR spectrum of compound Tn2 ....................................................................204
Figure 2.52: 13C NMR spectrum of compound Tn2...................................................................205
Figure 2.53: 1H-1H COSY NMR spectrum of compound Tn2...................................................206
Figure 2.54: gHMQC NMR spectrum of compound Tn2 ..........................................................207
Figure 2.55: gHMBC NMR spectrum of compound Tn2 ..........................................................208
Figure 2.56: 1H NMR spectrum of compound Tn1-NHS ..........................................................209
Figure 2.57: 13C NMR spectrum of compound Tn1-NHS .........................................................210
Figure 2.58: 1H-1H COSY NMR spectrum of compound Tn1-NHS .........................................211

xvii

Figure 2.59: gHMQC NMR spectrum of compound Tn1-NHS ................................................212
Figure 2.60: gHMBC NMR spectrum of compound Tn1-NHS.................................................213
Figure 2.61: 1H NMR spectrum of compound Tn2-NHS ..........................................................214
Figure 2.62: 13C NMR spectrum of compound Tn2-NHS .........................................................215
Figure 2.63: 1H-1H COSY NMR spectrum of compound Tn2-NHS .........................................216
Figure 2.64: gHMQC NMR spectrum of compound Tn2-NHS ................................................217
Figure 2.65: gHMBC NMR spectrum of compound Tn2-NHS.................................................218

xviii

LIST OF SCHEMES

Scheme 1.1: Synthesis of MUC1 lipo-(glyco)peptides. The (Tn-)MUC1 peptides 1-4 were
synthesized by solid phase peptide synthesis followed by coupling with the activated
phospholipid DPPE-SUC-NHS to yield MUC1 lipo-(glyco)peptides 5-8. ..................................29
Scheme 2.1: Synthesis of Tn1-NHS and Tn2-NHS ...................................................................166

xix

KEY TO ABBREVIATIONS

ADCC

antibody-dependent-cell-mediated cytotoxicity

APC

antigen presenting cell

BCR

B-cell receptor

BLI

Bio-Layer Interferometry

BMDC

bone-marrow derived dendritic cells

BSA

Bovine Serum Albumin

CAR

chimeric antigen receptor

CCL-19

chemokine (C-C motif) ligand 19

CCL-21

chemokine (C-C motif) ligand 21

CCR7

C-C chemokine receptor type 7

CD80

cluster of differentiation 80

CD86

cluster of differentiation 86

CDC

complement-dependent cytotoxicity

CFA

complete Freund’s adjuvant

CIES

carrier-induced epitopic suppression

CP

cyclophosphamide

CPMV

Cowpea mosaic virus

CTL

cytotoxic T cell

CTLA-4

cytotoxic T-lymphocyte-associated protein 4

CuAAC

copper(I)-catalyzed alkyne-azide cycloaddition

DC

dendritic cell

xx

DCM

dichloromethane

DIPEA

diisopropylethylamine

DLS

dynamic light scattering

DMAP

4-Dimethylaminopyridine

DMEM

Dulbecco's Modified Eagle Medium

DMF

dimethylformamide

DMSO

dimethyl sulfoxide

DMSO

dimethyl sulfoxide

DNA

deoxyribonucleic acid

EGFR

epidermal growth factor receptor

ELISA

enzyme-linked immunosorbent assay

ErbB2

receptor tyrosine-protein kinase erbB-2

FACS

fluorescence-activated cell sorting

FBS

fetal bovine serum

FDA

Food and Drug Administration

FITC

fluorescein isothiocyanate

Fmoc

fluorenylmethyloxycarbonyl

GalNAc

N-acetylgalactosamine

GM-CSF

granulocyte-macrophage colony-stimulating factor

HA

hemagglutinin

HATU

1-[Bis(dimethylamino)methylene]-1H-1,2,3-triazolo[4,5-b]pyridinium 3-oxid
hexafluorophosphate

HBTU

O-(benzotriazol-1-yl)-N,N,N’,N’-tetramethyluronium hexafluorophosphate

HMFG

human milk fat globulin

xxi

HOAT

1-hydroxy-7-azabenzotriazole

HOBt

1-hydroxybenzotriazole

HPG

homopropargyl glycine

HPLC

high performance liquid chromatography

HRP

horseradish peroxidase

ICP

inductively coupled plasma analysis

IFA

incomplete Freund’s adjuvant

IFN-γ

interferon gamma

IgG

Immunoglobulin G

IgM

Immunoglobulin M

IL-12

Interleukin 12

IL-6

Interleukin 6

imDC

immature dendritic cell

IONP

iron oxide nanoparticle

KLH

Keyhole limpet hemocyanin

LCMS

Liquid chromatography–mass spectrometry

LDL-C

low-density lipoprotein cholesterol

mAb

monoclonal antibody

MALDI-TOF matrix assisted laser desorption ionization-time of flight
MAPK

mitogen-activated protein kinase

MHC

major histocompatibility complex

MHC-I

major histocompatibility complex class 1

MHC-II

major histocompatibility complex class 2

xxii

MPLA

monophosphoryl lipid A

mQβ

mutant Qβ

MRI

magnetic resonance imaging

MS

mass spectrometry

MUC1

glycoprotein Mucin 1

MW

molecular weight

NHS

N-hydroxysuccinimide

NK

natural killer cell

NMR

nuclear magnetic resonance spectroscopy

NP

nanoparticle

OA-IONP

oleic acid coated iron oxide nanoparticle

OD

optical density

PAMP

pathogen-associated molecular pattern

PBS

phosphate-buffered saline

PBST

phosphate-buffered saline tween

PCSK9

protein converstase subtillisin/kexin type 9

PD-1

Programmed cell death protein 1

PDI

polydispersity index

PDI

polydispersity index

PD-L1

programmed death-ligand 1

PEG

polyethylene glycol

PLGA

Poly(d,l-lactic-co-glycolic acid)

Qβ

bacteriophage Qbeta

xxiii

RNA

ribonucleic acid

RTK

receptor tyrosine kinases

SASA

solvent accessible surface area

SDS-PAGE

sodium dodecyl sulfate polyacrylamide gel electrophoresis

SEC

Size-exclusion chromatography

SPION

superparamagnetic iron oxide nanoparticle

SPR

Surface plasmon resonance

ssRNA

single-stranded RNA

ST

sialiated Thomsen-Friedenreich antigen

STn

sialiated Thomsen-nouveau antigen

T antigen

Thomsen-Friedenreich antigen

TACA

tumor-associated carbohydrate antigen

TCR

T cell receptor

TEM

Transmission electron microscopy

TFA

trifluoroacetic acid

TGA

thermogravimetric analysis

Th

Helper T cell

THF

tetrahydrofuran

TIPS

triisopropylsilyl ether

TLC

thin layer chromatography

TLR

Toll-like receptor

Tm

melting temperature

TMSOTf

trimethylsilyl trifluoromethanesulfonate

xxiv

TMV

tobacco mosaic virus

Tn antigen

Thomsen-nouveau antigen

TNF-a

tumor necrosis factor alpha

TSTU

N,N,N’,N’-tetramethyl-O-(N-succinimidyl)uronium tetrafluoroborate

TT

Tetanus toxoid

VLP

virus-like particle

VNTR

variable number tandem repeat

wtQβ

wild-type Qβ

xxv

CHAPTER 1: Lipopeptide-Coated Iron Oxide Nanoparticles as Potential GlycoconjugateBased Synthetic Anticancer Vaccines1
1.1 Introduction
1.1.1

Cancer immunotherapy

Cancer is a leading cause of death and one of the most serious public health concerns.
According to the American Cancer Society, it was estimated that, there were 1.7 million new
cancer cases and about 590,000 people died from cancer in 2015 in US. In terms of total deaths
in the United States recorded in 2014, cancer is ranked as the second leading cause of death
(22.5% of the total of deaths) following heart diseases (23.4% of the total of deaths).2 Although
being ranked in the second place, with such a small gap of the difference and difficulty of finding
an effective cure, cancer is expected to become the number one leading cause of death within the
next few years. Worldwide, cancer causes 15% of mortality, with estimated 14 million of new
cases each year.3 The death rate worldwide is projected to reach 10 million by 2020, which may
cost healthcare systems up to one trillion dollars.4
Until now, cancer treatment strategies still generally rely on conventional approaches of
surgical resection, chemotherapy and radiation. However, chemotherapy has the limitation of
severe side effects. Although surgery and radiotherapy procedures are standard treatment options
for local cancers, they increase risk to generate metastasis5 (cancer cells spread from a primary
site through circulatory system to regenerate and grow in distant vital organs), which is even
more lethal and harder to cure.
A promising alternative to the classical treatment strategies is immunotherapy.6 By
harnessing the effective immune system to specifically kill cancer cells and maintain protective

1

responses against cancer recurrence, immunotherapy is heralded as a revolutionary treatment
being more efficacious with more cancer types and posing fewer potential side effects.
The idea of immunotherapy started back in 1884 when Anton Chekhov found strong
evidence of the correlation between immune response to pathogen infection and tumor
reduction.7 Afterward in 1893, surgical oncologist William Coley tested the Chekhov’s finding
by using a mixture of attenuated bacteria from Streptococcus pyogenes and Serratia marcescens,
called Coley’s toxins, as an immune activating agent to treat cancer patients, and he found some
beneficial results.8 This evidence implied the potential of activating the immune system to
control tumor growth.
Although there are many hurdles in developing successful cancer immunotherapy, cancer
immunology research remains highly active and has made huge progress in understanding how
the immune system deals with cancer cells. This has led to promising clinical translation of
immune checkpoint therapies (such as PD-1 and CTLA-4) and chimeric antigen receptor (CAR)
T-cell therapy. A lot of promises shown by recent successes in clinical trials,9 excited the
scientific community to mark “cancer immunotherapy” as a Breakthrough of the Year by Science
journal in 2013.10 Very recently, the PD-L1 monoclonal antibody, Pembrolizumab (Keytruda),
has been approved by FDA as a primary treatment, instead of chemotherapy, for metastatic nonsmall cell lung cancer.9e This approval further highlights the role of immunotherapy in revolution
of cancer treatment.
Besides immune checkpoint therapy and CARs, another type of cancer treatment that
researchers have been trying to demonstrate efficacy is an anti-cancer vaccine. When combined
with other treatments, a cancer vaccine is expected to not only maximize the therapeutic effect,
but also provide long lasting protection, which could potentially prevent reoccurrence of cancers

2

in cancer patients. A cancer vaccine is conceptualized from vaccination against pathogen
infection. In a conventional pathogen vaccine, live or inactivated microbes are utilized to induce
immune responses to elicite antibodies that specifically neutralize the corresponding microbes.
The induced immunity will maintain the immunological memory to elicit more potent protection
for future attack from the same microbe, providing long-term protection against the pathogen. To
be able to further understand how the concept of pathogenic vaccine can be applied to cancer
vaccines, thorough understanding of how immunity works is necessary.
1.1.2

Mechanism behind immunity

Two kinds of adaptive immune processes, humoral and cell-mediated immunity, are
cooperatively responsible for defending against pathogens in the immune system. The humoral
immune system is the first line of defense. It involves antibody secretion from activated B cells
after they recognize B-cell epitopes. The simplest B-cell activation is induced by a T cellindependent process, from which the low affinity and short lived IgM antibodies are secreted
(Figure 1.1).11 The other process, known as a T cell-dependent process, relies on participation of
T helper-cell activation generating cytokines to induce Ig-isotype switching from IgM to the long
lasting and higher affinity antibody IgG. Moreover, T cell-dependent humoral immunity also
generates memory cells, which are capable of inducing even more potent responses against
subsequent encounters with the same antigen.12 IgG has the potential to recognize and bind to
pathogen-associated antigens, marking the target. The antibody-bound pathogens can be
eradicated by either complement-dependent cytotoxicity (CDC) or antibody-dependent-cellmediated cytotoxicity (ADCC), in which macrophages, neutrophils or natural killer cells will be
recruited to inactivate or kill the targeted pathogen.13

3

Figure 1.1: A cartoon showing two types of humoral immune activation by a tumor antigen.
Upper panel – T cell-independent B-cell activation: the multivalent antigen crosslinks B cell
receptors without the help from T cells leading to IgM secretion. Lower panel − T cell-dependent
B-cell activation: In addition to B-cell activation by direct antigen recognition, the antigen can be
taken up by antigen presenting cells such as dendritic cells, which subsequently present the
antigen fragment to activate helper T cell (Th cell). The activated Th cell releases cytokines to
induce B cells to undergo Ig-isotype switching from IgM to IgG. The figure is adapted and
reproduced from reference14.
Cell-mediated immunity, involves the synchronized action of a variety of immune cells,
including antigen presenting cells (APCs), macrophages, natural killer cells (NKs), helper T
cells, and cytotoxic T cells. These cells interact with each other through cytokine signaling and
cellular surface molecules to induce effective immune protection. Among all antigen presenting
cells, dendritic cells (DCs) play a key role in inducing immune responses.15 DCs are located in
peripheral tissues, such as skin, which continuously seek out invading pathogens. Once the
pathogens encounter the body, DCs will internalize the foreign substances, or antigens, which are
4

subsequently processed into short peptides. Meanwhile, DCs undergo maturation expressing a
variety of cellular surface molecules, including co-stimulatory molecules CD80, CD86, and a
homing receptor, CCR7. This alteration allows DCs to migrate toward the secondary lymphatic
organs in response to a high concentration of chemokines CCL-19 and CCL-21, and present the
antigens to T cells residing there. To present the antigen to T-cell receptor (TCR) on the T cells,
the processed peptides need to be loaded into either the major histocompatibility complex
(MHC) class I or class II molecules, depending on the source of the antigens (Figure 1.2).
Endogenous antigens, which are derived from intracellular proteins in the APCs themselves, are
typically loaded on MHC class I molecules (MHC-I). In contrast, exogenous antigens, which are
derived from foreign substances and taken up by DCs, are normally loaded on MHC class II
molecules (MHC-II). Antigenic peptides loaded on MHC-II are presented to CD4+ helper T
cells, which are involved in cytokine secretion to promote B cell activation, resulting in IgM-toIgG class switching in humoral immunity described above. However, exogenous antigens can
possibly be transported into MHC-class-I presentation route via a process known as crosspresentation. The processed exogenous peptides loaded on MHC-I are presented to CD8+ T cells
or cytotoxic T lymphocytes (CTLs). Once presentation by MHC-I occurs, CTLs become
activated and leave the lymphatic organs, seeking for the same antigenic peptide presented by
MHC-I on the surface of infected cells. When CTLs recognizes the antigen, they bind to the
target cells and release cytotoxic granules to kill the infected cells.16

5

Figure 1.2: Illustration showing the process of cell-mediated immunity. a) The antigenpresenting cell uptakes and processes an antigen into a short fragment (CD8+ T-cell epitope).
The digested fragment is loaded onto MHC class I and presented to a CD8+ T cell. The activated
CD8+ T cell then proliferates and becomes cytotoxic T cells, which will be able to kill the
corresponding pathogens or cancer cells. b) The processed antigen fragments that are loaded onto
MHC class II will be presented to CD4+ T cell. The activated CD4+ T cells will release cytokines
in T-cell dependent B cell activation resulting in IgM-to-IgG isotype switching and the
generation of IgG secreting plasma cells and memory B cells. The figure is reproduced with
permission from reference17.
By analogy with B cell epitopes as pathogen’s signatures, to which the immune system
targets, the key towards making a successful cancer vaccine is to generate unique/overexpressed
cellular marker(s) that can differentiate cancer cells from normal cells. This differential marker
can be used to educate the immune system to target and selectively eradicate cancer cells. Due to
genetic- or epi-genetic mutations, human cancers either overexpress common markers or induce

6

unique aberrant self-derived molecules on their surface. Advances in high-throughput
technologies in genomic, proteomic and glycomic research help accelerate elucidation of
potential novel markers from tumor cell or tumor-associated microenvironment, leading to a
variety of targets to selectively fight different type of cancers (For a review see 18). One type of
important signatures discovered in all states of tumor progression, including transformation,
metastasis, angiogenesis and immune escape, is changes in glycosylation pattern.
1.1.3

Protein post-translation modification by glycosylation

After human genome sequencing was completed, it was surprising to find that functional
diversity of proteins in eukaryotes far exceeds the coding capacity of the genome. Beyond the
variety of amino acid translation and folding/refolding of the protein complexes, posttranslational modification plays a tremendous role to diversify the complexity of proteins that
regulate protein activity, cellular physiological state and signal communication between cells or
microenvironment.19 One of the common post-translation modifications in eukaryotes is
glycosylation.
Glycosylation involves selective addition of carbohydrate based molecules, or glycan,
onto a specific amino acid by glycosyltransferase enzymes and selective trimming of glycans by
cleaving its saccharide subunit by glycosidase enzymes. There are two common sites where the
glycan addition occurs. Glycan that is added onto the amide group in the side chain of asparagine
in peptide sequence Asn-X-Ser/Thr (where X can be any amino acid except proline) is called Nglycan. By contrast, O-glycan is referred to glycan addition to the hydroxyl group in the side
chain of serine or threonine.

7

1.1.4

Mucin 1

One of the most common cancer associated glycoproteins is Mucin 1 (MUC1). MUC1 is
a membrane-bound glycoprotein. It is originally translated as a pro-protein, and then undergoes
auto-proteolytic cleavage into C-terminal (MUC1-C) and N-terminal subunits (MUC1-N)
(Figure 1.3a). After the cleavage, both fragments link together through a stable, non-covalent
interaction. In the normal state, MUC1 is found extensively on epithelial cells and exclusively on
apical side of the cells (Figure 1.3c). The steric hindrance of heavy glycosylation on the Nterminal subunit stretches the core peptide into linear form. This linear form of MUC1 can
extend the protein terminal reach to over 200nm above the apical surface20 (general membrane
proteins extend out about 30nm21), and altogether forming a thick mucus layer on the epithelial
cells. The thick layer of MUC1 is thought to generally function as a lubricant or a protecting
layer against invasive pathogens22 and strong acidic environment (pH = 2) in the gastrointestinal
track.23 In addition to tissue protection, some investigations also suggested its role in cell
differentiation and intercellular communication.24
The C-terminal fragment (MUC1-C) contains a cytoplasmic domain (CD), a
transmembrane domain (TD), and an extracellular N-terminal domain (ED) (Note that Nterminal domain in this context is a part of the C-terminal subunit.) (Figure 1.3b). The
cytoplasmic domain involves intracellular signaling through mitogen-activated protein kinases
(MAPK) signaling pathway.25
Moreover, after cellular alteration due to tumorigenesis on cancer cells, the N-terminal
subunit (MUC1-N) will start to dissociate and leave the C-terminal subunit (MUC1-C), which
remain attached on the cell membrane (Figure 1.3c). The remaining C-terminal subunit (some
still have the N-terminal subunit connected) will delocalize to the entire cell surface, instead of
specific presentation on the apical side. This cellular morphology change is termed “loss of
8

polarity”. Under loss of polarity, the extracellular N-terminal domain in the C-terminal subunit is
responsible for interactions with receptor tyrosine kinases (RTKs), e.g., EGFR or ErbB2 through
galectin-3 on Asp-36 (Figure 1.3d). This cis-interaction is thought to amplify the aberrant over
expression of MUC1 on cancer cells. It is postulated that the loss of polarity and over-expression
of MUC1 on cancer cells contributes to intercellular repulsion resulting in metastasis and
immune evasion. Although targeting C-terminal subunit would regulate intracellular signaling
pathway associated with tumor transformation, C-terminal MUC1 is less applicable for immune
target as it is buried underneath thick layer of highly-glycosylated N-terminal subunit, making it
invisible to the immune system.

Figure 1.3: a) C-terminal (MUC1-C) and N-terminal subunit (MUC1-N) are connected by noncovalent interaction after auto-proteolytic cleavage. b) C-terminal MUC1 (MUC1-C) are
composed of a cytoplasmic domain (CD), a transmembrane domain (TM), and an extracellular
N-terminal domain (ED). N-glycan on Asp-36 can cis-bind to receptor tyrosine kinases (RTKs)
after loss of polarity. c) The N-terminal subunit (MUC1-N) will dissociate and leave the Cterminal subunit (MUC1-C) due to tumorigenesis on cancer cells. d) Cellular alteration due to
tumorigenesis causes loss of polarity or delocalization of the remaining C-terminal subunit to
entire cell surface, instead of specific presentation on the apical side. The C-terminal subunits
form cis-interactions with receptor tyrosine kinases (RTKs) causing amplification of the
aberrantly overexpression of MUC1 on cancer cells. This figure is adapted and reproduced with
permission from reference25.

9

The outer layer N-terminal subunit MUC1-N contains a variable number tandem repeats
(VNTR) of twenty amino acids, GVT*S*APDT*RPAPGS*T*APPAH. The number of this
repeating unit varies from 20 to 125 units depending on the alleles.26 Five amino acids, either
serine or threonine (starred letters), in the VNTR can potentially be sites for O-glycosylation
(Figure 1.4).22, 27 The core peptide in this variable number tandem repeat domain is immunogenic
and well known as a B cell epitope. The binding analysis of serum from cancer patients by
ELISA28 and microarray29 revealed that RPAPGS, PPAHGVT and PDTRP are the minimal
dominant epitopes in VNTR. The analysis also showed that sera from cancer patients bind
stronger to Tn-glycosylated MUC1 than unglycosylated one. This suggested that the
glycosylation in MUC1 sequence is crucial for antigenicity of the MUC1 antigen.

Figure 1.4: Variable number tandem repeats (VNTR) of twenty amino acids in N-terminal
subunit (MUC1-N). 5 potential amino acids (red letters) are potentially subjected to Oglycosylation. This figure is adapted and reproduced with permissions from references21, 25.
NMR assisted structure analysis of VNTR in MUC1 revealed that the secondary structure
of the MUC1 forms an ordered structure of rod shape. Five rigid amino acids of proline in
MUC1 sequence are thought to lead to this rod shape structure. The VNTR is composed of 2 βturn regions at APDTRP and PGST sequences.30 However, only the hydrophobic β-turn region
of APDTRP sequence forms protruding knob out of the rod shape structure.31 This protruding
region is believed to expose the immunodominant epitope of MUC1, which is correlated with the
10

dominant epitopes of vaccinate induced anti-MUC1 antibodies28 and many MUC1-specific
monoclonal antibodies, such as SM3 (PDTRP), BC2 (APDTR), HMFG1 (PDTR), HMFG2
(DTR).21, 32
1.1.5

Aberrant glycosylation in cancer cells

Although MUC1 is also found on normal epithelial tissues, MUC1 expressed on tumor
cells differs from those on normal cells in many ways. First, due to alteration in MUC1 gene
regulation, MUC1 is over-expressed (100 times compared with those expressed on normal cells)
on many types of cancer cells, including lung, pancreas, prostate cancers and especially breast
cancers (90% of breast carcinomas).33 This over-expression together with the loss of polarity in
the cell surface expression would, therefore, significantly increase the chance of immune
recognition towards cancer cells.
Secondly, in normal cells, the post-translational modification of O-glycosylation will
begin with the addition of an N-acetyl galactosamine residue (GalNAc) onto serine or threonine
in the VNTR domain in MUC1. The glycosylation will then be extended from the starting
GalNAc unit to core 1 – core 4 structures (Figure 1.5). Unlike genetic code derived cellular
products such as DNA, RNA and protein, where the sequence of subunits is encoded from their
templates, the occurrence of glycosyl elongation process depends on available substrates and
activity of glycosyltransferase enzymes (T-synthase) on the site where the glycosylation is taking
place. In cancer cells, however, the glycosylation enzyme, specifically Core-1 synthase
(C1GalT1), is improperly folded due to the absence of Cosmc chaperon in Endoplasmic
Reticulum caused by genetic/epigenetic mutation in the cancer cells (Figure 1.6).34

11

Figure 1.5: The process of O-glycosylation begins with the addition of a GalNAc moiety onto a
serine or threonine residue in a polypeptide. The glycosylation will then be extended from the
starting GalNAc unit by T-synthase to core 1 – core 4 structures. This figure is adapted and
reproduced with permission from reference34b.

12

Figure 1.6: The glycosylation enzyme T-synthase in cancer cells is malfunctioning due to
improper enzyme folding caused by the absent of Cosmc chaperon in the endoplasmic reticulum
in cancer cells. The malfunctioning T-synthase in cancer cells leads to the aberrant glycosylation
in glycopeptide MUC1. This figure is adapted and reproduced with permission from reference34b.
As a result, the glycosylation patterns found on cancer-associated MUC1 are more
truncated and sialylated.35 As a consequence of the shorter glycosylation, the core peptide
epitopes are more exposed and susceptible to be accessible and recognized by immune cells,
while MUC1 expressed on normal cells are more protected by the unaltered glycosylation
patterns.36 Moreover, the aberrant glycosylation generates distinct carbohydrate antigens, which
include Thomsen-Friedenreich (T) antigen (Galβ1-3GalNAc-α1-O-Ser/Thr), Thomsen-nouveau
(Tn) antigen (GalNAc-α1-O-Ser/Thr) or their sialylated product; STn and ST antigens (Figure
1.7). The presence of these antigens on cancer cells are well correlated with cancer prognosis as
they promote the tumorigenesis, progression and metastasis in the cancer cells.37 However, T and

13

ST antigens are also found in normal tissues38 while Tn and STn antigens are more exclusively
expressed on the cancer cells. Immunohistochemistry of a variety of cancer patients samples
indicated high expression level of Tn over 80% (85% in breast, 90% in ovary and 83% in
endometrium cancers) compared to normal tissues.39 The distinctly high expression of Tn or STn
antigens make them more attractive as targets for anti-cancer vaccine.40 Therefore, it is
envisioned that, in addition to MUC1 antigen, inducing immune response against these tumorassociated carbohydrate antigens (TACAs) would possibly selectively eradicate cancers.
OH
HO
AcHN
HO

OH

OH

HO

O

HO

HO

O

HO
AcHN O

O
HO

OH

AcHN O

AcHN O
STn

OH
HO
AcHN

OH CO2
O

O

HO

HO
AcHN

OH CO2 HO
O

OH
O

O
OH

HO

HO
O

O

HO

T

OH

O

HO

O

O

OH

Tn

OH CO2

HO

OH
O

HO

AcHN O

OH
O
OH

HO
O

O

AcHN O

α
(2-6)ST

α
(2-3)ST

Figure 1.7: The structure of TACAs; Tn, T and their sialiated products; α(2-3)ST, α(2-6)STn.
All of these different features make MUC1 glycoprotein a promising candidate of
antigens for anti-cancer vaccine. Moreover, a recent research ranked MUC1 as the second most
potential cancer associated antigen, according to the total score regarding therapeutic prospect
criteria such as therapeutic function, immunogenicity, specificity, and level of expression.41
1.1.6

Evidences supporting MUC1 based vaccine

There has been enthusiasm of finding and developing therapeutic monoclonal antibodies
that target selectively against TACAs or glycopeptide MUC1 on cancer cells.14 The discovery of

14

monoclonal antibody SM-3 that preferentially bound MUC1 on many types of cancer cells
relative to that on normal cells led to the development of novel monoclonal antibodies that
exhibited high selectivity towards tumors. Monoclonal antibody AS1402 is an example
exhibiting antibody-dependent cellular cytotoxicity towards cancer-associated MUC1 expressing
tumor cells. The promising efficacy of AS1402 made it enter clinical trials in phase I and II.
However, no significant difference in efficacy was observed when compared with conventional
approach based on chemotherapy. This unanticipated result in clinical evaluation is attributed to
the excess amount of the soluble MUC1-N released from cancer cells sequestering the
administrated monoclonal antibody subsequently diminishing the amount of the antibody
available to access the tumor-bound MUC1. Similarly, this situation would also happen with a
drug-conjugated monoclonal antibody against MUC1. Therefore, most of the anti-MUC1
monoclonal antibodies developed are still limited to diagnostic purposes, rather than for therapy.
Unlike passive immunotherapy using monoclonal antibodies, inducing immune response
against the cancer-associated MUC1 would be more attractive since the active immune response
can continuously generate the specific antibody to reduce the pool of secreted MUC1. In addition
to targeting local cancer, the antibodies generated can eliminate circulating cancer cells in the
blood, hence, preventing lethal metastases from developing. In addition to the high cost of
monoclonal antibody based therapies, the efficacy of the monoclonal antibody tends to decline
overtime due to the induced neutralizing antibodies against the repeatedly administered proteins.
Besides antibody responses, vaccination with MUC1 glycopeptide can also activate
cytotoxic T cells. It was believed that the antigen fragment, presented by the MHC molecule to
the T-cell receptor is limited to peptides and cell-mediated immunity, plays an indirect role in
immune activation against non-peptidic antigen such as carbohydrates. There were multiple

15

reports that T cell receptors can also recognize glycopeptide fragment bound on the MHC class I
molecule.42 Cytotoxic T cells isolated from pancreatic, ovarian and breast cancer patients were
found to recognize MUC1 glycopeptides and induce cytotoxicity to cancer cells in vitro.43
Epitope

mapping

studies

have

identified

peptide

STAPPHGV

and

glycopeptide

SAPDT(GalNAc)RPAPG, located in VNTR of MUC1 as CD8 T cell epitopes that bind to MHC
class I allele HLA-A2.44 Although these examples indicate the presence of MUC1 specific
cytotoxic T cells in cancer patients, they are not sufficiently effective to overcome tumor growth.
This is probably due to self-tolerance related immunosuppression due to overexpression of
MUC145 as well as aberrant glycosylation46 on cancer cells that inhibit the effector T cells to
eliminate the targeted cancer cells. Therefore, it is envisioned that the cooperation of humoral
and cell-mediate immune responses, together with immune check point therapy, would empower
the immune system to efficiently eliminate cancer as well as to prevent cancer recurrence.
1.1.7

Anti-MUC1 vaccine development

Anti-MUC1 vaccine has been under study for a while. In 1994, Apostolopoulos and
coworkers immunized mice with MUC1 containing a synthetic peptide, fusion protein, or natural
MUC1 isolated from human milk fat globulin (HMFG).47 Although these compounds generated
high antibody responses, they failed to protect mice from tumor challenge. In the same study, the
authors showed that immunizing mice with MUC1 transfected cancer cells can protect mice from
tumor challenge, despite the low antibody response. The protective response of the latter case
was contributed to Th1 type response, which is associated with activation of cytotoxic T cells.
Antibody responses were attributed mainly to Th2 response. This finding leads to the utilization
of carriers to bias immune response towards Th1 rather than Th2 for stronger protective effect of
the vaccine.47 Polysaccharide mannan is another example used to direct the type of the immune

16

response towards Th1 by modification of the polysaccharide carrier by oxidation.48 In addition,
the mannan carrier can enhance antigen uptake through C-type lectin receptor on antigen
presenting cell resulting in more efficient immune induction event and protection of human
MUC1 transgenic mouse model from tumor challenge.
Due to low immunogenicity of MUC1, immunogenic proteins have been used as MUC1
antigen carrier to enhance the immunogenicity of MUC1. Keyhole limpet hemocyanin (KLH)49
and tetanus toxoid (TT)50 are common protein carriers utilized for anti-MUC1 or anti-TACA
vaccines. Although these immunogenic proteins can strongly boost the immune response against
such low immunogenic antigens, the high immune response against the carrier itself, or linker in
some cases, was also found and thought to suppress the desired immunity against the MUC1 or
TACAs.51 This suppressive effect from the vaccine carrier is known as carrier-induced epitopic
suppression (CIES).52 This issue leads to increasing interest in investigating other vaccine carrier
candidates that have potential to preferentially focus immune response specific to MUC1
antigen, rather than the carrier.22
Over the past decade, when the concern of vaccine safety has become the top priority in a
clinical trial, the paradigm of vaccinology is to replace the undefined whole-microorganism or
extracted natural product derived vaccines with subunit vaccines, where their constructs are well
characterized, reproducible, stable and low in undesired side effects. In addition to using
immunogenic proteins as vaccine carriers, which usually suffer from carrier-induced epitopic
suppression (CIES) mentioned above, fully synthetic vaccines have become a main stream of
MUC1 vaccine development which is proposed to mitigate the carrier induced immune
suppression due to non-essential components incorporated.53 The well characterized synthetic
MUC1 vaccines can be not only easier to manufacture, but also more homogeneous, than

17

compounds isolated from natural sources. Moreover, the synthetic strategies allow the
glycosylation pattern on the MUC1 glycoprotein to be tuned to best represent the tumor
associated antigens. This tunable and uniformly defined compound provided insight about
structural factors of the vaccine, which enhance the knowledge for antigen design in vaccine
development.
The concept of fully synthetic vaccine relies on minimizing vaccine components down to
a construct containing only essential specific immune stimulating components, generally
including tumor associated antigen(s), Th epitope(s), and agonist of Toll-like receptor(s) (For
more detail about the fully synthetic vaccine, readers are directed to an intensive review53).
1.1.8

Particulate Vaccine

The immune system is normally prevented from responding against self- or self-derived
antigens and is tolerant to those antigens. Since tumor antigens are derived from self-antigens,
they are generally poorly immunogenic. Therefore, it is more challenging to develop anti-cancer
vaccines compared with classical vaccines against infectious diseases.
A number of strategies have been proposed for effective induction of immune responses
to break the immune tolerance. Those strategies include selection of suitable tumor associated
antigens as well as mean to deliver such antigens to activate the immune system, which can be
critical for the outcome of the vaccination.54
One proposed way to guarantee that the antigen is delivered to APC is ex-vivo
manipulation of DC by directly incubating the antigens with isolated DCs. The loaded DCs are
then re-infused back into the patients, allowing them to present the antigen and stimulate the
immune system to kill cancer cells. This approach was approved by Food and Drug
Administration (FDA) in 2010 with the trade name of Provenge for prostate cancer treatment.55

18

However, this approach relies on individual treatment, in which only DCs from the same patient
can be used, as cells from other patients can potentially cause immune rejection. Therefore, this
exclusive healthcare process is costly and may be impractical for most cancer patients. This
complication highlights the need for better vaccine formulation that can deliver the antigen to
DCs in vivo to circumvent expensive ex-vivo DC manipulation.
Another promising approach to improve the efficacy of antigen delivery to DCs in vivo is
by employing particulate vaccines based on nanoparticles. Several studies showed that
particulate materials can enhance delivery of antigenic molecules to APCs and elicit more potent
immune responses compared with administration of the molecules in soluble forms.56 Many
reasons are accounted for such effective antigen delivery by particulate vaccines.57 First, due to
the nanoscale size of particulate materials that resemble small pathogens like bacteria or virus,
they could be recognized by the immune cells in a similar manner as those invading foreign
substances.58 Second, particulate vaccines act as carrier vehicles protecting the antigenic
materials from degradation by enzymes or harsh conditions. This characteristic can increase the
amount of an intact antigen taken up into targeted cells, resulting in higher chances to activate
immune response with less material.59 Third, surface engineering on particulate particles by
conjugation with targeting molecules helps improve specificity towards the target cells, and
could reduce potential side effects.60 Moreover, highly organized presentation and repetitiveness
of antigenic epitopes on particulate nanomaterials can offer clustering effect for antigen
presentation on B cell receptors, which helps promote B cell activation generating high antibody
titers.61 Last, adjuvant or co-stimulatory signal molecules that help immune activation can be codelivered along with antigenic epitopes to activate the same targeted cells, which was shown to
be beneficial by many studies.62 Besides the incorporation of adjuvant, biocompatible probes,

19

such as fluorophore, quantum dot or MRI contrast agent, can be introduced to monitor the fate of
the particulate vaccine and cellular activity. The combination of therapeutic and imaging
functionalities in a single platform is a highly active research area termed “Theranostics”.63
1.1.9 Physical properties of a particulate vaccine determine the immune response
profile.
The physical characteristics of particulate system, such as size, hydrophobicity, surface
charge, have dramatic impacts on circulation time, bio-compatibility, bio-distribution and
cellular interaction of the particles. Size of particulate vaccine is one of the factors that plays an
important role in how the vaccine is delivered to interact with and activate immune system.
Particles with larger sizes (0.5–5 μm) are preferentially taken up by macrophages, while smaller
particles in range of viruses (20–200 nm) can dominantly target DC.64 Although particles up to
200 nm are able to get internalized by DC, only small particles 5–100 nm in size were purported
to contribute to effective DC mediated immune activation.65 Despite the fact that the DC in skin
can uptake particles larger than 100nm, these DCs are less capable of transporting the antigen to
present to B or T cells in lymph node. The in vivo imaging experiment by superparamagnetic
iron oxide nanoparticles66 showed that only less than 5% of DC population in lymph nodes
migrated from peripheral tissues. Moreover, the DCs that arrived the draining lymph nodes could
become exhausted or dead.67 In some cases, the skin-derived DCs have to pass the captured
antigen to LN-resident DCs. This transferring process could reduce the chance of maintaining
sufficient amount of the antigen to be present to the T cells.68 Therefore, direct trafficking of
antigen to the dendritic cells residing in lymph node is envisaged to be more efficient in inducing
immune activation. The crucial effect of size for particulate vaccines has also been emphasized
by the study from Reddy and coworkers.69 They found that NPs with 25nm in diameters can
target lymph node residing dendritic cells, while 100 nm NPs are less likely to drain into the
20

lymph nodes. However, too small particle (< 5 nm) is not efficient in delivery antigen into the
lymph node either, as it is more likely to diffuse out of lymph nodes into blood circulation.65
Altogether, these findings suggested that the proper size of particulate vaccine is crucial for
successful particulate vaccine.
1.1.10 Anti-MUC1 particulate vaccines
Several studies have applied a particulate vaccine for a MUC1 based vaccine. In 1998,
Kimberley and coworker used poly(d,l-lactic-co-glycolic acid) (PLGA) as a carrier for synthetic
MUC1 peptide.70 In that study, the PLGA was used to encapsulate the MUC1 peptide together
with adjuvant MPLA. The PLGA-MUC1 induced Th1 response with no MUC1 specific IgM and
low IgG titer. The large size of the PLGA micro-particle (500-900 nm in diameter) may
contribute to the low anti-MUC1 IgG response. In the same year, the same group also reported
the utilization of liposome based particle for MUC1 vaccine.71 It was shown that the
encapsulated MUC1 inside liposomes can induce only T cell response while the antigen
displayed on the surface of the particle can both elicit antibody and induce T cell response. The
results from this study demonstrated the effect of how antigen is incorporated in a particulate
vaccine on immune response profile. Although the liposomes bearing surface antigens were able
to induce IgM and IgG, the antibody titers resulting from the vaccine were not high. The size of
liposome base MUC1 vaccine in this case is around 800-900 nm. In another study, the diameters
were even bigger (1.7-2.1 μm),72 which are bigger than the suitable range for effective DC
targeting in lymph nodes.
Liposome formulation is another platform widely used as a weakly immunogenic carrier
for multicomponent fully synthetic MUC1 vaccine. The hydrophobic chains of the amphiphilic
component are substituted by adjuvant such as TLR agonist Pam3CysSK4, in which the lipid

21

chains facilitate the incorporation of the synthetic compound into the liposome.73 Several works
from Boons and colleagues demonstrated excellent examples of using liposome as a platform for
MUC1 vaccine.73-74 In 2005, Boons group first reported the investigation of liposomal vaccine of
fully synthetic three-component of lipidated glycopeptide containing TLR-2 agonist Pam3Cys,
Th epitope YAF peptide and Tn antigen in the same molecule. The synthetic compound was
incorporated onto the surface of liposome. Based on the method of preparation and negativestain TEM analysis, the size of the liposome is about 100 nm in diameter.74b The liposome
vaccine can induce IgG antibody from the vaccinated mice. This work pointed out the
importance of appending Th epitope in the construct as it was shown previously that the
Pam3Cys conjugated to Tn antigen induced low IgG response. Following this finding, the group
continued to apply the same construct to MUC1 glycopeptide, instead of Tn antigen.75 In this
work, they used fully synthetic three-component compound composed of B cell epitope from
MUC1, Th epitope from polio virus (PV) and TLR1 and 2 agonist Pam3CysSK4 or TLR2 and 6
agonist Pam2CysSK4 (Figure 1.8). It was found that Pam3CysSK4 has higher potency in
inducing strong IgG response more than Pam2CysSK4. The vaccines did not elicit antibody
against Th epitope, which highlight the minimal immunogenicity of this construct. This work
also showed that the covalent conjugation of the three components is important in inducing high
titer of the antibody response. In addition, the liposome formation containing of the three
components in the same particles can elicit much higher antibody than the mixture of all
components in saline solution which emphasizes the importance of particulate platform in
antigen delivery to the immune system. Further study in later publication indicated the
importance of Tn antigen in the construct for higher efficacy of the vaccine compared with nonglycosylated MUC1.76 It was proposed that the glycosylation on MUC1 peptide helps conserve

22

the conformation of the peptide as in native form, hence, induces immune response more specific
to the cancer related MUC1. The study showed high efficacy of the vaccine in inducing not only
humoral immune response to lyse the cancer cells via antibody dependent cellular cytotoxicity
(ADCC), but also cell-mediated immune response through the activation of MUC1 specific CTL
to kill MUC1 expressing cancer cells. The resulting cooperation of both immune protection arms
is believed to help reduce tumor size in a tumor challenge study.

Figure 1.8: Representative structures of fully synthetic three-component compounds composed
of B cell epitope from MUC1, Th epitope from polio virus (PV) and TLR1 and 2 agonist,
Pam3CysSK4, or TLR2 and 6 agonist, Pam2CysSK4. This figure is adapted and reproduced with
permission from reference75.
Self-assembled subunit MUC1 has been investigated by Payne and coworkers in 2012.77
The subunit MUC1 vaccine is composed of VNTR (glyco-) MUC1 peptide, T helper epitope
PADRE and build-in adjuvant Pam3CysSer. Although, the construct is similar to other
liposomal-based fully synthetic subunit MUC1 vaccine, they found that this compound can form
a nanoparticle by itself without the help from liposomal formulation additives such as Egg
phosphatidylcholine, phosphatidylglycerol and cholesterol.75 The size of the particle measured
by TEM is around 17-25nm. The self-assembled nanoparticle can induce IgM and IgG1, but low
titer of IgG2, which suggests Th2 type response. The elicited antibodies can recognize MCF7
and B16 cancer cells. More recently in 2015, Li and colleagues developed multilayer selfassembled subunit MUC1 vaccine based on interaction of electrostatic components.78 The Th
epitope conjugated with poly-lysine can form the core of particle with positive surface charge.

23

Adjuvant poly-glutamic with negative charge was coated onto the core particle as a second layer,
followed by third layer of positively charged poly-lysine, which was conjugated to MUC1
glycopeptide. The size of resulting particles is about 350nm. The particles were shown to be
taken up by APCs RAW264.6 and induce secretion of pro-inflammatory IL-6 and IL-12. The
titer of IgG induced by the multilayer particles was similar to glycopeptide MUC1 covalently
linked to Th epitope. The multilayer particle vaccine induced more IgM than IgG. Nevertheless,
sera from immunized mice showed binding to MCF-7 cells and induce a complement-dependent
cytotoxicity to kill cancer cells.
A particulate vaccine is not limited to a particle-based platform. Nanofiber construct has
also been applied to particulate MUC1 vaccine. Li and coworkers utilized peptide Q11, which
can self-assemble to form β-sheet construct and has adjuvant property, as a carrier with built-in
adjuvant for MUC1 antigen.79 The conjugated peptide mixture aggregated to form nanofibers
longer than 200nm. The study showed that putting Tn antigen on PDT*RP can elicit higher
antibody response than putting Tn on GST*AP or both positions. This finding indicated the
crucial position of glycosylation in MUC1 vaccine design. The self-assembly peptide Q11 did
not induce antibody response to itself which highlight minimal immunogenicity against the
carrier. The vaccine elicited predominantly IgG2a and IgM, which was possibly due to the lack
of Th epitope for antibody isotype switching.80 The elicited antibody showed binding to MFC-7
and induced complement dependent cytotoxicity to lyse the cells.
Very recently, gold nanoparticles were used as a carrier for MUC1 vaccine. MUC1
peptide together with T cell epitope P30 were conjugated on gold nanoparticles (20-30 nm).81
The resulting nanoparticle based vaccine can mediated both Th1 and Th2 immune responses.
The generated antisera from immunized mice showed binding to MCF-7 cells.

24

Although these studies pointed out the beneficial effects from particulate platforms and
the factor of size in inducing effective immune response against MUC1, most of the results are
still far from a practical candidate to overcome the tremendous challenge of anti-cancer vaccine
development. Therefore, new carrier platform is still needed in order to find a successful antiMUC1 vaccine to cure cancer.
1.1.11 Superparamagnetic iron oxide nanoparticle: SPION
Superparamagnetic Fe3O4 nanoparticles have been utilized extensively in drug delivery
and non-invasive in vivo imaging applications.82 This class of nanoparticle is shown to be
biocompatible with low safety concern when used as targeting carriers for therapeutic agents.83
Some iron oxide nanoparticles, such as Feridex I.V. (ferumoxides), Combidex (ferumoxtran-10),
Feraheme (ferumoxytol), have been approved by the FDA for use in human.84
With regards to immunotherapy applications, iron oxide nanoparticles have become a
promising antigen carrier to elicit immune response via peripheral dendritic cells. Mou, et al.
demonstrated that iron oxide nanoparticles could be internalized by both mature and immature
dendritic cells, and the internalization could induce initial maturation in which the essential
cellular surface markers related to maturation states, including co-stimulation marker CD80,
CD86 and MHC-II, were upregulated. The study also showed that the iron oxide nanoparticles
did not pose significant effects on maturation phenotype and viability of the labeled dendritic
cells, yet maintained the ability to activate T cells.85 In a very recent work, iron oxide
nanoparticles were evaluated as a safe, stable and built-in adjuvant vaccine delivery vehicle for a
recombinant malaria vaccine antigen. There was evidence supporting the efficient internalization
(> 90%) of iron oxide nanoparticle by dendritic cells. The iron oxide nanoparticles also showed
their abilities to activate dendritic cells to express co-stimulatory ligand CD86, and secrete

25

necessary cytokines for immune response (IL-6, TNF-α, IL1-β, IFN-γ, and IL-12). Mice
immunized with the iron oxide nanoparticle based malaria vaccine showed significant higher
antibody response compared with the vaccine formulated with a clinically acceptable adjuvant,
Montanide ISA51. Moreover, the nanoparticle based vaccine tested in nonhuman primates was
able to induce high immune response and high levels of parasite inhibition.86 Moreover, the size
of iron oxide nanoparticles can be tuned by a variety of preparation method. This advantage of
controllable size would allow preparation of the proper size of particulate vaccine more flexible.
Besides their tendency to activate dendritic cells, IONPs are well known as magnetic
resonance imaging (MRI) contrast agent83b, which could be used to monitor the migration of
labeled DCs in vivo after vaccine administration by a non-invasive method based on MRI.87 This
advantage could aid us in deciphering mechanism of the immune responses. Accordingly, it
could be hypothesized that iron oxide nanoparticles could have a potential as antigen carriers
with intrinsic immunomodulating properties, yet low immunogenicity against the carrier itself,
for immunotherapy based vaccine.
1.1.12 Self-assembly of amphiphilic-molecule coated iron oxide nanoparticles
As mentioned earlier, surface engineering on nanoparticles play an important role on
physical and biological properties of the nanoparticles in vaccine design.88 Iron oxide
nanoparticles can be generated by several methods including co-precipitation, thermal
decomposition, microemulsion, and hydrothermal synthesis.89 Among these methods, the
thermal decomposition method has been widely used to yield large quantities, tunable size and
high-quality monodispersed iron oxide nanoparticles.87a However, the nanoparticles made by this
method are coated by a hydrophobic layer of oleic acid or oleic amine, which are not soluble in
highly polar solvents. Hence, they are not suitable for bio-applications which require good

26

solubility in water. In order to apply the hydrophobic nanoparticle in vaccine delivery platform,
surface modifications on the nanoparticles is required.
Surface modification by covalent conjugation of ligand onto the nanoparticle surface
involves multi-step chemical synthesis. For example, a catechol group can coat iron oxide
nanoparticles well due to strong chelation of catechol with iron. However, the catechol group is
easily oxidized, which requires an additional protection step before coating process.90 An
alternative approach for surface modification relies on self-assembled hydrophobic-hydrophobic
interaction between the hydrophobic layer on iron oxide surface and hydrophobic groups on
amphiphilic ligands.91 This approach is simple and does not involve chemical conjugation.
Moreover, multicomponent coating layer for multi-functional nano-vaccine can be obtained by
mixing the coating components during the coating process.
Combining the promising tumor associated antigen MUC1 with the powerful antigen
carrier of iron oxide nanoparticle, the goal of the study in this chapter was to evaluate the
amphiphilically coated iron oxide nanoparticle as a MUC1 antigen carrier platform for anticancer vaccine.
1.2 Results and discussion
1.2.1

Synthesis of magnetic NPs coated with MUC1 lipopeptides and lipoglycopeptides

We utilized the thermal decomposition method92 to prepare high-quality monodispersed
iron oxide nanocrystals in large scale and with excellent control of particle diameters.
Homogeneity in size is important in NP based vaccine design, as NP diameters can significantly
impact their interactions with the immune system as well as their trafficking.69,

93

Covalent

derivatization of NPs can be tedious. The NPs synthesized through the thermal decomposition

27

method are coated with a hydrophobic layer of oleic acid or oleic amine. This provides a
platform for amphiphilic TACA to self-assemble on the NPs through hydrophobic-hydrophobic
interactions without the need to covalently functionalize NPs. This approach is operationally
simple, and an additional advantage is that multiple components can be readily introduced onto
the NPs through self-assembly to boost immune responses.
In order to attach MUC1 onto the NPs, MUC1 peptide and glycopeptide were synthesized
and conjugated with a phospholipid chain. The MUC1 peptide bearing 20 amino acid residues
AHGVTSAPDTRPAPGSTAPP corresponding to one full length tandem repeat region was
produced using solid phase peptide synthesis through Fmoc chemistry, using 2-chlorotrityl resin
as a solid support and O-(benzotriazol-1-yl)-N,N,N’,N’-tetramethyluronium hexafluorophosphate
(HBTU) and 1-hydroxybenzotriazole (HOBt) as coupling agents (Scheme 1.1). Upon completion
of the synthesis, the MUC1 peptide 1 was cleaved off the solid phase under an acidic condition
(95:2.5:2.5, TFA:TIPS:H2O), and purified by HPLC on a C18 reverse phase column. In order to
conjugate the peptide with the lipid chain, phosphatidylethanolamine was treated with succinic
anhydride to introduce a carboxylic group to the lipid part. The carboxylic group was then
activated with N,N,N’,N’-tetramethyl-O-(N-succinimidyl)uronium tetrafluoroborate (TSTU) to
form an NHS ester (DPPE-SUC-NHS). DPPE-SUC-NHS was incubated with MUC1 peptide 1
producing lipopeptide 5, which was purified through HPLC on a reverse phase C4 column.

28

Cl

O

O

N

O

O

loading: 0.91 mmol/g
A) Fmoc-cleavage:
20% piperidine/DMF
B) Amino acid-coupling:
SPPS
5 eq. Fmoc-AA-OH,
4.9 eq. HBTU, HOBT
19X
10 eq. DIPEA/DMF
(or 2eq.
Fmoc-pTn-Thr-OH,
1.9 eq. HATU, HOAT,
4 eq. DIPEA/DMF)

OAc
AcO
O

AcO

AcHN
O
FmocHN

COOH

Fmoc-pTn-Thr-OH

Ph Ph
Ph
N
H
N

O

N
H

O

O

H
N

pR1

tBu
O

N
O

N
H

O

O

H
N
O

O

H
N

N
H

N

O
tBu

H
N

N
H

O

O

tBu
O

O

O

H
N

O

O

O
NH O O
S
HN
N
H

O

H
N

N
H

O

H
N

N
H

O

HO
O
N
H

O
HO

O

H
N

N

O

O

H
N

N
H

O

O

H
N

O

N

O

1) Fmoc-cleavage:
20% piperidine/DMF
2) Resin-cleavage:
95:2.5:2.5 TFA:TIPS:H2O
3) 5% (v/v)
hydrazine hydrate/H2O

O

H
N

N

O

O
N

O

HO
O

H
N

H
N

N
H

O

O

O
HO

NH
HN

O

O

N

O

pR2

O

Cl

O
N
H

R1
H
N

N
H

O

H
N

N

O

O
tBu

N
O

O

H
N

N

O

HN

H 2N

O

O

O
N

N
H

OH

N

O

O

O

R2

NH2

O

AHGVTSAPDT*RPAPGST*APP 1- 4

O- P O
O +
NH4

O
O H

NH2

O

phosphatidylethanolamine

1) succinic anhydride/Et3N
1:9 tBuOH:CHCl3
-

O

R1

R2

yield

1

H

H

41%

2

Tn

H

13%

3

H

Tn

13%

4

Tn

Tn

11%

OH
HO

BF4

2)
N

N O

+

N

O

O

Tn = HO

AcHN
O

O

O
O
O H

O

O- P O
O +
NH4

O
O

N
H

N

O
O

O

DPPE-SUC-NHS 61% (2 steps)
R1

HN
N
H
N

O

O

O
N
H

NH
O

-

O P O
O

H
N
O

O
N
H

H
N
O
HO

HO
O
N
H

H
N
O

O

H
N

N
O

O

O
N
H

H
N

O
N

O

O

HO
O

H
N

N

O

N
H

O

H
N
O

O
HO

O

H
N

NH
HN

H O

O

O
N
H

O

N

OH

N

O

O

R2

NH2

O

R1

R2

yield

5

H

H

31%

6

Tn

H

34%

O

DPPE-AHGVTSAPDT*RPAPGST*APP 5- 8

7

H

Tn

28%

8

Tn

Tn

25%

OH
HO
Tn = HO

O
AcHN
O

Scheme 1.1: Synthesis of MUC1 lipo-(glyco)peptides. The (Tn-)MUC1 peptides 1-4 were
synthesized by solid phase peptide synthesis followed by coupling with the activated
phospholipid DPPE-SUC-NHS to yield MUC1 lipo-(glyco)peptides 5-8.

29

In addition to the unglycosylated MUC1 peptide 5, three MUC1 lipo-glycopeptides 6-8
were synthesized using Tn substituted threonine (Fmoc-pTn-Thr-OH) (For synthesis, see
section 1.4.2) to replace the corresponding threonine building block in solid phase peptide
synthesis (Scheme 1.1). Lipo-glycopeptide 6 contains a Tn antigen in the PDT*R region only
and lipo-glycopeptide 7 bears Tn as part of the GST*A sequence, while lipo-glycopeptide 8 has
the Tn in both locations. 1-[Bis(dimethylamino)methylene]-1H-1,2,3-triazolo[4,5-b]pyridinium
3-oxid hexafluorophosphate (HATU) and 1-hydroxy-7-azabenzotriazole (HOAT) were used as
coupling agents for adding Fmoc-pTn-Thr-OH to the peptide chain. After released from the
resin, the glycopeptides 6-8 were obtained by deprotection with 5% (v/v) hydrazine hydrate
followed by HPLC purification. These lipo(glyco)peptides are useful to probe the impact of the
number and the location of Tn on immune responses.
With the lipopeptides in hand, antigen coated magnetic NPs were prepared. The oleic
acid coated iron oxide NPs (OA-IONPs) were obtained by thermal decomposition of iron(III)
acetylacetonate (Fe(acac)3) in the presence of oleic acid and oleylamine at an elevated
temperature (Figure 1.9).94 The OA-IONPs produced have a mean size of 9 nm and a narrow
polydispersity index (PDI) of 0.079 when measured as a solution in chloroform. The highly
hydrophobic surface of the OA-IONPs rendered them insoluble in water (Figure 1.10). To
facilitate the surface polarity changes and reduce NP aggregation in water, a dual solvent
exchange method95 was utilized for antigen coating (Figure 1.9). A mixture of the lipopeptide
(DPPE-MUC1) and lipopolymer (DSPE-PEG2000) was added to a solution of OA-IONPs in
chloroform. This was followed by slow addition of DMSO. Chloroform was then slowly
evaporated under vacuum to induce the assembly of the amphiphilic DPPE-MUC1 and DSPEPEG on NPs. Subsequently, DMSO was replaced with water through dialysis. Using this

30

procedure, the solvent polarity gradually increased to strengthen the hydrophobic interactions
and assemble the lipopeptide and lipo-glycopeptide onto the NP. The NPs produced were well
dispersed in water (Figure 1.10). The control particle NP-PEG without any (glyco)peptide (NP9) was also prepared using DSPE-PEG2000 coating only.
Fe(acac)3
+
Oleic acid
+
Oleylamine
+
1,2-hexadecanediol

DPPE-MUC1 5-8

Benzyl ether

DSPE-PEG

200 °C 2h then
300 °C 1h

self-assembly
OA-IONPs
NP-MUC1(Tn) NP-5-8

Figure 1.9: Synthesis of the hydrophobic OA-IONPs by the thermal decomposition method,
and monolayer self-assembly coating of the NPs by phospholipid functionalized MUC1 or
MUC1(Tn) glycopeptide.
a)

b)

c)

d)

Figure 1.10: TEM images and hydrodynamic diameters from DLS a, c) OA-IONPs; b, d) NP5.

31

The magnetic NPs were characterized. Dynamic light scattering (DLS) indicated the
hydrodynamic diameters in water were around 35 nm (Table 1.1 and Figure 1.10). The
incorporation of the glycopeptides slightly increased the sizes of the coated NPs compared with
the control NP-9 with PEG only. The zeta-potentials of all NPs are slightly negative presumably
due to the phosphate groups present.
Table 1.1: Hydrodynamic diameters and zeta potentials of the NP vaccines in PBS

NP
NP-PEG (NP-9)
NP-5
NP-6
NP-7
NP-8

Diameter
(nm)
31.8
32.2
37.6
38.1
38.4

PDI

Zeta(mV)

0.257
0.294
0.288
0.265
0.269

-2.53
-2.86
-1.83
-2.94
-2.37

To ascertain the successful immobilization of the lipopeptides, the NPs were subjected to
mass spectrometry (MS) analysis. Since lipopeptides were attached through non-covalent
interactions, the coating of the NP could be readily ionized by matrix assisted laser desorption
ionization (MALDI). The MALDI-TOF mass spectrum of NP-5 showed the desired m/z ratio of
the lipopeptide 5 (MW=2661), which was not found in that of NP-9 coated with DSPE-PEG
only (Figure 1.11a, and Figure 1.22 for NP-6, NP-7 and NP-8). For lipopeptide quantification,
the NPs were loaded onto a SDS-PAGE gel for electrophoresis, which was then visualized
through silver staining (Figure 1.11b). The intensities of the bands were compared with a
calibration curve generated based on bands from known amounts of free lipopeptides. From this
analysis, it was determined that there was an average of 23 molecules of MUC1 per NP (see
section 1.4.13 and Appendix A).

32

Figure 1.11: a) MALDI-TOF mass spectrum of NP-5 coated with lipopeptide 5 ([M+H]+ =
2662) and DSPE-PEG (top spectrum); and NP-9 coated with DSPE-PEG only (bottom
spectrum). b) SDS-PAGE of DPPE-MUC1, NP-PEG (NP-9), and NP-MUC1 (NP-5). The gel
was visualized through silver staining.

1.2.2

In vitro activation of dendritic cells and detection of NP draining into local
lymph nodes in vivo.

Dendritic cells are important antigen presenting cells, which modulate the immune
responses.96 To test DC interactions, NP-9 was incubated with bone-marrow derived dendritic
cells (BMDC). The NPs do not directly induce maturation of DCs as the expression levels of costimulatory molecules and activation markers on dendritic cells were unchanged upon NP
incubation suggesting good biocompatibility of the NPs (Figure 1.12a).

33

The immune-potentiating activities of the NP construct can be bestowed by adding an
agonist of Toll-like receptor 4 (TLR4), monophospholipid A (MPLA).97 MPLA can elicit T cell
responses and antibody isotype class switching from IgM to IgG.98 With its amphiphilic nature,
MPLA could also be immobilized onto the NPs through hydrophobic interactions.99 The addition
of MPLA to NP-9 led to enhancement of the expression of co-stimulatory molecules, such as
CD40, CD80, CD86 and MHC class II on DC as indicated by FACS analysis (Figure 1.12a).
The expressions of these co-stimulatory molecules on APC are indication of immune activation.
To confirm NP interactions with cells, NP-9 was labeled with a fluorophore fluorescein
isothiocyanate (FITC). Upon incubation with BMDC, fluorescence microscopy showed
extensive green fluorescence inside the cells indicating NP uptake (Figure 1.12b vs Figure
1.12c). Similar NP uptake by BMDC was observed with or without MPLA (Figure 1.13).

34

Figure 1.12: a) Flow cytometry results showing the expression of cellular markers of
activation state (CD40, CD80, CD86 and MHCII) of BMDC after incubation with NP-PEG
(NP-9) (red line), or NP-PEG (NP-9) + MPLA (blue line). Confocal images of BMDC
incubated with b) PBS and c) NP-9 (FITC) + MPLA. Histology of sections from d) axillary
(local) lymph nodes, and e) inguins (distant) lymph node, stained by Prussian blue.

35

Figure 1.13: Microscopic images of Prussian blue staining of BMDC after incubation with
NP-9. Left) only dendritic cells; Middle) dendritic cells incubated with NP-9 (50 μg) in PBS
12 hrs.; Right) dendritic cells incubated with NP-9 (50 μg) and MPLA (2 μg/mL) in PBS 12 h.
An important feature of our NP is that their hydrodynamic diameters are around 35 nm,
which are within the size range for ready trafficking to lymph nodes for interactions with
resident immunological cells.69 To test transport to lymph nodes, NPs were injected
subcutaneously into mice under their scruff. After 24 h, mice were sacrificed and their lymph
nodes were removed and stained with Prussian blue, a dye sensitive to the presence of ferric ions.
Histological analysis showed that the axillary (local) lymph nodes close to the injection sites
exhibited extensive blue color in the B cell follicle region (Figure 1.12d), while there was much
less blue staining in inguins (distant) lymph nodes (Figure 1.12e). This result suggested that the
NPs could drain into local lymph nodes to interact with immunological cells.
1.2.3

Immunization with MUC1 coated NPs elicited strong anti-MUC1 IgG
responses.

To evaluate the abilities of NP vaccines to induce immune responses in vivo, C57BL/6
mice were injected with NP-MUC1 (NP-5, NP-6, NP-7, NP-8) (corresponding to 20 µg of
MUC1 peptide or glycopeptide) mixed with MPLA. Booster injections were performed on days
14 and 28. To decipher the importance of various vaccine components, control groups of mice
received NP-PEG (NP-9)/MPLA, MUC1 peptide 1/MPLA or MUC1 lipopeptide 5/MPLA at the
36

same doses of NP and MUC1 respectively. Sera were collected from all mice a week after the
final immunization.
The levels of antibody elicited were analyzed by enzyme-linked immunosorbent assay
(ELISA) coated with the corresponding MUC1 or MUC1(Tn) glycopeptide. Mice (n=5)
immunized with MUC1 NP vaccines elicited both IgG and IgM antibodies (Figure 1.14a,c) with
higher IgG titers. In contrast, MUC1 peptide 1 failed to generate any appreciable amounts of
anti-MUC1 antibodies. Interestingly, immunization with MUC1 lipopeptide 5 produced some
anti-MUC1 IgG antibodies (mean titer ~ 5,032), although the titers were significantly lower than
those induced by NP-5 (mean IgG titer ~ 36,603, Figure 1.14a). This has also been supported by
a study from Boons group74a where they found that mixture of lipidated MUC1 and MPLA can
induce IgG antibody response against MUC1. The ability of lipopeptide MUC1 to generate
antibodies may be due to the effect of lipid rendering MUC1 amphiphilic. The endogenous
mouse serum albumin could absorb the amphiphilic lipopeptide and deliver the antigen into the
lymph node for B cell activation.100 The higher potency of the MUC1 NP construct to induce
antibodies could be partly attributed to the efficient trafficking of NPs into the lymph nodes due
to the suitable size regime of the NPs.69 In addition, the NPs can present the glycopeptides in a
multivalent manner rendering more efficient crosslinking of B-cell receptors and potent cellular
activation.101
The availability of NPs bearing various MUC1 glycoforms enabled us to investigate the
effects of glycosylation on antibody titers. PDT*R-MUC1 NP-6 gave the highest IgG titers
(mean titers ~ 81,402) compared to the GST*A-MUC1 NP-7 (mean titers ~ 45,526) and the
unglycosylated MUC1 NP-5 (mean titers ~ 36,603) (Figure 1.14a). Interestingly, the

37

diglycosylated MUC1 NP-8 gave significantly lower IgG titers (mean titers ~ 7,530) than NP-6
and NP-7.
The anti-carrier responses were tested next. ELISA analysis showed that significantly
lower titers (~ 200) of antibodies were generated against the NP carrier by NP-5 than those
against MUC1 (Figure 1.14b). This suggests that the immune responses were primarily focused
on MUC1.

Figure 1.14: a) Anti-MUC1 and anti-Tn-MUC1 antibody titers from individual mouse (n=5),
collected on day 35 after immunization with NP-MUC1 (NP-5) and NP-MUC1(Tn) (NP-6, NP-7
and NP-8) vaccines, compared with soluble MUC1 peptide 1 and lipo-MUC1-peptide 5. The
anti-MUC1 antibody titers were determined by ELISA coated with corresponding
(glyco)peptides 1-4. b) IgG antibody titer from individual mouse, collected on day 35 after
immunization with NP-MUC1 (NP-5), against MUC1 peptide 1 and NP-9 c) IgM/IgG antibody

38

response determined by ELISA at 3200-fold dilution of serum from mice immunized with
different vaccines. d) IgG isotypes of antibody response determined by ELISA from mice
immunized with various vaccines.
The subtypes and cross-recognition of IgG antibodies elicited against MUC1 were
analyzed. Higher levels of IgG2b over IgG1 were observed in all MUC1 vaccinated groups
(Figure 1.14d), which suggested type 1 T helper cell (Th1)-skewed immune response and the
generation of cell mediated immunity.79, 102 The elicited antibodies from mice immunized with
all NP vaccines could recognize other Tn-MUC1 glycopeptides (Figure 1.15).

Figure 1.15: Cross-recognition of various MUC1 glycoforms by sera from mice immunized
with NP-5 – NP-8.

1.2.4

The antibodies from immunized mice showed binding and complement
dependent cytotoxicity against MUC1-expressing tumor cells.

As ELISA tests binding to synthetic MUC1 (glyco)peptides, it is important that
antibodies generated can recognize MUC1 on cancer cells. This was first tested with MUC1
transfected Ag104 cells, which express MUC1 containing exclusively Tn due to the dysfunction
of Cosmc, a molecular chaperone.103
MUC1-Ag104 cells were incubated with sera from immunized mice followed by FITC
labeled anti-mouse IgG secondary antibody. FACS analysis of the tumor cells indicated that the
serum from mice immunized with MUC1 peptide 1 did not bind with the cells much (Figure
1.16a). In contrast, the MUC1 NPs induced antibodies capable of recognizing MUC1-Ag104

39

strongly. The recognition was MUC1 dependent as antibody binding to MUC1-Ag104 was much
stronger than that to Ag104 cells without MUC1 transfection (Figure 1.17a). Moreover, the
induced antibodies showed high selectivities towards MUC1-Ag104 with little binding to normal
epithelial cells (Figure 1.17b). Consistent with the ELISA results, sera from mice immunized
MUC1 NP-6 exhibited strongest binding with MUC1-Ag104 cells. When these cells were
incubated with the rabbit complement as well as the sera from MUC1 NP immunized mice, the
majority of cancer cells were killed suggesting that the anti-MUC1 antibodies induced
complement dependent cytotoxicities to cancer cells (Figure 1.16b).

Figure 1.16: Flow cytometric analysis of the binding of antibodies induced by various
constructs to a) MUC1-Ag104 cells and c) MCF-7. MTS assay analysis of complementdependent cytotoxicity of antibodies induced by various vaccines on b) MUC1-Ag104 cells
and d) MCF-7. (** P < 0.05, *** P < 0.005,)

40

Figure 1.17: Flow cytometry showing the specific binding of anti-MUC1 antibody from
immunized mice a) against wild type Ag104 (Ag104(wt)) and MUC1 transfected Ag104 cells
(Ag104(MUC1)); b) against MUC1 transfected Ag104 cells (Ag104(MUC1)) and endothelial
cells (EA.hy926).
Next, the interactions of post-immune sera with human breast cancer cell MCF-7 were
studied. MCF-7 naturally expresses MUC1 on cell surface. Antibodies elicited by MUC1 NP
vaccines were also capable of binding with MCF-7 cells (Figure 1.16c). The binding of antibody
from mice immunized with NP-6 and NP-7 showed similar affinities and higher than those
immunized with unglycosylated MUC1 NP-5 and di-Tn MUC1 NP-8 vaccines. The MUC1 NP
vaccines were also capable of inducing complement dependent cytotoxicities against MCF-7
(Figure 1.16d).
1.2.5

Discussion

While magentic NPs have seen wide biomedical applications, they have not been utilized
as TACA carriers in vaccine development. With the MUC1-magentic NP vaccines, significantly
higher IgG antibody responses were observed compared to mice immunized with MUC1 peptide
or lipopeptide. The study from Hubbell and coworkers69 emphasized the crucial effect of size for
vaccines. NPs with 25nm diameters can target lymph node residing dendritic cells, which are
more efficient in immune activation than dendritic cells in skin, but 100nm NPs are less likely to

41

drain into the lymph nodes. The size of our NPs (30-40 nm) is likely a contributing factor to high
antibody responses. The fact that anti-MUC1 IgG antibodies were induced suggests that
magnetic NP vaccines can activate helper T cells and elicit antibody isotype switching without
the need for a traditional immunogenic protein carrier or additional helper T cell epitopes.
Furthermore, the magnetic NP itself is almost non-immunogenic inducing little anti-carrier
antibodies. These attributes combined suggest that magnetic NPs can be a useful platform for
glyco-conjugate based anti-cancer vaccines joining other types of NP such as gold NPs, polymer
NPs and virus like particles.70, 104
Compared to MUC1 expressed on normal cells, MUC1 on cancer cells bear shortened Oglycans as represented by the Tn antigen. Glycosylation of MUC1 leads to conformational
changes of the peptides.105 As a result, MUC1 glycopeptides become more immunogenic.106 This
is supported by our results that lipo-glycopeptide coated NPs induced higher antibody titers and
stronger binding with MUC1 positive tumor cells than unglycosylated MUC1 coated NP-5.
As each of the tandem repeats of MUC1 proteins contains five potential glycosylation
sites, MUC1 proteins on tumor cells are hetereogenously glycosylated. How the glycan structure
can influence the humoral responses is an active area of research.107 Within our NP constructs,
addition of Tn onto the peptide sequence PDT*R showed higher antibody responses than that
with the Tn on GST*A sequence. This suggests glycosylation in PDT*R region more potently
boosted the humoral response in our NP constructs.79, 107g On the other hand, further increase of
the number of glycans on the protein may not lead to improved antibody titers as indicated from
the reduced anti-MUC1 titers elicited by NP-8 bearing two Tns. So far, whether fully
glycosylation on MUC1 enhances immunogenicity of the vaccine is still unclear.53 Our results

42

can provide guidance to selection of glycopeptide structure for future MUC1 based vaccine
studies.
The cancer cell MUC1-Ag104 exclusively expresses Tn rather than longer O-glycans.103
As a result, its MUC1 proteins are expected to be solely glycosylated with Tn. The antibodies
from immunized mice bound more strongly and exhibited higher cytotoxicity with MUC1Ag104 as compared to heterogenously glycosylated MCF-7 cells.107e, 108 This suggests a potential
approach to improve recognition of MCF-7 cells is to incorporate MUC1 glycopeptides bearing
multiple types of glycan structures.
1.3 Conclusions
Iron oxide magnetic NPs were investigated as a new antigen carrier platform for MUC1based cancer vaccine. A simple procedure was developed to immobilize lipo(glyco)peptides onto
the NPs through self-assembly without the need for covalent NP functionalization. Good MUC1
specific IgG antibody responses were produced. Besides MUC1, this strategy can be readily
applied to vaccines targeting other glycopeptides. In addition, glycolipids such as gangliosides
are another class of important TACAs. The magnetic NP approach can be potentially useful for
vaccines targeting the amphiphilic glycolipids as well.
With the large surface area of the NPs, multiple lipopeptides were incorporated. The
resulting lipopeptide NPs could drain into local lymph nodes of mice upon vaccination and
activate the immune sytem to elicit MUC1 specific antibodies. Compared to the antigen in
soluble forms, the nano-vaccine induced higher antibody titers presumbly due to the suitable
sizes of NPs and the multivalent display of antigens on particle surface. Combined with the low
antibody titers against the carrier, this highlights the advantages of the magentic NP platform.

43

Immunological evaluations of MUC1 NPs demonstrated that the number and position of
Tn in the glycopeptide chain can impact antibody titers. A single Tn in the PDT*R region gave
the highest anti-MUC1 IgG titers. The antibodies generated not only selectively recognized
MUC1 expressing tumor cells, but also mediated complement dependent cytotoxicity for tumor
cell killing. Therefore, the magnetic NPs represent a new and effective platform for the
development of TACA based synthetic anti-cancer vaccines.

44

1.4 Materials and methods
1.4.1

Materials and instrumentation

All chemicals were reagent grade and used as received from the manufacturer, otherwise
noted. 1H NMR spectra were recorded on an Agilent-500M spectrometer and processed by
software MestReNova Version 10.0.2. Peptide or lipopeptide were purified on Shimadzu (LC-8A
Liquid Chromatograph Pump, DGU-14A Degasser and SPD-10A UV-Vis Detector.

TEM

images were collected on a JEM-2200FS operating at 200 kV using Gatan multiscan CCD
camera with Digital Micrograph imaging software. Ultrathin-carbon type A, 400 mesh copper
grids for TEM were purchased form Ted Pella, Inc. Thermogravimetric analysis (TGA) was
carried on a Thermal Advantage (TA Instruments-Waters LLC) TGA-Q500 series and the
samples were burned under nitrogen. The hydrodynamic diameter and zeta potential were
assessed on Malvern Zetasizer Nano zs instrument. FACS experiments were conducted on LSR
II flow cytometer.

45

1.4.2

Synthesis of Fmoc-pTn-Thr-OH

HO OH
1) NaN3, Tf2O, Toluene/H2O
O
,
HO
OH 2) K2CO3, CuSO4
NH2
H2O/Toluene/Methanol

HO OH
O
HO
OH
NH2

Ac2O, Pyridine, DMAP
(79%, 2 steps)

AcO OAc
O
AcO
OAc
N3

SI-2

SI-1

SI-3
H2NNH2.HOAc, DMF

HO

rt, 1h (72%)

SI-6
AcO
AcO

OAc
O
N3
O

FmocHN

COOtBu

TMSOTf, DCM/Et2O
MS 4A, -30 oC, 30min
a
(36% product)

AcO OAc
O
AcO
N3 O
SI-5

FmocHN
COOtBu
SI-7
Zn dust, CuSO4
THF/Ac2O/AcOH,
rt, 10min (92%)
AcO OAc
O
AcO
AcHN
O
FmocHN
SI-8

Cl3CCN, DBU
NH

DCM (dry), rt, 1h
(75%)

AcO OAc
O
AcO
OH
N3

CCl3

SI-4

OAc
AcO
(10:1) TFA:H2O
rt, 2h (99%)

AcO

O
AcHN
O

COOtBu

FmocHN

COOH

Fmoc-pTn-Thr-OH

Figure 1.18: Synthesis of Fmoc-pTn-Thr-OH.

1,3,4,6-Tetra-O-acetyl-2-azido-2-deoxy-D-galactopyranoside (SI-3):
The synthesis procedure was modified from reported literature.109 A solution of NaN3
(8.9 g, 136.7 mmol) in water (22.5 mL) was cooled down to 0°C. Toluene (22.5 mL) was added
into the solution. The solution was stirred vigorously while adding Tf2O (4.7 mL) over a period
of 5 minutes. The reaction was left stirred for 2 hours at 0°C. Saturated NaHCO3 solution was
added until the evolution of gas stopped. The organic phase was separated and the aqueous layer
was washed with toluene twice. The combined organic phase containing TfN3 was dried over
anhydrous Na2SO4. The solution of TfN3 was used in the next step without further purification.
Galactosamine hydrochloride (3.0 g, 13.9 mmol) was dissolved in water (45 mL). K2CO3 (2.89

46

g, 20.9 mmol) and CuSO4 (20.1 mg, 0.13 mmol) were added into the reaction flask followed by
MeOH (30 mL). The TfN3 solution was added into the reaction, followed by adding MeOH until
the mixture solution became homogeneous. The reaction was left stirred at room temperature for
18 hours. The reaction residue was then co-evaporated with toluene until almost dry. The
resulting syrup was dissolved in pyridine (15 mL) followed by cooling down to 0°C. A catalytic
amount of DMAP was added into the reaction. Ac2O (45 mL) was added dropwise, and the
reaction was left stirred for 2-3 hours. The excess Ac2O was neutralized by slow addition of
MeOH. The mixture was concentrated under vacuum, diluted with DCM and washed with 1M
HCl, Na2CO3 and H2O. The organic layer was dried over anhydrous NaSO4 and then
concentrated. The crude reaction mixture was purified by column chromatography (silica gel;
1:1, EtOAc:Hexanes) to yield compound SI-3 as a white solid (4.12 g, 79% from 2 steps). The
identity of the product was confirmed by comparison with reported literature.110 1H NMR (500
MHz, CDCl3) 5.52 (d, J = 8.5 Hz, 1H), 5.36 (dd, J = 3.3, 1.0 Hz, 1H), 4.87 (dd, J = 10.8, 3.3 Hz,
1H), 4.11 (qd, J = 11.3, 6.6 Hz, 2H), 3.98 (td, J = 6.7, 1.1 Hz, 1H), 3.82 (dd, J = 10.8, 8.5 Hz,
1H), 2.18 (s, 3H), 2.15 (s, 3H), 2.05 (s, 3H), 2.02 (s, 3H).
2-Azido-2-deoxy-3,4,6-tri-O-acetyl-α,β-D-galactopyranose (SI-4):111
Hydrazine acetate (66.6 mg, 0.723 mmol) in the reaction flask was flushed with nitrogen
gas for 10 min. Compound SI-3 (270.0 mg, 0.723 mmol) dissolved in DMF was added slowly
into the reaction flask. The reaction was left stirred for an hour. Upon completion, the reaction
mixture was diluted with EtOAc, washed with water, and dried over Na2SO4. The residue was
purified by column chromatography (silica gel; 3:2 Hexanes:EtOAc) to obtain SI-4 (mixture of α
and β product as colorless oil (170 mg, 72%, α : β = 3:2 estimated based on NMR spectrum).
Spectral analysis of the product compared with reported literature111 confirmed the identity of the

47

product. 1H NMR (500 MHz, CDCl3) The NMR spectrum is of the mixture of α and β product. δ
5.44 (dd, J = 3.2, 1.3 Hz, 1H (α)), 5.42 – 5.36 (m, 2H (α)), 5.32 (dd, J = 3.3, 1.0 Hz, 1H (β)),
5.27 (s, 1H), 4.80 (dd, J = 10.8, 3.3 Hz, 1H (β)), 4.68 (dd, J = 7.9, 4.2 Hz, 1H (β)), 4.44 (td, J =
6.5, 0.9 Hz, 3H (α)), 4.15 – 4.01 (m, 2H (α/β)), 3.89 (td, J = 6.5, 1.1 Hz, 1H (β)), 3.73 (dd, J =
11.0, 3.4 Hz, 1H (α)), 3.64 (dd, J = 10.9, 7.9 Hz, 1H (β)), 3.23 (d, J = 2.6 Hz, 1H (α)), 2.15 –
2.13 (m, 3H (β)), 2.13 (d, J = 3.0 Hz, 3H (α)), 2.04 (dd, J = 3.9, 1.1 Hz, 12H (α/β).
O-(3,4,6-Tri-O-acetyl-2-azido-2-deoxy-D-galactopyranoside) trichloroacetimi-date (SI5):
Compound SI-4 (5.0 g, 15.1 mmol) and 1,8-diazabicyclo[5.4.0]undec-7-ene (DBU) were
dissolved in dry DCM under nitrogen atmosphere. Trichloroacetonitrile (15.1 mL, 150.93 mmol)
was added drop wise into the reaction flask. The reaction was stirred at room temperature for an
hour. The reaction mixture was concentrated and purified by flash column chromatography
(silica gel; 4:1 to 2:1 Hexane:EtOAc) to obtain compound SI-5 as colorless oil (5.36 g, 75%).
Spectral analysis of the product compared with reported literature111 confirmed the identity of the
product. 1H NMR (500 MHz, CDCl3) δ 8.79 (s, 1H), 6.49 (d, J = 3.6 Hz, 1H), 5.52 (dd, J = 3.2,
1.3 Hz, 1H), 5.35 (dt, J = 8.6, 4.3 Hz, 1H), 4.40 (td, J = 6.6, 0.9 Hz, 1H), 4.19 – 3.94 (m, 3H),
2.15 (s, 3H), 2.05 (s, 3H), 1.98 (s, 3H).
N-(Fluoren-9-ylmethoxycarbonyl)-O-(3,4,6-tri-O-acetyl-2-azido-2-deoxy-α-Dgalactopyranosyl-L- threonine tert-butyl ester (SI-7):
The synthesis procedure was modified from reported literature112. Trichloroacetimidate
SI-5 (5.36 g, 11.27 mmol) and N-Fmoc-O-tBu-threonine SI-6113 (3.6 g, 9.39 mmol) were mixed
in the reaction flask with freshly activated molecular sieves 4A (10 g) under nitrogen gas.
Anhydrous DCM:Et2O (1:1, 120 mL) was added to dissolved the mixture, and the solution was

48

left stirred at -30°C for 30 min. TMSOTf (0.297 mL, 1.925 mmol) was added dropwise into the
reaction. The reaction was left stirred at 30°C for an hour. Upon monitoring the reaction, if there
was some starting material SI-6 left, 0.1 more eq. of TMSOTf was further added and the reaction
was allowed to proceed for another hour. The temperature of the reaction was then carefully
increased up to ‒10°C. Upon completion, diisopropylethylamine (DIPEA) was added to quench
the reaction. The reaction was diluted with DCM and washed with 0.1 M HCl and then water.
The organic layer was dried over Na2SO4 and then concentrated. The crude product was purified
by column chromatography (silica gel; 3:1 EtOAc:Hexane) to yield SI-7 (2.6 g, 36%). Spectral
analysis of the product compared with reported literature114 confirmed the identity of the product.
1

H NMR (500 MHz, CDCl3) δ 7.77 (d, J = 7.5 Hz, 2H), 7.63 (d, J = 7.2 Hz, 2H), 7.40 (td, J =

7.5, 2.4 Hz, 2H), 7.35 – 7.28 (m, 2H), 5.64 (d, J = 9.4 Hz, 1H), 5.47 (d, J = 2.6 Hz, 1H), 5.34
(dd, J = 11.2, 3.2 Hz, 1H), 5.11 (d, J = 3.6 Hz, 1H), 4.35 (dddd, J = 23.3, 15.5, 13.1, 6.9 Hz, 6H),
4.16 – 4.04 (m, 3H), 2.16 (d, J = 7.1 Hz, 3H), 2.07 (d, J = 9.2 Hz, 3H), 2.06 – 2.02 (m, 3H), 1.52
(d, J = 17.3 Hz, 9H), 1.37 (t, J = 13.7 Hz, 3H), 1.29 – 1.22 (m, 1H).
N-(Fluoren-9-ylmethoxycarbonyl)-O-(3,4,6-tri-O-acetyl-2-acetamido-2-deoxy-α-Dgalactopyranosyl-L-threonine tert-butyl ester (SI-8):114
Compound SI-7 (5 g, 7.15 mmol) was dissolved in 3:2:1 of THF:Ac2O: AcOH (120 mL).
Zinc dust (5.9 g, 89.35 mmol) was added and then 11 mL of saturated aq. CuSO4 was added to
activate zinc. The reaction was stirred at rt for about half an hour. After completion as monitored
by TLC, the zinc dust was removed by filtering the reaction mixture through Celite®. The filtrate
was coevaporated with toluene to concentrate the crude product. The crude product was purified
by column chromatography (silica gel; 1:1 EtOAc:Hexanes) to yield SI-8 (4.68 g, 92%). Spectral
analysis of the product compared with reported literature114 confirmed the identity of the product.

49

1

H NMR (500 MHz, CDCl3) δ 7.78 (d, J = 7.5 Hz, 2H), 7.64 (d, J = 6.9 Hz, 2H), 7.41 (td, J =

7.4, 2.9 Hz, 2H), 7.34 (dt, J = 11.9, 6.0 Hz, 2H), 5.89 (d, J = 9.6 Hz, 1H), 5.41 (d, J = 10.2 Hz,
2H), 5.09 (d, J = 8.8 Hz, 1H), 4.90 (d, J = 3.2 Hz, 1H), 4.63 (t, J = 8.9 Hz, 1H), 4.52 – 4.38 (m,
2H), 4.31 – 4.02 (m, 6H), 2.17 (s, 3H), 2.04 (s, 3H), 2.00 (s, 6H), 1.53 – 1.41 (m, 9H), 1.33 (d, J
= 6.3 Hz, 3H).
N-(Fluoren-9-ylmethoxycarbonyl)-O-(3,4,6-tri-O-acetyl-2-acetamido-2-deoxy-α-Dgalactopyranosyl-L- threonine (Fmoc-pTn-Thr-OH):
The synthesis procedure was modified from reported literature112. 10:1 TFA:H2O (10
mL) was added dropwise into compound SI-8 (4.7 g, 6.44 mmol) at rt. The reaction was stirred
for 2 hours. The mixture was coevaporated with toluene to remove the excess TFA and water.
The crude product was purified by column chromatography (silica gel, 5:1 DCM:MeOH) to yield
the product Fmoc-pTn-Thr-OH (4.27 g, 99%). Spectral analysis of the product compared with
reported literature112 confirmed the identity of the product. 1H NMR (500 MHz, CD3OD) δ 7.85
(d, J = 7.5 Hz, 2H), 7.72 (t, J = 8.1 Hz, 2H), 7.46 – 7.39 (m, 2H), 7.35 (tdd, J = 7.4, 4.7, 0.9 Hz,
2H), 5.42 (t, J = 6.6 Hz, 1H), 5.10 (dd, J = 11.5, 3.2 Hz, 1H), 4.96 (t, J = 8.0 Hz, 1H), 4.62 (dt, J
= 13.8, 6.9 Hz, 1H), 4.54 – 4.47 (m, 1H), 4.46 – 4.37 (m, 2H), 4.34 – 4.24 (m, 3H), 4.18 – 4.08
(m, 2H), 3.98 (d, J = 27.1 Hz, 1H), 2.16 (d, J = 6.3 Hz, 3H), 2.10 – 2.03 (m, 3H), 2.03 – 1.91 (m,
6H), 1.33 – 1.22 (m, 3H).
1.4.3

Synthesis of MUC1 1 and Tn-MUC1 2-4

The MUC1 lipopeptide was derived from conjugation of phospholipid (DSPE-SUCNHS) and the tandem repeat MUC1 peptide. The MUC1 peptide was synthesized using Fmocchemistry based solid phase support peptide synthesis, starting from a 2-chlorotrityl resin
preloaded with Fmoc-proline. The N-terminal protecting group, Fmoc-, was de-protected by 20%

50

piperidine in DMF. The amino acid coupling was carried out with Fmoc amino acids (5 eq.)
using HBTU/HOBt (4.9 eq.) and DIPEA (10 eq.), or Fmoc-Tn building block Fmoc-pTn-ThrOH (2eq.) using HATU/HOAT (1.9 eq.) and DIPEA (4 eq.). The peptide was cleaved from resin
by TFA/TIS/H2O=95/2.5/2.5 for 30 min. The excess TFA was evaporated out, peptide was
precipitated by diethyl ether and centrifuged to pallet the peptide precipitation. The peptide was
further reprecipitated three times. To remove the acetyl protecting group of the Tn, the crude
peptide was treated with 5% (v/v) hydrazine acetate for 2 hours. The crude reaction was
neutralized to pH 7. The deprotected peptide was then purified by HPLC, using reverse phase
column SUPERCOSIL LC18, 25cm x10 mm 5 µm with gradient solvent CH3CN and H2O (0.1%
TFA) gradient 0-22% in 25min and to 100% in 10min. The product was identified by MALDITOF.
1.4.4

Purification and characterization of (glyco)-peptides 1–4

1: HRMS: m/z calc. for C80H127N25O28: 1887.0430; found: 1887.9166 [M+H]+.
2: HRMS: m/z calc. for C88H140N26O33: 2090.2370; found: 2091.6226 [M+H]+.
3: HRMS: m/z calc. for C88H140N26O33: 2090.2370; found: 2091.4449 [M+H]+.
4: HRMS: m/z calc. for C96H153N27O38: 2293.4310; found: 2293.9621 [M+H]+.

51

HN
N
O
H 2N

N
H

H
N

O

H
N

N
H

O

HO
O
N
H

O
HO

H
N

O

H
N

N
O

O

OH
H
N

O
N
H

O
N

O

H
N

N

O

HO
O
N
H

O

O
HO

1

SPD-10Avp Ch1-220nm
MUC1_no_Tn_#1_noFmoc_007_r

H
N

O

O
N
H

O
HO

N

OH

N

O

O

NH
HN

800

O

H
N

NH2

(Molecular Weight: 1887.0430)

SPD-10Avp Ch2-260nm
MUC1_no_Tn_#1_noFmoc_007_r

Solvent B Conc.
120

Retention Time

29.400

700

600

100

80
500

mVolts

300

40

200

20

100

0

0

Percent

60

400

-20

-100
-40

0.0

2.5

5.0

7.5

10.0

12.5

15.0

17.5

20.0

22.5

25.0

27.5
Minutes

30.0

32.5

35.0

37.5

40.0

42.5

45.0

47.5

50.0

52.5

55.0

Figure 1.19: HPLC chromatogram and MALDI-TOF mass spectrum of the MUC1 peptide 1,
and the MUC1 glycopeptide 2, 3 and 4.

52

Figure 1.19: (Cont’d)
HO

O

HO
HN
N
O
H2N

N
H

H
N
O

O
N
H

H
N
O
HO

HO
O
N
H

H
N

O
N

AcHN
O

O

H
N

N
H

O

O

OH

H
N

O

H
N

N

O

O

H
N

N

O

O

HO
O
N
H

O
HO

SPD-10Avp Ch1-220nm
071312_run_H_MUC1_2_OH#2004
071312_run_H_MUC1_2_OH#2004.dat

O
HO

O

O
N
H

N

OH

N
O

O

NH
HN

2

H
N

NH2

(Molecular Weight: 2090.2370)

SPD-10Avp Ch2-260nm
071312_run_H_MUC1_2_OH#2004
071312_run_H_MUC1_2_OH#2004.dat

20000

Solvent B Conc.
Running HMUC1OH_060512_2.met

17500

2000

15000
1500

10000
1000
7500

500

5000

2500
0
0
0.0

2.5

5.0

7.5

10.0

12.5

15.0

17.5

20.0

22.5
Minutes

25.0

53

27.5

30.0

32.5

35.0

37.5

40.0

42.5

mVolts

mVolts

12500

Figure 1.19: (Cont’d)
HN
N
O
H2N

H
N

N
H

O
N
H

O

H
N

HO
O
N
H

O
HO

O

H
N

O

H
N

N

N
H

O

O

OH
H
N

O
N

O

3

2.947

H
N

N
O

HO
O
N
H

O

SPD-10Avp Ch2-260nm
MUC1_1,0_Tn_#3_006_r

O

H
N
O

O
N
H

O

N

OH

N

O

O

NHAc

NH
HN

SPD-10Avp Ch1-220nm
MUC1_1,0_Tn_#3_006_r

O

O

HO

1600

H
N

O

NH2

OH

HO OH

(Molecular Weight: 2090.2370)

Solvent B Conc.
120

1400
100
1200
80

26.987

1000

60

40
600
20
400
0
4.093

200

-20
0
-40
-200
0.0

2.5

5.0

7.5

10.0

12.5

15.0

17.5

20.0

22.5

25.0
Minutes

27.5

54

30.0

32.5

35.0

37.5

40.0

42.5

45.0

47.5

50.0

Percent

mVolts

800

Figure 1.19: (Cont’d)
HO

O

HO
HN
N
O
H 2N

O

H
N

N
H

H
N

N
H

O

HO
O

O
HO

N
H

H
N

O

H
N

N

AcHN
O

O

N
H

O

O

OH

H
N

O
N

O

H
N

N

O

O

HO
O
N
H

O
HO

4

SPD-10Avp Ch1-220nm
MUC1_1,2_Tn_#4_noFmoc_005_r

O

O

O

H
N

N
H

O

N

OH

N
O

O

NHAc

NH
HN

2500

O

H
N

O

NH2

OH

HO OH

(Molecular Weight: 2293.4310)

SPD-10Avp Ch2-260nm
MUC1_1,2_Tn_#4_noFmoc_005_r

Solvent B Conc.
120

Retention Time

20.653

2250

2000

100

1750

80

1500
60

40
1000

20

750

500
0
250
-20
0
-40

-250
0

2

4

6

8

10

12

14

16

18

20
Minutes

22

55

24

26

28

30

32

34

36

38

40

Percent

mVolts

1250

1.4.5

Synthesis of lipo-(Tn)-peptide (DPPE-MUC1 5 and DPPE-Tn-MUC1 6-8

The phospholipid was linked to succinic acid linker by reaction of DPPE with succinic
anhydride and 2 eq. of Et3N. The carboxylic acid group of the succinic linker was then activated
by TSTU (N,N,N′,N′-tetramethyl-O-(N-succinimidyl)uranium tetrafluoroborate) to provide
compound DSPE-SUC-NHS. The activated phospholipid was coupled to N-terminal of the
purified (glyco)peptide 1-4. The lipopeptide was purified by HPLC, using C4-column (Kromasil;
5μm, 4.6x150 mm 5 μm; part # PSL847277), with gradient 30% isopropanol in H2O (0.1% TFA)
to 100% in 40 minutes.
1.4.6

Purification and characterization of lipo-(glyco)-peptide 5–8

5: HRMS: m/z calc. for C121H202N26O38P: 2660.0653; found:2661.2769 [M+H]+.
6: HRMS: m/z calc. for C129H215N27O43P: 2863.2593; found:2864.1654 [M+H]+.
7: HRMS: m/z calc. for C129H215N27O43P: 2863.2593; found:2864.2926 [M+H]+.
8: HRMS: m/z calc. for C137H228N28O48P: 3066.4533; found:3067.2689 [M+H]+.

56

HN

O

O

N
H

N
H

O
P
O

O

O

H
N

N
H

O

HO
O

H
N

N
H

O
HO

H
N

O
N

OH
H
N

O
N
H

O

O

H
N

N

O

O

O

5

HO
O
N
H

O

H
N

O
N

N
H

O
HO

O

OH

N
O

NH
HN

NH2

(Molecular Weight: 2660.07)

SPD-10Avp Ch1-220nm
DPPE_suc_MUC1_noTn_1_isopropanol_H2O_30-90% in 30min.met007reinj

mVolts

N

O

O

O

Area

1800

H
N

O

H O

O

O

HO

O

-

H
N

SPD-10Avp Ch2-260nm
DPPE_suc_MUC1_noTn_1_isopropanol_H2O_30-90% in 30min.met007reinj
Area

Solvent B Conc.

1800

1600

1600

1400

1400

1200

1200

1000

1000

800

800

600

600

400

400

200

200

0

mVolts

N
O

H
N

0
0

5

10

15

20

25

30
Minutes

35

40

45

50

55

Figure 1.20: HPLC chromatogram and MALDI-TOF mass spectrum of the lipopeptide 5, and
lipo-glycopeptide 6, 7 and 8.

57

Figure 1.20: (Cont’d)
OH
HO
O

HO
HN

N
H

O
P

O

H
N

N
H

O

O
HO

HO
O
N
H

H
N

H
N

N
O

O

O

O
N
H

H
N

O

H
N

N

O

O

H
N

N

O

O

HO
O
N
H

O
HO
HN

O

6

H
N
O
HO

O

O
N
H

N

O

NH2

(Molecular Weight: 2863.26)

SPD-10Avp Ch1-220nm
DPPE_suc_MUC1_2_isopropanol_H2O_30-90% in 30min.met003reinj

SPD-10Avp Ch2-260nm
DPPE_suc_MUC1_2_isopropanol_H2O_30-90% in 30min.met003reinj

300

250

250

200

200

150

150

100

100

50

50

0
0.0

0
2.5

5.0

7.5

10.0

12.5

15.0

17.5

OH

N

O

NH

H O
O

300

O

O

-

O

O

mVolts

O

N
H

O

H
N

20.0

22.5

25.0
Minutes

27.5

58

30.0

32.5

35.0

37.5

40.0

42.5

45.0

47.5

Solvent B Conc.

mVolts

N
O

H
N

O

AcHN

Figure 1.20: (Cont’d)
HN
H
N

O

N
H

O
P

O

H
N

N
H

O

O
HO

HO
O
N
H

H
N

H
N

N

O
N
H

O

O

OH
H
N

O

H
N

N

O

O

H
N

N

O

HO
O
N
H

O

O

HN
O

7

N

N
H

O
OH

NH2

OH
OH

(Molecular Weight: 2863.26)

SPD-10Avp Ch1-220nm
DPPE_suc_MUC1_3_isopropanol_H2O_30-90% in 30min.met006reinj

SPD-10Avp Ch2-260nm
DPPE_suc_MUC1_3_isopropanol_H2O_30-90% in 30min.met006reinj

450

400

350

350

300

300

250

250

200

200

150

150

100

100

50

50

0

0
2.5

5.0

7.5

10.0

12.5

15.0

17.5

O

O

400

0.0

OH

N

O

NHAc

NH

H O

O

O

H
N

O
HO

O

450

O

O

-

O

O

mVolts

O

N
H

O

H
N

20.0

22.5
Minutes

25.0

59

27.5

30.0

32.5

35.0

37.5

40.0

42.5

Solvent B Conc.

mVolts

N
O

Figure 1.20: (Cont’d)
OH
HO

N
H

O

O

P
O

O

H
N

N
H

N
H

O

H
N

N
H

O
HO

H
N

O

H
N

N
O

O

-

O

O

O

H
N

N
H

O

O

H
N

N

O

HO
O
N
H

O

O

HN
O
O

8

O

N
H

O
NHAc
OH

NH2

OH
OH

SPD-10Avp Ch2-260nm
DPPE_MUC1_4_isopropanol_H2O_30-90% in 30min.met006reinj

Solvent B Conc.
200

180

160

160

140

140

120

120

100

100

80

80

60

60

40

40

20

20

0

0
10

15

20

O

O

180

5

N

(Molecular Weight: 3066.45)

SPD-10Avp Ch1-220nm
DPPE_MUC1_4_isopropanol_H2O_30-90% in 30min.met006reinj

0

O

O

H
N

NH

H O

200

H
N

N

HO

O

O

mVolts

O

O

H
N

AcHN

HO
O

25
Minutes

30

60

35

40

45

50

mVolts

N
O

O

HO

HN

OH

N
O

1.4.7

Preparation of iron oxide NPs (OA-IONPs)

A mixture of iron (III) acetylacetonate [Fe(acac)3], 1,2-hexadecanediol, oleic acid, oleyl
amine in benzyl ether were stirred under a flow of nitrogen. The mixture was heated to 200°C for
2 hours, followed by refluxing (300 °C) for 1 hour. The black mixture was allowed to cool down
to room temperature, and the excess starting materials were washed out by adding ethanol into
the mixture followed by external magnetic separation. The iron oxide NPs dispersed in toluene
were centrifuged at 6,000 rpm to further remove the large particulates, and the supernatant
containing OA-IONPs were collected (5 mg/mL).
1.4.8

The number of OA-IONP nanoparticle was estimated by TEM and TGA
analysis.

The lattice volume of magnetite is 592 Ã…3 and each lattice composes of 8 Fe3O4
molecules. The average diameter of OAIONP determined from TEM is 8.16 nm. Assuming the
OAIONP is a sphere, the number of lattices in one OAIONP particle is 153 and each OAIONP
particle contains 1,222 molecules of Fe3O4 (MW = 232). Therefore, 1 particle has the mass of
3.24×10-19 g. From thermogravimetric analysis (TGA) measurements, OAIONPs have 33.17 %
weight change (Figure S6), implying that the metal core (Fe3O4) weight accounted for 66.8% of
total weight. Therefore, on average, there are (0.6683/3.24×10-19) = 2.06 × 1018 particles in 1 g
sample.

61

Figure 1.21: TGA curve of OA-IONP.

1.4.9

Preparation of NP5-9

The lipopolymer (DSPE-PEG, 2 mg) dispersed in 100 μl chloroform was mixed with
OA-IONPs (1 mg), which were pre-dissolved in THF. The lipopeptide or lipoglycopeptide (1
mg) dissolved in DMSO (50 μl) was added into the mixture. DMSO (4 mL) was slowly added
into the mixture while shaking. The incubated mixture was left sonicated for 30 min, then, all
low boiling point solvents, chloroform and THF, were completely evaporated under vacuum for
2 hours. Water (20 mL) was slowly added into the vial while shaking. DMSO and excess starting
materials were removed by centrifugal filter (100 kD cut off), and washed with water 5 times.
The solution of NPs was finally filtered through 0.22 μm filter to remove any large particles. The
NPs coated only with lipopolymer (NP-PEG, NP-9), used as a control, were synthesized by the
same procedure. For NP-PEG-FITC used in dendritic cell uptake experiment, the NPs were
coated with the same procedure as NP-PEG, but DSPE-PEG(2000)-NH2 was used instead. The
coated NPs was subsequently reacted with FITC in water. The excess FITC was washed

62

extensively by centrifugal filter (100 kD cut off). The FITC conjugated NPs were then resuspended in PBS.
1.4.10 Verification of the glyco-lipopeptide (DSPE-MUC1(Tn) 6, 7 and 8 on the
coated nanoparticles
The existence of glyco-lipopeptide on the coated nanoparticles was determined by
MALDI-TOF.

Figure 1.22: MALDI-TOF mass spectrum of glyco-lipopeptide coated OAIONP; NP-6, NP7, NP-8 indicate the present of the glyco-lipopeptide on each nanoparticle. The clustered
peaks in the base line represent the coating DSPE-PEG.

63

Figure 1.22: (Cont’d)

64

1.4.11 Quantification of the lipopeptide (DSPE-MUC1) on the coated nanoparticles
The quantification of lipopeptide on the nanoparticles was determined by the intensity of
silver staining on SDS-PAGE from image analysis by ImageJ software. (Data are shown in
APPENDIX A)
1.4.12 The ratio of DPPE-MUC1 and DSPE-PEG coated on each nanoparticle
determined by Malachite Green phosphate assay
Since each of all coating materials is composed of a phosphate group, the amount of
phosphate, determined by Malachite Green phosphate assay kit, could refer to the amount of the
coating molecules. Malachite green phosphate detection kit (Sciencell Research Lab) was used to
quantify the phosphate concentration in solution.91 To prepare phosphate solution, 500 μg of
nanoparticle sample was dissolved in 500 μL of 70% perchloric acid. The solution was heated at
160 °C for 20 minutes. 10M NaOH was added into the solution up to 2 mL to neutralize
perchloric acid. The prepared solution was analyzed by the assay kit following the manufacturer
instruction. It was determined that 1 g of nanoparticles have 0.2 mmol of phosphate. Since 1 g
nanoparticles have 0.08 mmol of DPPE-MUC1 (determined by silver staining), the amount of
DSPE-PEG on the nanoparticles was determined to be 0.12 mmol. Therefore, the estimated ratio
of DPPE-MUC1 and DSPE-PEG coating on each nanoparticle was about 2:3.
1.4.13 Elemental analysis for estimation of the number of DPPE-MUC1 molecules
coated on a single nanoparticle
Assuming that iron atom content in metal core of the nanoparticle is not changed after
coating, the iron content of OAIONP after coating, analyzed by Inductively Coupled Plasma
Analysis (ICP), was compared with that of uncoated nanoparticles, of which the number of
particles had been determined by TGA analysis. The normalized iron content was calculated to
estimate the number of nanoparticle after coating. The number of DSPE-MUC1 molecules

65

(estimated by SDS-PAGE method) divided by a number of iron oxide nanoparticles (estimated
by ICP) gave the number of DPPE-MUC1 molecules coated on a single nanoparticle.
1.4.14 Bone marrow derived dendritic cell culture
Dendritic cells (DCs) were derived from bone marrow cells of C57BL/6 mice as
described by Lutz.115 Briefly, bone marrow was collected from the tibias and femurs. Red blood
cells were depleted by ACK lysing buffer (Life Technologies). The bone marrow cells (2.5 × 106
cells) were collected and cultured in 100-mm Petri dishes containing RPMI 1640 medium (10
mL) supplemented with 10% heat-inactivated FBS, 50 μM 2-mercaptoethanol, 1% antibioticantimicotic, and 20 ng/mL mouse recombinant granulocyte-macrophage colony-stimulating
factor (GM-CSF, Peprotech). After 9 days, non-adherent and loosely adherent cells (imDCs)
were harvested, washed, and used for in vitro experiments. To determine the NP uptaken by
dendritic cells, DCs were incubated with 50 μg/mL NP-PEG-FITC, MPLA 2 µg/mL in a 8-well
plate culture at a density of 2 × 104 cells per well at 37 °C for 12 h. After washing, the cells were
fixed with 4% paraformaldehyde for 20 min at room temperature. The fixed cells were observed
under fluorescent microscope. The NP uptaken by dendritic cells was also confirmed by Prussian
blue staining after incubation of DCs with NP-9 (50 μg) with or without MPLA (2 μg/mL).
(Figure 1.13)
1.4.15 Flow cytometry of dendritic cellular marker expression
After incubation of NP-PEG (50 μg) with 2 μg/mL MPLA, DCs were stained with
allophycocyanin (APC)-conjugated anti-mouse CD11c monoclonal antibody for 30min on ice to
label the cell membrane. After washing twice with FACs buffer (1% BSA + 0.1% NaN3/PBS),
DCs were further stained with R-phycoerythrin (PE)-conjugated anti-mouse CD40, or CD80, or
CD86, or I-Ab monoclonal antibodies 30min on ice. The cells were washed again twice with
66

FACS buffer, re-suspended in FACS buffer, and detected with a LSR II instrument. Data
analysis was done with Flowjo software. (All monoclonal antibodies in this experiment are from
BD Pharmingen, San Diego, CA, USA)
1.4.16 Histology of the NPs in the targeted lymph node
8 week- C57BL/6 mice were injected subcutaneously under scruff with NP-9 (500 μg)
and MPLA (20 μg) in PBS (100 μl). Approximately 24 hour post-injection, the axillary and
inguins lymph nodes were excised. The lymph nodes tissue was sent to Investigative
HistoPathology Laboratory (Michigan State University, MI, USA) where histologic slides were
prepared and analyzed by Prussian blue iron stain on a nuclear fast red background.
1.4.17 Mouse immunization
Pathogen-free female C57BL/6 mice age 7-9 weeks were obtained from breeding and
cared for in the University Laboratory Animal Resources facility of Michigan State University.
All animal care procedures and experimental protocols have been approved by the Institutional
Animal Care and Use Committee (IACUC) of Michigan State University. Mice (5 mice each
group) were immunized subcutaneously under scruff with NP or soluble vaccine in 100μl PBS
on days 0, 14 and 28. Serum samples were collected on day 0 (before immunization) and day 35.
1.4.18 ELISA
A 96-well nunc microtiter plate was coated with 10 μg/mL, 100 μl/well of purified
MUC1 or glyco MUC1 peptides in 0.05 M carbonate buffer (pH 9.6) and incubated at 4°C
overnight. The plate was then washed four times with PBS/0.5% Tween-20 (PBST), followed by
blocking with 1% (v/v) BSA in PBS at room temperature for 1 hour. Subsequently, the plates
were washed four times with PBST. Then, the plates were incubated with 100 μl of diluted

67

mouse antisera in 0.1% BSA/PBS at 37°C for 2 hours, followed by washing four times with
PBST. Bound antibodies were detected with 1:2000 diluted horseradish peroxidase (HRP)
conjugated goat-anti-mouse IgG, or IgG1, or IgG2b, or IgG2c, or IgG3 at 37 °C for 1 hour,
followed by washing four times with PBST. Then, plates were incubated with TMB substrate for
15 min. The reaction was stopped with 2M H2SO4 (50 µL), and the absorbances were measured
at 450 nm using a microplate autoreader (BioRad). The titer was determined by regression
analysis with log10 dilution plotted with optical density. The titer was calculated as the highest
dilution that gave OD = 0.3.
1.4.19 Cell culture
MUC1-Ag104: a kind gift from Prof. Dapeng Zhou (University of Texas MD Anderson
Cancer Center): culture medium: DMEM, 10% FBS, 100 U/mL/100 ug/mL Pen/Step (All from
Sigma Aldrich); MCF-7: a kind gift from Prof. Olivera J. Finn (University of Pittsburgh) Eagle’s
minimum essential medium with L-glutamine (2 mM), non-essential amino acids and sodium
pyruvate, bovine insulin (10 µg/mL), and FBS (10%), 100 U/mL/100 µg/mL Pen/Step.
EA.hy926(Endothelial cell): culture medium: DMEM, 10% FBS, 100 U/mL/100 ug/mL
Pen/Step (All from Sigma Aldrich)
1.4.20 Flow cytometry analysis
wt-Ag104, EA.hy926, MUC1-Ag104 or MCF-7 cells (3 × 105 cells) were incubated with
1/20 dilution antisera in PBS from different groups of immunized mice for 30 minutes on ice.
The cells were washed twice with FACS buffer (1% BSA + 0.1% NaN3/PBS) and incubated with
a 1:50 diluted goat anti-mouse IgG labelled with FITC (BioLegend, 405305) for 30 min on ice.
The cells were washed again twice with FACS buffer, re-suspended in FACS buffer, and
detected with a LSR II instrument. Data analysis was performed with Flowjo software.

68

1.4.21 Complement dependent cytotoxicity
Complement dependent cytotoxicity on MUC1-Ag104 and MCF-7 tumor cells was
determined by MTS assay. MUC1-Ag104 or MCF-7 7000 cells/well were incubated on ice with
1/20 dilution in 100μl PBS of antisera from different groups of immunized mice. After removing
the unbound antisera through washing, rabbit sera 1/5 dilution in 100 μl culture medium were
added, then incubated at 37°C for 8 hours. MTS (CellTiter 96® AQueous One Solution Cell
Proliferation Assay; Promega, 20 μl) was added into each well and further incubated at 37°C for
4 hours. The optical absorption of the MTS assay was measured at 490nm. Only cells cultured in
medium were used as positive control (maximum OD) and culture medium as a negative control
(minimum OD). All data were done in four repeats. The cytotoxicity were calculated by the
formula: cytotoxicity (%) = (OD positive control ‒ OD experimental)/(OD positive control ‒ OD
negative control) x 100.

69

APPENDICES

70

APPENDIX A

Quantification of the lipopeptide (DSPE-MUC1) on the coated nanoparticles

Lane
2
3
4
5
6
7
8
9

sample
load (μL) quantity (μg)
5 (0.1g/L)
2
0.2
5 (0.1g/L)
6
0.6
5 (0.1g/L)
10
1
5 (0.1g/L)
14
1.4
5 (0.1g/L)
18
1.8
NP-9
18
NP-5
4
0.72
NP-5
8
1.47

peak area
1331.184
15279.246
20401.439
25187.095
27770.924
17062.489
25030.217

percent 5 μg/μL
1.008
11.57
15.448
19.072
21.029
12.92
0.18
18.953
0.18

Figure 1.23: Quantification of the lipo(glyco)peptide on the coated nanoparticles.

71

Figure 1.23: (Cont’d)

Lane sample
2
3
4
5
6
7
8
9

6 (0.1g/L)
6 (0.1g/L)
6 (0.1g/L)
6 (0.1g/L)
6 (0.1g/L)
NP-9
NP-6
NP-6

load
(μL)
2
6
10
14
18
18
4
8

Quantity
(μg)
0.2
0.6
1
1.4
1.8
1.42
2.03

peak area

percent 6 μg/μL 6 μg/μL(Avg)

1727.205
10593.903
13205.974
16790.823
19940.087
16889.409
21688.258

1.713
10.506
13.097
16.652
19.775
16.749
21.509

72

0.36
0.25

0.30

Figure 1.23: (Cont’d)

Lane

sample

2
3
4
5
6
7
8
9

7 (0.1g/L)
7 (0.1g/L)
7 (0.1g/L)
7 (0.1g/L)
7 (0.1g/L)
NP-9
NP-7
NP-7

load Quantity
7
7
peak area percent
(μL)
(μg)
μg/μL μg/μL (Avg)
2
0.2
602.335
0.841
6
0.6
7075.205 9.881
10
1
10443.861 14.586
14
1.4
13043.518 18.216
18
1.8
14198.589 19.83
18
2
1.26
11530.811 16.104 0.63
0.54
4
1.79
14708.882 20.542 0.45

73

Figure 1.23: (Cont’d)

Lane

sample

2
3
4
5
6
7
8
9

8 (0.1g/L)
8 (0.1g/L)
8 (0.1g/L)
8 (0.1g/L)
8 (0.1g/L)
NP-9
NP-8
NP-8

load Quantity
8
8
peak area percent
(μL)
(μg)
μg/μL μg/μL (Avg)
2
0.2
2762.033 3.685
6
0.6
7449.004 9.939
10
1
10266.075 13.697
14
1.4
13059.146 17.424
18
1.8
16940.995 22.603
18
2
1.00
10066.953 13.432 0.50
0.44
4
1.51
14405.903 19.221 0.38

74

APPENDIX B

NMR spectra

Figure 1.24: 1H NMR spectrum of SI-3.

75

Figure 1:25: 1H NMR spectrum of SI-4.

76

Figure 1.26: 1H NMR spectrum of SI-5.

77

Figure 1.27: 1H NMR spectrum of SI-7.

78

Figure 1.28: 1H NMR spectrum of SI-8.

79

Figure 1.29: 1H NMR spectrum of Fmoc-pTn-Thr-OH.

80

REFERENCES

81

REFERENCES

1.
Sungsuwan, S.; Yin, Z.; Huang, X., Lipopeptide-coated iron oxide nanoparticles
as potential glycoconjugate-based synthetic anticancer vaccines. ACS Applied Materials &
Interfaces 2015, 7 (31), 17535-17544.
2.
Heron, M., Deaths: Leading causes for 2014. National Vital Statistics Reports
2016, 65 (5), 1.
3.
McGuire, S., World cancer report 2014. Geneva, Switzerland: World Health
Organization, International Agency for Research on Cancer, WHO Press, 2015. Advance in
Nutrition 2016, 7 (2), 418-9.
4.
Grodzinski, P., Themed issue on cancer nanotechnology. Integrative Biology :
Quantitative Biosciences from Nano to Macro 2012, 5 (1), 17-18.
5.
Hamidreza, B.; Jagdish, R.; Kevin, L., Minimizing metastatic risk in radiotherapy
fractionation schedules. Physics in Medicine and Biology 2015, 60 (22), N405.
6.
Apostolopoulos, V.; Weiner, D.; Gong, J., Cancer vaccines: methods for inducing
immunity. Expert Review of Vaccines 2008, 7 (7), 861-862.
7.
Gresser, I., A. Chekhov, M.D., and Coley's Toxins. New England Journal of
Medicine 1987, 317 (7), 457-457.
8.
Nauts, H. C., Bacteria and cancer--antagonisms and benefits. Cancer Surveys
1989, 8 (4), 713-23.
9.
(a) Drake, C. G.; Lipson, E. J.; Brahmer, J. R., Breathing new life into
immunotherapy: review of melanoma, lung and kidney cancer. Nature Review Clinical Oncology
2014, 11 (1), 24-37; (b) Melero, I.; Gaudernack, G.; Gerritsen, W.; Huber, C.; Parmiani, G.;
Scholl, S.; Thatcher, N.; Wagstaff, J.; Zielinski, C.; Faulkner, I.; Mellstedt, H., Therapeutic
vaccines for cancer: an overview of clinical trials. Nature Review Clinical Oncology 2014, 11
(9), 509-524; (c) Hamid , O.; Robert , C.; Daud , A.; Hodi , F. S.; Hwu , W.-J.; Kefford , R.;
Wolchok , J. D.; Hersey , P.; Joseph , R. W.; Weber , J. S.; Dronca , R.; Gangadhar , T. C.;
Patnaik , A.; Zarour , H.; Joshua , A. M.; Gergich , K.; Elassaiss-Schaap , J.; Algazi , A.; Mateus
, C.; Boasberg , P.; Tumeh , P. C.; Chmielowski , B.; Ebbinghaus , S. W.; Li , X. N.; Kang , S.
P.; Ribas , A., Safety and tumor responses with Lambrolizumab (Anti–PD-1) in melanoma. New
England Journal of Medicine 2013, 369 (2), 134-144; (d) Wolchok , J. D.; Kluger , H.; Callahan
, M. K.; Postow , M. A.; Rizvi , N. A.; Lesokhin , A. M.; Segal , N. H.; Ariyan , C. E.; Gordon ,
R.-A.; Reed , K.; Burke , M. M.; Caldwell , A.; Kronenberg , S. A.; Agunwamba , B. U.; Zhang ,
X.; Lowy , I.; Inzunza , H. D.; Feely , W.; Horak , C. E.; Hong , Q.; Korman , A. J.; Wigginton ,
J. M.; Gupta , A.; Sznol , M., Nivolumab plus Ipilimumab in advanced melanoma. New England
Journal of Medicine 2013, 369 (2), 122-133; (e) Reck, M.; Rodríguez-Abreu, D.; Robinson, A.

82

G.; Hui, R.; Csőszi, T.; Fülöp, A.; Gottfried, M.; Peled, N.; Tafreshi, A.; Cuffe, S.; O’Brien, M.;
Rao, S.; Hotta, K.; Leiby, M. A.; Lubiniecki, G. M.; Shentu, Y.; Rangwala, R.; Brahmer, J. R.,
Pembrolizumab versus chemotherapy for PD-L1–positive non–small-cell lung cancer. New
England Journal of Medicine 2016, 375 (19), 1823-1833.
10.

McNutt, M., Cancer immunotherapy. Science 2013, 342 (6165), 1417-1417.

11.

DeFranco, A., B-cell activation 2000. Immunological Reviews 2000, 176, 5-9.

12.
Stavnezer, J., Immunoglobulin class switching. Current Opinion in Immunology
1996, 8 (2), 199-205.
13.
Buskas, T.; Thompson, P.; Boons, G.-J., Immunotherapy for cancer: synthetic
carbohydrate-based vaccines. Chemical Communications 2009, (36), 5335-5349.
14.
Loureiro, L.; Carrascal, M.; Barbas, A.; Ramalho, J.; Novo, C.; Delannoy, P.;
Videira, P., Challenges in antibody development against Tn and Sialyl-Tn antigens.
Biomolecules 2015, 5 (3), 1783.
15.
Palucka, K.; Banchereau, J., Cancer immunotherapy via dendritic cells. Nature
Reviews. Cancer 2012, 12 (4), 265-277.
16.
Kim, J.; Mooney, D., In vivo modulation of dendritic cells by engineered
materials: Towards new cancer vaccines. Nano Today 2011, 6 (5), 466-477.
17.
Wolfert, M. A.; Boons, G.-J., Adaptive immune activation: glycosylation does
matter. Nature Chemical Biology 2013, 9 (12), 776-784.
18.
Kessler, J. H.; Melief, C. J. M., Identification of T-cell epitopes for cancer
immunotherapy. Leukemia 2007, 21 (9), 1859-1874.
19.
(a) Karve, T. M.; Cheema, A. K., Small changes huge impact: The role of protein
posttranslational modifications in cellular homeostasis and disease. Journal of Amino Acids
2011, 2011; (b) Wang, Y.-C.; Peterson, S. E.; Loring, J. F., Protein post-translational
modifications and regulation of pluripotency in human stem cells. Cell Research 2014, 24 (2),
143-160.
20.
(a) Bramwell, M. E.; Wiseman, G.; Shotton, D. M., Electron-microscopic studies
of the CA antigen, epitectin. Journal of Cell Science 1986, 86 (1), 249-261; (b) Hilkens, J.;
Ligtenberg, M. J. L.; Vos, H. L.; Litvinov, S. V., Cell membrane-associated mucins and their
adhesion-modulating property. Trends in Biochemical Sciences 17 (9), 359-363.
21.
Singh, R.; Bandyopadhyay, D., MUC1: a target molecule for cancer therapy.
Cancer Biology & Therapy 2007, 6 (4), 481-6.

83

22.
Tang, C.-K.; Apostolopoulos, V., Strategies used for MUC1 immunotherapy:
preclinical studies. Expert Review of Vaccines 2008, 7 (7), 951-962 and references cited therein.
23.
Richardson, P. J.; Macmillan, D., Mucin-based vaccines. In Glycoscience:
Chemistry and Chemical Biology, Fraser-Reid, B. O.; Tatsuta, K.; Thiem, J., Eds. Springer
Berlin Heidelberg: Berlin, Heidelberg, 2008; pp 2645-2698.
24.
(a) Singh, P. K.; Hollingsworth, M. A., Cell surface-associated mucins in signal
transduction. Trends in Cell Biology 2006, 16 (9), 467-476; (b) Hollingsworth, M. A.; Swanson,
B. J., Mucins in cancer: protection and control of the cell surface. Nature Reviews: Cancer 2004,
4 (1), 45-60.
25.
Kufe, D. W., MUC1-C oncoprotein as a target in breast cancer: activation of
signaling pathways and therapeutic approaches. Oncogene 2013, 32 (9), 1073-1081.
26.
Hanisch, F.-G.; Müller, S., MUC1: the polymorphic appearance of a human
mucin. Glycobiology 2000, 10 (5), 439-449.
27.
Kufe, D., Mucins in cancer: function, prognosis and therapy. Nature Reviews.
Cancer 2009, 9 (12), 874-885.
28.
von Mensdorff-Pouilly, S.; Petrakou, E.; Kenemans, P.; van Uffelen, K.;
Verstraeten, A. A.; Snijdewint, F. G. M.; van Kamp, G. J.; Schol, D. J.; Reis, C. A.; Price, M. R.;
Livingston, P. O.; Hilgers, J., Reactivity of natural and induced human antibodies to MUC1
mucin with MUC1 peptides and N-acetylgalactosamine (GalNAc) peptides. International
Journal of Cancer 2000, 86 (5), 702-712.
29.
Blixt, O.; Bueti, D.; Burford, B.; Allen, D.; Julien, S.; Hollingsworth, M.;
Gammerman, A.; Fentiman, I.; Taylor-Papadimitriou, J.; Burchell, J. M., Autoantibodies to
aberrantly glycosylated MUC1 in early stage breast cancer are associated with a better prognosis.
Breast Cancer Research 2011, 13 (2), 1-16.
30.
Engelmann, K.; Baldus, S. E.; Hanisch, F.-G., Identification and topology of
variant sequences within individual repeat domains of the human epithelial tumor mucin MUC1.
Journal of Biological Chemistry 2001, 276 (30), 27764-27769.
31.
Fontenot, J. D.; Tjandra, N.; Bu, D.; Ho, C.; Montelaro, R. C.; Finn, O. J.,
Biophysical characterization of one-, two-, and three-tandem repeats of human mucin (MUC-1)
protein core. Cancer Research 1993, 53 (22), 5386-5394.
32.
MacLean, G. D.; Bowen-Yacyshyn, M. B.; Samuel, J.; Meikle, A.; Stuart, G.;
Nation, J.; Poppema, S.; Jerry, M.; Koganty, R.; Wong, T.; et al., Active immunization of human
ovarian cancer patients against a common carcinoma (Thomsen-Friedenreich) determinant using
a synthetic carbohydrate antigen. Journal of Immunotherapy (1991) 1992, 11 (4), 292-305.

84

33.
Tang, C.-K.; Katsara, M.; Apostolopoulos, V., Strategies used for MUC1
immunotherapy: human clinical studies. Expert Review of Vaccines 2008, 7 (7), 963-975.
34.
(a) Ju, T.; Lanneau, G. S.; Gautam, T.; Wang, Y.; Xia, B.; Stowell, S. R.; Willard,
M. T.; Wang, W.; Xia, J. Y.; Zuna, R. E.; Laszik, Z.; Benbrook, D. M.; Hanigan, M. H.;
Cummings, R. D., Human tumor antigens Tn and Sialyl Tn arise from mutations in Cosmc.
Cancer Research 2008, 68 (6), 1636-1646; (b) Ju, T.; Otto, V. I.; Cummings, R. D., The Tn
antigen—structural simplicity and biological complexity. Angewandte Chemie International
Edition 2011, 50 (8), 1770-1791; (c) Ju, T.; Aryal, R. P.; Kudelka, M. R.; Wang, Y.; Cummings,
R. D., The Cosmc connection to the Tn antigen in cancer. Cancer Biomark 2014, 14 (1), 63-81.
35.
Ju, T.; Cummings, R., A unique molecular chaperone Cosmc required for activity
of the mammalian core 1 beta 3-galactosyltransferase. Proceedings of the National Academy of
Sciences of the United States of America 2002, 99 (26), 16613-16618.
36.
Hull, S.; Bright, A.; Carraway, K.; Abe, M.; Hayes, D.; Kufe, D., Oligosaccharide
differences in the DF3 sialomucin antigen from normal human milk and the BT-20 human breast
carcinoma cell line. Cancer Communications 1989, 1 (4), 261-267.
37.
Varki, A.; Kannagi, R.; Toole, B. P., Glycosylation Changes in Cancer. 2 ed.;
Cold Spring Harbor Laboratory Press: La Jolla, CA, USA, 2009; Vol. 2.
38.
(a) Kudelka, M. R.; Ju, T.; Heimburg-Molinaro, J.; Cummings, R. D., Chapter
three - simple sugars to complex disease—Mucin-type O-glycans in cancer. In Advances in
Cancer Research, Richard, R. D.; Lauren, E. B., Eds. Academic Press: 2015; Vol. Volume 126,
pp 53-135; (b) Wang, P.-H.; Lee, W.-L.; Juang, C.-M.; Yang, Y.-H.; Lo, W.-H.; Lai, C.-R.;
Hsieh, S.-L.; Yuan, C.-C., Altered mRNA expressions of sialyltransferases in ovarian cancers.
Gynecologic Oncology 2005, 99 (3), 631-639; (c) Videira, P. A.; Correia, M.; Malagolini, N.;
Crespo, H. J.; Ligeiro, D.; Calais, F. M.; Trindade, H.; Dall'Olio, F., ST3Gal.I sialyltransferase
relevance in bladder cancer tissues and cell lines. BMC Cancer 2009, 9 (1), 357; (d) Schneider,
F.; Kemmner, W.; Haensch, W.; Franke, G.; Gretschel, S.; Karsten, U.; Schlag, P. M.,
Overexpression of sialyltransferase CMP-sialic acid:Galβ1,3GalNAc-R α6-sialyltransferase is
related to poor patient survival in human colorectal carcinomas. Cancer Research 2001, 61 (11),
4605-4611.
39.
Sedlik, C.; Heitzmann, A.; Viel, S.; Ait Sarkouh, R.; Batisse, C.; Schmidt, F.; De
La Rochere, P.; Amzallag, N.; Osinaga, E.; Oppezzo, P.; Pritsch, O.; Sastre-Garau, X.; Hubert,
P.; Amigorena, S.; Piaggio, E., Effective antitumor therapy based on a novel antibody-drug
conjugate targeting the Tn carbohydrate antigen. OncoImmunology 2016, 5 (7), e1171434.
40.
(a) Osako, M.; Yonezawa, S.; Siddiki, B.; Huang, J.; Ho, J. J. L.; Kim, Y. S.;
Sato, E., Immunohistochemical study of mucin carbohydrates and core proteins in human
pancreatic tumors. Cancer 1993, 71 (7), 2191-2199; (b) Cao, Y.; Karsten, U. R.; Liebrich, W.;
Haensch, W.; Springer, G. F.; Schlag, P. M., Expression of thomsen-friedenreich-related
antigens in primary and metastatic colorectal carcinomas. A reevaluation. Cancer 1995, 76 (10),
1700-1708; (c) David, L.; Nesland, J. M.; Clausen, H.; Carneiro, F.; Sobrinho-Simoes, M.,

85

Simple mucin-type carbohydrate antigens (Tn, sialosyl-Tn and T) in gastric mucosa, carcinomas
and metastases. APMIS. Supplementum 1992, 27, 162-72.
41.
Cheever, M.; Allison, J.; Ferris, A.; Finn, O.; Hastings, B.; Hecht, T.; Mellman, I.;
Prindiville, S.; Viner, J.; Weiner, L.; Matrisian, L., The prioritization of cancer antigens: A
national cancer institute pilot project for the acceleration of translational research. Clinical
Cancer Research : An Official Journal of the American Association for Cancer Research 2009,
15 (17), 5323-5337.
42.
(a) Galli-Stampino, L.; Meinjohanns, E.; Frische, K.; Meldal, M.; Jensen, T.;
Werdelin, O.; Mouritsen, S. o., T-cell recognition of tumor-associated carbohydrates: The nature
of the glycan moiety plays a decisive role in determining glycopeptide immunogenicity. Cancer
Research 1997, 57 (15), 3214-3222; (b) Glithero, A.; Tormo, J.; Haurum, J. S.; Arsequell, G.;
Valencia, G.; Edwards, J.; Springer, S.; Townsend, A.; Pao, Y.-L.; Wormald, M.; Dwek, R. A.;
Jones, E. Y.; Elliott, T., Crystal structures of two H-2Db/glycopeptide complexes suggest a
molecular basis for CTL cross-reactivity. Immunity 1999, 10 (1), 63-74; (c) Haurum, J. S.;
Arsequell, G.; Lellouch, A. C.; Wong, S. Y.; Dwek, R. A.; McMichael, A. J.; Elliott, T.,
Recognition of carbohydrate by major histocompatibility complex class I-restricted,
glycopeptide-specific cytotoxic T lymphocytes. The Journal of Experimental Medicine 1994,
180 (2), 739-744; (d) Haurum, J. S.; Tan, L.; Arsequell, G.; Frodsham, P.; Lellouch, A. C.; Moss,
P. A. H.; Dwek, R. A.; McMichael, A. J.; Elliott, T., Peptide anchor residue glycosylation: effect
on class I major histocompatibility complex binding and cytotoxic T lymphocyte recognition.
European Journal of Immunology 1995, 25 (12), 3270-3276; (e) Jensen, T.; Galli-Stampino, L.;
Mouritsen, S.; Frische, K.; Peters, S.; Meldal, M.; Werdelin, O., T cell recognition of Tnglycosylated peptide antigens. European Journal of Immunology 1996, 26 (6), 1342-1349.
43.
(a) Vlad, A. M.; Muller, S.; Cudic, M.; Paulsen, H.; Otvos, L.; Hanisch, F.-G.;
Finn, O. J., Complex carbohydrates are not removed during processing of glycoproteins by
dendritic cells: Processing of tumor antigen MUC1 glycopeptides for presentation to major
histocompatibility complex class II–restricted T cells. The Journal of Experimental Medicine
2002, 196 (11), 1435-1446; (b) Ioannides, C. G.; Fisk, B.; Jerome, K. R.; Irimura, T.; Wharton, J.
T.; Finn, O. J., Cytotoxic T cells from ovarian malignant tumors can recognize polymorphic
epithelial mucin core peptides. The Journal of Immunology 1993, 151 (7), 3693-703.
44.
(a) Doménech, N.; Henderson, R. A.; Finn, O. J., Identification of an HLA-A11restricted epitope from the tandem repeat domain of the epithelial tumor antigen mucin. The
Journal of Immunology 1995, 155 (10), 4766-74; (b) Brossart, P.; Heinrich, K. S.; Stuhler, G.;
Behnke, L.; Reichardt, V. L.; Stevanovic, S.; Muhm, A.; Rammensee, H.-G.; Kanz, L.; Brugger,
W., Identification of HLA-A2–restricted T-cell epitopes derived from the MUC1 tumor antigen
for broadly applicable vaccine therapies. Blood 1999, 93 (12), 4309-4317; (c) Ninkovic, T.;
Kinarsky, L.; Engelmann, K.; Pisarev, V.; Sherman, S.; Finn, O. J.; Hanisch, F.-G., Identification
of O-glycosylated decapeptides within the MUC1 repeat domain as potential MHC class I (A2)
binding epitopes. Molecular Immunology 2009, 47 (1), 131-140.

86

45.
Agrawal, B.; Krantz, M. J.; Reddish, M. A.; Longenecker, B. M., Rapid induction
of primary human CD4+ and CD8+ T cell responses against cancer-associated MUC1 peptide
epitopes. International Immunology 1998, 10 (12), 1907-16.
46.
Perdicchio, M.; Ilarregui, J. M.; Verstege, M. I.; Cornelissen, L. A. M.; Schetters,
S. T. T.; Engels, S.; Ambrosini, M.; Kalay, H.; Veninga, H.; den Haan, J. M. M.; van Berkel, L.
A.; Samsom, J. N.; Crocker, P. R.; Sparwasser, T.; Berod, L.; Garcia-Vallejo, J. J.; van Kooyk,
Y.; Unger, W. W. J., Sialic acid-modified antigens impose tolerance via inhibition of T-cell
proliferation and de novo induction of regulatory T cells. Proceedings of the National Academy
of Sciences 2016, 113 (12), 3329-3334.
47.
Apostolopoulos, V.; Xing, P. X.; McKenzie, I. F., Murine immune response to
cells transfected with human MUC1: immunization with cellular and synthetic antigens. Cancer
Research 1994, 54 (19), 5186-93.
48.
Apostolopoulos, V.; Pietersz, G. A.; Gordon, S.; Martinez-Pomares, L.;
McKenzie, I. F., Aldehyde-mannan antigen complexes target the MHC class I antigenpresentation pathway. European Journal of Immunology 2000, 30 (6), 1714-23.
49.
(a) Danishefsky, S. J.; Allen, J. R., From the laboratory to the clinic: A
retrospective on fully synthetic carbohydrate-based anticancer vaccines. Angewandte Chemie,
International Edition in English 2000, 39, 836-863; (b) Sabbatini, P. J.; Ragupathi, G.; Hood, C.;
Aghajanian, C. A.; Juretzka, M.; Iasonos, A.; Hensley, M. L.; Spassova, M. K.; Ouerfelli, O.;
Spriggs, D. R.; Tew, W. P.; Konner, J.; Clausen, H.; Abu Rustum, N.; Dansihefsky, S. J.;
Livingston, P. O., Pilot study of a heptavalent vaccine-Keyhole Limpet Hemocyanin conjugate
plus QS21 in patients with epithelial ovarian, fallopian tube, or peritoneal Cancer. Clinical
Cancer Research 2007, 13 (14), 4170-4177.
50.
(a) Hoffmann-Roder, A.; Kaiser, A.; Wagner, S.; Gaidzik, N.; Kowalczyk, D.;
Westerlind, U.; Gerlitzki, B.; Schmitt, E.; Kunz, H., Synthetic antitumor vaccines from Tetanus
Toxoid conjugates of MUC1 glycopeptides with the Thomsen-Friedenreich antigen and a
fluorine-substituted analogue. Angewandte Chemie, International Edition in English 2010, 49
(45), 8498-8503; (b) Rich, J. R.; Wakarchuk, W. W.; Bundle, D. R., Chemical and
chemoenzymatic synthesis of S-linked ganglioside analogues and their protein conjugates for use
as immunogens. Chemistry – A European Journal 2006, 12, 845-858.
51.
(a) Musselli, C.; Livingston, P. O.; Ragupathi, G., Keyhole limpet hemocyanin
conjugate vaccines against cancer: the Memorial Sloan Kettering experience. Journal of Cancer
Research and Clinical Oncology 2001, 127 Suppl 2, R20-6; (b) Buskas, T.; Li, Y.; Boons, G.-J.,
The immunogenicity of the tumor-associated antigen Lewis y may be suppressed by a
bifunctional cross-linker required for coupling to a carrier protein. Chemistry – A European
Journal 2004, 10 (14), 3517-3524.
52.
Jegerlehner, A.; Wiesel, M.; Dietmeier, K.; Zabel, F.; Gatto, D.; Saudan, P.;
Bachmann, M. F., Carrier induced epitopic suppression of antibody responses induced by virus-

87

like particles is a dynamic phenomenon caused by carrier-specific antibodies. Vaccine 2010, 28
(33), 5503-5512.
53.
Gaidzik, N.; Westerlind, U.; Kunz, H., The development of synthetic antitumour
vaccines from mucin glycopeptide antigens. Chemical Society Reviews 2013, 42 (10), 44214442.
54.
(a) Joshi, M.; Unger, W.; Storm, G.; van Kooyk, Y.; Mastrobattista, E., Targeting
tumor antigens to dendritic cells using particulate carriers. Journal of Controlled Release :
Official Journal of the Controlled Release Society 2012, 161 (1), 25-37; (b) Zhu, G.; Zhang, F.;
Ni, Q.; Niu, G.; Chen, X., Efficient nanovaccine delivery in cancer immunotherapy. ACS Nano
2017.
55.
Mellman, I.; Coukos, G.; Dranoff, G., Cancer immunotherapy comes of age.
Nature 2011, 480 (7378), 480-489.
56.
Reddy, R.; Zhou, F.; Nair, S.; Huang, L.; Rouse, B. T., In vivo cytotoxic T
lymphocyte induction with soluble proteins administered in liposomes. The Journal of
Immunology 1992, 148 (5), 1585-9.
57.
Xiang, S.; Scalzo-Inguanti, K.; Minigo, G.; Park, A.; Hardy, C.; Plebanski, M.,
Promising particle-based vaccines in cancer therapy. Expert Review of Vaccines 2008, 7 (7),
1103-1119.
58.
(a) de Haan, A.; Haijema, B.; Voorn, P.; Meijerhof, T.; van Roosmalen, M.;
Leenhouts, K., Bacterium-like particles supplemented with inactivated influenza antigen induce
cross-protective influenza-specific antibody responses through intranasal administration. Vaccine
2012, 30 (32), 4884-4891; (b) McKee, S.; Young, V.; Clow, F.; Hayman, C.; Baird, M.;
Hermans, I.; Young, S.; Ward, V., Virus-like particles and α-galactosylceramide form a selfadjuvanting composite particle that elicits anti-tumor responses. Journal of Controlled Release :
Official Journal of the Controlled Release Society 2012, 159 (3), 338-345.
59.
Waeckerle-Men, Y.; Allmen, E.; Gander, B.; Scandella, E.; Schlosser, E.;
Schmidtke, G.; Merkle, H.; Groettrup, M., Encapsulation of proteins and peptides into
biodegradable poly(D,L-lactide-co-glycolide) microspheres prolongs and enhances antigen
presentation by human dendritic cells. Vaccine 2006, 24 (11), 1847-1857.
60.
Thomann-Harwood, L.; Kaeuper, P.; Rossi, N.; Milona, P.; Herrmann, B.;
McCullough, K., Nanogel vaccines targeting dendritic cells: Contributions of the surface
decoration and vaccine cargo on cell targeting and activation. Journal of Controlled Release :
Official Journal of the Controlled Release Society 2012, 166 (2), 95-105.
61.
Bachmann, M.; Rohrer, U.; Kündig, T.; Bürki, K.; Hengartner, H.; Zinkernagel,
R., The influence of antigen organization on B cell responsiveness. Science (New York, N.Y.)
1993, 262 (5138), 1448-1451.

88

62.
(a) Black, M.; Trent, A.; Tirrell, M.; Olive, C., Advances in the design and
delivery of peptide subunit vaccines with a focus on toll-like receptor agonists. Expert Review of
Vaccines 2010, 9 (2), 157-173; (b) Wille-Reece, U.; Flynn, B. J.; Loré, K.; Koup, R. A.; Kedl, R.
M.; Mattapallil, J. J.; Weiss, W. R.; Roederer, M.; Seder, R. A., HIV Gag protein conjugated to a
Toll-like receptor 7/8 agonist improves the magnitude and quality of Th1 and CD8+ T cell
responses in nonhuman primates. Proceedings of the National Academy of Sciences of the United
States of America 2005, 102 (42), 15190-15194; (c) Kastenm; xFc; ller, K.; Wille-Reece, U.;
Lindsay, R. W. B.; Trager, L. R.; Darrah, P. A.; Flynn, B. J.; Becker, M. R.; Udey, M. C.;
Clausen, B.; xF; rn, E.; Igyarto, B. Z.; Kaplan, D. H.; ller, W.; Germain, R. N.; Seder, R. A.,
Protective T cell immunity in mice following protein-TLR7/8 agonist-conjugate immunization
requires aggregation, type I IFN, and multiple DC subsets. The Journal of Clinical Investigation
121 (5), 1782-1796.
63.
Lim, E.-K.; Kim, T.; Paik, S.; Haam, S.; Huh, Y.-M.; Lee, K., Nanomaterials for
theranostics: Recent advances and future challenges. Chemical Reviews 2015, 115 (1), 327-394.
64.
(a) Xiang, S. D.; Scholzen, A.; Minigo, G.; David, C.; Apostolopoulos, V.;
Mottram, P. L.; Plebanski, M., Pathogen recognition and development of particulate vaccines:
Does size matter? Methods 2006, 40 (1), 1-9; (b) Thiele, L.; Merkle, H. P.; Walter, E.,
Phagocytosis of synthetic particulate vaccine delivery systems to program dendritic cells. Expert
Review of Vaccines 2002, 1 (2), 215-226.
65.
Moyer, T. J.; Zmolek, A. C.; Irvine, D. J., Beyond antigens and adjuvants:
formulating future vaccines. The Journal of Clinical Investigation 126 (3), 799-808.
66.
Mou, Y.; Hou, Y.; Chen, B.; Hua, Z.; Zhang, Y.; Xie, H.; Xia, G.; Wang, Z.;
Huang, X.; Han, W.; Ni, Y.; Hu, Q., In vivo migration of dendritic cells labeled with synthetic
superparamagnetic iron oxide. International Journal of Nanomedicine 2011, 6, 2633-2640.
67.
(a) MacPherson, G. G.; Fossum, S.; Harrison, B., Properties of lymph-borne
(veiled) dendritic cells in culture. II. Expression of the IL-2 receptor: role of GM-CSF.
Immunology 1989, 68 (1), 108-113; (b) Matsuno, K.; Kudo, S.; Ezaki, T.; Miyakawa, K.,
Isolation of dendritic cells in the rat liver lymph. Transplantation 1995, 60 (7), 765-8; (c) Pugh,
C. W.; MacPherson, G. G.; Steer, H. W., Characterization of nonlymphoid cells derived from rat
peripheral lymph. The Journal of Experimental Medicine 1983, 157 (6), 1758-1779.
68.
(a) Inaba, K.; Turley, S.; Yamaide, F.; Iyoda, T.; Mahnke, K.; Inaba, M.; Pack,
M.; Subklewe, M.; Sauter, B.; Sheff, D.; Albert, M.; Bhardwaj, N.; Mellman, I.; Steinman, R.
M., Efficient presentation of phagocytosed cellular fragments on the major histocompatibility
complex class II products of dendritic cells. The Journal of Experimental Medicine 1998, 188
(11), 2163-2173; (b) Allan, R. S.; Waithman, J.; Bedoui, S.; Jones, C. M.; Villadangos, J. A.;
Zhan, Y.; Lew, A. M.; Shortman, K.; Heath, W. R.; Carbone, F. R., Migratory dendritic cells
transfer antigen to a lymph node-resident dendritic cell population for efficient CTL priming.
Immunity 2006, 25 (1), 153-162; (c) Belz, G. T.; Behrens, G. M. N.; Smith, C. M.; Miller, J. F.
A. P.; Jones, C.; Lejon, K.; Fathman, C. G.; Mueller, S. N.; Shortman, K.; Carbone, F. R.; Heath,

89

W. R., The CD8α+ dendritic cell is responsible for inducing peripheral self-tolerance to tissueassociated antigens. The Journal of Experimental Medicine 2002, 196 (8), 1099-1104.
69.
Reddy, S. T.; van der Vlies, A. J.; Simeoni, E.; Angeli, V.; Randolph, G. J.;
O’Neil, C. P.; Lee, L. K.; Swartz, M. A.; Hubbell, J. A., Exploiting lymphatic transport and
complement activation in nanoparticle Vaccines. Nature Biotechnology 2007, 25, 1159-1164.
70.
Newman, K. D.; Sosnowski, D. L.; Kwon, G. S.; Samuel, J., Delivery of MUC1
mucin peptide by poly(D,L-lactic-co-glycolic acid) microspheres induces type 1 T helper
immune responses. Journal of Pharmaceutical Sciences 1998, 87 (11), 1421-1427.
71.
Guan, H. H.; Budzynski, W.; Koganty, R. R.; Krantz, M. J.; Reddish, M. A.;
Rogers, J. A.; Longenecker, B. M.; Samuel, J., Liposomal formulations of synthetic MUC1
peptides:  Effects of encapsulation versus surface display of peptides on immune responses.
Bioconjugate Chemistry 1998, 9 (4), 451-458.
72.
Samuel, J.; Budzynski, W. A.; Reddish, M. A.; Ding, L.; Zimmermann, G. L.;
Krantz, M. J.; Koganty, R. R.; Longenecker, B. M., Immunogenicity and antitumor activity of a
liposomal MUC1 peptide-based vaccine. International Journal of Cancer 1998, 75, 295-302.
73.
Lakshminarayanan, V.; Thompson, P.; Wolfert, M. A.; Buskas, T.; Bradley, J. M.;
Pathangey, L. B.; Madsen, C. S.; Cohen, P. A.; Gendler, S. J.; Boons, G.-J., Immune recognition
of tumor-associated mucin MUC1 is achieved by a fully synthetic aberrantly glycosylated MUC1
tripartite vaccine. Proceedings of the National Academy of Sciences 2012, 109 (1), 261-266.
74.
(a) Ingale, S.; Wolfert, M. A.; Buskas, T.; Boons, G.-J., Increasing the
antigenicity of synthetic tumor-associated carbohydrate antigens by targeting toll-like receptors.
ChemBioChem 2009, 10 (3), 455-463; (b) Buskas, T.; Ingale, S.; Boons, G.-J., Towards a fully
synthetic carbohydrate-based anticancer vaccine: Synthesis and immunological evaluation of a
lipidated glycopeptide containing the tumor-associated Tn antigen. Angewandte Chemie
International Edition 2005, 44 (37), 5985-5988.
75.
Ingale, S.; Wolfert, M. A.; Gaekwad, J.; Buskas, T.; Boons, G.-J., Robust immune
responses elicited by a fully synthetic three-component vaccine. Nature Chemical Biology 2007,
3 (10), 663-667.
76.
Lakshminarayanan, V.; Thompson, P.; Wolfert, M. A.; Buskas, T.; Bradley, J. M.;
Pathangey, L. B.; Madsen, C. S.; Cohen, P. A.; Gendler, S. J.; Boons, G.-J., Immune recognition
of tumor-associated mucin MUC1 is achieved by a fully synthetic aberrantly glycosylated MUC1
triparticle vaccine. Proceedings of the National Academy of Sciences of the United States of
America 2012, 109, 261-266.
77.
Wilkinson, B. L.; Day, S.; Chapman, R.; Perrier, S.; Apostolopoulos, V.; Payne,
R. J., Synthesis and immunological evaluation of self-assembling and self-adjuvanting
tricomponent glycopeptide cancer-vaccine candidates. Chemistry – A European Journal 2012, 18
(51), 16540-16548.

90

78.
Liu, Y.-F.; Sun, Z.-Y.; Chen, P.-G.; Huang, Z.-H.; Gao, Y.; Shi, L.; Zhao, Y.-F.;
Chen, Y.-X.; Li, Y.-M., Glycopeptide nanoconjugates based on multilayer self-assembly as an
antitumor vaccine. Bioconjugate Chemistry 2015, 26 (8), 1439-1442.
79.
Huang, Z.-H.; Shi, L.; Ma, J.-W.; Sun, Z.-Y.; Cai, H.; Chen, Y.-X.; Zhao, Y.-F.;
Li, Y.-M., A totally synthetic, self-assembling, adjuvant-free MUC1 glycopeptide vaccine for
cancer therapy. Journal of the American Chemical Society 2012, 134 (21), 8730-8733.
80.
Restuccia, A.; Fettis, M. M.; Hudalla, G. A., Glycomaterials for
immunomodulation, immunotherapy, and infection prophylaxis. Journal of Materials Chemistry
B 2016, 4 (9), 1569-1585.
81.
Cai, H.; Degliangeli, F.; Palitzsch, B.; Gerlitzki, B.; Kunz, H.; Schmitt, E.;
Fiammengo, R.; Westerlind, U., Glycopeptide-functionalized gold nanoparticles for antibody
induction against the tumor associated mucin-1 glycoprotein. Bioorganic & Medicinal Chemistry
2016, 24 (5), 1132-1135.
82.
Lee, N.; Yoo, D.; Ling, D.; Cho, M. H.; Hyeon, T.; Cheon, J., Iron oxide based
nanoparticles for multimodal imaging and magnetoresponsive therapy. Chemical Reviews 2015,
115 (19), 10637-10689.
83.
(a) Tassa, C.; Shaw, S.; Weissleder, R., Dextran-coated iron oxide nanoparticles:
a versatile platform for targeted molecular imaging, molecular diagnostics, and therapy.
Accounts of Chemical Research 2011, 44 (10), 842-852; (b) Mi Kyung, Y.; Jinho, P.; Sangyong,
J., Magnetic nanoparticles and their applications in image-guided drug delivery. Drug Delivery
and Translational Research 2011, 2.
84.
Zhang, C.; Liu, T.; Gao, J.; Su, Y.; Shi, C., Recent development and application
of magnetic nanoparticles for cell labeling and imaging. Mini Reviews in Medicinal Chemistry
2010, 10 (3), 193-202.
85.
Mou, Y.; Chen, B.; Zhang, Y.; Hou, Y.; Xie, H.; Xia, G.; Tang, M.; Huang, X.;
Ni, Y.; Hu, Q., Influence of synthetic superparamagnetic iron oxide on dendritic cells.
International Journal of Nanomedicine 2011, 6, 1779-1786.
86.
Pusic, K.; Aguilar, Z.; McLoughlin, J.; Kobuch, S.; Xu, H.; Tsang, M.; Wang, A.;
Hui, G., Iron oxide nanoparticles as a clinically acceptable delivery platform for a recombinant
blood-stage human malaria vaccine. FASEB Journal : Official Publication of the Federation of
American Societies for Experimental Biology 2013, 27 (3), 1153-1166.
87.
(a) Ruirui, Q.; Chunhui, Y.; Mingyuan, G., Superparamagnetic iron oxide
nanoparticles: from preparations to in vivo MRI applications. Journal of Materials Chemistry
2009, 19; (b) Ulbrich, K.; Holá, K.; Šubr, V.; Bakandritsos, A.; Tuček, J.; Zbořil, R., Targeted
drug delivery with polymers and magnetic nanoparticles: Covalent and noncovalent approaches,
release control, and clinical studies. Chemical Reviews 2016, 116 (9), 5338-5431.

91

88.
Dobrovolskaia, M.; McNeil, S., Immunological properties of engineered
nanomaterials. Nature Nanotechnology 2007, 2 (8), 469-478.
89.
Wu, W.; He, Q.; Jiang, C., Magnetic iron oxide nanoparticles: synthesis and
surface functionalization strategies. Nanoscale Research Letters 2008, 3 (11), 397-415.
90.
(a) Amstad, E.; Gillich, T.; Bilecka, I.; Textor, M.; Reimhult, E., Ultrastable iron
oxide nanoparticle colloidal suspensions using dispersants with catechol-derived anchor groups.
Nano Letters 2009, 9 (12), 4042-4048; (b) Jiang, S.; Eltoukhy, A. A.; Love, K. T.; Langer, R.;
Anderson, D. G., Lipidoid-coated iron oxide nanoparticles for efficient DNA and siRNA
delivery. Nano Letters 2013, 13 (3), 1059-1064.
91.
Tong, S.; Hou, S.; Ren, B.; Zheng, Z.; Bao, G., Self-assembly of phospholipidPEG coating on nanoparticles through dual solvent exchange. Nano Letters 2011, 11 (9), 37203726.
92.
Park, J.; An, K.; Hwang, Y.; Park, J.-G.; Noh, H.-J.; Kim, J.-Y.; Park, J.-H.;
Hwang, N.-M.; Hyeon, T., Ultra-large-scale syntheses of monodisperse nanocrystals. Nature
Materials 2007, 3, 891-896.
93.
Dobrovolskaia, M.; McNeil, S., Immunological properties of engineered
nanomaterials. Nature Nanotechnology 2007, 2 (8), 469-478.
94.
Sun, S.; Zeng, H.; Robinson, D. B.; Raoux, S.; Rice, P. M.; Wang, S. X.; Li, G.,
Monodisperse MFe2O4 (M = Fe, Co, Mn) nanoparticles. Journal of the American Chemical
Society 2004, 126, 273-279.
95.
Tong, S.; Hou, S.; Ren, B.; Zheng, Z.; Bao, G., Self-assembly of phospholipidPEG coating on nanoparticles through dual solvent exchange. Nano Letters 2011, 11 (9), 37203726.
96.
Steinman, R. M., Dendritic cells: Versatile controllers of the immune system.
Nature Medicine 2007, 13, 1155-1159.
97.
Iwasaki, A.; Medzhitov, R., Toll-like receptor control of the adaptive immune
responses. Nature Immunology 2004, 5 (10), 987-995.
98.
Pihlgren, M.; Silva, A. B.; Madani, R.; Giriens, V.; Waeckerle-Men, Y.;
Fettelschoss, A.; Hickman, D. T.; López-Deber, M. P.; Ndao, D. M.; Vukicevic, M.; Buccarello,
A. L.; Gafner, V.; Chuard, N.; Reis, P.; Piorkowska, K.; Pfeifer, A.; Kündig, T. M.; Muhs, A.;
Johansen, P., TLR4- and TRIF-dependent stimulation of B lymphocytes by peptide liposomes
enables T cell–independent isotype switch in mice. Blood 2012, 121 (1), 85-94.
99.
Jeong, J.; Kwon, E.-K.; Cheong, T.-C.; Park, H.; Cho, N.-H.; Kim, W., Synthesis
of multifunctional Fe3O4–CdSe/ZnS nanoclusters coated with Lipid A toward dendritic cellbased immunotherapy. ACS Applied Materials & Interfaces 2014, 6 (7), 5297-5307.

92

100. Liu, H.; Moynihan, K. D.; Zheng, Y.; Szeto, G. L.; Li, A. V.; Huang, B.; Van
Egeren, D. S.; Park, C.; Irvine, D. J., Structure-based programming of lymph-node targeting in
molecular vaccines. Nature 2014, 507 (7493), 519-522.
101. Bachmann, M. F.; Jennings, G. T., Vaccine delivery: A matter of size, geometry,
kinetics and molecular patterns. Nature Reviews: Immunology 2010, 10 (11), 787-796.
102. Steinhagen, F.; Kinjo, T.; Bode, C.; Klinman, D. M., TLR-based immune
adjuvants. Vaccine 2011, 29 (17), 3341-3355.
103. (a) Schietinger, A.; Philip, M.; Yoshida, B. A.; Azadi, P.; Liu, H.; Meredith, S. C.;
Schreiber, H., A mutant chaperone converts a wild-type protein into a tumor-specific antigen.
Science 2006, 314, 304-308; (b) Wang, Y.; Ju, T.; Ding, X.; Xia, B.; Wang, W.; Xia, L.; He, M.;
Cummings, R. D., Cosmc is an essential chaperone for correct protein O-glycosylation.
Proceedings of the National Academy of Sciences of the United States of America 2010, 107,
9228-9233.
104. (a) Peri, F., Clustered carbohydrates in synthetic vaccines. Chemical Society
Reviews 2013, 42, 4543-4556; (b) Brinas, R. P.; Sundgren, A.; Sahoo, P.; Morey, S.;
Rittenhouse-Olson, K.; Wilding, G. E.; Deng, W.; Barchi, J. J., Design and synthesis of
multifunctional gold nanoparticles bearing tumor-associated glycopeptide antigens as potential
cancer vaccines. Bioconjugate Chemistry 2012, 23, 1513-1523; (c) Yin, Z.; Comellas-Aragones,
M.; Chowdhury, S.; Bentley, P.; Kaczanowska, K.; BenMohamed, L.; Gildersleeve, J. C.; Finn,
M. G.; Huang, X., Boosting immunity to small tumor-associated carbohydrates with
bacteriophage Qβ capsids. ACS Chem. Biol. 2013, 8, 1253-1262; (d) Parry, A. L.; Clemson, N.
A.; Ellis, J.; Bernhard, S. S. R.; Davis, B. G.; Cameron, N. R., 'Mulicopy multivalent'
glycopolymer-stabilized gold nanoparticles as potential synthetic cancer vaccines. Journal of the
American Chemical Society 2013, 135, 9362-9365; (e) Ojeda, R.; de Paz, J. L.; Barrientos, A. G.;
Martin-Lomas, M.; Penades, S., Preparation of multifunctional glyconanoparticles as a platform
for potential carbohydrate-based anticancer vaccines. Carbohydrate Research 2007, 342 (3-4),
448-59.
105. (a) Kinarsky, L.; Suryanarayanan, G.; Prakash, O.; Paulsen, J.; Clausen, H.;
Hanisch, F. A.; Hollingsworth, M. A.; Sherman, S., Conformational studies on the MUC1
tandem repeat glycopeptides: Implication for the enzymatic O-glycosylation of the mucin protein
core. Glycobiology 2003, 13, 929-939; (b) Karsten, U.; Serttas, N.; Paulsen, H.; Danielczyk, A.;
Goletz, S., Binding patterns of DTR-specific antibodies reveal a glycosylation-conditioned
tumor-specific epitope of the epithelial mucin (MUC1). Glycobiology 2004, 14 (8), 681-692; (c)
Matsushita, T.; Ohyabu, N.; Fujitani, N.; Naruchi, K.; Shimizu, H.; Hinou, H.; Nishimura, S.,
Site-specific conformational alteration induced by sialylation of MUC1 tandem repeating
glycopeptides at an epitope region for the anti-KL-6 monoclonal antibody. Biochemistry 2013,
52, 402-414.
106. (a) von Mensdorff-Pouilly, S.; Moreno, M.; Verheijen, R. H. M., Natural and
induced humoral responses to MUC1. Cancers 2011, 3 (3), 3073-3103; (b) Ryan, S. O.; Turner,
M. S.; Gariépy, J.; Finn, O. J., Tumor antigen epitopes interpreted by the immune system as self

93

or abnormal-self differentially affect cancer vaccine responses. Cancer Research 2010, 70, 57885796.
107. (a) Burford, B.; Gentry-Maharaj, A.; Graham, R.; Allen, D.; Pedersen, J. W.;
Nudelman, A. S.; Blixt, O.; Foukala, E. O.; Bueti, D.; Dawnay, A.; Ford, J.; Desai, R.; David, L.;
Trinder, P.; Acres, B.; Schwientek, T.; Gammerman, A.; Reis, C. A.; Silva, L.; Osorio, H.;
Hallett, R.; Wandall, H. H.; Mandel, U.; Hollingsworth, M. A.; Jacobs, I.; Fentiman, I.; Clausen,
H.; Taylor-Papadimitriou, J.; Menon, U.; Burchell, J. M., Autoantibodies to MUC1
glycopeptides cannot be used as a screening assay for early detection of breast, ovarian, lung or
pancreatic cancer. British Journal of Cancer 2013, 108, 2045-2055; (b) Tarp, M. A.; Sorensen,
A. L.; Mandel, U.; Paulsen, H.; Burchell, J.; Taylor-Papadimitriou, J.; Clausen, H., Identification
of a novel cancer-specific immunodominant glycopeptide epitope in the MUC1 tandem repeat.
Glycobiology 2007, 17, 197-209; (c) Sorensen, A. L.; Reis, C. A.; Tarp, M. A.; Mandel, U.;
Ramachandran, K.; Sankaranarayanan, V.; Schwientek, T.; Graham, R.; Taylor-Papadimitriou,
J.; Hollingsworth, M. A.; Burchell, J.; Clausen, H., Chemoenzymatically synthesized multimeric
Tn/STn MUC1 glycopeptides elicit cancer-specific anti-MUC1 antibody responses and override
tolerance. Glycobiology 2006, 16 (2), 96-107; (d) Brockhausen, I., Mucin-type O-glycans in
human colon and breast cancer: glycodynamics and functions. EMBO Reports 2006, 7 (6), 599604; (e) Muller, S.; Hanisch, F. G., Recombinant MUC1 probe authentically reflects cell-specific
O-glycosylation profiles of endogenous breast cancer mucin. high density and prevalent core 2based glycosylation. Journal of Biological Chemistry 2002, 277 (29), 26103-26112; (f)
Westerlind, U.; Hobel, A.; Gaidzik, N.; Schmitt, E.; Kunz, H., Synthetic vaccines consisting of
tumor-associated MUC1 glycopeptide antigens and a T-cell epitope for the induction of a highly
specific humoral immune response. Angewandte Chemie, International Edition in English 2008,
47 (39), 7551-7556; (g) Cai, H.; Sun, Z.-Y.; Huang, Z.-H.; Shi, L.; Zhao, Y.-F.; Kunz, H.; Li, Y.M., Fully synthetic self-adjuvanting thioether-conjugated glycopeptide-lipopeptide antitumor
vaccines for the induction of complement-dependent cytotoxicity against tumor cells. Chemistry
– A European Journal 2013, 19 (6), 1962-1970.
108. Bäckström, M.; Link, T.; Olson, F. J.; Karlsson, H.; Graham, R.; Picco, G.;
Burchell, J.; Taylor-Papadimitriou, J.; Noll, T.; Hansson, G. C., Recombinant MUC1 mucin with
a breast cancer-like O-glycosylation produced in large amounts in chinese-hamster ovary cells.
Biochemical Journal 2003, 376, 677-686.
109. Koeller, K. M.; Smith, M. E. B.; Wong, C.-H., Chemoenzymatic synthesis of
PSGL-1 glycopeptides: Sulfation on tyrosine affects glycosyltransferase-catalyzed synthesis of
the O-glycan. Bioorganic & Medicinal Chemistry 2000, 8 (5), 1017-1025.
110. Vasella, A.; Witzig, C.; Chiara, J.-L.; Martin-Lomas, M., Convenient synthesis of
2-azido-2-deoxy-aldoses by diazo transfer. Helvetica Chimica Acta 1991, 74 (8), 2073-2077.
111. Guazzelli, L.; Catelani, G.; D’Andrea, F.; Giannarelli, A., Stereoselective entry
into the D-GalNAc series starting from the D-Gal one: A new access to N-acetyl-D-galactosamine
and derivatives thereof. Carbohydrate Research 2009, 344 (3), 298-303.

94

112. Wu,
Z.;
Guo,
X.;
Guo,
Z.,
Chemoenzymatic
synthesis
of
glycosylphosphatidylinositol-anchored glycopeptides. Chemical Communications 2010, 46 (31),
5773-5774.
113. Schultz, M.; Kunz, H., Synthetic O-glycopeptides as model substrates for
glycosyltransferases. Tetrahedron: Asymmetry 1993, 4 (6), 1205-1220.
114. Winans, K. A.; King, D. S.; Rao, V. R.; Bertozzi, C. R., A chemically synthesized
version of the insect antibacterial glycopeptide, diptericin, disrupts bacterial membrane integrity.
Biochemistry 1999, 38 (36), 11700-11710.
115. Lutz, M. B.; Kukutsch, N.; Ogilvie, A. L. J.; Rößner, S.; Koch, F.; Romani, N.;
Schuler, G., An advanced culture method for generating large quantities of highly pure dendritic
cells from mouse bone marrow. Journal of Immunological Methods 1999, 223 (1), 77-92.

95

CHAPTER 2: Engineered Virus-Like Particle Qβ as a Novel Carrier for TACA-Based
Anticancer Vaccines
2.1 Introduction
2.1.1

Virus-like particle as a vaccine carrier

The first part of this dissertation has already shown the importance of nanoparticle
platform that helps direct the antigen into lymph node and multivalent display of the antigen to B
cells resulting in higher immune response when compared with the soluble form. Although the
combination of the nanoparticle with adjuvant MPLA can bypass the requirement of Th epitope
for antibody isotype switching, the IgG titers of the generated antibodies were still inferior to
those induced by immunogenic protein carriers. This is probably due to the lack of direct effect
from the Th epitope. Another type of carrier platforms that our group has demonstrated its
promising potential in activating the immune system to elicit strong anti-TACA immune
responses is virus-like particle.
Virus-like particles (VLPs) are highly organized nano-constructs built from self-assembly
of multimeric subunits of one or more proteins. This self-assembled nanoparticle resembles the
structural organization of the protein in a viral capsid. VLPs differ from natural viruses in the
way that VLPs are not able to infect host and they are non-replicating due to the lack of
infectious viral genetic materials. Many features of VLPs render themselves a highly attractive
candidate platform for vaccine application. The repetitiveness of highly ordered organization of
the protein(s) in the VLPs is well recognized as pathogen-associated molecular patterns
(PAMPs)1, which is ideal for effective polyvalent display of antigen to crosslink B-cell receptors
to induce intense cellular signaling for strong immune activation.2 The distance between subunits
of the capsid allows positioning B cell epitopes 5-10 nm away from each other, which was found

96

to optimally activate B cells.3 Similar to the iron oxide nanoparticle, the nanostructure of the
VLPs, which is in size range of 20 to 100 nm, can efficiently drain into lymph nodes to directly
interact with residing immune cells, which has been demonstrated in the first chapter (For
review, see4). During the recombinant protein expression, the nucleotide molecules (RNA) from
E. coli cell host can be encapsulated in the empty cavity of the VLPs. These non-infectious
genetic materials can act like internal adjuvants, and subsequently be released after particle
dissociation during cellular uptake to stimulate internal cellular signals via TLR3/7/8/9 in the
antigen presenting cells. Moreover, the production of VLPs can be done in a variety of
expression systems including plant, bacterial, yeast, insect, mammalian cell and cell-free
systems. These expression systems allow the production to be scaled up to manufacturing level.5
All of these characteristics make VLPs a promising platform for vaccine development, which has
been utilized in many recent vaccines including those against viruses, bacteria and chronic
diseases.6
2.1.2

Bacteriophages

Viruses are viewed as the simplest organism that live to transfer genetic material, either
DNA or RNA, into their host cells in order to replicate themselves. The hosts for viruses extend
from single-cell organism to vertebrate. The specificity of the host to viruses depends on the
compatibility of the cellular machinery that a certain group of viruses will take over for the
replication. A group of viruses that specifically infects only bacteria is known as bacteriophages,
or phages.
2.1.3

Bacteriophage Qβ

Bacteriophage Qβ belongs to genus allolevivirus, which is in Leviviridae family. This
bacteriophage carries a single-stranded RNA genome encoding for a maturation protein (A1-

97

protein), a replicase enzyme and a coat protein. The production of Qβ VLP can be carried out by
recombinant protein expression in E. coli, yeast and cell-free protein synthesis, which provide
flexibility in research and capacity in large-scale production.7 The monomer of Qβ’s coat protein
is composed of 132 amino acids. It can be divided into 9 domains including 2 domains of beta
hairpin (βA and βB) starting from the N-terminus, followed by 5 domains of stranded beta sheets
(βC, βD, βE, βF, βG), and ending with 2 domains of alpha-helixes (aA and aB) towards the Cterminus (Figure 2.1a). The alignment of the alpha-helixes of a subunit over beta stands F and G
of another subunit results in initial dimer formation (Figure 2.1b,c). The beta-sheet domains are
located in the internal side of the capsid, which is involved the binding to the hairpin sequence of
the encapsulated RNA.8 The single-stranded RNA is believed to facilitate the self-assembly of
the viral capsid by forming an initial complex with a few dimers first. This intermediate complex
will attract each other to assemble to form fivefold- and quasi-sixfold units. These multifoldunits will finally assemble to form a well-organized icosahedral construct. Each Qβ viral capsid
is composed of 180 units of the monomer per capsid with triangulation number (T) = 3.9 The Qβ
viral capsid has diameter approximately 27 nm.10 In vaccine applications, this single-stranded
RNA (ssRNA) is an agonist of TLR7,11 where their interaction helps enhance immune activation
via Th1 type response12 and presentation of Th epitopes on MHC class II.13 In contrast to
recombinantly expressed coat protein from E. coli, the native viral capsid contains 3-5 subunits
of maturation protein or A1 protein, in which the amino acid sequence is extended C-terminally
to 196 amino acids as a result of natural read-through of the stop codon UGA in the gene of the
coat protein.14 This extended domain of A1 protein is believed to help infect bacteria.10, 15 The
incorporation of A1 protein into the natural viral capsid suggests that extending of the C-terminal
of some subunits with a short peptide does not disrupt the ability of the admixed proteins to form

98

the capsid. Since the C-terminally extended peptide was found to be exposed on the surface, this
implication has been applied for in situ conjugation by genetic manipulation to link an antigen
peptide for vaccine application16 or a poly-histidine tag for ease of purification.17 Qβ VLP is
exceptionally stable compared to other viral capsids from the same family due to inter-subunit
disulfide bonds between cysteine residues at positions 74 and 80 (green residues in Figure 2.1d)
of the adjacent subunit where they form networks to hold five- and six-fold units together
(Figure 2.1d).8c, 18
a)

b)

c)

d)

Figure 2.1: Qβ protein structure (PDB-ID: 1QBE), a.) Qβ subunit protein with secondary
structure domains; b,c) The alignment of the dimer subunit and all lysine residues; d) The
organization of fivefold- and quasi-sixfold units to form icosahedral shape with triangulation
number (T) = 3. The green residues are cysteines at position 74 and 80, which form an intrasubunit disulfide bond.

99

2.1.4

Bacteriophage Qβ VLP in vaccine applications

Qβ VLP has been long investigated, both pre-clinically and clinically, as a vaccine carrier
for many antigens by Martin F. Bachmann’s group and Cytos Biotechnology. A vaccine against
nicotine for smoking-cessation was evaluated in 2005.19 Due to the low immunogenicity of
nicotine, inducing potent immune response to neutralize and block the addictive molecule into
the brain was challenging. Cytos Biotechnology has demonstrated that covalently conjugating
nicotine onto Qβ VLP in high valency number (585 nicotine molecules per particle) can greatly
enhance the immunogenicity of nicotine. Administering the nicotine conjugate vaccine with
alum adjuvant can induce Th1 immune response in mice, rats and rabbits. The titers of the
antibody response were shown to be 50-fold higher than titers from nicotine conjugated to a
common carrier protein, BSA. The vaccine was shown to reduce the nicotine level in brain by
approximately half in the vaccinated mice. The Qβ VLP as a carrier platform for nicotine proved
safe and low in side-effect in phase I clinical trial. In phase II clinical trial, the nicotine
conjugated vaccine was safe and able to induce the immune response in all immunized patients.
However, only a group of the subjects that showed sufficiently high antibody response achieved
statistically significant difference in smoking-cessation.
In 2006, Bachmann’s group reported using Qβ VLP to induce antibodies against a house
dust mite allergen Der p1 in human subjects (phase I clinical trial).20 The study indicated that the
repetitive pattern display of otherwise non-immunogenic peptide allergen on VLP can enhance
immunogenicity of the antigen. The vaccine was capable of inducing IgM and IgG response
without the help from adjuvant. The immune response was found to be dose-dependent.
In 2007, Qβ based vaccine has been investigated to generate antibody against a selfantigen, angiotensin II, for hypertension treatment.21 The short peptide of angiotensin II
(angiotensin1-8) covalently linked to Qβ VLP was found to induce strong antibody response with
100

high affinity against the whole angiotensin II in mice and rats without using an adjuvant. The
vaccinated rats were found to have significant lower blood pressure compared with a control
group. However, the antibody response subsided over time after the last injection. Phase I
clinical trial of this vaccine was shown to be highly efficient in human subject (100% responder
rate), yet well tolerated and safe. With the promising results, this angiotensin II conjugated Qβ
vaccine (CYT006-AngQβ) was assessed in phase II clinical trial. Although the vaccine proved
immunogenic, well tolerated and no adverse side effect, the efficacy of the vaccine was dose
dependent and the antibody response was also reversible as found in phase I. Only a dose of 300
μg induced sufficient anti-angiotensin II antibody titers to significantly reduce blood pressure in
patients.
The use of Qβ VLP as a carrier platform for glycoprotein hemagglutinin (HA) to induce
neutralizing antibodies against H5N1 influenza virus has been evaluated in 2013.22 E. coli
derived globular head domain of hemagglutinin (HA) glycoprotein, which was found as a
neutralizing epitope on the influenza viral capsid23, was conjugated on Qβ VLP. Compared with
a licensed anti-H5N1 influenza vaccine, Panvax, the antigen-Qβ VLP conjugate formulated with
alum adjuvant induced as high neutralizing antibody titer as Panvax. Although, the Qβ-based
vaccine requires approximately 5 times higher dose of the globular HA content to induce
comparable titer, the Qβ-based vaccine is superior over Panvax in activating T helper cells to
elicit Th1 related cytokine interferon-γ (IFN-γ), while the protecting immunity from Panvax did
not involve T helper cell activation. This is due to the presence of Th epitope on both the
globular protein and the Qβ VLP. Both arms of immunities were thought to synchronize in
reducing virus titers in challenged mouse and ferret animal models. Moreover, in another

101

publication, mice immunized with the conjugate vaccine were protected from lethal infection
with homologous and highly drifted viral strains.23c
One important inference from this work is the potential Th epitopes of Qβ VLP.
EPIMAX technique was utilized to reveal the peptide regions in Qβ viral capsid that are capable
of activating CD4+ T cells in splenocytes from mice. Peptide regions 41-71 and 101-132 (Table
2.1) were found to induce CD4+ T cells to release high level of cytokine IFN-γ, hence, these two
regions are suspected to contain Th epitopes (Figure 2.2). The resulting peptide regions are
aligned on the 3D crystal structure of Qβ subunit as shown in Figure 2.3.

Figure 2.2: Qβ specific T cell responses were measured from level of cytokines secreted from
splenocytes of HA conjugated Qβ immunized mice with peptide pools spanning Qβ capsid
protein regions. Each bar represents the total cytokine response to each peptide pool and the
colored boxes represent level of each specific cytokine. Each peptide pool is composed of 5
peptides fragments that have the overlap sequences as listed in Table 2.1. The figure is
reproduced from reference22.

102

Table 2.1: Sequences of Qβ specific peptides used for re-stimulation of splenocytes from the
vaccinated mice.22
Protein
Qβ
Qβ
Qβ
Qβ
Qβ
Qβ
Qβ
Qβ
Qβ
Qβ
Qβ
Qβ
Qβ
Qβ
Qβ
Qβ
Qβ
Qβ
Qβ
Qβ
Qβ
Qβ
Qβ
Qβ
Qβ
Qβ
Qβ
Qβ
Qβ
Qβ

Peptide #
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30

Peptide pools
Qβ 1
Qβ 1
Qβ 1
Qβ 1
Qβ 1
Qβ 2
Qβ 2
Qβ 2
Qβ 2
Qβ 2
Qβ 3
Qβ 3
Qβ 3
Qβ 3
Qβ 3
Qβ 4
Qβ 4
Qβ 4
Qβ 4
Qβ 4
Qβ 5
Qβ 5
Qβ 5
Qβ 5
Qβ 5
Qβ 6
Qβ 6
Qβ 6
Qβ 6
Qβ 6

103

Amino Acid Sequence
AKLETVTLGNIGKDG
TVTLGNIGKDGKQTL
GNIGKDGKQTLVLNP
KDGKQTLVLNPRGVN
QTLVLNPRGVNPTNG
LNPRGVNPTNGVASL
GVNPTNGVASLSQAG
TNGVASLSQAGAVPA
ASLSQAGAVPALEKR
QAGAVPALEKRVTVS
VPALEKRVTVSVSQP
EKRVTVSVSQPSRNR
TVSVSQPSRNRKNYK
SQPSRNRKNYKVQVK
RNRKNYKVQVKIQNP
NYKVQVKIQNPTACT
QVKIQNPTACTANGS
QNPTACTANGSCDPS
ACTANGSCDPSVTRQ
NGSCDPSVTRQAYAD
DPSVTRQAYADVTFS
TRQAYADVTFSFTQY
YADVTFSFTQYSTDE
TFSFTQYSTDEERAF
TQYSTDEERAFVRTE
TDEERAFVRTELAAL
RAFVRTELAALLASP
RTELAALLASPLLID
AALLASPLLIDAIDQ
ASPLLIDAIDQLNPAY

Figure 2.3: X-ray crystal structure of Qβ subunit (1qbe). The red and blue colored regions
display the most probable Th epitopes. Red region = Qβ41-71, Blue region = Qβ101-132.
In this study22, the importance of the ssRNA packaged in Qβ VLP was illustrated. The
presence of the encapsulated ssRNA in Qβ enhanced the expression of IFNγ in CD4+ T cell and
elicited antibody titers 4 times higher than the titer from the capsid with ssRNA replaced by
polyglutamic acid. Although the difference in the total titer was not statistically significant, the
inclusion of the ssRNA directed the immune response towards Th1 type response as shown by
higher IgG2a over IgG1 response, which was reversed in the titers from the one without the
encapsulated ssRNA. Since the lack of the ssRNA does not significantly affect the total
neutralizing titer when administered with alum adjuvant, directing immunity to favor Th1 or Th2
response could be controlled by Qβ VLP devoid of or containing the encapsulated ssRNA.
In 2010, Qβ VLP was assessed by Dannis R. Burton and M.G. Finn groups as an antigen
carrier for inducing broadly neutralizing antibodies against a cluster of high mannose glycan, a
“glycan shield” of the glycoprotein gp120 displayed on the surface spike of HIV.24 Inducing
protective humoral immunity to generate neutralizing antibodies against HIV is highly
challenging as the conserved epitope on the viral envelop spike is shielded by highly variable

104

immunogenic epitope and clusters of glycans. The discovery of broadly neutralizing monoclonal
antibody 2G12, which binds the high-mannose glycan shield and protect the viral infection,
suggested an alternative target for anti-HIV vaccine development. Due to the multivalent antigen
display pattern of Qβ, the attached antigens can mimic the cluster of trimeric structure of the
viral envelop spike glycoprotein. Branched oligomannose glycans were conjugated via CuAAC
reaction on the wild-type Qβ, mutant QβK16M or QβHPG, where the most reactive lysine at
position 16 was replaced by an unnatural amino acid homopropargyl glycine (Figure 2.1). The
mannoside Qβ conjugates were found to well represent the epitope of mAb 2G12 as shown by
strong binding profile from sandwich ELISA. Although the Qβ glyco-conjugates was able to
elicit high titers of antibodies specific to the synthetic high-mannose glycans, they failed to
induce antibodies that have specific binding against the native glycan shield on HIV as the mAb
2G12. One important implication from this work is that the QβK16M-Man9 elicited lower
antibodies against the Qβ carrier than QβK16M-Man4 and much lower than naked QβK16M.
This suggested that the bulkier the size of antigen attached on the Qβ, the lower the titers of anticarrier antibodies. This is probably because the immunogenic B-cell epitopes on Qβ capsid could
be shielded by the attached antigen, making the carrier epitope less accessible to Qβ-specific B
cells.

105

Figure 2.4: Top panel: Branched oligomannose glycans were conjugated via CuAAC reaction
on the wild-type Qβ, mutant QβK16M or QβHPG, where the most reactive lysine at position 16
was replaced by an unnatural amino acid homopropargyl glycine. Bottom panel: Synthesis of
QβHPG glycoconjugates QβHPG-Man8 (11) and QβHPG-Man8/Man9 (12). The figure is
reproduced with permission from reference22.
Qβ VLP has also been used as a carrier for inducing antibodies against inflammatory
cytokine interleukin-1β (IL-1β) to treat type 2 diabetes.25 In 2014, a “detoxified version” of IL1β chemically conjugated on Qβ VLP was shown to be safe and able to mount IgG antibodies to
neutralize IL-1B and improved glucose tolerance in diet-induced type 2 diabetes mouse model.
This vaccine was further assessed in nonhuman primate subjects followed by phase I and II
clinical trial with patients with type 2 diabetes.26 Although the vaccine was demonstrated to be

106

clearly safe in both subjects in the studies, the efficacy of the vaccine is relatively low, as the
titers of anti-IL-1B IgG induced were not sufficiently high compared with the results tested in
mouse model. To generate the neutralizing titers of the anti-IL-1B IgG, the vaccine needed to be
given in high dose (900 μg/injection) up to eight injections. Moreover, the titers elicited were
decreased over time after immunization. The anti-carrier immune response against the Qβ was
found to be relatively strong and this is suspected to be a factor responsible for low titers against
the conjugated antigen.
In 2015, Erin Crossey and colleagues reported Qβ VLP based vaccine to induce
antibodies against protein converstase subtillisin/kexin type 9 (PCSK9), which is a protein that
disrupts a regulation process of low-density lipoprotein cholesterol (LDL-C) in blood
circulation.27 High level of this secretory protein leads to increasing level of LDL-C, a purported
cause of hypercholesterolemia, atherosclerosis and cardiovascular disease. Even though,
inducing potent immunity against this self-antigen was considered challenging due to B cell
tolerance, this study is one of many cases mentioned earlier showing that conjugating the selfantigen on Qβ VLP can break B cell tolerance and generated strong neutralizing immunity
against the self-antigen in mice and non-human primate macaques.28
In addition to Cytos Biotechnology AG, Pfizer Vaccine Immunotherapeutics has also
been working on utilizing Qβ VLP in vaccine application. In 2016, there was a report of using
Qβ VLP for anti-IgE vaccine aiming to treat both allergic asthma and rhinitis.11 The main part of
this study was on the importance of the encapsulated ssRNA. The role of the RNA as a TLR7
agonist was emphasized through the elicited high antibody response in wide-type mice but low in
TLR7-knocked out mice. The lack of the encapsulated RNA can be compensated by adding
external adjuvants including alum and CpG adjuvants.

107

In conclusion, many studies and clinical trials have proved the Qβ VLP as a promising
immunogenic antigen carrier to break B cell tolerance and induce high antibody responses
against self-antigens. The high potential of Qβ VLP in such purpose renders itself highly
attractive for the development of TACA-based anticancer vaccine, where the antigens are selfantigens and weakly immunogenic. Moreover, after more than a decade, there is still no
approved vaccine derived from Qβ VLP. This is probably due to the Qβ based vaccines
mentioned above have not yet been optimized to be potent enough for approval. This also
suggests that much improvement of this vaccine carrier construct is still needed.
2.1.5

Qβ VLP as a carrier for TACA-based anti-cancer vaccines.

The major challenge of anti-TACA vaccine is the low immunogenicity of TACAs. Two
main factors are believed to contribute to their low immunogenicity. First, unlike glycopeptide
MUC1, most TACAs are non-peptidic. Hence, administering TACAs alone fails to induce
effective immunity due to the lack of help from T helper cells.29 Secondly, TACAs are selfderived antigens, to which the self-tolerance mechanism suppresses their immunogenicity in
order to prevent autoimmunity. Therefore, immunogenic carriers are generally required to render
TACAs sufficiently immunogenic.
Keyhole limpet haemocyanin (KLH), or tetanus toxoid (TT) are traditional immunogenic
proteins used for TACA based vaccine design. Despite strong immunogenicity of KLH,
vaccination of KLH-Tn failed to generate IgG of anti-Tn antibodies probably due to the very low
immunogenicity of the Tn antigen.30 Another reason for the low anti-TACA response is the
improper antigen display. This has been supported by studies from Danishefsky and Lo-Man
groups. They showed that by putting Tn antigen together into a trimeric cluster, instead of
monomeric form, the constructs can elicit more antibodies than those from the monomeric Tn

108

conjugated constructs.31 As mentioned in the first chapter, the pattern of antigen display on the
vaccine construct plays a crucial role to effectively cross link B cell receptor to induce strong
cellular signals for B cell activation leading to IgM-to-IgG isotype switching and subsequent
potent antibody response. Since KLH is amorphous where its antigen display is not highly
ordered, it is not very effective for generating a strong humoral immune response. Moreover,
KLH

is a glycoprotein, containing native glycans,32 which can possibly compete with

conjugated TACAs for anti-glycan B cell responses.
Unlike KLH or TT, VLP is superior to those carriers for the proper size and highly
organized display pattern for particulate vaccine as described above. Our group has demonstrated
the utility of VLPs as a promising antigen carrier platform for TACA based anti-cancer vaccines.
In 2008, our group started to apply VLP as an immunogenic carrier for anti-TACA based
vaccine. Cowpea mosaic virus (CPMV) was the first VLP that was examined for the purpose.
CPMV is a plant virus, thus, non-infective and safe to humans. The viral capsid is composed of
60 subunits of a self-assembly protein to form a 30 nm icosahedral capsid. The Tn antigen
(GalNAc-a-O-Ser/Thr) was selected as a prototypical model for TACA in this study. Maleimide
linked Tn was reacted with site-specific mutagenesis derived cysteines on the exterior surface of
the viral capsid. The number of Tn loaded was 60 Tn/capsid. The immunization was tested in
mouse with a dose of 40 μg of Tn/mouse. The anti-Tn IgG titer elicited from the immunization
was 10,500. The sera from the immunized mice showed binding to Tn expressed cancer cells
MCF-7 and multidrug resistant breast cancer cell line NCI-ADR RES as determined by FACS.
This work established a new type of carrier platform for presenting TACA in an organized
display pattern to induce strong immune response against otherwise low immunogenic antigen of

109

the monomeric Tn antigen. This encouraging finding led to exploring other promising VLPs for
highly effective carriers for anti-TACA vaccine.
In 2012, tobacco mosaic virus (TMV) capsid was evaluated as a carrier for Tn antigen.33
TMV capsid derives from self-assembly protein of 2130 subunits to form a 300 nm long nanorod.34 Tn antigen was conjugated to genetically inserted cysteine near C-termini, which is
exposed on the capsid surface. From the analysis, 410 Tn antigens were attached on each capsid.
The TMV-Tn vaccine induced low level of IgG or IgM anti-Tn antibodies (titer ≈ 1,600)
presumably due to the low density of Tn antigens on the viral capsid. The efficiency of
conjugation was improved by robust reaction of copper(I) catalyzed azide-alkyne cycloaddition
reaction (CuAAC). The number of Tn attached on TMV was increased up to 1530 Tn/TMV.
However, there were little changes of IgG/IgM titers compared with the previous method of
conjugation. When the conjugation site was changed to Tyr 139, which locates close to the
capsid’s surface, 2000 copies of Tn were linked onto a TMV capsid due to the well exposed and
reactive residue at this position. Putting the antigen on such a well exposed point on the capsid
could potentially get better recognition by B cells. Significantly higher antibody titers (titer ≈
2550) were elicited from immunized mice by this formulation. Note that, the dose in this
administration was 4 times (20 μg vs 4 μg Tn/mouse) higher than the previous two constructs.
By extending the linker to better exposed the Tn out from the surface, the resulting IgG antibody
titers increased up to about 7000 with 4μg of Tn/mouse dose. However, with 20 μg of Tn/mouse
dose, the short and long linkers elicited comparable antibody titers. This suggests that increasing
the linker length does not help increase the immune response. The resulting antibodies could
bind to Tn or GalNAc containing antigens coated on glycan microarrays and native Tn on human
leukemia Jurkat cells as determined by FACS. It is interesting that, despite the lower titer, the

110

serum from the dose of 20 μg of Tn can bind stronger against the cells, compared with the serum
from mice receiving of 4μg Tn. This work indicated that the increased number of Tn on the
construct is not responsible for the higher antibody response, but the location where the antigen
is displayed, is crucial in inducing strong immune responses.
In 2013, it was the first time that Qβ VLP was reported by our group as a carrier for
TACA based anti-cancer vaccine.35 In contrast to rod shape of TMV, Qβ has icosahedral shape,
which can present an antigen in an ordered manner. Although Qβ and CPMV are about the same
in size, their capsid surface topologies are different. The CPMV is composed of 60 asymmetric
subunits of 66 kDa protein, while Qβ is composed of 180 subunits of 14 kDa protein. By
controlling reaction time and equivalence of the azide-modified Tn in the CuAAC reaction, the
number of Tn loaded onto the Qβ capsid could be varied from 78, 150 to 340 Tn/Qβ (Figure 2.5).
Compared with other VLPs mentioned before, Qβ is superior to CPMV or TMV in ability to
induce dramatically higher IgG titers (titers ≈ 263,600) at the same antigen dose (4μg of
Tn/mouse).
In addition to antibody response against Tn, it was found that the vaccine can also induce
immune response against the carrier Qβ and the triazole linker (titers ≈ 35,300), which may
suppress the desired immune response against the Tn. The impact of local density of the
immobilized Tn on Qβ VLP has also been investigated. Qβ-Tn conjugates with varied density of
Tn on each capsid (low density (78 Tn/Qβ), medium density (150 Tn/Qβ) and high density (340
Tn/Qβ)) were injected into groups of mice by either keeping amount of Qβ constant or both the
total amounts of Tn and Qβ constant. The results showed that only groups that received high
local density Qβ-Tn generated strong IgG antibody response. This suggests the importance of the
high local density of the antigen on each particle in inducing high IgG antibody response. These

111

results provided another crucial factor for the design in the vaccine development. The resulting
sera from the immunized mice showed specific binding to GalNAc containing glycans coated on
glyco-microarray chip and native Tn expressed on human leukemia cancer cells, Jurkat cells.
The higher potency of Qβ over other VLPs in inducing immunity against TACA excited us to
investigate further into detail of this construct aiming to find the best formulation of this carrier
for anti-TACA-based vaccine. This led to a following study by the same group of investigators.

Figure 2.5: Synthesis of Qβ-triazole-Tn via CuAAC reaction. The reaction condition can be
adjusted to provide a variable number of Tns (78, 150 and 340 Tns) attached on the viral capsid.
This figure is adapted and reproduced with permission from reference35.

112

Figure 2.6: a) a table showing characteristic details of the vaccine compound with varied Tn
density used in 6 groups to investigate the effect of antigen density on the viral capsid. b) ELISA
results of IgG and c) IgM antibodies from 6 groups of immunized mice at 1/6400 dilution. This
figure is adapted and reproduced with permission from reference35.
In 2015, our group found that the conjugation linker between the Tn and Qβ played an
important role in generating of protecting antibodies against Tn expressing cancer cells.36 The
results showed that the triazole formed in the linker from CuAAC conjugation method can
induce immune response against the linker. In contrast to the previous finding, increasing the
density of the Tn on each capsid from 360 to 540 did not result in higher anti-Tn IgG antibody
titer, but higher anti-triazole-linker IgG antibody titer was produced instead (Figure 2.7a-c). This
suggests that there are some optimal points in increasing the number of the attached antigen on
each capsid to obtain the best result, especially in this case that there are other competitive
immunogenic components in the construct, such as the rigid triazole ring. The triazole
immunogen can compete with Tn to dominate the immune response and suppress anti-Tn

113

immunity. Although the resulting sera can bind to Tn-expressing Jutkat cells, they failed to bind
to Tn expressing murine breast cancer TA3Ha cells (Figure 2.7d).
In contrast, when removing the competing epitope in the linker by changing the linker
from the rigid triazole linker to a non-rigid alkyl amide linker, the vaccine construct could not
only elicit significantly higher titers of IgG antibody against Tn (1,461,000 vs 263,600) (Figure
2.7e,f), but the resulting sera also showed binding to both Jurkat and TA3Ha cells. The new
vaccine construct significantly improved survival rate of mice in tumor challenge from 0% to
50% when combined with chemotherapy. This finding clearly supports that an immunogenic
component in the vaccine construct can indeed suppress the desired immune response against
TACA. The further mechanistic investigation found that it is not the triazole moiety itself that
interferes the binding between the Tn and B cell receptor, rather most likely the induced antitriazole polyclonal antibodies hindered the recognition of Tn by Tn-specific B cells. Moreover,
this induced anti-triazole antibody was found to generate faster than those against the Tn. In
summary, this work suggested that any potentially immunogenic components in the vaccine
construct should be removed to minimize the suppressing effect towards the desired antigen
caused by the induced antibodies against the interfering component.

114

Figure 2.7: a) Vaccine constructs Qβ-Tn 4 and Qβ-Tn 5. b,c) IgG titers elicited from the vaccine
constructs against Tn or triazole. The increased number of attached Tn induced lower anti-Tn
antibody titers due to suppression from increased anti-triazole immune response. d) Specific
recognition against Tn-expressing cancer cells of the elicited antibodies from Qβ-Tn 1 and QβTn 6. e) Vaccine constructs Qβ-Tn 6 where the triazole linker was replaced with low
immunogenic alkyl linker. f) anti-Tn antibody titers elicited from Qβ-Tn6. The IgG titers became
higher compared with those from Qβ-Tn 4 and Qβ-Tn 5. This figure is adapted and reproduced
with permission from reference36.
Investigations described above contributed key knowledge for the design of VLP based
anti-TACA vaccine as the following: 1) Qβ is, by far, the best carrier for the anti-TACA vaccine;
2) A co-adjuvant has been optimized; 3) The local density of the antigen on each capsid plays an
important role for effective immune response; and 4) Unnecessary immunogenic component,
such as immunogenic linker, should be excluded to maximize the desired immune response
against TACA. However, another big challenge still remains, which is the robust
immunogenicity of the carrier Qβ itself. Similar to the triazole linker, the strong antibody
response against the carrier can cause carrier-induced epitopic suppression (CIES) resulting in
reduction of the desired immune response against TACA.37 It is envisioned that minimizing such
strong immunogenicity of the carrier would re-focus the immunity towards generating higher
potency of the desired immune response against TACAs. To logically address this issue, we need
115

to understand the mechanism of the suppressing effect for a rational approach towards carrier
modification.
2.1.6

Carrier-Induced Epitopic Suppression (CIES) in Qβ

Carrier-Induced Epitopic Suppression (CIES) is referred as an effect derived from preexisting or co-induced immunity against immunogenic carrier that suppresses immune response
against any weaker immunogen attached on the related carrier. The exact mechanism of CIES is
still unclear. Based on several studies, the main immune cells responsible for CIES are B cells.38
The mechanism of CIES has been proposed by several views. The investigation from Schutze et.
al. led to a theory of antigen/carrier specific B cells competition, where the higher rate of
proliferation of carrier-specific B cells will dominate the number of haptan-specific B cells in
competing for the antigen binding and stimulating cytokines for cellular activation.38a In contrast,
Galelli et. at. found that the immunogenic carrier does not alter the number of haptan-specific
memory B cells, but it prevents the memory B cells from turning into antibody releasing plasma
cells.38c In addition to both theories, CIES is also generally viewed as the clearance mediated by
pre-existing innate immunity against the carrier.
The effect of CIES on Qβ VLP as a vaccine carrier has been studied by the Bachmann
group.37 In this study, an 18 amino acid peptide antigen from Salmonella (D2) was used as a
model antigen. The CIES effect on Qβ was evaluated by comparing the antibody titers from
naive mice and pre-immunized mice with the carrier Qβ. The result showed that the antibody
titers against D2 antigen from pre-immunized mice were statistically significantly lower than
those from naïve mice. This result clearly indicated the suppression effect of pre-existing
immunity against Qβ due to CIES. An interesting finding in this study is the effect of antigen
density on the carrier on the reduction of CIES. It was found that the higher the antigen density

116

(142, 293 vs 13, 56, 94), the lower the suppression from pre-existing anti-carrier immunity
(Figure 2.8). The authors gave an explanation from a mechanistic investigation that the preexiting carrier-specific antibodies will bind the subsequently injected vaccine. The bound
antibodies sterically interfere the presentation of the antigen and the binding between the antigen
and B-cell receptors. The increased antigen density can help block the anti-carrier specific
antibodies, resulting in less interference and increasing B cell interaction with the desired antigen
attached. This explanation resembles the finding from our group that the induced anti-triazole
antibodies will bind to the Qβ-Tn vaccine and sterically blocked Tn recognition by Tn-specific B
cells. It is worth noting that the pre-immunization with the carrier did not change the anti-carrier
antibodies titers from the vaccination, except with highest antigen density (293 D2/Qβ), where
the anti-carrier significantly reduced in the naïve mice, yet the anti-D2 antibodies titers increased
in pre-immunized mice. This is because the higher density of the attached antigen better shields
the B cell epitopes on the carrier, making the carrier less recognizable by carrier-specific B cells.
The shielding effect caused by the attached antigen is correlated well with the finding from an
investigation of Qβ based anti-HIV vaccine by Burton and Finn groups, which has already been
mentioned above.24 Besides the increased antigen density, the authors suggested repeated
injections and increasing dose of the administration will also help to overcome the suppression
effect from CIES, leading to higher anti-D2 antibody response.
The mechanism of CIES of Qβ was investigated further by passively transferring of
antibodies or B cells or CD4+ T cells from pre-immunized mice into naïve mice, which were
subsequently immunized with the vaccine conjugate. The result showed that antibodies and B
cells are responsible for the CIES. This study also inferred that heterogeneous prime-boost
strategy for reducing CIES may not work with Qβ based vaccine as pre-immunizing the immune

117

system with D2 antigen conjugated with another VLP, AP205, did not significantly enhance the
titers of the antibodies against D2 antigen after subsequent injection with the D2-Qβ conjugate.

Figure 2.8: Antibody titers against D2 peptide (attached antigen) and Qβ VLP (carrier) elicited
from Qβ primed- or naïve mice after 1st, 2nd and 3rd vaccination. The result suggests that the
higher density of D2 on the Qβ helped reduce the suppression from CIES. This figure is adapted
and reproduced with permission from reference37.
The aforementioned studies showed clearly that VLP Qβ has the ability to cause CIES to
the attached antigen. The suppression could limit the full potential of the Qβ in inducing
maximum immune response against the antigen. Although the suppression effect could be
partially addressed by the suggested solutions, including increasing the density of the antigen,
repeated injection or increasing the dose, the improved results were still very subtle. Therefore,

118

an innovative strategy for reducing the CIES caused by the Qβ carrier is needed to unlock its
maximum potential towards the best carrier for TACA-based anticancer vaccine.
The robust immunity against the vaccine carrier originates from B cell activation through
binding with B cell epitopes in the Qβ capsid protein. In order to reduce undesired immune
response, B cell epitopes on Qβ capsid protein will have to be either removed or modified to
block the interactions with B cells. The strategy to achieve this was investigated as the following:
1) Firstly, the candidate fragments for B cell epitopes were searched based on
computational prediction from available 3D structure, together with analysis of binding of
synthetic peptide fragments by anti-capsid sera.
2) The potential B cell epitope on the viral capsid surface was subjected to site specific
mutagenesis to induce structural changes and introduce a new conjugation site. The mutated Qβ
capsid was then conjugated with a TACA antigen model and tested for its ability to shield the
dominant epitope to further prevent recognition by B cells.
3) The Qβ VLP mutant was stabilized by additional disulfide network to make it less
susceptible to disassembly after reactions to conjugate the antigen onto the new conjugation
sites. In addition, the higher stability of the capsid can potentially enable longer interactions of
the conjugate with immune cells leading to stronger immune activation. The best mutant Qβ was
selected based on the criteria of higher stability, decreased immunogenicity against the carrier
and increased antibody response towards the conjugated antigen.
2.2 Results and discussion
2.2.1

B cell epitope prediction

B cell epitopes are immunogenic fragments of a protein recognizable by B cell receptors
(BCRs). The recognition of B cell epitopes occurs through complementary interactions between

119

binding sites of B cell receptors and the antigenic fragments on the surface of an immunogen. B
cell epitopes are categorized into continuous and discontinuous types. The continuous, or linear,
epitopes are simple short fragments where all recognizable residues are aligned in sequence.
However, 90% of B cells epitopes are discontinuous or conformational epitopes39, in which the
fragments or residues responsible for the binding with BCR are not contiguous, but brought close
together by the folding of tertiary or quaternary protein structure. The type of B cell epitopes on
the Qβ capsid was tested first by peptide scanning experiment. Eight synthetic 30-amino-acid
peptides with overlapping sequence by 15 amino acids covering the entire amino acid sequence
of Qβ capsid protein (Figure 2.9a) were immobilized onto ELISA plate individually. Serum
from wide-type Qβ (wtQβ)-immunized mice was used to test the peptide recognition by antiwtQβ IgG antibodies. None of the synthetic peptides showed strong binding to the IgG anti-Qβ
antibodies from the serum compared with the binding with the whole capsids coated on the
ELISA plate (Figure 2.9b).
a)

Figure 2.9: a) Eight of synthetic 30-amino-acid peptides that overlapped sequence by 15
amino acids covering the entire amino acid sequence of Qβ capsid protein. b) ELISA result of
peptide scanning experiment showing the binding of the peptides fragments with the antiwtQβ IgG antibodies. The synthetic peptides were coated on the ELISA plate. The dilution of
serum (1/64000 dilution) from wtQβ-immunized mice was added to test recognition towards
each peptide fragments. Group (-) is a negative control group where only PBS was used in
coating process.

120

Figure 2.9: (Cont’d)
b)

4
3
2
1
0

For conformational epitopes, random mutations of B cell epitope on the 132-amino acid
Qβ viral capsid protein involves tedious work and high cost of mutations to the viral capsid. Due
to the complex structures of the capsid, the computational prediction based on available epitope
database are generally not very accurate. Nevertheless, the prediction could provide guidance
for potential mutation points and rational design in engineering the viral capsid, making the B
cell determination more practical with less time and cost. DiscoTope 2.0 server40
(http://www.cbs.dtu.dk/services/DiscoTope/) is one of available prediction severs for
discontinuous B cell epitopes. The prediction model is based on analysis of three-dimensional
structure of an input protein structure. The prediction algorithm behind DiscoTope employs
propensity scores from amino acid statistics, spatial proximity information and surface
accessibility profile of the protein structure to guide the determination of potential epitope
region. The prediction correlates well with available accessible surface profile from virus like
particle database (http://viperdb.scripps.edu/)41 (Figure 2.10 and Figure 2.11).

121

Figure 2.10: Discontinuous B cell epitope prediction by DiscoTope 2.0 server40 showing in
electron cloud surface is overlaid over 3D structure of Qβ capsid protein. The red areas represent
protein fragments that obtain high scores from the prediction.

Figure 2.11: A graph showing solvent accessible surface area (SASA) of each amino acid
residue in representative chain B of Qβ capsid protein (1qbe). The figure and data were obtained
from VIPERdb (http://viperdb.scripps.edu).41
Since our strategy for reducing anti-carrier antibody response is based on structural
modification to block the interactions between B cell epitopes and B cell receptors, selected
amino acid residues in the protein sequence were subjected to site-specific mutations to lysine in
order to introduce both structural change and new conjugation site for an antigen of interest to
122

additionally block the recognition by B cell receptors. In contrast to polymers or synthetic
inorganic nanoparticles, a single change of the viral capsid protein by the site-specific mutation
can distribute the structural change evenly over all identical 180 subunits and the display pattern
can be controlled completely and precisely over the capsid surface.
In addition to the prediction, the selection of a potential amino acid for the modification
is also based on following criteria: 1) the amino acid needs to be exposed well on the surface as
the highly accessible residue is more likely to interact with BCR; 2) it should not be involved in
inter-subunit interaction as the change may disrupt the self-assembly ability of the protein; 3) the
amino acid should not be in part of Th epitopes to avoid reduction of Th activation.
Regarding the first criteria, the well-exposed residues can be determined by the solvent
accessible surface area (SASA) from the available data mentioned above (Figure 2.11). The
amino acid residues that are found to be critical for self-assembly of the capsid were collected
from literature reports7a, 42 (Table 2.2 and Table 2.3). The potential Th epitopes of Qβ have been
reported22 and mentioned earlier in the introduction (Figure 2.3).
Table 2.2: Qβ mutants reported that assemble to form the capsid.

entry

Mutation(s)

category

Yield(mg/L) Tm (°C)

1

WT

-

++

83.3

242a

K16M

exterior charge/reactive
site

na

na

342a

T93M

internal reactive site

na

na

342b

D14R

exterior charge

-

na

442b

N10R

exterior charge

++

na

542b

T18R

exterior charge

++

na

642b

D14R/T18R

exterior charge

-

unstable

123

Table 2.2: (Cont’d)
entry

Mutation(s)

category

Yield(mg/L) Tm (°C)

77a

C74S

Remove disulfide

+

61.7

87a

C74S/C80S

Remove disulfide

++

61

97a

Y62F

+

82.8

107a

D81N

++

78.7

117a

Q65H

RNA binding

++

78.6

127a

D91N

RNA binding

+

79.4

137a

Q65H/D91N

RNA binding

+

81.6

147a

Y62F/C74S/C80S

combination

++

60.4

157a

D81N/C74S/C80S

combination

++

62

167a

Q65H/C74S

combination

+

60.7

177a

D91N/C74S

combination

+

62.1

187a

Q65H/D91N/C74S combination

++

61.4

197a

Y62R

interdimer
H-bond

+

67.3

207a

Y62W

Trp replace

+

77.0

217a

Y99W

Trp replace

+

74.8

227a

Y132W

C-term.Trp replace

+

80.9

237a

L35W

Trp replace

++

72.2

247a

P23A

structure

-

73.8

257a

K2Q

exterior charge

++

74.5

267a

K13Q/K16Q

exterior charge

++

75.6

277a

A1S

conjugation handle

+

73.9

2843

K13E

exterior charge

na

na

2943

K13Q

exterior charge

na

na

3043

K16E

exterior charge

na

na

3143

K16Q

exterior charge

na

na

3243

K16F

exterior charge

na

na

Interdimer
H-bond
Interdimer
salt bridge

124

Table 2.2: (Cont’d)
entry

Mutation(s)

category

Yield(mg/L) Tm (°C)

3343

K16Y

exterior charge

na

na

3443

K46Q

exterior charge

na

na

3543

K13Q/K16Q

exterior charge

na

na

Note: Yield ++ : >80 mg/L, + : >20-80 mg/L, −: <20 mg/L, na : not applicable
Table 2.3: Qβ mutants that fail to assemble into the VLP.

Entry

Mutation(s)

Entry

Mutation(s)

142b

WT_C-R2,5,8

127a

R86W

242b

WT_C-G2,5R2,5,8

137a

F94H, F94L, F94W

342b

D14GKQT18 to R514-18

147a

F96H, F96W

4a

N10R/T18R

157a

E104Q

57a

K2E

167a

E111Q

67a

L8W

177a

L128W

77a

L19W

187a

C74S/V108I

87a

L35G, L35H, L35A,
L35V

1943

K46E

97a

Y62E

2043

K13E/K16E

107a

C74H

2143

K2Q/K46Q

117a

C80H

2243

K2Q/K13Q/K16Q

Note: WT_C-R2,5,8 = mQβ with C terminal peptide extensions of polyarginine composed of 2, 5
and 8 arginine subunits, respectively. WT_C-G2,5R2,5,8 = mQβ with C terminal peptide
extensions of the polyarginine with polyglycine linker composed of 2 and 5 glycine subunits,
respectively. D14GKQT18 to R514-18 = mQβ, where the native peptide fragment D14GKQT18 is
replaced by polyarginine of 5 arginine subunits.
Based on the prediction and the criteria mentioned above, threonine at position 7 (T7),
asparagine at position 10 (N10), alanine at position 38 (A38), threonine at position at 75 (T75),
glutamic acid at position 103 (E103), alanine at position 117 (A117) and proline at 119 (P119)

125

were assigned as potential amino acid residues for the modification. Although E103, A117 and
P119 are on the region of the potential Th epitope determined by EPIMAX analysis22 (Figure
2.2 and Figure 2.3), they are expected not to disrupt the Th epitope sequence as they are located
close to the end of the determined region and it would be interesting to find out if they are crucial
for the immunogenicity of the carrier. (Please note that the known Th epitopes were elucidated
from BALB/c mouse in which MHC class II alleles (H-2d) in TCR differs from those in
C57BL/6 mouse (H-2b).44 Therefore, the known Th epitopes may not necessarily represent the
epitope for C57BL/6 mouse, the animal model in our study.)
The residues were modified genetically by site-specific mutagenesis. Each of the mutated
plasmids was transformed into a bacteria vector for the viral capsid protein expression. All
expressed mutated proteins, except E103K, were found to assemble to form viral capsids. The
characteristic properties of the Qβ mutants are summarized as in Table 2.4.
Table 2.4: Physical characteristics of Qβ mutants.

Yield(mg/L)

SEC rv. (mL)

Z-Ave
(d.nm)

PDI

Zeta
potential

WT

60

11.7

28.79

0.046

-2.89

T7K

10

11.8

29.00

0.278

-1.08

N10K

12

11.7

28.72

0.192

-1.90

A38K

16

12.7

26.58

0.083

-1.43

T75K

25

12.0

29.02

0.096

-1.64

A117K

31

12.1

29.73

0.187

-1.54

P119K

22

12.1

29.72

0.070

-2.00

A40C/D102C

38

11.8

29.06

0.031

-1.67

A38K/A40C/D102C

26

12.6

27.55

0.028

-1.55

A40S/D102S

20

12.0

27.82

0.028

-1.37

A40C/D102C/K13R

15

11.9

28.86

0.119

-1.97

Qβ Mutants

126

Since the Qβ capsid is composed of 180 subunits, a small local change of an amino acid
could dramatically alter the global charge of the capsid. The mutation of the native amino acids
to lysine in all mutants makes the surface charge of the mutant capsids more positive as assessed
by Zeta potential (Table 2.4) and non-denaturing agarose gel (Figure 2.12:). In non-denaturing
agarose gel, all mutants moved towards the cathode indicating higher positive surface charge of
the mutants compared with wtQβ, which moved towards the anode. The positive charge of the
mutants is supposedly to be derived from the new lysine from the mutation as the positive charge
was neutralized after the conjugation reaction of surface lysines with NHS-Tn 1. This change in
the surface charge after mutation could be another evidence to support that the amino group in
the side chain of the non-native lysine is exposed on the external surface, which could provide
extra conjugation site for the antigen for epitope shielding in an anticipated mutation point.
Prasuhn and coworkers have investigated the effect of positive charges on Qβ on plasma
clearance rate.42a They found that the high surface positive charge of Qβ slowed down the
plasma clearance rate. The change in the surface charge in our Qβ mutants would allow longer
plasma circulation time, which would increase the chance of maintaining sufficient amount of
the injected vaccine for immune activation. Moreover, the longer plasma circulation time will
also help minimize the dose in vaccination and in therapeutic drug delivery. It should be noted
that mQβ(T7K) and mQβ(N10K) are the most positively charged mutants, probably because
these residues are located in the most exposed area, which would alter the surface charge the
most. However, the surface charge of mQβ(T75K) is the least altered. This may be because this
lysine is only partially solvent exposed.

127

Figure 2.12: Electrophoretic mobility of Qβ whole capsids by native agarose gel. The samples
(~30 μg of each capsid protein) were loaded into 0.7% agarose gel in PBS with SYBR Safe DNA
gel strain as a straining reagent for the encapsulated RNA. The electrophoresis was performed in
TEA buffer at 4°C for 4 hours. Top panel) The encapsulated RNA strained in the capsids was
detected by UV light. Middle panel) The capsid proteins were detected by Coomassie staining.
Bottom panel) Overlaying the two panels confirms the presence of the encapsulated RNA in the
mQβs.
Although the sizes of the mutant capsids are slightly different, it should be noted that the
size of A38K mutant is noticeably smaller than other mutants (Table 2.4, Figure 2.14). This is
probably because A38 is located in the domain found to have an influence on the arrangement

128

between subunits.7a Therefore, a change in this residue may alter subunit organization, thus,
change in the capsid size. X-ray crystallography analysis suggests the difference in space group
of A38K mutant compared with wild-type Qβ. A38K mutant has space group I23 and contains 5
chains in an asymmetric unit, but the wild-type Qβ has space group R3 and contains 20 chains in
an asymmetric unit. Although both structures can closely superimpose with each other, the reconstruction of the full capsid from the repeating units by respective symmetry operations failed
to provide the full capsid of A38K mutant. (Data is not shown) (The X-ray crystal structure
analysis was done by kind help from Dr. Xiangshu Jin.) Fiedler and coworkers reported that
changing nearby leucine residue at position 35 to tryptophan or phenylalanine (L35W, L35F)
reduces the capsid size of Qβ from diameter of 28 nm down to 21 nm.7a Since L35 and A38 are
located in the same domain that involves the inter-subunit organization to cause difference in the
capsid size, it is of interest for study of manipulation of this domain to control the size of the
viral capsid. Such controllable size of the capsid would allow us to investigate the effect of size
on immunization profile and drug delivery efficiency. Moreover, the slightly change in size will
also allow the fine-tuning of antigen display pattern of the VLP, which play crucial role in
antigen cluttering for B cell activation.
2.2.2

Improve stability of Qβ VLP

The distinct inter-subunit disulfide bonds in Qβ viral capsid provide exceptionally high
stability to the construct over other viral capsids from the same family.7a For example, MS2 VLP
has a melting temperature (Tm) about 66°C45, while Qβ has Tm up to 83°C7a. Despite its high
stability, changing amino acids may alter the structural conformation of the protein folding
leading to decreased stability of the capsid as shown in many cases reported in the literature
(Table 2.2).7a The low stability of the capsid may not endure harsh condition in conjugation

129

process involving organic solvents and reagents. Moreover, the less stable carrier may alter the
fate of the vaccine contents delivered into the immune system, which potentially reduce the
efficiency of the vaccine.46 For instance, the early degradation may expose inner B cell
epitope(s), or lose the particulate characteristic of the particle, which is crucial for inducing
strong immune responses. The self-assembled structure of the viral capsid was therefore
engineered to strengthen the stability of the capsid to accommodate structural modification and
rigorous condition in conjugate reaction. The rational design is based on additional disulfide
bonds to reinforce the covalent network between the subunits in the capsid construct. An amino
acid pair, in which each of them is from adjacent subunits but brought in spatial proximity in 3D
structure to potentially form a disulfide bond after being mutated into cysteine, was searched by
Disulfide

by

Design

2.0

web-based

modeling

software47

(DbD,

http://cptweb.cpt.wayne.edu/DbD2/). The algorithm of the software calculates the predicted
potential of a candidate amino acid pair as B-factor, the higher B-factor, the higher the potential
to form disulfide bond that can increase stability of the protein complex. From the prediction, an
amino acid pair of A40 and D102 gives the highest B-factor. The proximity (≈ 4 Å) of the beta
carbons in the side chain of A40 and D102 was confirmed by 3D structure (Figure 2.13). We,
therefore, mutated these two amino acids to cysteines to determine the ability of the mutant
capsid protein to form additional disulfide bonds for increased capsid stability. The result
showed that the mutant A40C/D102C can assemble to form the capsid similar to wtQβ as
determined by size and shape from SEC (blue line vs red line in Figure 2.14a, DLS (Table 2.4),
and TEM, respectively (Figure 2.14b).

130

a)

b)

Figure 2.13: X-ray crystal structure of wtQβ showing a) distances between β-carbon of
residues involving disulfide formation; b) disulfide bond networks from native disulfide
bonds between C74 and C80 (green residues) in wtQβ and expected non-native disulfide
bonds in mQβ A40C/D102C (yellow residues).
a)

Figure 2.14: a) Size exclusion chromatograms of wtQβ (red) and mQβs, A38K(yellow),
A38K/A40C/A102C (green), A40C/D102C (blue); b) TEM images of wtQβ and mQβs.

131

Figure 2.14: (Cont’d)
b)

WT

A40C/D102C

A40S/D102S

A38K/A40C/D102C

The formation of the additional disulfide bonds in mQβ(A40C/D102C) was confirmed by
non-reducing SDS-PAGE (Figure 2.15). Any mQβs involving A40C/D102C mutation showed
multimeric protein bands, while other mQβs including mQβ(A40S/D102S), which is chemically
equivalent but unable to form the disulfide bonds, showed similar band pattern as wtQβ (Figure
2.15b).

132

Figure 2.15: a) SDS-PAGE of the viral capsids in non-reductive (oxidative) condition (Left)
and reductive condition (right).
From the thermal stability measurements, the addition of non-native disulfide bond was
found to improve the stability of the capsid (Figure 2.16). The increased stability derived from
the non-native disulfide bonds was supported by the decreased stability of mQβ(A40S/D102S)
(Figure 2.16 middle). The structural change in mQβ(A38K) was found to decrease the stability
of the capsid. This is probably because A38K is involved in interaction between subunit as seen
in the effect of the alteration of this point on the capsid size. However, the addition of non-native
disulfide bonds can help strengthen the stability of the capsid up close to that of wtQβ as shown
by the increased thermal stability of mQβ(A38K/A40C/D102C) (Figure 2.16 bottom).

133

2.5
2

WT
A38K

1.5

A38K/A40C/D102C
A40C/D102C

1

OD310

A40S/D102S

0.5
0

K13R/A40C/D102C
T75K
65

70

75

-0.5

80

85

A117K

90

Temperature (C°)

1.8
1.6
1.4
1.2
1

WT

OD310 0.8

A40C/D102C

0.6

A40S/D102S

0.4
0.2
0
-0.2

70

75

80
Temperature (C°)

85

90

Figure 2.16: Thermal stability of mQβs determined by UV absorption at λ = 310 nm at
increasing temperature.

134

Figure 2.16: (Cont’d)
2.5
2
1.5
OD310

WT

1

A38K
A38K/A40C/D102C

0.5
0
-0.5

65

70

75

80

85

90

Temperature (C°)

Although the impact of non-covalent interactions between the interdimer residues on the
stability of Qβ VLP has been intensively studied by Fiedler and coworkers7a, the additional
stability due to non-native di-sulfide bond between subunits had not been observed before. This
enhanced stability would confer flexibility in engineering and applications of this type of protein
particle.
To assess the potency of mQβ in inducing immunity against either TACA or the carriers
themselves, a prototypical TACA, Tn1 (Figure 2.17, see experimental section 2.5.15 for the
synthesis), were immobilized on the surface of mQβs via amide formation between amino groups
of exposed lysines and NHS group of NHS-Tn1 (Figure 2.17). LCMS together with data
processing with maximum entropy deconvolution algorithm (MaxEnt1)48 was used to determine
the number of Tn1 on each capsid, as we found this method gave comparable results to
Microfluidic capillary gel electrophoresis analysis49, yet with more quantitative information and
convenience (details for the method are included in experimental section).

135

HO
HO

OH
HO

O

O

O
NH2

N

O
O

AcHN

O
N
H

O

O

HO

AcHN

OH

O

H
N

OH
O

O
N
H

O

PBS pH=7

OH
O

n

TACA
wtQβ-Tn1/mQβ-Tn1

wtQβ/mQβ

Figure 2.17: Conjugation reaction between NHS-Tn1 with the various mQβs.
Table 2.5: The average number of Tn1 conjugated on each capsid of Qβ particle and yield of
Qβ-Tn1 conjugate. [% addn Tn = (Tn1/subunitmQβ − Tn1/subunitwtQβ) × 100 / Tn1/subunitwtQβ]

Qβs

Tn1/Qβ

Tn1/subunit

%addn
Tn

WT

332

1.84

0

73

T7K

423

2.35

28

89

N10K

402

2.23

21

69

A38K

410

2.27

23

73

A38K/A40C/D102C

498

2.77

51

64

A40C/D102C

436

2.42

32

57

A40S/D102S

410

2.33

27

66

K13R/A40C/D102C

328

1.82

-1

79

A75K

447

2.48

34

72

A117K

390

2.16

17

77

P119K

394

2.19

19

73

136

Yield
(%)

Table 2.6: Physical characteristics of Qβ-Tn1 conjugates.
Qβ-Tn1 conjugates

SEC rv. (mL)

Z-Ave (d.nm)

PDI

WT-Tn1

11.7

29.62

0.086

T7K-Tn1

11.6

29.35

0.025

N10K-Tn1

11.6

28.82

0.063

A38K-Tn1

12.6

26.82

0.028

T75K-Tn1

11.8

31.66

0.110

A117K-Tn1

11.9

30.77

0.105

P119K-Tn1

11.9

31.87

0.169

A40C/D102C-Tn1

11.6

29.37

0.072

A38K/A40C/D102C-Tn1

12.4

27.61

0.024

From the average number of the conjugated Tn1 on each capsid of mQβ, it was surprising
that despite no additional lysine added into the mQβ(A40C/D102C), the average number of Tn1
per Qβ is as high as other mQβs with an additional lysine. After comprehensive analysis of the
structure affected by the residue changes, we found that there is non-covalent interaction,
probably hydrogen bond (≈ 3 Å), between the carboxyl group on the side chain of D102 and the
amino group on the side chain of K13 (solid blue line in Figure 2.18). This interaction may
suppress the reactivity of the amino group in conjugation reaction. This explanation is also
supported by another finding50 that lysine 13 in the wtQβ is not reactive, as changing reactive
lysine to arginine (mQβ(K13R)) did not reduce the number of conjugated molecules
(fluorescein-NHS ester) compared with wtQβ. Therefore, when D102 is mutated to cysteine and
its side chain no longer binds the K13 residue, the amino group in the side chain of K13 can
possibly rotate out to the external surface and become more available to react with NHS-Tn1.
This is also supported by the reduced average number of Tn1 on mQβ(K13R/A40C/D102C)

137

(323Tn1/particle)

when

compared

with

mQβ(A40C/D102C)

(436Tn1/particle)

and

mQβ(A40S/D102S) (410Tn1/particle) (Table 2.5).

Figure 2.18: X-ray crystal structure of wtQβ showing the hydrogen bond interaction (solid blue
line) between the carboxyl group on the side chain of D102 and the amino group on the side
chain of K13(distance = 3.145 Ã…).

2.2.3

Immunization study

The ability of mQβ-Tn1 conjugates in reducing unwanted anti-carrier immune response
and increasing desired anti-TACA immune response were evaluated in vivo. C57BL/6 female
mice (n=5) were injected subcutaneously with 0.1 mL of the various mQβ-Tn1 conjugates as
emulsion with complete Freund’s adjuvant (CFA) for prime injection on day 0 and with
incomplete Freund’s adjuvant (IFA) for boost injections on days 14 and 28. The dose for each
injection was 1.93μg based on the amount of the attached Tn1. The sera from immunized mice
were collected on day 35 and used to determine the induced anti-Tn or anti-mQβ antibodies titers
by ELISA coated with BSA-Tn1 or mQβ. ELISA results showed that all mQβs we picked for in

138

vivo study elicited higher antibodies titers against Tn1 antigen, but lower antibodies titers against
self-carriers compared with wtQβ (Figure 2.19). The mutant that can induce highest anti-Tn1
antibody response is mQβ(A38K/A40C/D102C). To rule out variations between ELISA analysis,
the amount of elicited IgG antibodies from different groups of the study were measured based on
optical density (OD450) in the same ELISA plate against BSA-Tn1 and corresponding carriers at
sera dilution 1/819200 and 1/1638400, respectively. The result pointed out a reverse trend of the
titers of antibodies against Tn1 and mQβs, that is any vaccine that elicited low anti-carrier
antibodies induced inversely proportionally high anti-Tn1 antibodies (Figure 2.19c,d). The
higher elicited IgG2 over IgG1 in mQβs suggest T-cell dependent immune response bias towards
Th1 response (Figure 2.19e).
These results suggested that reducing CIES of the Qβ based vaccine construct can indeed
result in enhanced anti-TACA antibody response. The number of Tn1 on each capsid seemed to
play a role in increasing anti-Tn antibody response similar to what have been suggested by
Bachmann group.37 However, this is not the case for T75K and A117K mutants, as mQβ(T75K)
has higher Tn1/capsid (447 versus 390 Tn1/capsid) but induced lower titer of anti-Tn1 antibodies
than mQβ(A117K) (Figure 2.19a). Interestingly, based on the antibody titers, the potency of
mQβ(A38K/A40C/D102C) in inducing anti-Tn1 antibody response seems to be as a result of a
combination of potency from A38K and A40C/D102C mutants (Figure 2.19a). This suggested
that the structural changes for suppressing CIES could be combined together in order to
minimize the suppression from a carrier caused by multiple B-cell epitopes.

139

a)

b)

c)

d)

e)

Figure 2.19: ELISA results of post-immunized sera (day 35) from groups of mice (n=5)
vaccinated with variant mQβ-Tn1. a and b) Anti-Tn1 titers of the post-immunized sera
presented in linear and log scale, respectively. The statistical significance of differences
between a mQβ and wtQβ was determined by the Student t test (** р < 0.01; *** р < 0.001;
**** р < 0.0001) c) OD450 from the ELISA result of the post-immunized sera at 1/819200
dilution against BSA-Tn1. d) OD450 from the ELISA result of the post-immunized sera at
1/1638400 against the corresponding carrier capsids. The statistical significance of differences
between a mQβ and wtQβ was determined by the Student t test. e) OD450 from ELISA result at
1/819200 sera dilution of IgG subtypes antibodies (IgG1, IgG2b, IgG2c and IgG3) elicited by
wtQβ-Tn1, mQβ(A38K/A40C/D102C)-Tn1 and mQβ(A40C/D102C)-Tn1 immunization
against BSA-Tn1.

140

Since the structural change in mQβ(A40C/D102C) and mQβ(A38K/A40C/D102C) is
believed to make K13 become more reactive towards NHS-Tn1, it is reasonable to postulate that
the conjugation of Tn1 on K13 would help together with conjugated Tn1 on K16 to block the
flexible and highly exposed loop, which is potentially a dominant B cell epitope based on the
prediction. This would explain the statistically significant reduction of anti-carrier antibody
response

and

higher

anti-Tn1

antibody

response

in

mQβ(A40C/D102C)

and

mQβ(A38K/A40C/D102C).
This hypothesis is also supported by analysis from a competitive ELISA. In the
competitive ELISA, sera from a wtQβ-immunized mouse at dilution 1/204800 was incubated
with the wtQβ, mQβ(A40C/D102C) or mQβ-Tn conjugates with different number of Tn,
respectively. The mixtures of the pre-incubated sera with the corresponding Qβ were added into
ELISA plate coated with wtQβ. Any viral capsid that can be recognized by anti-wtQβ antibodies
will compete with the coated wtQβ for binding with the antibodies. Qβ capsids with higher
binding avidity with anti-wtQβ antibodies will reduce the available antibodies binding on the
plate which will result in proportionally lower OD from the analysis. Despite the fact that A40
and D102 are not highly exposed residues, the result suggested that the changes of these residues
can reduce the recognition of the capsid by the antibodies, where the interaction generally
involves highly exposed residues (Figure 2.20). The effect became more obvious with the mQβTn conjugates, where the Tns could possibly conjugated to K13 and shielded the suggested B
cell epitope. The lower antibody recognition of mQβ(A40C/D102C)-Tn2(560) compared with
mQβ(A40C/D102C)-Tn1(436) suggested better B cell epitope shielding with higher numbers of
Tn on the capsid.

141

Figure 2.20: Competitive ELISA showing reduced anti-wtQβ antibody recognition of mQβ-Tn
conjugates.

2.2.4

Binding of the elicited antibody against tumor cells

To test binding of sera from immunized mice against native Tn expressed on cancer cells,
human lymphoma Jurkat cells were used as a model for Tn expressing cancer cells. Quantitative
flow cytometry of Jurkat binding with anti-Tn mAb (Chi-Tn mAb) reportedly showed that there
are average 5 × 105 Tn’s expressed on each cell.51 Although the serum from
mQβ(A38K/A40C/D102C)-Tn1 immunized mice showed the highest titers, the binding of the
serum on Jurkat cells was relatively weak compared with other mQβs (Figure 2.21 left panel).
This may indicate the difference in specificity or affinity of the antibodies elicited by different
mQβ where the patterns of Tn display are different.
Murine mammary adenocarcinoma cell line, TA3Ha, is another Tn expressing cancer cell
line commonly used in testing specific binding and in vivo cell growing inhibition by anti-Tn
antibodies.31c, 51-52 The flow cytometry data showed that the sera from the mQβ immunized mice

142

bound TA3Ha cells with affinity comparable with the binding of the sera from wtQβ immunized
mice and Tn-specific mAb. The low binding of TA3Ha cells with the antibodies is probably due
to the low expression level of Tn on this cell line (1.5 × 105 Tn’s/cell), which was reportedly
determined by quantitative flow cytometry.51 Moreover, the loss of Tn expression during in vitro
cell culturing could also happen as indicated by the weak binding of the anti-Tn mAb (bric111
mAb) to the cells (Figure 2.21 right panel).

143

a)

Jurkat cells

b)

TA3Ha cells

Figure 2.21: Flow cytometry showing binding of elicited IgG antibodies by Qβ conjugates; a and b)
Histogram showing binding recognition of the elicited antibodies against Jurkat cells and TA3Ha
cells, respectively, c and d) Graph of median fluorescent intensities of the binding recognition of the
elicited antibodies towards Jurkat cells and TA3Ha cells, respectively.

144

Figure 2.21: (Cont’d)
c)

d)

2.2.5

Tumor challenge

Due to the ease of its synthesis, Tn1 (Figure 2.22a) was used as a simplest prototypical
TACA in the initial immunization to find out the best mutant carrier capable of inducing highest
immune response against TACA. However, in term of cancer cell binding, Tn2 (Figure 2.22a)
was found to be superior to Tn1 as wtQβ-Tn2 and mQβ(A38K/A40C/D102C)-Tn2 can induce
anti-TACA antibodies that bind Jurkat cells with higher affinity compared with the serum from
mice immunized with wtQβ-Tn1 and mQβ(A38K/A40C/D102C)-Tn1, respectively (Figure
2.22b).
HO

a)

OH

HO

O

HO

HO

O
N
H

O

O
AcHN

AcHN
O

OH

O
OH

N
H

O

O

Tn1

O
H
N

OH

O

Tn2

Figure 2.22: a) Chemical structures of Tn1 and Tn2. b) MFI of cellular binding against Jurkat
cells of the serum from mice immunized with wtQβ-Tn2 and mQβ(A38K/A40C/D102C)-Tn2
compared with those from wtQβ-Tn1 and mQβ(A38K/A40C/D102C)-Tn1.

145

Figure 2.22: (Cont’d)
b)

Tn2 was, therefore, chosen as a TACA in tumor challenge experiment. To rule out the
factor of the antigen density on the viral capsid, the number of Tn2 on both wtQβ and
mQβ(A38K/A40C/D102C) were controlled to be equally attached on each capsid approximately
370 Tn2/particle. Groups of 10 mice were administered subcutaneously with either wtQβ-Tn2 or
mQβ(A38K/A40C/D102C)-Tn2. The doses for each administration were kept constant, 1.93μg
based on the amount of the attached Tn2. The adjuvants and schedule for vaccination were the
same as those vaccinations in initial trial for mQβs. CFA and IFA were used in prime and boost
injections, respectively. Mice were vaccinated in 2-week interval (day 0, 14 and 28).
Sera from the vaccinated mice were collected a week after the last injection to determine
the anti-Tn antibodies titers and selective binding to the Tn-expressing tumor cells. Preliminary
ELISA results showed that mQβ(A38K/A40C/D102C)-Tn2 elicited higher amount of anti-Tn
IgG antibodies than the serum from mice given wtQβ-Tn2 (Figure 2.23). Although there was not
statistical significance between groups of mice, the data suggested higher potency of the
mQβ(A38K/A40C/D102C) in eliciting Tn-specific antibodies, despite the similar number of Tn
attached on the viral capsid. The higher antibody response could contribute to the structural

146

change of the B cell epitope due to mutation. However, it is reasonable to expect that the higher
density of the antigen would better shield the carrier’s B cell epitope, resulting in lower CIES,
hence even higher titers of anti-Tn antibodies.

Figure 2.23: OD450 from the ELISA result of the post-immunized sera at 1/819200 dilution
against BSA-Tn2 from mice immunized with wtQβ-Tn2 and mQβ(A38K/A40C/D102C)-Tn2.
The statistical significance of differences was determined by the Student t test.
For tumor challenge, murine mammary adenocarcinoma cell line, TA3Ha, was used as a
Tn expressed xenograft cancer model. The model has been used in many investigations of Tnbased cancer vaccines.31c, 51-52, 53 This cell line was grown by passage on A/J mice to minimize
the loss of Tn expression overtime caused by in vitro culture. Two groups of mice were
immunized

following

previously

described

procedure

with

wtQβ-Tn2

and

mQβ(A38K/A40C/D102C)-Tn2, respectively. The immunization was done on day -36, -22 and 8 before the tumor challenge. On day 0 (after blood collection), 5000 cells of TA3Ha cells were
injected intraperitoneally into all mice. A day after (day 1), cyclophosphamide (CP) at a dose of
50 mg/kg was injected intraperitoneally. The survival of all mice was monitored from the day CP
was

given

(day

1)

till

day

30.

The

147

protective

efficacies

of

wtQβ-Tn2

and

mQβ(A38K/A40C/D102C)-Tn2 were compared by Kaplan-Meier survival curves. There was not
statistically difference in the binding of the induced antibodies from both vaccines against
TA3Ha cells (Figure 2.24). Although the difference is not statistically significant, the mQβ
showed higher survival rate of the challenged mice compared with wtQβ (Figure 2.25) (Control
experiments have been done in reference36.) To investigate immune protection against tumor
recurrence due to immune memory after tumor challenge, group of five mice surviving the first
tumor challenge were rechallenged with 5,000 TA3Ha cells without further vaccination and
administration of CP. All mice immunized with the mQβ-Tn2 conjugates survived from the
second tumor challenge for 30 days. This suggested protection against tumor recurrence of
immune memory in the immunized mice.

148

a)

TA3Ha cells

b)

Figure 2.24: Flow cytometry showing binding of elicited IgG antibodies by wtQβ-Tn2 and
mQβ(A38K/A40C/D102C)-Tn2 a) Histogram showing binding recognition of the elicited
antibodies against TA3Ha cells, respectively, b) Graph comparing median fluorescent intensities
of the binding recognition of the elicited antibodies towards TA3Ha cells.

149

a)

b)

Figure 2.25: Kaplan-Meier survival curves comparing the protective effect of wtQβ-Tn2 and
mQβ(A38K/A40C/D102C)-Tn2: a) after 1st tumor challenge with treatment of CP (n=10), b)
after 2nd tumor challenge without any further treatment (n=5). Statistical analysis of survival is
determined by using the log-rank test in GraphPad Prism software. Note: Control experiments
have been done in reference36.

2.3 Conclusions
Bacteriophage Qβ has been demonstrated as a promising immunogenic carrier able to
break self-tolerance to induce strong antibody response against TACA.35 Carrier-induced
epitopic suppression (CIES) due to its strong immunogenicity is potentially problematic for VLP

150

based vaccine, which limits the full potential of this type of carrier in inducing maximum desired
immune response against TACA.37
From the results presented in this study, the carrier-induced epitopic suppression (CIES)
of Qβ VLP can be addressed by engineering the viral capsid to block the recognition of the B cell
epitopes by B cell receptors. Non-native disulfide bonds introduced into the capsid were found to
not only enhance the stability of the engineered capsids, but also induce structural change to
allow the conjugated antigen to shield the B cell epitope. Our results showed that reducing the
unwanted anti-carrier immune response of the mQβs can enhance the wanted titers of antibodies
against TACA. The approaches presented in this study provide a fundamental implication for
rational design of engineered VLP-based carrier to maximize the potency of vaccines targeting
TACA expressing cancers as well as other diseases.
2.4

Future perspective
The studies shown in this work has been demonstrated the proof-of-principle of

engineering VLP carrier to suppress CIES effect in order to improve the potency of the vaccine
in inducing the desired immune response against TACAs. Besides, there is a lot of room for
further improvement that are worth exploring in this promising platform.
In term of B cell epitope mapping, although the computational-based prediction can guide
us to the potential regions of the B cell epitopes, the exact location of the epitopes could be
further identified using monoclonal antibodies against the capsid. The monoclonal antibodies
elicited by hybridoma B cells from immunized mice could be used for 3D epitope mapping
based on cryo-electron microscopy reconstruction method54 to pinpoint the exact location of the
conformational epitopes.

151

Moreover, the monoclonal antibodies could be used to compare the binding against the
capsid after B cell epitope editing or shielding by SPR or Bio-Layer Interferometry (BLI)
techniques. In addition to the location, these techniques would provide insight about the binding
affinity of the monoclonal antibodies against the modified B cell epitope(s) which will help us
narrow down the targeted residues for the next experimental design.
A novel strategy of presenting vaccine carrier with tolerogenic CD22 ligand for reducing
the unwanted anti-carrier immune response is also of high interest to be investigated. Sialic acidbinding immunoglobulin-like lectins 2, known as CD22, was found to have a function as B cell
inhibitory co-receptor.55 Evidence from several studies56 suggested that B cell antigen in copresenting with CD22 ligand (Figure 2.26) can regulate B cell activation specific to that antigen.
The physical tethering of CD22 ligand with the antigen will recruit intracellular domain of CD22
towards B cell receptor. The interaction in close proximity between signaling domains of both
receptors can suppress BCR mediated activating signal, leading to B cell tolerance specifically to
the antigen that binds to the corresponding B cell. The effects has been confirmed by a variety of
display platforms including polymer56c,

57

and liposome.56d Macauley et al. have proved that

CD22 ligand in conjugation with antigens can suppress the antigen-specific antibody production,
yet preserve the immune response against unrelated antigens.56d Those studies also showed that
the inhibitory effect is not only for T cell independent antigen, but also for T cell-dependent
antigen where the antigen specific silencing comes through antigen specific B cell deletion from
the polyclonal B cell repertoire. Since CD22 is thought to be conserved functionally between
mouse and human,56b this suggests that the concept of CD22 based specific B cell tolerance
could be practical in clinical trials.

152

O
HN
OH
HO
GcHN

COO

O

OH

O
HO

HO

O
HO
OH

O
HO

O
O
NHAc

Figure 2.26: Chemical structure of tolerogenic CD22 ligand.
Therefore, it could be postulated that injecting Qβ displaying CD22 ligand prior to
immunization would tolerize the Qβ specific B cells. Thus, anti-carrier immune response would
be suppressed in subsequent immunization with Qβ-TACA. The synthesis procedure of CD22
ligand has been reported.58 The synthetic CD22 ligand can be conjugated onto Qβ capsid in
similar way as TACA or by using chemoenzymatic reaction to extend the oligosaccharide units
from conjugated monosaccharide on VLP.59 Alternatively, the conjugation site can be
manipulated through site-specific unnatural amino acid incorporated into the capsid. This will
ensure the optimized distance between the ligand and the predicted/identified capsid epitope,59 as
well as the optimized density of the ligand, in order to properly enforce the ligation between B
cell receptor and CD22 to induce the most inhibitory effect.56c The level of antibody response
against the desired antigens correlated with unwanted anti-Qβ response can be compared with
immunization without prior tolerization.
As mentioned in the introductions in both chapters of this dissertation, the defined display
pattern of the antigen on the capsid play a crucial role in proper B cell receptor crosslink. This
work suggests the ability of genetic mutation to precisely control the TACA antigen display
pattern to mimic the native one in order to induce specific antibodies recognizing the native form
of TACA on cancer cells. For example, the conjugation of Tn antigen onto the reactive lysines at

153

position 13 and 16 together with position 10 (from N10K) would be expected to yield
consecutive glycosylation that mimic the native trimeric Tn cluster in syndecan-1, of which high
cellular expression was well correlated with tumor invasion and metastasis.60 This hypothesis is
also supported by the finding that a synthetic dendrimer glycopeptide MAG-Tn3, where Tn
antigen is presented in trimeric cluster form, showed promising results for TACA-based
anticancer vaccine,31c which are currently under evaluation in clinical trials.52a The role of
patterned antigen display could also be closely investigated through site-specific orthogonal
conjugation via chemical mutation48b or unnatural-amino-acid incorporation derived from amber
codon suppression.
Moreover, the adjustable size of the VLP could be accomplished through mutation at
inter-subunit domain as reported in literature,7a together with our finding on A38K mutant. The
adjustable size of the capsid can provide an additional way to fine tune the antigen display
pattern. Moreover, the understanding of the inter-subunit interaction of this domain not only
helps establish models for protein self-assembly in computational design,61 but also aid research
in virology evolution field. The ability to tune the size of the VLP capsid will overcome the
limitation of this construct in nanoparticle applications, such as drug delivery, in vivo imaging
and nano-reactor.62

154

2.5 Materials and methods
2.5.1

Site-directed mutagenesis of Qβ VLPs

Primers were designed following a guildline in the manual of QuikChange SiteDirected

Mutagenesis

Kit.

Online

based

software

PrimerX

(http://www.bioinformatics.org/primerx/) was used to generate the primer sequence, or the
sequence can be designed manually in some cases. The designed primers were further analyzed
for proper %GC and Tm again by Oligoanalyzer 3.1 from IDT Inc. All primers were
commercially synthesized by IDT Inc. For PCR reaction, the reagent mixture and cycling setting
are prepared by adding reagents, respectively, as the following,
Reagents
10X buffer
20 ng plasmid template (from 20 ng/μl)
125 ng Forward primer (from 100 ng/μl)
125 ng Reverse primer (from 100 ng/μl)
dNTP mix
BP561-1 water
Pfu turbo

μl
5
1
1.25
1.25
1
39.5
1

PCR thermocycler setting
Number of
cycles
1X

17X

Finish

Temperature

Time

95 C°
95 C°
5 C° less than
Tm of the
primers, or
using gradian
68 C°
4 C°

30 Sec
30 Sec
1 Min

6 Min
till done

After PCR reaction, the resulting reaction was added 1μl DpnI and incubated at 37°C for
1 hour to digest the template plasmid DNA. The reaction’s products were verified by 0.8%

155

agarose gel electrophoresis with ethidium bromide as a staining reagent. The reactions were then
used without purification to transform DH5a E.coli. The transformed DH5a E. coli cultures
were plated onto SOB agar plate with 20μg/mL Kanamycin sulfate and incubated at 37°C
overnight. 4-6 colonies were selected to inoculate 6 mL SOB with 20ug/mL Kanamycin and
incubated at 37°C overnight to amplify the E. coli. Mutated DNA plasmid from the bacteria
cultures were extracted with QIAprep Spin Miniprep Kit (QIAGEN). The extracted plasmids
were submitted to GENEWIZ for sequencing. Plasmid of the mutated plasmids that provide
correct DNA sequences with highest scores of sequencing quality were used for transformation
into BL21(DE3)pLysS E. coli by the heat shock method, then plated on SOB agar plate as DH5a
E. coli. A single colony was selected for protein expression.
Table 2.7: Primers used in the construction of mutant Qβ VLPs
Primer #
1

Name
CP_T7K_F1

2

CP_T7K_R1

3

CP_N10K_F1

4

CP_N10K_R1

5
6
7

CP_K13R_F1
CP_K13R_R1
CP_A38K_F1

8

CP_A38K_R1

9

CP_A38K_[A40C]_F1

10

CP_A38K_[A40C]_R1

11
12

CP_A40C_F1
CP_A40C_R1

Sequence
5'-ATTAGAGACTGTTAAGTTAGGTAACATCGGG3'
5'-CCCGATGTTACCTAACTTAACAGTCTCTAAT3'
5'-CTGTTACTTTAGGTAAGATCGGGAAAGATGG3'
5'-CCATCTTTCCCGATCTTACCTAAAGTAACAG3'
5'-GGTAACATCGGGAGAGATGGAAAACAA-3'
5'-TTGTTTTCCATCTCTCCCGATGTTACC-3'
5'GCCTCGCTTTCACAAAAGGGTGCAGTTCCTGCG
-3'
5'CGCAGGAACTGCACCCTTTTGTGAAAGCGAGG
C-3'
5'-CCTCGCTTTCACAAAAGGGTTGTGTTCCTGC3'
5'GCAGGAACACAACCCTTTTGTGAAAGCGAGG-3'
5'-CACAAGCGGGTTGTGTTCCTGCGCTGG-3'
5'-CCAGCGCAGGAACACAACCCGCTTGTG-3'

156

Table 2.7: (Cont’d)
Primer #
13
14
15
16
17
18
19
20
21
22
23

Name
CP_A40S_F1
CP_A40S_R1
CP_T75K_F1
CP_T75K_R1
CP_D102C_F1
CP_D102C_R1
CP_D102S_F1
CP_D102S_R1
CP_E103K_F1
CP_E103K_R1
CP_A117K_F1

24

CP_A117K_R1

25

CP_P119K_F1

26

CP_P119K_R1

2.5.2

Sequence
5'-CACAAGCGGGTTCAGTTCCTGCGCTGG-3'
5'-CCAGCGCAGGAACTGAACCCGCTTGTG-3'
5'-CCGACCGCTTGCAAGGCAAACGGTTC-3'
5'-GAACCGTTTGCCTTGCAAGCGGTCGG-3'
5'-GCAGTATAGTACCTGTGAGGAACGAGC-3'
5'-GCTCGTTCCTCACAGGTACTATACTGC-3'
5'-GCAGTATAGTACCTCTGAGGAACGAGC-3'
5'-GCTCGTTCCTCAGAGGTACTATACTGC-3'
5'-GTATAGTACCGATAAGGAACGAGCTTTTG-3'
5'-CAAAAGCTCGTTCCTTATCGGTACTATAC-3'
5'GCTTGCTGCTCTGCTCAAGAGTCCTCTGCTGAT
CG-3'
5'CGATCAGCAGAGGACTCTTGAGCAGAGCAGCA
AGC-3'
5'GCTCTGCTCGCTAGTAAGCTGCTGATCGATGC-3'
5'GCATCGATCAGCAGCTTACTAGCGAGCAGAGC3'

Qβ viral capsid protein expression and purification

A single colony of BL21(DE3)pLysS E. coli with mutated plasmid was selected to be
inoculated into starting culture of 50 mL SOC containing 20ug/mL Kanamycin. The starting
culture was grown overnight at 37°C, 230 rpm. After overnight, the resulting cloudy culture was
then transferred into 1L culture medium with the antibiotic selection. The culture was continued
at the same condition until the OD600 was between 0.7-1.0, 1mL of 1M isopropyl β-D-1thiogalactopyranoside (IPTG) was then added into the culture to induce protein expression (final
concentration = 1mM). The culture was continued 4-5 hours. After 4-5 hours, the bacteria were
pelleted at 6,000 rpm for 30min. The culture medium was discarded. The pellets were resuspended in 0.1M PBS pH 7. The bacteria in the suspension were then lysed with a probe

157

sonicator in an ice bath. The sonication generator was set at power of 30% for 10 min, with
interval of 5 second pulses and 5 second stops. The lysis was centrifuged at 14,000 rpm for 20
min. The supernatant containing the capsid protein was added PEG 8000 to final concentration
of 10% (w/v) and put on a nutating mixer at 4°C overnight to allow complete protein
precipitation. The precipitate was pelleted down at 14,000rpm for 20 min. The pellet was
resuspended in 0.1M PBS pH=7. The re-suspended solution was 1:1 (v/v) mixed with 1:1 (v/v)
chloroform/n-butanol till the mixture turns colloid. The colloidal mixture was centrifuged at
7,000 rpm for 1 hour to separate layer. The top (aqueous) layer was collected. Viral capsid
protein in the collected aqueous layer was further purified by sucrose density gradients 10-40%
(w/v). The linear (continuous) sucrose gradients was prepared following freezing-thawing
method.63 The loaded sucrose gradients were centrifuged with swing bucket rotor SW32 rotor at
28,000 rpm for 5 hours. The viral capsid band can be visualized by LED light shining through
the top of the tube. The bright blue band from scattered light was collected as fractions of 1mL.
The collected fraction was analyzed for purity of the capsid by size-exclusion chromatography
using column Superose 6 resin 10/300 (void volume = 9mL). The fraction that shows a single
peak at elution around 11-15 mL was determined as a fraction containing pure VLP. The
remaining sucrose in the collected fraction was removed by filtration through Millipore 100k
MWCO centrifugal filter tube, and washed thoroughly with the PBS buffer. Total protein
concentration in the final solution was quantified by Pierce BCA Protein Assay Kit, using bovine
serum albumin as the standard. The purified VLP was characterized by size-exclusion
chromatography, Dynamic light scattering (DLS), and transmission electron microscopy (TEM)
for particles’ size, homogeneity, shape, and purity. The change of the amino acid(s) as a result of
mutation was determined by the molecular weight difference compared with wide-type Qβ. The

158

molecular weight of the protein was determined by LCMS QTOF ESI mass spectroscopy and the
multiple charge mass spectrums were transformed to single charge by Maximum Entropy
deconvolution algorithm (MaxEntTM 1)48
2.5.3

Synthesis and characterization of Qβ or mQβ conjugates36

13.2 mg of VLP Qβ or mQβ (5.1 nmol particle, 0.9 μmol subunit, 3.6 μmol reactive
amines) suspended in potassium phosphate buffer (0.1 M, pH=7, 5.5 mL) was added into a 15mL falcon tube. DMSO 0.35 mL was slowly dropped into the solution. Tn1-NHS or Tn2-NHS
(20 mg/mL in 0.35 mL, 0.017 mmol, 4.7 eq. to the reactive amine) was added into the reaction
tube. The reaction mixture was rotated on a rotating mixer at room temperature overnight. The
reaction was diluted with 0.1 M PBS pH=7 to total volume 50 mL. The VLP conjugates were
purified by filtration through Millipore 100k MWCO centrifugal filter tube, and washed
thoroughly with the PBS buffer. The purified VLP conjugates were characterized as described
above. The average number of conjugated Tn1 or Tn2 on each viral capsid subunit was estimated
from the intensity of peaks in the deconvoluted mass spectra from LCMS analysis. Results are
shown in Figure 2.30.
2.5.4

Size exclusion chromatography (SEC)

SEC analysis and purification were performed on an AKTApure 25L system, equipped
with Superose 6 Increase 10/300 GL column. 0.1 M potassium phosphate buffer pH=7 was used
as the eluent with a flow rate of 0.5 mL/min at 4 °C. The capsid protein was detected with a UV
detector at wavelength 280nm. 0.5 mL of sample was injected. The sample was eluted with 1.5
column volume and the fractions were collected every 1mL. Results are shown in Figure 2.29.

159

2.5.5

Non-denaturing agarose gel

The viral capsid samples (30 μg of each capsid protein) were loaded into 0.7% agarose
gel in PBS with SYBR Safe DNA gel stain as a staining reagent for the encapsulated RNA. The
electrophoresis was performed in TEA (Tris-acetate-EDTA) buffer at 4°C for 4 hours. After
visualizing the encapsulated RNA bands by UV light, the gel was later stained with Coomassie
blue stain to detect the capsid protein.
2.5.6

Thermal stability measurement of viral capsid by temperature varied UVVis spectroscopy

1mg/mL of VLPs in potassium phosphate buffer (0.1 M, pH=7) was measured against the
buffer as a standard solution. 1cm quartz cuvettes with caps were used as cells for the sample and
standard buffer. The measurement was done with Varian Cary 1 Bio UV-Vis spectroscopy
equipped with Cary temperature variable controller (Agilent Technologies). The wavelength was
set at 310 nm as this wavelength gives the most sensitivity for detecting the denatured protein
(Figure 2.27). The absorbances were measured every 1 °C with temperature change at a rate
5°C/min from 25°C to 60°C, then the absorbances were measured every 0.5 °C with temperature
change at a rate 1°C /min from 60 °C to 90 °C.

160

Figure 2.27: UV-visible absorption of wtQβ at varied temperature from 25 to 90°C. The
estimated wavelength that provides the most different absorption is 310 nm (dashed line).

2.5.7

Dynamic light scattering (DLS) and transmission electron microscopy (TEM)

The hydrodynamic diameter and zeta potential were assessed on a Malvern Zetasizer
Nano zs instrument. TEM images were collected on a JEM-2200FS operating at 200 kV using
Gatan multiscan CCD camera with Digital Micrograph imaging software. Samples were
prepared on ultrathin-carbon type A, 400 mesh copper grids, or ultrathin C film on holey carbon
support film, 400 mesh, Cu for high resolution TEM (Ted Pella, Inc.). The viral capsids were
strained by aqueous 2% uranyl acetate. Results are shown in Figure 2.28.
2.5.8

Immunization studies36

Pathogen-free C57BL/6 female mice age 6−10 weeks were obtained from the Jackson
Laboratory and maintained in the University Laboratory Animal Resources facility of Michigan
State University. All animal care procedures and experimental protocols have been approved by
the Institutional Animal Care and Use Committee (IACUC) of Michigan State University.
Groups of 5 mice were injected subcutaneously under the scruff on day 0 with 0.1 mL of various
161

Qβ constructs as emulsions in complete Freund’s adjuvant (Sigma-Aldrich, F5881), and boosters
were given subcutaneously under the scruff on days 14 and 28 with 0.1 mL of various Qβ
constructs as emulsions in incomplete Freund’s adjuvant (Sigma-Aldrich, F5506). All Tn
vaccine constructs administered have the same amounts of Tn antigen (1.93 μg). Serum samples
were collected on day 0 (before immunization), 7, and 35. The final bleeding was done by
cardiac bleed.
2.5.9

Enzyme-linked immunosorbent assay (ELISA)

A Nunc MaxiSorp® flat-bottom 96 well plate was coated with BSA-Tn (10ug/mL) or
corresponding Qβ capsids (1ug/mL) in PBS pH = 7.4, overnight at 4 °C. The coated plate was
then washed 4 times with PBS/0.5% Tween-20 (PBST), followed by the addition of 1% (w/v)
BSA in PBS to each well and incubation at room temperature for one hour. The plate was
washed again 4 times with PBST. 100 μl of the dilution of mouse sera in 0.1% BSA/PBS were
added in each well. (For competitive ELISA, the diluted sera were incubated with 50 μg of the
viral capsids at 37 °C for 1 hour before adding into the plate.) The plate was incubated for two
hours at 37 °C and washed. A 1:2000 diluted horseradish peroxidase (HRP)-conjugated goat
anti-mouse IgG, IgG1, IgG2b, IgG2c, IgG3 or IgM antibody (Jackson ImmunoResearch
Laboratory IgG #115−035−071, IgM #115−035−075) in 0.1% BSA/PBS was added to each well,
respectively. The plate was incubated for one hour at 37 °C, washed, and a solution of 3,3′,5,5′tetramethylbenzidine (TMB) was added. Color was allowed to develop for 15 min, and then a
solution of 0.5 M H2SO4 (50 μl) was added to stop the reaction. The optical density was
measured at 450 nm using a microplate autoreader (BioRad). Each experiment was repeated at
least four times, and the average of the quadruplicate was used to calculate the titer. The titer was

162

determined by regression analysis with log10 dilution plotted with optical density. The titer was
calculated as the highest dilution that gave OD = 0.3.
2.5.10 Cell cultures
Human lymphoma Jurkat cells (kindly provided by Profs. Barbara Kaplan and Norbert
Kaminski, Michigan State University) were cultured in RPMI 1640 supplemented with 10%
FBS, 2 mM L-glutamine, 1 mM sodium pyruvate, minimal essential medium nonessential amino
acid, 100 U/mL each of penicillin G, and streptomycin.
Murine mammary adenocarcinoma cell line TA3Ha (kindly provided by Prof. John
Hilkens, The Netherlands Cancer Institute) were isolated from ascites collected from passage
growing on A/J mice. The cells were cultured using RPMI 1640, 10% FBS, 100 U/mL penicillin
and 100 U/mL streptomycin.
2.5.11 Flow cytometry experiment
Cells were harvested from the culture. The cells suspended in FACS buffer (5% FBS,
0.1% NaN3 in PBS) were incubated with 1:20 diluted mice sera on ice for 30 min. The cell
suspension was centrifuged at 1600 rpm, 5 min at 4°C to remove the unbound antibodies. The
cell-bound IgG antibodies were then labeled with goat anti-mouse IgG conjugated with FITC
(BioLegend, 405305) for 30 min. The excess secondary antibody was washed out and the cells
were suspended in FACS buffer. Acquisition of cells was performed with LSR II (BD), and data
was analyzed with FlowJo® software (Tree Star Inc.).
2.5.12 Anti-tumor immunoprotection (Tumor challenge)
After day 35 of the immunization, 5,000 cells of TA3Ha were intraperitoneally injected
into groups of C57BL/6 mice (n=10) on day 36. Mice were injected cyclophosphamide (50

163

mg/kg) intraperitoneally on day 37. Survival of mice was monitored for 30 days. Statistical
analysis of survival was performed with GraphPad Prism using log-rank test.
2.5.13 Liquid chromatography–mass spectrometry (LCMS)
The samples for LCMS were prepared with the following procedure: 1:1 v/v of 40μg/mL
of VLP stock solution and 100mM DTT was mixed and incubated in a water bath at 37°C for 30
min. One drop of 50% formic acid was added into the mixture. The samples are ready for the
LCMS. LCMS was performed on Waters Xevo G2-XS quadrupole/time-of-flight UPLC/MS/MS.
The liquid chromatography was done on ACQUITY UPLC® Peptide BEH C18 column, 130Å,
1.7 μm, 2.1 mm × 150 mm, using gradient eluent from 95% 0.1% formic acid in water to 95%
0.1% formic acid in ACN (0.3 mL/min flowrate) at column temperature 40°C. The multiple
charge mass spectra were transformed to single charge by using algorithm MaxEnd148a. The
average numbers of Tn/subunit were analyzed by signal intensity of mass spectrum. Results are
shown in Figure 2.30.
2.5.14 Transmission electron microscopy (TEM) Images
WT

A38K

A40C/D102C

Figure 2.28: TEM images of wild-type Qβ and various Qβ mutants.

164

Figure 2.28: (Cont’d)
A38K/A40C/D102C

T75K

A117

A40S/D102S

T7K

N10K

2.5.15 Synthesis of Tn1 and Tn2
All chemicals were reagent grade and used as received from the manufacturer, otherwise
noted. 1H NMR spectra were recorded on an Agilent-500M spectrometer and processed by
MestReNova version 10.0.2.

165

AcO OAc
O
AcO
OAc
N3

AcO OAc
O
AcO
OH
N3

H2NNH2.OAc, DMF
rt, 1h

AcO OAc
O
AcO
N3

Cl3CCN, DBU
DCM (dry), rt, 1h

SI-5 (83%)

SI-4 (95%)

SI-3

HO

0C to rt, DMF, 18h

COOH

FmocHN

AcO

OAc

AcO

Zn dust, CuSO4

O

AcO

MeOH
rt, 1h.

THF/Ac2O/AcOH,rt, 10min

AcHN

FmocHN

AcO

HO
7N NH3 in MeOH
O

FmocHN

FmocHN

HO
O
N
O

COOH

O
O

O

O
N

DIPEA, DMF, rt 12h

O
O

HO
HO
7N NH3 in MeOH
H
N

FmocHN

0 C to rt for 12h
OH

HO

OH
N

AcHN
O
H
N

H 2N
O

O
SI-14 (89%)

O

O

O

OH
O

Tn1-NHS (72%)

HBTU/HOBT
DIPEA
1:1 DCM:THF,
rt 4h
AcO OAc
O
AcO
AcHN
O

O
N
H

O

Tn1 (95%)

OH

OH

AcHN
O

O

67 % alpha
58 % pure alpha

O

HO

N

OH
O

SI-13 (97%)

O
O

H 2N

H 2N

COOBn

SI-11 NMR yield
Isolated yield

O

AcHN

0 C to rt for 12h

a/β = 10:1

N3
O

COOBn

OH
O

HO

AcHN

O

AcO

SI-12 (91%)

O

OAc

O

OAc
AcO

TMSOTf, DCM/dioxane
MS 4A, rt, 30min

COOBn

SI-10 (82%)

SI-9

H2/Pd-C

CCl3

HO

BnBr, DIPEA

FmocHN

NH

O

O
O

OH

O
O

O

HO

N

O
AcHN

O

O

O
N

DIPEA, DMF, rt 12h

OH

O
O

O

O
N
H

H
N

OH

O

Tn2-NHS (78%)

Tn2 (99%)

Scheme 2.1: Synthesis of Tn1-NHS and Tn2-NHS

2.5.16 Synthesis procedure
N-(Fluoren-9-ylmethoxycarbonyl)-O-(3,4,6-tri-O-acetyl-2-azido-2-deoxy-α-Dgalactopyranosyl-L- serine benzyl ester (SI-11)64:
Trichloroacetimidate SI-549 (3.01 g, 6.33 mmol) and N-Fmoc-O-Bn-Serine SI-1065 (2.2
g, 5.28 mmol) were mixed in the reaction flask with freshly activated molecular sieves 4A (10 g)

166

under nitrogen gas. Anhydrous DCM:Dioxane (1:1, 60 mL) was added to dissolve the mixture,
and the solution was left stirred at rt. for 30 min. TMSOTf (0.297 mL, 1.925 mmol) was added
dropwise into the reaction. The reaction was left stirred at rt. for an hour. Upon monitoring the
reaction, if there was some starting material SI-5 left, 0.1 more eq. of TMSOTf was further
added and the reaction was allowed to proceed for another hour. Upon completion,
diisopropylethylamine (DIPEA) was added to quench the reaction. The reaction was diluted with
DCM and washed with 0.1 M HCl and then water. The organic layer was dried over Na2SO4 and
then concentrated. The crude product was purified by column chromatography (silica gel; 3:1
EtOAc:Hexane) to yield SI-11(alpha) (2.23 g, 58%). Spectral analysis of the product compared
with reported literature64 confirmed the identity of the product. 1H NMR (500 MHz, Chloroformd) δ 7.76 (dt, J = 7.7, 0.9 Hz, 2H), 7.66 – 7.59 (m, 2H), 7.44 – 7.28 (m, 9H), 6.00 (d, J = 8.1 Hz,
1H), 5.40 (dd, J = 3.4, 1.2 Hz, 1H), 5.31 – 5.19 (m, 3H), 4.87 (d, J = 3.6 Hz, 1H), 4.62 (dt, J =
8.2, 3.1 Hz, 1H), 4.45 – 4.36 (m, 2H), 4.24 (t, J = 7.2 Hz, 1H), 4.17 (dd, J = 10.9, 3.2 Hz, 1H),
4.10 – 3.94 (m, 4H), 3.59 (dd, J = 11.2, 3.6 Hz, 1H), 2.15 (s, 3H), 2.07 (s, 3H), 1.96 (s, 3H).
N-(Fluoren-9-ylmethoxycarbonyl)-O-(3,4,6-tri-O-acetyl-2-acetamido-2-deoxy-α-Dgalactopyranosyl-L-serine benzyl ester (SI-12):66
The synthesis procedure was modified from reported literature.66 Compound SI-11 (2.41
g, 3.30 mmol) was dissolved in 3:2:1 of THF:Ac2O: AcOH (60 mL). Zinc dust (2.72 g, 41.23
mmol) was added and then 5 mL of saturated aq. CuSO4 was added to activate zinc. The reaction
was stirred at rt. for about half an hour. After completion as monitored by TLC, the zinc dust was
removed by filtering the reaction mixture through Celite®. The filtrate was coevaporated with
toluene to concentrate the crude product. The crude product was purified by column
chromatography (silica gel; 1:1 EtOAc:Hexanes) to yield SI-12 (2.24 g, 91%). Spectral analysis

167

of the product compared with reported literature confirmed the identity of the product. 1H NMR
(500 MHz, Chloroform-d) δ 7.77 (d, J = 7.5 Hz, 2H), 7.61 (d, J = 7.5 Hz, 2H), 7.43 – 7.28 (m,
9H), 5.88 (d, J = 8.3 Hz, 1H), 5.58 (d, J = 9.5 Hz, 1H), 5.31 (d, J = 3.2 Hz, 1H), 5.20 (q, J = 12.1
Hz, 2H), 5.04 (dd, J = 11.4, 3.2 Hz, 1H), 4.78 (d, J = 3.7 Hz, 1H), 4.66 – 4.48 (m, 2H), 4.43 (d, J
= 7.1 Hz, 2H), 4.23 (t, J = 7.1 Hz, 1H), 4.16 – 3.89 (m, 5H), 2.16 (s, 3H), 2.01 (s, 3H), 1.97 (s,
3H), 1.91 (s, 3H).
N-(Fluoren-9-ylmethoxycarbonyl)-O-(3,4,6-tri-O-acetyl-2-acetamido-2-deoxy-α-Dgalactopyranosyl-L- serine (SI-13):66
The synthesis procedure was as reported.66 The reaction yielded the product SI-13 (0.88
g, 98%). Spectral analysis of the product compared with reported literature66 confirmed the
identity of the product.
N-(Fluoren-9-ylmethoxycarbonyl)-O-(3,4,6-tri-O-acetyl-2-acetamido-2-deoxy-α-Dgalactopyranosyl-L-serine 2-ethanolyl amide (SI-14):
Compound SI-13 (1.90 g, 2.89 mmol) in 1:1 anhydrous THF:DCM was activated using
HBTU (1.2 g, 3.18 mmol), HOBt (0.43 g, 3.18 mmol) and DIPEA (1.1 mL, 6.37 mmol) at rt. for
20 min. Ethanolamine (0.22 mL, 3.62 mmol) was added into the reaction mixture. Upon
completion, the precipitate was filtered out and the crude mixture in filtrate was dried and
purified by column chromatography (silica gel; 2-10% Methanol in Hexanes) to yield 1.8 g.
(89%). Spectral analysis of the product compared with reported literature confirmed the identity
of the product.66 1H NMR (500 MHz, Chloroform-d) δ 7.75 (d, J = 7.6 Hz, 2H), 7.57 (d, J = 7.5
Hz, 2H), 7.39 (t, J = 7.5 Hz, 2H), 7.30 (t, J = 7.5 Hz, 2H), 6.87 (t, J = 5.7 Hz, 1H), 6.37 (d, J =
9.5 Hz, 1H), 5.92 (d, J = 7.4 Hz, 1H), 5.35 – 5.28 (m, 1H), 5.11 (dd, J = 11.4, 3.2 Hz, 1H), 4.89
(d, J = 3.3 Hz, 1H), 4.57 (ddd, J = 11.4, 9.5, 3.6 Hz, 1H), 4.50 – 4.31 (m, 3H), 4.17 (dt, J = 24.6,

168

6.5 Hz, 2H), 4.08 – 3.98 (m, 2H), 3.92 (d, J = 8.8 Hz, 1H), 3.73 (d, J = 17.4 Hz, 3H), 3.44 (s,
2H), 3.08 (s, 1H), 2.15 (s, 3H), 2.00 (s, 3H), 1.97 (s, 3H), 1.95 (s, 3H).
O-2-acetamido-2-deoxy-α-D-galactopyranosyl-L-serine or O-2-acetamido-2-deoxy-α-Dgalactopyranosyl-L-serine 2-ethanolyl amide (Tn1 or Tn2):
The synthesis procedure was as from reported literature.66 Compound SI-13 (100 mg,
0.152 mmol) or SI-14 (660 mg, 0.94 mmol) under N2 at 0 °C was added 5mL of 7N ammonia in
methanol. The reaction was warm up to rt. overnight. Upon completion, the solvent was
evaporated by flowing N2 gas. The crude reaction mixture was dissolved in MeOH and then
precipitated in EtOAc. The filtrate was dried to yield Tn1 (43.4 mg, 92 %) or Tn2 (330 mg, 99
%), respectively. Tn1: 1H NMR (500 MHz, Methanol-d4) δ 4.81 (d, J = 3.7 Hz, 1H), 4.31 (dd, J
= 10.9, 3.6 Hz, 1H), 4.06 (d, J = 17.2 Hz, 1H), 3.92 – 3.65 (m, 7H), 2.01 (s, 3H). Tn2: 1H NMR
(500 MHz, Methanol-d4) δ 4.78 (d, J = 3.7 Hz, 1H), 4.28 (dd, J = 11.0, 3.7 Hz, 1H), 3.92 – 3.65
(m, 7H), 3.65 – 3.49 (m, 3H), 3.37 – 3.28 (m, 3H), 2.00 (s, 3H).
N-(N-Hydroxysuccinimidyl
adipoyl)-O-2-acetamido-2-deoxy-α-D-galactopyranosyl-Lserine
or
N-(N-Hydroxysuccinimidyl
adipatyl)-O-2-acetamido-2-deoxy-α-Dgalactopyranosyl-L-serine 2-ethanolyl amide (Tn1-NHS or Tn2-NHS):
Disuccinimidyl adipate (5 eq.) in anhydrous DMF (0.5 mL) was added to Tn1 (40 mg,
0.13 mmol) or Tn2 (66 mg, 0.18 mmol) dissolved in DMF (0.5 mL). DIPEA (1 eq.) was added
in the reaction mixture. The reaction was left stirred for 2-3 h. Upon completion, DMF was
evaporated under vacuum until dryness. The crude product was precipitated in EtOAc twice and
then washed with 10% MeOH in EtOAc 3-5 times to remove the excess diNHS-linker. The final
precipitate was dried under vacuum to yield Tn1-NHS (50 mg, 72%). Tn1-NHS: 1H NMR (500
MHz, Methanol-d4) δ 4.83 (d, J = 3.7 Hz, 1H), 4.65 (t, J = 4.0 Hz, 1H), 4.25 (dd, J = 11.0, 3.7
Hz, 1H), 3.99 – 3.62 (m, 5H), 2.83 (s, 4H), 2.73 – 2.62 (m, 2H), 2.35 (t, J = 6.8 Hz, 2H), 2.00 (d,

169

J = 7.7 Hz, 4H), 1.77 (dt, J = 6.9, 3.5 Hz, 4H); Tn2-NHS (84.5 mg, 78 %). Tn2-NHS: 1H NMR
(500 MHz, Methanol-d4) δ 4.82 (d, J = 3.8 Hz, 1H), 4.59 (t, J = 5.2 Hz, 1H), 4.26 (dd, J = 11.0,
3.7 Hz, 1H), 3.92 – 3.65 (m, 8H), 3.60 (td, J = 5.8, 1.8 Hz, 2H), 3.37 – 3.26 (m, 6H), 2.83 (s,
4H), 2.73 – 2.63 (m, 2H), 2.42 – 2.27 (m, 2H), 2.01 (d, J = 2.0 Hz, 4H), 1.82 – 1.70 (m, 3H).

170

APPENDICES

171

APPENDIX A

Size Exclusion Chromatograms
Qβ(WT) and Qβ(WT)-Tn1

Qβ(T7K) and Qβ(T7K)-Tn1

Figure 2.29: Size-exclusion chromatography of wild-type Qβ, varied Qβ mutants and their Tn1
derivatives.

172

Figure 2.29: (Cont’d)
Qβ(N10K) and Qβ(N10K)-Tn1

Qβ(A38K) and Qβ(A38K)-Tn1

173

Figure 2.29: (Cont’d)
Qβ(A38K/A40C/D102C) and Qβ(A38K/A40C/D102C)-Tn1

Qβ(A40C/D102C) and Qβ(A40C/D102C)-Tn1

174

Figure 2.29: (Cont’d)
Qβ(T75K) and Qβ(T75K)-Tn1

Qβ(A117K) and Qβ(A117K)-Tn1

175

Figure 2.29: (Cont’d)
Qβ(P119K) and Qβ(P119K)-Tn1

176

APPENDIX B

Liquid chromatography–mass spectra
Qβ_WT_Tn1

Figure 2.30: Mass spectra of wild-type Qβ-Tn1 and varied Qβ mutant-Tn1 after applying
MaxEnd1 algorithm.

177

Figure 2.30: (Cont’d)
Qβ_T7K_Tn1

Qβ_N10K_Tn1

178

Figure 2.30: (Cont’d)
Qβ_K13R/A40C/D102C_Tn1

Qβ_A38K_Tn1

179

Figure 2.30: (Cont’d)
Qβ_A38K/A40C/D102C_Tn1

Qβ_A38K/A40C/D102C_Tn2

180

Figure 2.30: (Cont’d)
Qβ_A40C/D102C_Tn1

Qβ_A40C/D102C_Tn2

181

Figure 2.30: (Cont’d)
Qβ_A40S/D102S_Tn1

Qβ_T75K_Tn1

182

Figure 2.30: (Cont’d)
Qβ_A117K_Tn1

Qβ_P119K_Tn1

183

8.5
8.0
7.5
7.0
6.5
6.0
5.5
5.0
4.5
f1 (ppm)

184
4.0

Figure 2.31: 1H NMR spectrum of compound SI-11
3.5
2.98
3.16
2.80

1.26

6.37

2.05

1.30

1.13

3.18

1.09

1.08

8.34

1.94

2.00

7.77
7.77
7.77
7.76
7.75
7.75
7.63
7.63
7.62
7.62
7.62
7.61
7.42
7.41
7.40
7.40
7.39
7.39
7.38
7.38
7.37
7.36
7.36
7.36
7.35
7.34
7.34
7.34
7.33
7.33
7.32
7.32
7.32
7.31
7.31
7.31
7.30
6.01
5.99
5.40
5.40
5.40
5.39
5.29
5.28
5.26
5.26
5.24
5.23
4.87
4.86
4.63
4.61
4.42
4.41
4.40
4.25
4.24
4.18
4.17
4.16
4.15
4.07
4.07
4.06
4.06
4.02
4.01
4.01
4.00
3.99
3.99
3.61
3.60
3.58
3.58
2.15
2.07
1.96

APPENDIX C

NMR spectra

N-(Fluoren-9-ylmethoxycarbonyl)-O-(3,4,6-tri-O-acetyl-2-azido-2-deoxy-α-D-galactopyranosylL- serine benzyl ester (SI-11):
a_Tn_3OAc_N3_Fmoc_Ser_OBn_2_PROTON_01

250

200

150

100

50

0

3.0
2.5
2.0
1.5
1.0

a_Tn_3OAc_N3_Fmoc_Ser_OBn_3_CARBON_01
100

90

80

70

60

50

40

30

20

10

0

-10
180

170

160

150

140

130

120

110

100
90
f1 (ppm)

80

Figure 2.32: 13C NMR spectrum of compound SI-11

185

70

60

50

40

30

20

10

a_Tn_3OAc_N3_Fmoc_Ser_OBn_3_gCOSY_01

1.5
2.0
2.5
3.0
3.5

4.5
5.0
5.5
6.0
6.5
7.0
7.5
8.0

8.0

7.5

7.0

6.5

6.0

5.5

4.5
5.0
f2 (ppm)

4.0

Figure 2.33: 1H-1H COSY NMR spectrum of compound SI-11

186

3.5

3.0

2.5

2.0

f1 (ppm)

4.0

a_Tn_3OAc_N3_Fmoc_Ser_OBn_3_gHMQC_01
20
30
40
50
60

80
90
100
110
120
130
140
150

8.5

8.0

7.5

7.0

6.5

6.0

5.5

5.0
f2 (ppm)

4.5

Figure 2.34: gHMQC NMR spectrum of compound SI-11

187

4.0

3.5

3.0

2.5

2.0

1.5

f1 (ppm)

70

a_Tn_3OAc_N3_Fmoc_Ser_OBn_3_gHMBCAD_01
20
30
40
50
60
70

90
100
110
120
130
140
150
160
170
180
8.5

8.0

7.5

7.0

6.5

6.0

5.5

5.0
f2 (ppm)

4.5

Figure 2.35: gHMBC NMR spectrum of compound SI-11

188

4.0

3.5

3.0

2.5

2.0

f1 (ppm)

80

8.5
8.0
7.5
7.0
6.5
6.0
5.5

189

4.5
5.0
f1 (ppm)

Figure 2.36: 1H NMR spectrum of compound SI-12
4.0
2.82
6.00
2.80

5.33

1.14

4.16

0.97

1.28
2.09
1.26

1.22

1.06

8.57

1.92

2.00

a_Tn_3OAc_NAc_Fmoc_Ser_OBn_2_PROTON_01
5.89
5.87
5.59
5.57
5.32
5.31
5.29
5.24
5.21
5.19
5.17
5.05
5.05
5.03
5.03
4.78
4.77
4.62
4.61
4.60
4.59
4.59
4.56
4.55
4.54
4.53
4.52
4.51
4.44
4.43
4.25
4.23
4.22
4.14
4.12
4.11
4.10
4.08
4.07
4.06
4.05
4.05
4.04
4.03
4.02
4.02
4.00
3.99
3.98
3.97
3.97
3.95
3.95
2.16
2.04
2.01
1.99
1.97
1.91

7.77
7.76
7.62
7.60
7.42
7.40
7.39
7.38
7.37
7.35
7.34
7.34
7.33
7.32
7.32
7.31
7.30

N-(Fluoren-9-ylmethoxycarbonyl)-O-(3,4,6-tri-O-acetyl-2-acetamido-2-deoxy-α-Dgalactopyranosyl-L-serine benzyl ester (SI-12):
280

260

240

220

200

180

160

140

120

100
80

60

40

20

0

3.5
3.0
2.5
2.0

-20

1.5
1.0

a_Tn_3OAc_NAc_Fmoc_Ser_OBn_3_CARBON_01
50

45

40

35

30

25

20

15

10

5

0

-5
170

160

150

140

130

120

110

100

90
f1 (ppm)

80

Figure 2.37: 13C NMR spectrum of compound SI-12

190

70

60

50

40

30

20

10

1.0

a_Tn_3OAc_NAc_Fmoc_Ser_OBn_3_gCOSY_01

1.5
2.0
2.5
3.0
3.5

4.5
5.0
5.5
6.0
6.5
7.0
7.5
8.0
7.5

7.0

6.5

6.0

5.5

5.0

f2 (ppm)

4.5

4.0

Figure 2.38: 1H-1H COSY NMR spectrum of compound SI-12

191

3.5

3.0

2.5

2.0

f1 (ppm)

4.0

a_Tn_3OAc_NAc_Fmoc_Ser_OBn_3_gHSQCAD_01

20
30
40
50
60
70

90
100
110
120
130
140
150
160
170
180
8.0

7.5

7.0

6.5

6.0

5.5

5.0
f2 (ppm)

4.5

Figure 2.39: gHMQC NMR spectrum of compound SI-12

192

4.0

3.5

3.0

2.5

2.0

f1 (ppm)

80

10

a_Tn_3OAc_NAc_Fmoc_Ser_OBn_3_gHMBCAD_01

20
30
40
50
60
70
80

100
110
120
130
140
150
160
170
180
190
8.0

7.5

7.0

6.5

6.0

5.5

4.5
5.0
f2 (ppm)

Figure 2.40: gHMBC NMR spectrum of compound SI-12

193

4.0

3.5

3.0

2.5

2.0

1.5

f1 (ppm)

90

5.93
5.92
5.37
5.36
5.32
5.32
5.32
5.32
5.12
5.12
5.10
5.09
4.90
4.89

6.38
6.36

7.76
7.75
7.58
7.57
7.41
7.39
7.38
7.31
7.30
7.28
7.26
6.89
6.87
6.86

aTn_3OAc_NAc_Fmoc_Ser_OEtOH_13_PROTON_01

4.60
4.59
4.58
4.57
4.57
4.57
4.56
4.55
4.45
4.44
4.39
4.38
4.38
4.21
4.20
4.18
4.16
4.15
4.13
4.05
4.04
4.02
3.93
3.91
3.76
3.75
3.71
3.44
2.15
2.14
2.04
2.02
2.02
2.00
1.99
1.97
1.96
1.95

N-(Fluoren-9-ylmethoxycarbonyl)-O-(3,4,6-tri-O-acetyl-2-acetamido-2-deoxy-α-Dgalactopyranosyl-L-serine 2-ethanolyl amide (SI-14):
240
230
220
210
200
190
180
170
160
150
140
130
120
110
100
90
80
70
60
50
40
30
20
10

8.5

8.0

7.5

7.0

6.5

6.0

5.5

5.0
f1 (ppm)

4.5

Figure 2.41: 1H NMR spectrum of compound SI-14

194

4.0

3.5

3.0

2.5

-10

9.04

3.22

2.05

3.22

5.88

3.04

1.25

1.10

1.24

2.00

1.07

1.06

1.18

4.47

2.12

2.00

0

2.0

-20
1.5

aTn_3OAc_NAc_Fmoc_Ser_OEtOH_14_CARBON_01
24

22

20

18

16

14

12

10

8

6

4

2

0

-2
230

220

210

200

190

180

170

160

150

140

130

120

110
100
f1 (ppm)

90

Figure 2.42: 13C NMR spectrum of compound SI-14

195

80

70

60

50

40

30

20

10

0

-10

1.5

aTn_3OAc_NAc_Fmoc_Ser_OEtOH_14_gCOSY_01

2.0
2.5
3.0
3.5
4.0

5.0
5.5
6.0
6.5
7.0
7.5
8.0

7.5

7.0

6.5

6.0

5.5

5.0

4.5
f2 (ppm)

4.0

Figure 2.43: 1H-1H COSY NMR spectrum of compound SI-14

196

3.5

3.0

2.5

2.0

1.5

f1 (ppm)

4.5

aTn_3OAc_NAc_Fmoc_Ser_OEtOH_14_gHSQCAD_01
20
30
40
50
60

80
90
100
110
120
130
140
150
8.0

7.5

7.0

6.5

6.0

5.5

4.5
5.0
f2 (ppm)

Figure 2.44: gHMQC NMR spectrum of compound SI-14

197

4.0

3.5

3.0

2.5

2.0

f1 (ppm)

70

aTn_3OAc_NAc_Fmoc_Ser_OEtOH_14_gHMBCAD_01
20
30
40
50
60
70
80

100
110
120
130
140
150
160
170
180
190
8.0

7.5

7.0

6.5

6.0

5.5

5.0

4.5
f2 (ppm)

4.0

Figure 2.45: gHMBC NMR spectrum of compound SI-14

198

3.5

3.0

2.5

2.0

1.5

1.0

f1 (ppm)

90

260

2.01
2.01
2.00

4.07
4.04
3.87
3.87
3.85
3.80
3.79
3.78
3.77
3.77
3.76
3.74
3.71
3.71
3.69
3.68

4.82
4.81

a_Tn_noEtOH_002_PROTON_01

4.33
4.32
4.31
4.30

O-2-acetamido-2-deoxy-α-D-galactopyranosyl-L-serine (Tn1):

240

220

200

180

160

140

120

100

80

60

40

20

5.6

5.4

5.2

5.0

4.8

6.30

1.00

1.27

5.8

4.6

4.4

3.10

0

4.2

4.0

3.8

3.6

3.4
3.2
f1 (ppm)

Figure 2.46: 1H NMR spectrum of compound Tn1

199

3.0

2.8

2.6

2.4

2.2

2.0

-20
1.8

1.6

1.4

1.2

1.0

a_Tn_noEtOH_CARBON_01
5.0

4.5

4.0

3.5

3.0

2.5

2.0

1.5

1.0

0.5

0.0

-0.5
230

220

210

200

190

180

170

160

150

140

130

120

110
100
f1 (ppm)

Figure 2.47: 13C NMR spectrum of compound Tn1

200

90

80

70

60

50

40

30

20

10

0

-10

a_Tn_noEtOH_gCOSY_01
0.0

0.5

1.0

1.5

2.5

3.0

3.5

4.0

4.5

5.0

5.0

4.5

4.0

3.5

3.0

2.5
f2 (ppm)

2.0

Figure 2.48: 1H-1H COSY NMR spectrum of compound Tn1

201

1.5

1.0

0.5

0.0

f1 (ppm)

2.0

10

a_Tn_noEtOH_gHSQCAD_01

20

30

40

60

70

80

90

100

5.2

5.0

4.8

4.6

4.4

4.2

4.0

3.8

3.6

3.4
3.2
f2 (ppm)

Figure 2.49: gHMQC NMR spectrum of compound Tn1

202

3.0

2.8

2.6

2.4

2.2

2.0

1.8

1.6

f1 (ppm)

50

a_Tn_noEtOH_gHMBCAD_01
20
30
40
50
60
70
80

100
110
120
130
140
150
160
170
180
190

5.0

4.5

4.0

3.5
f2 (ppm)

Figure 2.50: gHMBC NMR spectrum of compound Tn1

203

3.0

2.5

2.0

1.5

f1 (ppm)

90

O-2-acetamido-2-deoxy-α-D-galactopyranosyl-L-serine 2-ethanolyl amide (Tn2):
4.79
4.78

4.30
4.29
4.27
4.27
3.88
3.88
3.87
3.87
3.87
3.86
3.85
3.84
3.82
3.82
3.81
3.81
3.81
3.80
3.80
3.78
3.77
3.76
3.75
3.75
3.75
3.74
3.73
3.71
3.70
3.69
3.68
3.63
3.62
3.61
3.60
3.60
3.58
3.57
3.56
3.55
3.54
3.53
3.52
3.35
3.34
3.33
3.31
3.31
3.31
3.30
2.00

a_Tn_Ser_Et_OH_1_PROTON_01

500

450

400

350

300

250

200

150

100

50

5.2

5.0

4.8

4.6

4.4

4.2

4.0

3.6

3.06

3.8

2.72

3.89

5.4

6.30

1.03

1.00

0

3.4
3.2
f1 (ppm)

Figure 2.51: 1H NMR spectrum of compound Tn2

204

3.0

2.8

2.6

2.4

2.2

2.0

1.8

1.6

1.4

a_Tn_Ser_Et_OH_2_CARBON_01

35

30

25

20

15

10

5

0

230

220

210

200

190

180

170

160

150

140

130

120

110
100
f1 (ppm)

Figure 2.52: 13C NMR spectrum of compound Tn2

205

90

80

70

60

50

40

30

20

10

0

-10

a_Tn_Ser_Et_OH_2_gCOSY_01
1.5

2.0

2.5

3.5

4.0

4.5

5.0

5.5
5.0

4.8

4.6

4.4

4.2

4.0

3.8

3.6

3.4
f2 (ppm)

3.2

3.0

Figure 2.53: 1H-1H COSY NMR spectrum of compound Tn2

206

2.8

2.6

2.4

2.2

2.0

1.8

f1 (ppm)

3.0

a_Tn_Ser_Et_OH_2_gHSQCAD_01
0
10
20
30
40

60
70
80
90
100
110
120
130

6.2

6.0

5.8

5.6

5.4

5.2

5.0

4.8

4.6

4.4

4.2

4.0
3.8
f2 (ppm)

3.6

Figure 2.54: gHMQC NMR spectrum of compound Tn2

207

3.4

3.2

3.0

2.8

2.6

2.4

2.2

2.0

1.8

1.6

f1 (ppm)

50

a_Tn_Ser_Et_OH_2_gHMBCAD_01
0

20

40

60

100

120

140

160

180

200

220
6.0

5.5

5.0

4.5

4.0
f2 (ppm)

Figure 2.55: gHMBC NMR spectrum of compound Tn2

208

3.5

3.0

2.5

2.0

1.5

f1 (ppm)

80

5.2
5.0
4.8
4.6
4.4
4.2
4.0
3.8
3.6
3.4
3.2
f1 (ppm)

209
3.0
2.8

Figure 2.56: 1H NMR spectrum of compound Tn1-NHS
2.6
2.4
3.92

2.2
3.15

2.13

2.00

3.82

7.02

1.01

3.93
3.91
3.91
3.90
3.90
3.89
3.88
3.88
3.87
3.87
3.87
3.84
3.83
3.83
3.82
3.82
3.81
3.81
3.77
3.77
3.76
3.75
3.74
3.74
3.73
3.71
3.71
3.70
3.70
3.68
3.67
2.83
2.70
2.70
2.69
2.68
2.68
2.68
2.67
2.67
2.36
2.35
2.35
2.34
2.33
1.99
1.80
1.80
1.79
1.78
1.77
1.77
1.76
1.75
1.75

4.26
4.25
4.24
4.23

4.66
4.65
4.64

4.83
4.82

Tn1_NHS_21_PROTON_01

1.00

1.04

N-(N-Hydroxysuccinimidyl-adipoyl)-O-2-acetamido-2-deoxy-α-D-galactopyranosyl-L-serine
(Tn1-NHS):

2400

2200

2000

1800

1600

1400

1200

1000

800

600

400

200

0

2.0
1.8
1.6
1.4

-200

Tn1_NHS_12_CARBON_01
24

22

20

18

16

14

12

10

8

6

4

2

0

-2
200

190

180

170

160

150

140

130

120

110

100
f1 (ppm)

90

80

Figure 2.57: 13C NMR spectrum of compound Tn1-NHS

210

70

60

50

40

30

20

10

0

Tn1_NHS_23_gCOSY_01

1.5

2.0

2.5

3.5

4.0

4.5

5.0

5.0

4.8

4.6

4.4

4.2

4.0

3.8

3.6

3.4
3.2
f2 (ppm)

3.0

2.8

2.6

Figure 2.58: 1H-1H COSY NMR spectrum of compound Tn1-NHS

211

2.4

2.2

2.0

1.8

1.6

f1 (ppm)

3.0

Tn1_NHS_22_gHSQCAD_01

20

30

40

60

70

80

90

100
4.9 4.8 4.7 4.6 4.5 4.4 4.3 4.2 4.1 4.0 3.9 3.8 3.7 3.6 3.5 3.4 3.3 3.2 3.1 3.0 2.9 2.8 2.7 2.6 2.5 2.4 2.3 2.2 2.1 2.0 1.9 1.8 1.7
f2 (ppm)

Figure 2.59: gHMQC NMR spectrum of compound Tn1-NHS

212

f1 (ppm)

50

Tn1_NHS_12_gHMBCAD_01

20
30
40
50
60
70
80

100
110
120
130
140
150
160
170
180
190
4.8

4.6

4.4

4.2

4.0

3.8

3.6

3.4
3.2
f2 (ppm)

3.0

2.8

Figure 2.60: gHMBC NMR spectrum of compound Tn1-NHS

213

2.6

2.4

2.2

2.0

1.8

f1 (ppm)

90

3.87
3.87
3.86
3.86
3.86
3.85
3.84
3.81
3.81
3.80
3.80
3.79
3.78
3.76
3.76
3.76
3.75
3.75
3.74
3.73
3.73
3.72
3.71
3.70
3.61
3.61
3.60
3.60
3.59
3.58
3.34
3.33
3.31
3.31
3.31
3.31
3.30
3.30
2.83
2.69
2.68
2.67
2.67
2.66
2.36
2.35
2.34
2.34
2.01
2.01
1.77
1.76
1.76
1.75

4.60
4.59
4.59
4.58

4.82
4.81

NHS_a_Tn_Ser_Et_OH_1_PROTON_01

4.28
4.27
4.26
4.25

N-(N-Hydroxysuccinimidyl adipatyl)-O-2-acetamido-2-deoxy-α-D-galactopyranosyl-L-serine 2ethanolyl amide (Tn2-NHS):
400

350

300

250

200

150

100

50

5.2

5.0

4.8

4.6

4.2

4.0

3.4

3.2
3.0
f1 (ppm)

2.8

2.6

Figure 2.61: 1H NMR spectrum of compound Tn2-NHS

214

2.4

2.2

2.0

4.04

3.35

2.31

2.03

3.6

3.90

3.8

5.21

1.26

4.4

2.20

5.4

8.31

5.6

1.26

1.00

0

1.8

1.6

1.4

1.2

1.0

0.8

0.6

14

NHS_a_Tn_Ser_Et_OH_2_CARBON_01

13
12
11
10
9
8
7

6
5
4

3
2
1

0
-1
200

190

180

170

160

150

140

130

120

110

100
f1 (ppm)

90

80

70

Figure 2.62: 13C NMR spectrum of compound Tn2-NHS

215

60

50

40

30

20

10

0

1.0

NHS_a_Tn_Ser_Et_OH_2_gCOSY_01

1.5

2.0

3.0

3.5

4.0

4.5

5.0

5.2

5.0

4.8

4.6

4.4

4.2

4.0

3.8

3.6

3.4
3.2
f2 (ppm)

3.0

2.8

2.6

Figure 2.63: 1H-1H COSY NMR spectrum of compound Tn2-NHS

216

2.4

2.2

2.0

1.8

1.6

f1 (ppm)

2.5

NHS_a_Tn_Ser_Et_OH_2_gHSQCAD_01

0

10

20

30

50

60

70

80

90

100

110
5.8

5.6

5.4

5.2

5.0

4.8

4.6

4.4

4.2

4.0

3.8
3.6
3.4
f2 (ppm)

3.2

3.0

Figure 2.64: gHMQC NMR spectrum of compound Tn2-NHS

217

2.8

2.6

2.4

2.2

2.0

1.8

1.6

1.4

f1 (ppm)

40

NHS_a_Tn_Ser_Et_OH_2_gHMBCAD_01

-10
0
10
20
30
40
50
60

80
90
100
110
120
130
140
150
160
170
180
5.8

5.6

5.4

5.2

5.0

4.8

4.6

4.4

4.2

4.0

3.8
3.6
3.4
f2 (ppm)

3.2

3.0

Figure 2.65: gHMBC NMR spectrum of compound Tn2-NHS

218

2.8

2.6

2.4

2.2

2.0

1.8

1.6

f1 (ppm)

70

REFERENCES

219

REFERENCES

1.
Bachmann, M. F.; Zinkernagel, R. M., Neutralizing antiviral B cell responses.
Annual Review of Immunology 1997, 15 (1), 235-270.
2.
(a) Jegerlehner, A.; Storni, T.; Lipowsky, G.; Schmid, M.; Pumpens, P.;
Bachmann, M. F., Regulation of IgG antibody responses by epitope density and CD21-mediated
costimulation. European Journal of Immunology 2002, 32 (11), 3305-3314; (b) Bachmann, M.;
Rohrer, U.; Kundig, T.; Burki, K.; Hengartner, H.; Zinkernagel, R., The influence of antigen
organization on B cell responsiveness. Science 1993, 262 (5138), 1448-1451.
3.
Vogelstein, B.; Dintzis, R. Z.; Dintzis, H. M., Specific cellular stimulation in the
primary immune response: a quantized model. Proceedings of the National Academy of Sciences
of the United States of America 1982, 79 (2), 395-399.
4.
Zabel, F.; Kündig, T. M.; Bachmann, M. F., Virus-induced humoral immunity: on
how B cell responses are initiated. Current Opinion in Virology 2013, 3 (3), 357-362.
5.
Shirbaghaee, Z.; Bolhassani, A., Different applications of virus-like particles in
biology and medicine: Vaccination and delivery systems. Biopolymers 2016, 105 (3), 113-132.
6.
Tan, M.; Jiang, X., Subviral particle as vaccine and vaccine platform. Current
Opinion in Virology 2014, 6, 24-33.
7.
(a) Fiedler, J. D.; Higginson, C.; Hovlid, M. L.; Kislukhin, A. A.; Castillejos, A.;
Manzenrieder, F.; Campbell, M. G.; Voss, N. R.; Potter, C. S.; Carragher, B.; Finn, M. G.,
Engineered mutations change the structure and stability of a virus-like particle.
Biomacromolecules 2012, 13 (8), 2339-2348; (b) Rohovie, M. J.; Nagasawa, M.; Swartz, J. R.,
Virus-like particles: Next-generation nanoparticles for targeted therapeutic delivery.
Bioengineering & Translational Medicine 2017, 1-15.
8.
(a) Lim, F.; Spingola, M.; Peabody, D. S., The RNA-binding site of bacteriophage
Qβ coat protein. Journal of Biological Chemistry 1996, 271 (50), 31839-31845; (b) Overby, L.
R.; Barlow, G. H.; Doi, R. H.; Jacob, M.; Spiegelman, S., Comparison of two serologically
distinct ribonucleic acid bacteriophages I. properties of the viral particles. Journal of
Bacteriology 1966, 91 (1), 442-448; (c) Lau, J. L.; Baksh, M. M.; Fiedler, J. D.; Brown, S. D.;
Kussrow, A.; Bornhop, D. J.; Ordoukhanian, P.; Finn, M. G., Evolution and protein packaging of
small-molecule RNA aptamers. ACS Nano 2011, 5 (10), 7722-7729.

220

9.
(a) Hung, P. P.; Ling, C. M.; Overby, L. R., Self-assembly of Qβ and MS2 phage
particles: possible function of initiation complexes. Science 1969, 166 (3913), 1638-1640; (b)
Medrano, M.; Fuertes, M. Á.; Valbuena, A.; Carrillo, P. J. P.; Rodríguez-Huete, A.; Mateu, M.
G., Imaging and quantitation of a succession of transient intermediates reveal the reversible selfassembly pathway of a simple icosahedral virus capsid. Journal of the American Chemical
Society 2016, 138 (47), 15385-15396.
10.
Golmohammadi, R.; Fridborg, K.; Bundule, M.; Valegård, K.; Liljas, L., The
crystal structure of bacteriophage Qβ at 3.5 å resolution. Structure 1996, 4 (5), 543-554.
11.
Akache, B.; Weeratna, R.; Deora, A.; Thorn, J.; Champion, B.; Merson, J.; Davis,
H.; McCluskie, M., Anti-IgE Qb-VLP conjugate vaccine self-adjuvants through activation of
TLR7. Vaccines 2016, 4 (1), 3.
12.
Jegerlehner, A.; Maurer, P.; Bessa, J.; Hinton, H. J.; Kopf, M.; Bachmann, M. F.,
TLR9 signaling in B cells determines class switch recombination to IgG2a. The Journal of
Immunology 2007, 178 (4), 2415-2420.
13.
(a) Blander, J. M.; Medzhitov, R., Toll-dependent selection of microbial antigens
for presentation by dendritic cells. Nature 2006, 440 (7085), 808-812; (b) Bachmann, M. F.;
Jennings, G. T., Vaccine delivery: a matter of size, geometry, kinetics and molecular patterns.
Nature Reviews Immunology 2010, 10 (11), 787-796.
14.
(a) Hofstetter, H.; Monstein, H. J.; Weissmann, C., The readthrough protein A1 is
essential for the formation of viable Qβ particles. Biochimica et Biophysica Acta (BBA) - Nucleic
Acids and Protein Synthesis 1974, 374 (2), 238-251; (b) Weiner, A. M.; Weber, K., A single
UGA codon functions as a natural termination signal in the coliphage Qβ coat protein cistron.
Journal of Molecular Biology 1973, 80 (4), 837-855.
15.
Dai, X.; Li, Z.; Lai, M.; Shu, S.; Du, Y.; Zhou, Z. H.; Sun, R., In situ structures of
the genome and genome-delivery apparatus in a single-stranded RNA virus. Nature 2017, 541
(7635), 112-116.
16.
Vasiljeva, I.; Kozlovska, T.; Cielens, I.; Strelnikova, A.; Kazaks, A.; Ose, V.;
Pumpens, P., Mosaic Qβ coats as a new presentation model. FEBS Letters 1998, 431 (1), 7-11.
17.
Udit, A. K.; Brown, S.; Baksh, M. M.; Finn, M. G., Immobilization of
bacteriophage Qβ on metal-derivatized surfaces via polyvalent display of hexahistidine tags.
Journal of Inorganic Biochemistry 2008, 102 (12), 2142-2146.
18.
Ashcroft, A. E.; Lago, H.; Macedo, J. M. B.; Horn, W. T.; Stonehouse, N. J.;
Stockley, P. G., Engineering thermal stability in RNA phage capsids via disulphide bonds.
Journal of Nanoscience and Nanotechnology 2005, 5 (12), 2034-2041.

221

19.
Maurer, P.; Jennings, G. T.; Willers, J.; Rohner, F.; Lindman, Y.; Roubicek, K.;
Renner, W. A.; Müller, P.; Bachmann, M. F., A therapeutic vaccine for nicotine dependence:
preclinical efficacy, and phase I safety and immunogenicity. European Journal of Immunology
2005, 35 (7), 2031-2040.
20.
Kündig, T. M.; Senti, G.; Schnetzler, G.; Wolf, C.; Prinz Vavricka, B. M.;
Fulurija, A.; Hennecke, F.; Sladko, K.; Jennings, G. T.; Bachmann, M. F., Der p 1 peptide on
virus-like particles is safe and highly immunogenic in healthy adults. Journal of Allergy and
Clinical Immunology 2006, 117 (6), 1470-1476.
21.
Ambuhl, P. M. a.; Tissot, A. C. b.; Fulurija, A. b.; Maurer, P. b.; Nussberger, J. c.;
Sabat, R. d.; Nief, V. a.; Schellekens, C. b.; Sladko, K. b.; Roubicek, K. b.; Pfister, T. b.;
Rettenbacher, M. b.; Volk, H.-D. e.; Wagner, F. f.; Muller, P. b.; Jennings, G. T. b.; Bachmann,
M. F. b., A vaccine for hypertension based on virus-like particles: preclinical efficacy and phase
I safety and immunogenicity. Journal of Hypertension 2007, 25 (1), 63-72.
22.
Skibinski, D. A. G.; Hanson, B. J.; Lin, Y.; von Messling, V.; Jegerlehner, A.;
Tee, J. B. S.; Chye, D. H.; Wong, S. K. K.; Ng, A. A. P.; Lee, H. Y.; Au, B.; Lee, B. T. K.;
Santoso, L.; Poidinger, M.; Fairhurst, A.-M.; Matter, A.; Bachmann, M. F.; Saudan, P.;
Connolly, J. E., Enhanced neutralizing antibody titers and Th1 polarization from a novel
Escherichia coli derived pandemic influenza vaccine. PLoS ONE 2013, 8 (10), e76571.
23.
(a) Jeon, S. H.; Arnon, R., Immunization with influenza virus hemagglutinin
globular region containing the receptor-binding pocket. Viral Immunology 2002, 15 (1), 165-176;
(b) Chiu, F.-F.; Venkatesan, N.; Wu, C.-R.; Chou, A.-H.; Chen, H.-W.; Lian, S.-P.; Liu, S.-J.;
Huang, C.-C.; Lian, W.-C.; Chong, P.; Leng, C.-H., Immunological study of HA1 domain of
hemagglutinin of influenza H5N1 virus. Biochemical and Biophysical Research Communications
2009, 383 (1), 27-31; (c) Jegerlehner, A.; Zabel, F.; Langer, A.; Dietmeier, K.; Jennings, G. T.;
Saudan, P.; Bachmann, M. F., Bacterially produced recombinant influenza vaccines based on
virus-like particles. PLoS ONE 2013, 8 (11), e78947.
24.
Astronomo, R. D.; Kaltgrad, E.; Udit, A. K.; Wang, S.-K.; Doores, K. J.; Huang,
C.-Y.; Pantophlet, R.; Paulson, J. C.; Wong, C.-H.; Finn, M. G.; Burton, D. R., Defining criteria
for oligomannose immunogens for HIV using icosahedral virus capsid scaffolds. Chemistry &
Biology 2010, 17 (4), 357-370.
25.
Spohn, G.; Schori, C.; Keller, I.; Sladko, K.; Sina, C.; Guler, R.; Schwarz, K.;
Johansen, P.; Jennings, G. T.; Bachmann, M. F., Preclinical efficacy and safety of an anti-IL-1β
vaccine for the treatment of type 2 diabetes. Molecular Therapy — Methods & Clinical
Development 2014, 1, 14048.
26.
Cavelti-Weder, C.; Timper, K.; Seelig, E.; Keller, C.; Osranek, M.; Lassing, U.;
Spohn, G.; Maurer, P.; Muller, P.; Jennings, G. T.; Willers, J.; Saudan, P.; Donath, M. Y.;
Bachmann, M. F., Development of an Interleukin-1[beta] vaccine in patients with type 2
diabetes. Molecular Therapy 2016, 24 (5), 1003-1012.

222

27.
(a) Qian, Y.-W.; Schmidt, R. J.; Zhang, Y.; Chu, S.; Lin, A.; Wang, H.; Wang, X.;
Beyer, T. P.; Bensch, W. R.; Li, W.; Ehsani, M. E.; Lu, D.; Konrad, R. J.; Eacho, P. I.; Moller,
D. E.; Karathanasis, S. K.; Cao, G., Secreted PCSK9 downregulates low density lipoprotein
receptor through receptor-mediated endocytosis. Journal of Lipid Research 2007, 48 (7), 14881498; (b) Kwon, H. J.; Lagace, T. A.; McNutt, M. C.; Horton, J. D.; Deisenhofer, J., Molecular
basis for LDL receptor recognition by PCSK9. Proceedings of the National Academy of Sciences
2008, 105 (6), 1820-1825.
28.
Crossey, E.; Amar, M. J. A.; Sampson, M.; Peabody, J.; Schiller, J. T.;
Chackerian, B.; Remaley, A. T., A cholesterol-lowering VLP vaccine that targets PCSK9.
Vaccine 2015, 33 (43), 5747-5755.
29.
Mond, J. J.; Lees, A.; Snapper, C. M., T cell-independent antigens type 2. Annual
Review of Immunology 1995, 13 (1), 655-692.
30.
Kagan, E.; Ragupathi, G.; Yi, S. S.; Reis, C. A.; Gildersleeve, J.; Kahne, D.;
Clausen, H.; Danishefsky, S. J.; Livingston, P. O., Comparison of antigen constructs and carrier
molecules for augmenting the immunogenicity of the monosaccharide epithelial cancer antigen
Tn. Cancer Immunology, Immunotherapy 2005, 54 (5), 424-430.
31.
(a) Kuduk, S. D.; Schwarz, J. B.; Chen, X.-T.; Glunz, P. W.; Sames, D.;
Ragupathi, G.; Livingston, P. O.; Danishefsky, S. J., Synthetic and immunological studies on
clustered modes of mucin-related Tn and TF O-linked antigens:  The preparation of a
glycopeptide-based vaccine for clinical trials against prostate cancer. Journal of the American
Chemical Society 1998, 120 (48), 12474-12485; (b) Lo-Man, R.; Vichier-Guerre, S.; Perraut, R.;
Dériaud, E.; Huteau, V.; BenMohamed, L.; Diop, O. M.; Livingston, P. O.; Bay, S.; Leclerc, C.,
A fully synthetic therapeutic vaccine candidate targeting carcinoma-associated Tn carbohydrate
antigen induces tumor-specific antibodies in nonhuman primates. Cancer Research 2004, 64
(14), 4987-4994; (c) Lo-Man, R.; Vichier-Guerre, S.; Bay, S.; Dériaud, E.; Cantacuzène, D.;
Leclerc, C., Anti-tumor immunity provided by a synthetic multiple antigenic glycopeptide
displaying a tri-Tn glycotope. The Journal of Immunology 2001, 166 (4), 2849-2854.
32.
Geyer, H.; Wuhrer, M.; Kurokawa, T.; Geyer, R., Characterization of keyhole
limpet hemocyanin (KLH) glycans sharing a carbohydrate epitope with Schistosoma mansoni
glycoconjugates. Micron 2004, 35 (1–2), 105-106.
33.
Yin, Z.; Nguyen, H. G.; Chowdhury, S.; Bentley, P.; Bruckman, M. A.;
Miermont, A.; Gildersleeve, J. C.; Wang, Q.; Huang, X., Tobacco mosaic virus as a new carrier
for tumor associated carbohydrate antigens. Bioconjugate Chemistry 2012, 23 (8), 1694-1703.
34.
Culver, J. N., Tobacco mosaic virus assembly and disassembly: Determinants in
pathogenicity and resistance. Annual Review of Phytopathology 2002, 40 (1), 287-308.

223

35.
Yin, Z.; Comellas-Aragones, M.; Chowdhury, S.; Bentley, P.; Kaczanowska, K.;
BenMohamed, L.; Gildersleeve, J. C.; Finn, M. G.; Huang, X., Boosting immunity to small
tumor-associated carbohydrates with bacteriophage Qβ capsids. ACS Chemical Biology 2013, 8
(6), 1253-1262.
36.
Yin, Z.; Chowdhury, S.; McKay, C.; Baniel, C.; Wright, W. S.; Bentley, P.;
Kaczanowska, K.; Gildersleeve, J. C.; Finn, M. G.; BenMohamed, L.; Huang, X., Significant
impact of immunogen design on the diversity of antibodies generated by carbohydrate-based
anticancer vaccine. ACS Chemical Biology 2015, 10 (10), 2364-2372.
37.
Jegerlehner, A.; Wiesel, M.; Dietmeier, K.; Zabel, F.; Gatto, D.; Saudan, P.;
Bachmann, M. F., Carrier induced epitopic suppression of antibody responses induced by viruslike particles is a dynamic phenomenon caused by carrier-specific antibodies. Vaccine 2010, 28
(33), 5503-5512.
38.
(a) Schutze, M. P.; Deriaud, E.; Przewlocki, G.; LeClerc, C., Carrier-induced
epitopic suppression is initiated through clonal dominance. The Journal of Immunology 1989,
142 (8), 2635-40; (b) Leclerc, C.; Schutze, M. P.; Deriaud, E.; Przewlocki, G., The in vivo
elimination of CD4+ T cells prevents the induction but not the expression of carrier-induced
epitopic suppression. The Journal of Immunology 1990, 145 (5), 1343-9; (c) Galelli, A.; Charlot,
B., Clonal anergy of memory B cells in epitope-specific regulation. The Journal of Immunology
1990, 145 (8), 2397-405.
39.
Evans, M. C., Recent advances in immunoinformatics: application of in silico
tools to drug development. Curr Opin Drug Discov Devel 2008, 11 (2), 233-41.
40.
Haste Andersen, P.; Nielsen, M.; Lund, O., Prediction of residues in
discontinuous B-cell epitopes using protein 3D structures. Protein Science 2006, 15 (11), 25582567.
41.
Carrillo-Tripp, M.; Shepherd, C. M.; Borelli, I. A.; Venkataraman, S.; Lander, G.;
Natarajan, P.; Johnson, J. E.; Brooks, C. L.; Reddy, V. S., VIPERdb2: an enhanced and web API
enabled relational database for structural virology. Nucleic Acids Research 2009, 37 (suppl 1),
D436-D442.
42.
(a) Prasuhn, D. E.; Singh, P.; Strable, E.; Brown, S.; Manchester, M.; Finn, M. G.,
Plasma clearance of bacteriophage Qβ particles as a function of surface charge. Journal of the
American Chemical Society 2008, 130 (4), 1328-1334; (b) Udit, A. K.; Everett, C.; Gale, A. J.;
Reiber Kyle, J.; Ozkan, M.; Finn, M. G., Heparin antagonism by polyvalent display of cationic
motifs on virus-like particles. ChemBioChem 2009, 10 (3), 503-510.
43.
Hovlid, M. L. The chemical and genetic engineering of Qβ virus-like particles for
cell targeting and delivery. The Scripps Research Institute, La Jolla,, 2014.

224

44.
Jessen, B.; Faller, S.; Krempl, C. D.; Ehl, S., Major histocompatibility complexdependent cytotoxic T lymphocyte repertoire and functional avidity contribute to strain-specific
disease susceptibility after murine respiratory syncytial virus infection. Journal of Virology
2011, 85 (19), 10135-10143.
45.
Plevka, P.; Tars, K.; Liljas, L., Structure and stability of icosahedral particles of a
covalent coat protein dimer of bacteriophage MS2. Protein Science : A Publication of the
Protein Society 2009, 18 (8), 1653-1661.
46.
Link, A.; Zabel, F.; Schnetzler, Y.; Titz, A.; Brombacher, F.; Bachmann, M. F.,
Innate immunity mediates follicular transport of particulate but not soluble protein antigen. The
Journal of Immunology 2012, 188 (8), 3724-3733.
47.
Craig, D. B.; Dombkowski, A. A., Disulfide by Design 2.0: a web-based tool for
disulfide engineering in proteins. BMC Bioinformatics 2013, 14 (1), 346.
48.
(a) Da Ren, H. S. G., Paul Raimville, Tom Wheat, Reb J. Russell and Jeff R.
Mazzeo Mass spectrometry quantification of protein mixtures; Water Corperation: Milford, MA,
USA, 2004; (b) Wright, T. H.; Bower, B. J.; Chalker, J. M.; Bernardes, G. J. L.; Wiewiora, R.;
Ng, W.-L.; Raj, R.; Faulkner, S.; Vallée, M. R. J.; Phanumartwiwath, A.; Coleman, O. D.;
Thézénas, M.-L.; Khan, M.; Galan, S. R. G.; Lercher, L.; Schombs, M. W.; Gerstberger, S.;
Palm-Espling, M. E.; Baldwin, A. J.; Kessler, B. M.; Claridge, T. D. W.; Mohammed, S.; Davis,
B. G., Posttranslational mutagenesis: A chemical strategy for exploring protein side-chain
diversity. Science 2016.
49.
Sungsuwan, S.; Yin, Z.; Huang, X., Lipopeptide-coated iron oxide nanoparticles
as potential glycoconjugate-based synthetic anticancer vaccines. ACS Applied Materials &
Interfaces 2015, 7 (31), 17535-17544.
50.
Brown, S. D. Bacteriophage Qβ: A versatile platform for nanoengineering The
Scripps Research Institute, La Jolla,, 2010.
51.
Sedlik, C.; Heitzmann, A.; Viel, S.; Ait Sarkouh, R.; Batisse, C.; Schmidt, F.; De
La Rochere, P.; Amzallag, N.; Osinaga, E.; Oppezzo, P.; Pritsch, O.; Sastre-Garau, X.; Hubert,
P.; Amigorena, S.; Piaggio, E., Effective antitumor therapy based on a novel antibody-drug
conjugate targeting the Tn carbohydrate antigen. OncoImmunology 2016, 5 (7), e1171434.
52.
(a) Laubreton, D.; Bay, S.; Sedlik, C.; Artaud, C.; Ganneau, C.; Dériaud, E.; Viel,
S.; Puaux, A.-L.; Amigorena, S.; Gérard, C.; Lo-Man, R.; Leclerc, C., The fully synthetic MAGTn3 therapeutic vaccine containing the tetanus toxoid-derived TT830-844 universal epitope
provides anti-tumor immunity. Cancer Immunology, Immunotherapy 2016, 65 (3), 315-325; (b)
Hubert, P.; Heitzmann, A.; Viel, S.; Nicolas, A.; Sastre-Garau, X.; Oppezzo, P.; Pritsch, O.;
Osinaga, E.; Amigorena, S., Antibody-dependent cell cytotoxicity synapses form in mice during
tumor-specific antibody immunotherapy. Cancer Research 2011, 71 (15), 5134-5143.

225

53.
(a) Lo-Man, R.; Bay, S.; Vichier-Guerre, S.; Dériaud, E.; Cantacuzène, D.;
Leclerc, C., A fully synthetic immunogen carrying a carcinoma-associated carbohydrate for
active specific immunotherapy. Cancer Research 1999, 59 (7), 1520-1524; (b) Posey, Avery D.,
Jr.; Schwab, Robert D.; Boesteanu, Alina C.; Steentoft, C.; Mandel, U.; Engels, B.; Stone,
Jennifer D.; Madsen, Thomas D.; Schreiber, K.; Haines, Kathleen M.; Cogdill, Alexandria P.;
Chen, Taylor J.; Song, D.; Scholler, J.; Kranz, David M.; Feldman, Michael D.; Young, R.;
Keith, B.; Schreiber, H.; Clausen, H.; Johnson, Laura A.; June, Carl H., Engineered CAR T cells
targeting the cancer-associated Tn-glycoform of the membrane mucin MUC1 control
adenocarcinoma. Immunity 44 (6), 1444-1454.
54.
Tseng, Y.-S.; Agbandje-Mckenna, M., Mapping the AAV capsid host antibody
response toward the development of second generation gene delivery vectors. Frontiers in
Immunology 2014, 5 (9).
55.
(a) Sgroi, D.; Varki, A.; Braesch-Andersen, S.; Stamenkovic, I., CD22, a B cellspecific immunoglobulin superfamily member, is a sialic acid-binding lectin. Journal of
Biological Chemistry 1993, 268 (10), 7011-7018; (b) Crocker, P. R.; Mucklow, S.; Bouckson,
V.; McWilliam, A.; Willis, A. C.; Gordon, S.; Milon, G.; Kelm, S.; Bradfield, P., Sialoadhesin, a
macrophage sialic acid binding receptor for haemopoietic cells with 17 immunoglobulin-like
domains. The EMBO Journal 1994, 13 (19), 4490-4503.
56.
(a) Macauley, M. S.; Crocker, P. R.; Paulson, J. C., Siglec-mediated regulation of
immune cell function in disease. Nature Reviews Immunology 2014, 14 (10), 653-666; (b) Poe, J.
C.; Tedder, T. F., CD22 and Siglec-G in B cell function and tolerance. Trends in Immunology
2012, 33 (8), 413-420; (c) Courtney, A. H.; Puffer, E. B.; Pontrello, J. K.; Yang, Z.-Q.;
Kiessling, L. L., Sialylated multivalent antigens engage CD22 in trans and inhibit B cell
activation. Proceedings of the National Academy of Sciences 2009, 106 (8), 2500-2505; (d)
Macauley, M. S.; Pfrengle, F.; Rademacher, C.; Nycholat, C. M.; Gale, A. J.; von Drygalski, A.;
Paulson, J. C., Antigenic liposomes displaying CD22 ligands induce antigen-specific B cell
apoptosis. The Journal of Clinical Investigation 2013, 123 (7), 3074-3083.
57.
Duong, B. H.; Tian, H.; Ota, T.; Completo, G.; Han, S.; Vela, J. L.; Ota, M.;
Kubitz, M.; Bovin, N.; Paulson, J. C.; Nemazee, D., Decoration of T-independent antigen with
ligands for CD22 and Siglec-G can suppress immunity and induce B cell tolerance in vivo. The
Journal of Experimental Medicine 2010, 207 (1), 173-187.
58.
(a) Blixt, O.; Paulson, J. C., Biocatalytic preparation of N-glycolylneuraminic
acid, deaminoneuraminic acid (KDN) and 9-azido-9-deoxysialic acid oligosaccharides.
Advanced Synthesis & Catalysis 2003, 345 (6-7), 687-690; (b) Collins, B. E.; Blixt, O.; Han, S.;
Duong, B.; Li, H.; Nathan, J. K.; Bovin, N.; Paulson, J. C., High-affinity ligand probes of CD22
overcome the threshold set by cis ligands to allow for binding, endocytosis, and killing of B
cells. The Journal of Immunology 2006, 177 (5), 2994-3003.
59.
Kaltgrad, E.; O'Reilly, M. K.; Liao, L.; Han, S.; Paulson, J. C.; Finn, M. G., Onvirus construction of polyvalent glycan ligands for cell-surface receptors. Journal of the
American Chemical Society 2008, 130 (14), 4578-4579.

226

60.
Matsumoto, Y.; Zhang, Q.; Akita, K.; Nakada, H.; Hamamura, K.; Tokuda, N.;
Tsuchida, A.; Matsubara, T.; Hori, T.; Okajima, T.; Furukawa, K.; Urano, T.; Furukawa, K., ppGalNAc-T13 induces high metastatic potential of murine Lewis lung cancer by generating
trimeric Tn antigen. Biochemical and Biophysical Research Communications 2012, 419 (1), 713.
61.
(a) Hsia, Y.; Bale, J. B.; Gonen, S.; Shi, D.; Sheffler, W.; Fong, K. K.;
Nattermann, U.; Xu, C.; Huang, P.-S.; Ravichandran, R.; Yi, S.; Davis, T. N.; Gonen, T.; King,
N. P.; Baker, D., Design of a hyperstable 60-subunit protein icosahedron. Nature 2016, 535
(7610), 136-139; (b) Bale, J. B.; Gonen, S.; Liu, Y.; Sheffler, W.; Ellis, D.; Thomas, C.; Cascio,
D.; Yeates, T. O.; Gonen, T.; King, N. P.; Baker, D., Accurate design of megadalton-scale twocomponent icosahedral protein complexes. Science 2016, 353 (6297), 389-394; (c) Zhang, L.;
Lua, L. H. L.; Middelberg, A. P. J.; Sun, Y.; Connors, N. K., Biomolecular engineering of viruslike particles aided by computational chemistry methods. Chemical Society Reviews 2015, 44
(23), 8608-8618.
62.
Asensio, M. A.; Morella, N. M.; Jakobson, C. M.; Hartman, E. C.; Glasgow, J. E.;
Sankaran, B.; Zwart, P. H.; Tullman-Ercek, D., A selection for assembly reveals that a single
amino acid mutant of the bacteriophage MS2 coat protein forms a smaller virus-like particle.
Nano Letters 2016, 16 (9), 5944-5950.
63.
Luthe, D. S., A simple technique for the preparation and storage of sucrose
gradients. Analytical Biochemistry 1983, 135 (1), 230-232.
64.
Ludek, O. R.; Gu, W.; Gildersleeve, J. C., Activation of glycosyl
trichloroacetimidates with perchloric acid on silica (HClO4–SiO2) provides enhanced αselectivity. Carbohydrate Research 2010, 345 (14), 2074-2078.
65.
Mukai, S.; Flematti, G. R.; Byrne, L. T.; Besant, P. G.; Attwood, P. V.; Piggott,
M. J., Stable triazolylphosphonate analogues of phosphohistidine. Amino Acids 2012, 43 (2),
857-874.
66.
Miermont, A.; Barnhill, H.; Strable, E.; Lu, X.; Wall, K. A.; Wang, Q.; Finn, M.
G.; Huang, X., Cowpea mosaic virus capsid: A promising carrier for the development of
carbohydrate based antitumor vaccines. Chemistry – A European Journal 2008, 14 (16), 49394947.

227