PHENOTYPIC CHARACTERIZATION OF ALLELIC VARIANTS OF THE
MECHANISTIC TARGET OF RAPAMYCIN (mTOR)
By
Joy Gary

A DISSERTATION
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of
Pathobiology - Doctor of Philosophy
2015

ABSTRACT
PHENOTYPIC CHARACTERIZATION OF ALLELIC VARIANTS OF THE
MECHANISTIC TARGET OF RAPAMYCIN (mTOR)
By
Joy Gary
mTOR is a serine/threonine kinase at the hub of multiple signaling pathways, with roles
in proliferation, translation, and growth. The PI3K/AKT/mTOR pathway is frequently
hyperactivated in cancers and can be targeted pharmacologically. To better understand
the role of mTOR in cancer treatment and in response to cell stressors, mouse models
of decreased mTOR and of a single nucleotide polymorphism (SNP) in Mtor were
evaluated. Specifically, mice with T-cell-specific, constitutively-active AKT (Lck-MyrAkt)
that develop spontaneous thymic lymphomas were crossed to mice with genetically
reduced mTOR expression (knock down, KD). Genetic mTOR reduction was associated
with prolonged survival (24 weeks in KD mice versus 14 weeks in WT mice), though
both eventually developed pre-T lymphoblastic leukemia/lymphoma (pre-T LBL).
Transcriptional profiling of the murine pre-T LBL revealed that mTOR KD was
associated with decreased expression of Cdk6, a critical proliferative control node in Tcell development and oncogenic transformation. The combination of a mTOR inhibitor
(rapamycin) and a CDK4/6 inhibitor (PD-0332991, palbociclib) cooperatively decreased
viability and signaling downstream of drug targets in murine thymic lymphoma cells and
human T-cell acute lymphoblastic leukemia/lymphoma (T-ALL/LBL) cell lines. In
addition, the role of mTOR in response to cell stressors was examined in the context of
inflammatory, genotoxic, and oncogenic stress. In this study, a rare SNP in Mtor
(C1977T, leading to the amino acid substitution R628C), found in BALB/c mice, was

linked to decreased DNA damage response (DDR) through gene expression profiling in
an inflammatory environment. Mice with the SNP (628C KI) had significantly decreased
survival post total body irradiation (TBI) compared to WT and heterozygous mice.
Mouse embryonic fibroblasts (MEFs) and bone marrow from 628C KI mice were more
sensitive to DNA damage and the DNA damage proteins FANCD2 and ATM were
decreased in KI MEFs. Downstream targets of mTOR, most notably those
phosphorylated by mTORC2, were also decreased in KI MEFs, especially the target
PKCα. Proliferation was decreased by irradiation in WT MEFs, and was minimally
affected by irradiation in KI MEFs. KI mice exposed to fractionated irradiation over
several weeks developed thymic lymphomas more rapidly and had decreased survival
compared to WT mice. Finally, to evaluate oncogenic stress, keratinocytes from KI
mice were Ras-transformed and grafted onto nude mice, resulting in a higher rate of
papilloma development than seen with keratinocytes from WT mice. The mTOR KD
mouse model confirmed the importance of mTOR in T-cell leukemia/lymphoma, while
the KI model highlighted the role of mTOR in response to cell stressors that put
selective pressure on cancer cells. These findings emphasize the continued importance
of research into therapies targeting mTOR and mTOR’s role in cancer progression.

Copyright by
THE UNITED STATES GOVERNMENT
2015

This work is dedicated to the many people who supported me through the process of
graduate school, including the members of the Mock laboratory, the Comparative
Molecular Pathology laboratory and fellows, the Sally Rosen Kaplan Fellowship, the
Pathobiology and Diagnostic Investigation Department at MSU, my loving husband, and
my dear family. Thank you for your support and for believing in me.

v

ACKNOWLEDGEMENTS

Many thanks to the current and past members of the Mock Laboratory, the Laboratory
of Cancer Biology and Genetics, and the Comparative Biomedical Scientist Training
program (NCI) for support and advice, and to my graduate committee: Dr. Matti Kiupel
(MSU major advisor), Dr. Beverly Mock (NCI major advisor), Dr. Joshua Webster, Dr.
Vilma Yuzbasiyan-Gurkan, and Dr. Jennifer Thomas, as well as my program mentor Dr.
Mark Simpson. Thanks also to our collaborator, Joseph Testa, at Fox Chase Cancer
Center. Much gratitude to the many who offered suggestions and advice during
experimental design and manuscript preparation, including Doug Lowy, Peter Aplan,
James Mitchell, Urbain Weyemi, Andre Nussenzweig, Elsa Callen Moreu, Yves
Pommier, Alexander Kovalchuk, Michelle Herrmann, Jinqui Chen, and Remy Bosselut.
Also thanks to the above for their willingness to share insights, reagents, and technical
expertise from their laboratories. We also thank Maudeline Etienne, Dena Tran, Zaw
Phyo, Solomon Lynch, Kenneth Felsenstein, and Ben Gamache for insights and
assistance with these studies. J.G. is a fellow in the NIH Comparative Biomedical
Scientist Training Program supported by the National Cancer Institute in partnership
with Michigan State University. This work was supported by the Intramural Research
Program of the National Institutes of Health, National Cancer Institute, Center for
Cancer Research. The contents of this publication do not necessarily reflect the views
or policies of the Department of Health and Human Services, nor does the mention of
trade names, commercial products, or organizations imply endorsement by the U.S.
Government.

vi

TABLE OF CONTENTS

LIST OF TABLES ………………………………………………………….………….. x
LIST OF FIGURES …………………………………………………………………… xi
KEY TO ABBREVIATIONS ………….……………………………………….…..... xvi
CHAPTER 1: Introduction ……………………………………………………….….... 1
mTOR: The signaling pathway, structure, and roles in the normal cell ..… 1
mTOR in cancer.……………………………………………………………….. 4
mTOR mutations…………………………………………….………….……… 7
The BALB/c allele of mTOR is a susceptibility gene for
plasmacytoma formation……………………………………………………… 7
Project goals ……..………………………………………………………...… 12
Hypotheses………………………………………………………………..….. 13
CHAPTER 2: General Methods……………………………………….…………..... 14
Mice ……………………………………………………………………………. 14
Collection of cells and tissues ………………………………..…………….. 14
Flow cytometry and protein analysis ………………………………………. 15
Genotyping ………………………………………………….……….…….… 18
Microarray and RT-PCR ………………………………………………,….… 18
Glycolysis analysis …………………………………………………….…….. 19
Statistical analysis ………………………………………………………...…. 20
CHAPTER 3: Constitutive mTOR inhibition in mouse thymic pre-T LBL identifies Cdk6
as a target for combination treatment of T-ALL/LBL……………………………… 21
Abstract ……………………………………………………………………..… 22
Introduction ………………………………………………………………...…. 22
Methods ……………………………………………………………………….. 23
Mice ……………………………………………………………………. 23
Flow cytometry and protein analysis …………………………….…. 24
Pre-T LBL clonality …………………………………..………..……... 25
Pre-T LBL cell culture and fluorescence in situ
hybridization (FISH) ………………………………….…………….… 26
Microarray and RT-PCR ……………………..……………….…...… 26
Drug treatment of murine pre-T LBL cells …..…………….……..... 27
Matrix dose response screen in human T-ALL/LBL cell lines …… 27
Results………………………………………………………………..…….…. 28
Pre-tumor thymocytes from mTOR KD mice have decreased
mTOR activity…………………………………………..……….…..… 28
Genetic and pharmacologic mTOR inhibition prolonged survival
of Lck-Akt mice ……………………………………………………….. 32
vii

CDK6 is decreased in KD thymic pre-T LBL …………………...… 39
Murine pre-T LBL is sensitive to inhibition of mTOR and/or
CDK4/6 …………………………………………………………...…... 42
The combination of CDK4/6 and mTOR inhibition is cooperative
in human T-ALL/LBL cell lines ……………………………………… 46
Discussion …………………………………………………………………..… 53
CHAPTER 4: A rare, naturally occurring SNP in Mtor (C1977T) is associated with
increased sensitivity to stress at the cellular and organismal level …………….. 57
Introduction …………………………………………………………………... 57
Materials and Methods ……………………………………………………… 59
Mice…….……………………………………………………………… 59
Microarray and RT-PCR …………………………………………….. 60
Cell culture ………………………………………………………….… 61
Comet Assay ……………………………………………………….… 63
Immunoblotting, immunohistochemistry, and
immunofluorescence ………………………………………………… 63
Flow cytometry and proliferation ……………………………….…… 65
Results ………………………………………………………………………… 66
Characterization of 628C KI mice ………………………………..… 66
Predicted effects of 628C allele ……………………………….….… 67
Transcriptional differences in cells exposed to inflammatory
stress………………………………………………………………..…. 68
Phenotypic changes associated with DNA damage …………..…. 72
Assessing DNA damage by Comet Assay in bone marrow treated
ex vivo ………………………………………………………………… 75
Assessing DNA damage by Comet Assay and micronuclei in mouse
embryonic fibroblasts……………………………………………….… 77
Assessing DNA damage by colony formation in transformed
MEFs ………………………………………………………………….. 79
DNA damage response proteins following irradiation in MEFs..… 81
Downstream targets of mTOR following irradiation in MEFs ….… 81
Proliferation …………………………………………………………… 85
Irradiation-induced thymic lymphoma ……………………………… 86
Ras-transformed 628C KI keratinocytes form larger papillomas more
rapidly than WT keratinocytes ……………………………………… 87
Discussion…………………………………………………………………….. 89
CHAPTER 5: Synthesis and Conclusions ………………………………………… 93
APPENDICES ………………………………………………………………………… 98
APPENDIX A: Additional results from mTOR WT and 628C KI mice that are not
significantly different by genotype ..………………………………………… 99
APPENDIX B: Levels of three miRNAs are differentially expressed between WT
and 628C KI B220+ splenocytes by Nanostring; the magnitude of the differences
by Real Time PCR were not significant ………………………………….. 102
viii

APPENDIX C: Glycolysis is similar in primary and transformed mTOR WT and
628C KI, and mTOR WT and KD mouse embryonic fibroblasts ….…… 104
APPENDIX D: Top Molecular and Cellular Functions identified by Ingenuity
Pathway Analysis in genes from bone marrow of pristane-treated
animals ………………………………………………………………………. 106
APPENDIX E: Apoptosis and cell cycle in WT and 628C KI MEFs 3 hours and 18
hours post irradiation ……………………………….……………………… 114
REFERENCES ……………………………………………………………..…….… 116

ix

LIST OF TABLES

Table 1:

Antibodies used in this project, including company and
catalog number ………………………………………………….….…… 17

Table 2:

Top enriched molecular and cellular function networks in bone marrow
from pristane-treated animals identified by Ingenuity Pathway
Analysis ………………………………………………………….………. 70

Table 3:

Differentially expressed genes associated with DNA damage response (zscore = 0.864, p-value of overlap = 0.002) identified by Ingenuity Pathway
Analysis in bone marrow from pristane-treated mice ……………….. 71

Table 4:

Cell Morphology-associated top molecular functions as identified by Ingenuity
Pathway Analysis ………………………………………………….…… 105

Table 5:

Small Molecule Biochemistry-associated top molecular functions as identified
by Ingenuity Pathway Analysis ………………………………….…….. 107

Table 6:

DNA Replication, Recombination, and Repair-associated top molecular
functions as identified by Ingenuity Pathway Analysis ……….….… 109

Table 7:

Molecular Transport-associated top molecular functions as identified by
Ingenuity Pathway Analysis …………………………………………… 112

Table 8:

Gene Expression-associated top molecular functions as identified by
Ingenuity Pathway Analysis ..…………………………………….…… 113

x

LIST OF FIGURES

Figure 1:

Simplified diagram of the mTOR pathway showing the
components of mTORC1 and 2, mTOR inhibitors, and the main
downstream mTOR targets …………..………………..…….……..... 2

Figure 2:

Schematic of the mTOR protein with important domains
highlighted ………..………………………………………….……..….. 4

Figure 3:

Photomicrographs of a mesenteric oil granuloma (A,B) and a
mesenteric plasma cell tumor (C,D) from pristane-primed mice …. 9

Figure 4:

Diagram illustrating the introduction of the SNP at nucleotide 1977 in
Mtor, originally found in the BALB/c and NZB mice, onto a B6;129
background through homologous recombination, and the resulting amino
acid substitution at 628 ……..………………………………..……….. 11

Figure 5:

Schematic summarizing the characteristics of the strains
bred to produce the Lck-Akt/mTOR WT (WT) and Lck-Akt/mTOR
KD (KD) mice ………………………..………………………….…...… 24

Figure 6A: Digital bands from a capillary-based immunoassay assessing levels of
downstream targets of mTOR in pre-tumor thymocytes (4 weeks) in two
representative mice …………..………………………….…………… 29
Figure 6B: Chemiluminescence peaks from a capillary-based immunoassay assessing
levels of downstream targets of mTOR in pre-tumor thymocytes (4 weeks)
in two representative mice …..….……………………….…………… 30
Figure 7:

Flow cytometry scatter plots for thymic CD4 and CD8 labeling (A),
with bar graphs of absolute numbers (B) and percents (C) of each
cell type …….…..…………………………………………………….… 31

Figure 8:

Flow cytometry scatter plots (A) and bar graphs of absolute numbers (B)
and percentages of cells (C) for CD44 and CD25-labeled, lineagedepleted T- lymphocytes from pre-tumor thymi …………..……..… 32

Figure 9:

Photomicrographs of thymic lymphomas from WT and KD mice… 33

Figure 10:

Survival curve for Lck-Akt/mTOR WT and Lck-Akt/mTOR KD
mice ….………………………………………….……………………… 34

xi

Figure 11A: Digital bands from a capillary-based immunoassay assessing levels of
downstream targets of mTOR in pre-T LBL from two representative
mice …..………………………………………………………………… 34
Figure 11B: Chemiluminescence peaks from a capillary-based immunoassay
assessing levels of downstream targets of mTOR in pre-T LBL from two
representative mice .………..………………………………………… 35
Figure 12:

Flow cytometry scatter plots of CD4 and CD8-labeled populations in
thymic pre-T LBL from WT and KD mice …………...……………… 36

Figure 13:

Clonality of pre-T LBL assessed by nested PCR for T- cell receptor
rearrangement ……..…………………………………………………. 36

Figure 14:

TCRα/Myc translocations in WT and KD mice …………..…..……. 37

Figure 15:

Proportions of TCRα/Myc translocations and MYC protein levels in WT
and KD pre-T LBL …………….………………………………….…… 38

Figure 16:

Survival curve from Lck-Akt mice treated with a mTOR inhibitor
(everolimus) ……………………………………………..…………..… 39

Figure 17:

Transcript and protein levels of CDK6 and protein expression of other
cell cycle regulators in WT and KD thymic pre-T LBL ……..……… 41

Figure 18:

Protein and transcript levels ofCdkn2a (p16) in WT (n=4) and KD
(n=3) tumors ………………………….…..…………………….……... 42

Figure 19:

Levels of CDKN1A (p21) and cyclin D1 protein in a representative KD
tumor compared to a WT tumor ….….………………………....……. 42

Figure 20:

Viability and CDK6 protein levels from WT and KD thymic pre-T LBL
cells treated with rapamycin ……..…………………………………… 44

Figure 21:

Viability of WT and KD pre-T LBL cells with increasing doses of a
CDK4/6 inhibitor (PD-0332991) ……..…………………………….… 44

Figure 22:

Cell cycle and apoptosis were analyzed post treatment with a
mTORi and a CDK4/6i in mTOR WT pre-T LBL cells …….….…… 45

Figure 23:

Percent viability of WT thymic pre-T LBL cells treated with a mTORi,
a CDK4/6i, and a combination of the two inhibitors …….…….…… 46

Figure 24:

Activity of the combination of a CDK4/6 inhibitor (PD-0332991) and
a mTOR inhibitor (rapamycin) evaluated in human T-ALL/LBL cell
lines ……………….……….…………………………………………… 48
xii

Figure 25:

Combination index of T-ALL/LBL cell lines treated with a mTORi
(rapamycin), a CDK4/6i (PD-0332991), and a combination of the two
agents …………………………………………………….…………… 49

Figure 26:

Cell cycle proteins from six T-ALL/LBL cell lines treated with
PD-0332991, rapamycin, and the combination of the two agents .. 50

Figure 27:

Downstream targets of mTOR, phospho-ribosomal S6S240/244 and
phospho-AKTS473 were evaluated in T-ALL/LBL cell lines treated with
1 nM rapamycin, 500 nM PD-0332991, and the combination of the two
agents ……………………………………………………….………….. 51

Figure 28:

Four representative T-ALL/LBL cells lines treated with increasing doses
of a dual mTOR inhibitor, PP242, or a mTORC1 inhibitor, rapamycin, in
combination with increasing doses of a CDK4/6 inhibitor (PD-0332991)
for 48 hours …………………………………..……………………...… 52

Figure 29:

Immunoblot analysis of one T-ALL/LBL cell line (TIB-153), evaluating
phospho-RB, RB, CDK6, cyclin D3, and phospho-AKTS473 after
treatment with the combination of PP242 (1.25 µM) and the CDK4/6
inhibitor (500 nM), as well as the combination of rapamycin (1 nM) and
the CDK4/6i (500nM) ……………………………………….………... 53

Figure 30:

Principal components analyses of genes from tissues of the non-pristanetreated animals (A), pristane-treated animals (B), and bone marrow of
pristane-treated animals (C); the genes are most different in the pristanetreated bone marrow ……………...………………………………….. 69

Figure 31:

Fancd2, Fancc, and Fancg transcripts are lower in bone marrow from
pristane-treated KI mice by RT-PCR in samples from microarray analysis,
but not in additional animals …..……………….………………….… 72

Figure 32:

Kaplan-Meier survival curve for mTOR WT, heterozygous (Het), and
628C KI mice treated with 8 Gy gamma irradiation …..…………… 73

Figure 33:

Severe bone marrow depletion (pancytopenia) in irradiated mice
collected 18 days post 8 Gy total body irradiation (A), in comparison
to untreated, aged-matched mice (B) …..…………………………... 74

Figure 34:

Cleaved caspase 3 labeling in WT and KI bone marrow and small
intestines, with quantification of labeling by color deconvolution (%
positive pixels) ….………..………………………………………….… 75

Figure 35A: Representative comets from untreated and irradiated (6 Gy) WT and
628C KI bone marrow cells 2.5 hours post irradiation …………….. 76
xiii

Figure 35B: Comparison of the average tail moment from WT and KI irradiated bone
marrow cells ………………………………………….……………...… 77
Figure 36:

Representative comets from untreated and treated WT and KI MEFs at 5
minutes and one hour after 4 Gy gamma irradiation, and comparison of
average tail moment from WT and KI MEFs at these time points .. 78

Figure 37:

Percent cells with micronuclei for WT and KI MEFs irradiated at 4 Gy
and collected at time points post irradiation …………………..…… 79

Figure 38:

Colony formation and surviving fraction of transformed WT and KI MEFs
10 days after 2, 4, 6, and 8 Gy gamma irradiation ………………… 80

Figure 39:

Immunoblot of DDR proteins at 30 minutes, 1 hour, 3 hours, and
6 hours post 4 Gy gamma irradiation in mTOR WT and 628C KI
primary MEFs …..……………………………………………………… 81

Figure 40: Downstream targets of mTORC1 and mTORC2 at time points post 4 Gy
irradiation in WT and 628C KI MEFs ……..………………………… 83
Figure 41:

PKCα labeling in untreated and 4 Gy-irradiated WT and 628C KI MEFs
6 hours post irradiation ….……..…………………………………..… 84

Figure 42:

Labeling for F-actin in untreated WT and 628C KI MEFs, and in WT
and KI MEFs 6 hours post 4 Gy irradiation ………………………… 84

Figure 43:

Proliferation based on percent confluence in untreated and irradiated
WT and 628C KI MEFs …………………………………………….… 85

Figure 44:

Survival curve of WT and 628C KI mice exposed to fractionated
doses of 1.75 Gy, once weekly for 4 weeks, that developed thymic
lymphomas ……………………………………………………………. 87

Figure 45:

Papilloma volume from WT and 628C KI Ras-transformed keratinocytes
grafted onto nude mice ………………………………..……………… 88

Figure 46:

Immunoblots of FANCD2 and phospho-PKCα (PRKCa) in WT and
628C KI keratinocytes, both untreated (Un) and Ras-transformed
(ras) …………………………………………………………………….. 88

Figure 47:

Polymorphonuclear cells (PMNs) and lymphocytes from untreated (WT
and KI) and pristane-treated (designated WTP and KIP) mTOR WT
and 628C KI mice by CBC …………..………………………….…… 99

xiv

Figure 48:

Average protein expression levels by quantification of western blot
bands or by size-based, automated, capillary immunoassay system
(peak area), showing levels of downstream targets of mTOR ..… 101

Figure 49:

Spot intensity by Nanostring array for miR30a, miR101, and mir423-5P,
and transcript levels by RT-PCR for each miR in WT and KI bone
marrow cells …………….……………………………………….…… 103

Figure 50:

Curves representing glycolytic function in SV40-transformed and primary
mTOR WT, KI, and KD mouse embryonic fibroblasts …………… 105

Figure 51:

Percent cells in early and late apoptosis 3 hours and 18 hours post
4 Gy irradiation in WT and KI MEFs by flow cytometry ..……...… 114

Figure 52:

Cell cycle by flow cytometry in WT and KI MEFs 3 hours and 18
hours post 4 Gy irradiation …….……………..…………………..… 115

xv

KEY TO ABBREVIATIONS

4E-BP1 – Eukaryotic translation initiation factor 4E-binding protein 1
AKT – V-Akt murine thymoma viral oncogene homolog
ATM – Ataxia telangiectasia mutated
CDK4 - Cyclin-dependent kinase 4
CDK6 - Cyclin-dependent kinase 6
CDKN1A (p21) – Cyclin-dependent kinase inhibitor 1A
CDKN1B (p27) – Cyclin-dependent kinase inhibitor 1B
CDKN2A (p16) – Cyclin-dependent kinase inhibitor 2A
DDR – DNA damage response
DEPTOR – DEP domain TOR-binding protein
DMEM – Dubecco’s modified eagle medium
DNA-PK – DNA-dependent protein kinase
EIF4E – Eukaryotic translation initiation factor 4E
FANCD2 – Fanconi Anemia group D2 protein
FAT – FRAP, ATM, and TRRAP
FBS – Fetal bovine serum
FKBP12 – FKBP-rapamycin-associated protein 12
FRAP – FKBP-rapamycin associated protein
HEAT – Huntington, Elongation factor 3, PR65A, Tor
IMDM – Iscove’s modified debecco’s medium
KD – Knock down

xvi

KI – Knock in
LCK – Lymphocyte-specific protein kinase tyrosine kinase
MEF - Mouse embryonic fibroblast
mSIN1 – Mammalian stress-activated protein kinase interacting protein
MNDAL – Myeloid cell nuclear differentiation antigen-like
MSLT8 – Mammalian lethal with Sec-13 protein 8
mTOR – Mechanistic target of rapamycin
mTORC1 – Mechanistic target of rapamycin complex 1
mTORC2 – Mechanistic target of rapamycin complex 2
PBS – Phosphate buffered saline
PI3K – Phosphatidylinositol 3-Kinase
PKCα – Protein kinase C, alpha
PRAS40 – Proline-rich AKT substrate, 40 kDa
PROTOR – Protein observed with Rictor
PTEN – Phosphatase and tensin homolog
RAFT1 – Rapamycin and FKBP12 target
RAPT1 – Rapamycin target 1
Raptor – Regulatory associated protein of mTOR
RB – Retinoblastoma protein
Rictor – RPTOR independent companion of mTOR, complex 2
RPMI – Roswell Park Memorial Institute medium
P70SK6 (S6K) – Ribosomal protein S6 kinase, 70 kDa
RpS6 (S6) - Ribosomal protein S6

xvii

SGK – Serum- and glucocorticoid-induced kinase
SNP – Single nucleotide polymorphism
TSC1/2 – Tuberous sclerosis complex
TBS – Tris-buffered saline
WT – Wild-type

xviii

CHAPTER 1: Introduction
mTOR: The signaling pathway, structure, and roles in the normal cell
The mechanistic target of rapamycin (mTOR, formerly known as FRAP, RAPT1,
or RAFT1) is a highly-conserved serine/threonine kinase (Brunn, Fadden et al. 1997) in
the PI3K/AKT pathway (Sekulić, Hudson et al. 2000). mTOR is a central hub in the
complex regulation of cell growth and metabolism, which functions by integrating
environmental cues such as growth factors, insulin (Withers, Ouwens et al. 1997),
oxygen, and amino acids (Jewell, Russell et al. 2013). mTOR phosphorylates
downstream targets, initiating changes in transcription, translation, lipogenesis, and
nutrient transport, as well as autophagy, mRNA degradation, and apoptosis [reviewed in
(Hall 2008) and (Laplante and Sabatini 2009)]. Mtor is the mammalian homolog of the
Saccharomyces cerivisiae gene products DDR/Tor1 and DDR/Tor2 (Alarcon, Cardenas
et al. 1996); these yeast Tor proteins were identified as targets of the
immunosuppressive macrolide compound, rapamycin, in an earlier mutation screen
(Cafferkey, Young et al. 1993).
mTOR is active when incorporated in one of two different complexes: mTORC1
or mTORC2. mTORC1 is composed of mTOR, RAPTOR, PRAS40, MLST8 (GβL), and
DEPTOR, while mTORC2 is composed of mTOR, RICTOR, PROTOR, mSIN1, MLST8
(GβL), and DEPTOR [(Loewith, Jacinto et al. 2002), (Jacinto, Loewith et al. 2004)], and
reviewed in [(Roberto Zoncu 2011); Figure 1)]. In both complexes, DEPTOR negatively
regulates mTOR activity (Peterson, Laplante et al. 2009); mTORC1 is also negatively
regulated by the TSC1/TSC2 complex (Garami, Zwartkruis et al. 2003). The most
extensively studied targets of mTORC1 are 4E-BP1 and S6K (Burnett, Barrow et al.
1

1998), which augment translation. When mTORC1 phosphorylates 4E-BP1, it releases
EIF4E, which promotes cap-dependent translation (Richter and Sonenberg 2005); when
mTOR activates S6K, it increases mRNA biogenesis, cap-dependent translation, and
the translation of ribosomal proteins (Ma and Blenis 2009). The main targets for
mTORC2 are AKT, PKCα, and SGK, which are involved in cytoskeleton
rearrangements, proliferation, and cell survival [(Tchevkina and Komelkov 2012)
(Jacinto, Loewith et al. 2004); Figure 1]. mTOR has many other targets, as the mTOR
signaling pathway is extremely complex, with a variety of upstream signals and
regulators and downstream targets and effectors as mapped by Caron et al. (Caron,
Ghosh et al. 2010). Because of this complexity, knowledge about the targets and
functions of mTOR is constantly growing.

Figure 1: Simplified diagram of the mTOR pathway showing the components of
mTORC1 and 2, mTOR inhibitors, and the main downstream mTOR targets. Figure
adapted from (Guertin and Sabatini 2009, Zhang, Readinger et al. 2011).
2

Figure 1 (cont’d). Inhibitory signals are indicated by red lines with cross bars, while
activating signals are shown with green arrows. Proteins represented by green ovals
have been shown to be oncogenes, while those that are red have been shown to be
tumor suppressors. The compounds shown next to the subunits in purple text are
inhibitors that act on each mTOR complex.
mTOR is a large protein composed of 2549 amino acids (289 KDa) that is a
member of the PI3K-related kinase (PIKK) family (Figure 2). The N-terminus of the
protein contains numerous tandem-repeated domains composed of two antiparallel αhelices known as HEAT domains [(for Huntington, Elongation factor 3, PR65/A subunit
of PP2A, and Tor; orange rectangles in Figure 2 (Perry and Kleckner 2003), (Tchevkina
and Komelkov 2012)]. These HEAT domains are sites of protein-protein interaction,
and have not been well characterized in mTOR (Knutson 2010). Other, well
characterized domains of the protein include the FAT domain (FRAP, ATM, TRAPP),
the FRB domain [(FKBP12-rapamycin binding domain, (Tchevkina and Komelkov
2012)], and the PI3K catalytic kinase domain, which is near the C-terminus of the
protein. The kinase and FRB domains have been well studied, because of FKBP12‘s
role in binding rapamycin, which results in inhibition of the kinase function of the protein
[(Chen, Zheng et al. 1995),(Sabatini, Erdjument-Bromage et al. 1994)].

3

Figure 2: Schematic of the mTOR protein with important domains highlighted.
Note that the thin, orange rectangles represent HEAT domains. Also shown is the
amino acid substitution at aa628 produced by a single nucleotide polymorphism that is
referred to throughout the manuscript. Light blue ovals show approximate binding sites
of interacting proteins. Figure adapted from (Laplante and Sabatini 2012).
mTOR in cancer
The PI3K/AKT/mTOR pathway is often deregulated in cancer cells, usually
through Pi3k or Pten mutations, receptor tyrosine kinase activation (Samuels, Wang et
al. 2004, Hollander, Blumenthal et al. 2011), and Akt amplifications [reviewed in
(Altomare and Testa 2005)]. Constitutive PI3K/AKT activation is found in 50% of denovo acute myeloid leukemia samples (Tamburini, Elie et al. 2007), and mTORC1
activation was detected in almost all AML samples tested [(Xu, Thompson et al. 2005),
(Tamburini, Green et al. 2009)]. In prostate cancer, deletions or mutations in the
PI3K/AKT/ mTOR pathway inhibitor, Pten, are common genetic alterations (Ruscetti and
Wu 2013). Elevated levels of phosphorylated downstream targets of mTOR, including
phosphorylated 4E-BP1 and S6, are apparent in many cancers, including mammary
carcinoma, colorectal carcinoma, endometrial cancers, glioblastoma, hepatocellular
carcinoma, pulmonary adenocarcinomas, lymphoma, melanoma, ovarian carcinoma,
prostate carcinomas, and renal cell carcinomas, indicating mTOR activation [reviewed

4

in (Menon and Manning 2009)]. Because of mTOR’s role in integrating growth signals,
which leads to protein translation and cell growth, it is not surprising that it is often
activated in cancer cells.
Dysregulation of the PI3K/AKT/mTOR pathway in cancer has been reported to
have a role in cancer initiation and progression through many of its downstream targets.
In mouse models of prostate cancer with PTEN deletion, mTORC2 activity is required
for both tumor formation and growth (Guertin, Stevens et al. 2009). In human prostate
cancer cells with PTEN deletion, a study using ribosome profile mapping of targets
translationally controlled by mTOR showed the affected cellular processes to be
proliferation, metabolism, protein synthesis, and invasion (Hsieh, Liu et al. 2012). In
multiple cancers, mTOR’s role in inhibiting 4E-BP1, and thus promoting translation,
allows the tumor cells to ramp up cell cycle activators, anti-apoptosis genes, and
ribosome biogenesis, promoting cell growth [reviewed in (Hay and Sonenberg 2004,
Sengupta, Peterson et al. 2010)]; mTOR also regulates HIF1α in response to hypoxia,
which is a major pressure experienced by neoplastic cells (Hudson, Liu et al. 2002). In
addition, mTOR is a major regulator of autophagy, which is the process by which the
cell degrades organelles and proteins in lysosomes to release intracellular nutrients as
an adaptive response to nutrient stress, a strategy utilized by some cancer cells
(Kroemer, Mariño et al. 2010). Finally, mTORC1 activates a protein SREBP1, which is
involved in lipogenesis and the pentose phosphate pathway, which is increased in
tumor cells (Porstmann, Santos et al. 2008). All of these roles of mTOR provide tumor
cells with a growth advantage in the face of nutritional stress and promote the
dysregulated growth that is a hallmark of cancer.

5

Because of its role in tumor growth, inhibition of mTOR has been found to be a
promising treatment for some cancers. The first mTOR inhibitor to be discoved was
rapamycin, which is a macrolide antibiotic originally discovered on Rapa Nui island in
1970. Rapamycin is secreted by the bacterial strain, Streptomyces hygroscopicus as an
anti-fungal mechanism [(Vezina, Kudelski et al. 1975), and reviewed in (Tchevkina and
Komelkov 2012)]. In yeast first, and then in human cells, rapamycin was found to have
anti-proliferative properties, and was immunosuppressive in mammals [(Brown, Albers
et al. 1994), reviewed in (Tchevkina and Komelkov 2012)]. Rapamycin acts by binding
to the protein FKBP12, and inhibiting mTORC1 kinase activity (Chen, Zheng et al.
1995). Through this mechanism, rapamycin and other first generation mTOR inhibitors,
such as everolimus, mostly inhibit mTORC1 and tend to inhibit mTORC2 only after longterm treatment (Sarbassov, Ali et al. 2006). However, when first generation inhibitors
suppress mTORC1 activity, they dysregulate downstream negative feedback
mechanisms, resulting in enhanced PI3K-AKT signaling (Wan, Harkavy et al. 2006).
Newer, second generation mTOR inhibitors, such as PP242, AZD2014, and Torin1,
inhibit both mTOR complexes 1 and 2 by binding to the catalytic site as ATPcompetitive inhibitors [(Thoreen, Kang et al. 2009), (Feldman, Apsel et al. 2009)].
Rapamycin was found to suppress tumor growth in the early eighties (Eng,
Sehgal et al. 1984) and has since been studied as a treatment for a variety of tumors.
mTOR inhibitors are currently approved for renal cell carcinoma, Tuberous Sclerosis
Complex (rare genetic disease leading to formation of multiple neoplasms caused by
mutation in Tsc1/2), pancreatic neuroendocrine tumor, and subependymal giant cell

6

astrocytoma and are being tested in combination with other chemotherapeutic agents
for a variety of cancer types (clincialtrials.gov).
mTOR mutations
A less common mechanism of PI3K/AKT/mTOR dysregulation in cancers is a
mutation in Mtor itself. A total number of 480 Mtor coding mutations are listed in the
COSMIC database [Catalog of the Somatic Mutations In Cancer,
http://cancer.sanger.ac.uk/cancergenome/projects/cosmic/ (Forbes, Bindal et al. 2011)].
Some of these mutations (S2215Y and R2505P) confer hyperactivity to the protein, with
increased phosphorylation of downstream targets (Sato, Nakashima et al. 2010) while
other mutations are nonsense mutations, leading to an early termination of translation.
Additional mutations are missense, leading to a single amino acid substitution, which
can be silent or affect the structure and function of the protein. Single nucleotide
polymorphisms (SNPs) in Mtor in humans have been associated with an increased risk
of death in esophageal cancer patients (Hildebrandt, Yang et al. 2009), and an
increased risk of developing microsatellite instability (MSI)1 in colon tumors (Slattery,
Herrick et al. 2010). However, only a few of the SNPs in Mtor have been characterized,
and the relevance of mutations in Mtor to carcinogenesis is only beginning to be
investigated.
The BALB/c allele of mTOR is a susceptibility gene for plasmacytoma formation
A naturally-occurring SNP in Mtor was discovered by our lab in BALB/c and NZB
mice at an otherwise highly conserved site (C1977T). This SNP was uncovered by
genetic mapping during positional cloning studies of alleles associated with
susceptibility to plasma cell tumor formation (Bliskovsky, Ramsay et al. 2003).

7

BALB/cAnPt and NZB/BlNJ mice are almost uniquely susceptible to mesenteric plasma
cell tumor formation after intraperitoneal (IP) pristane (alkane oil that is a common
component of many mineral oils; 2,6,10,14 tetramethylpentadecane) injections
(priming); 60% of BALB/cAnPt and 30% of NZB/BINJ mice develop these mesenteric
plasma cell tumors when given IP pristane [(Potter and Wiener 1992) Figure 3C,D]. The
tumors form in sites of mixed granulomatous inflammation (Figure 3A,B) after pristane
injections are given at day 0, 60, and 120 [0.5 ml IP, (Potter 1983, Potter and Wiener
1992)]. Mesenteric inflammation, referred to as oil granulomas, are composed of
variable aggregates of macrophages that occasionally contain neutrophils,
multinucleate giant cells, aggregates of lymphocytes and plasma cells, surround
variably-sized clear vacuoles, and are occasionally associated with fibrosis and
mineralization (Figure 3A,B). Tumors arise following a latency period of 200-300 days
[(Morse 1980), (Potter 1983)]. These plasma cell tumors develop as sheets of
neoplastic plasma cells within the granulomas, and can be classified by cellular
morphologies into plasmacytic, plasmablastic, and anaplastic subgroups [(Qi, Zhou et
al. 2007), Figure 3C,D], though the molecular and clinical consequences of each
morphologic subgroup are unclear. The tumors require IL6 to grow and are
accompanied by ascites (Hilbret 1995) and secretion of IgG or IgA antibodies (Potter
and Wiener 1992). Immune system stimulation is also required for tumor formation, as
specific pathogen free mice (SPF) mice do not develop plasma cell tumors [(McIntire
and Princler 1969), (Byrd, McDonald et al. 1991)]. Interestingly, pristane injected into
other locations does not stimulate tumor formation, except for rare subcutaneous
sarcomas (Potter and Wiener 1992).

8

A

B

C

D

Figure 3: Photomicrographs of a mesenteric oil granuloma (A,B) and a mesenteric
plasma cell tumor (C,D) from pristane-primed mice. Images taken at 2X (A,C), 20X
(B,D), and 40X (inset D), Hematoxylin and eosin.
Through genetic linkage studies, our lab determined that 4 susceptibility alleles
are linked with plasma cell tumor formation in BALB/cAnPt and NZB/BINJ mice (Mock,
Krall et al. 1993), including alleles of Cdkn2a [p16; (Zhang, Ramsay et al. 1998, Zhang,
DuBois et al. 2001)], Mtor [(Mock, Hartley et al. 1997, Bliskovsky, Ramsay et al. 2003)],
a new gene named Mndal (Zhang, Kagan et al. 2009), and a remaining allelic variant
which has not been linked to a gene. One of these susceptibility genes, Mtor, was
found to have a polymorphism in susceptible mice at an otherwise highly conserved
region of the gene. Specifically, BALB/cAnPt and NZB/BINJ mice have a rare single
nucleotide polymorphism in Mtor (C1977T) in exon 12, which leads to a single amino
9

acid substitution (cysteine instead of arginine) at aa 628 (R628C). The consequences
of this single amino acid substitution on the structure and function of the protein are
unknown, and became one of our major research questions.
To specifically explore the consequences of the SNP in the BALB/c allele of Mtor,
we created a knock in mouse through homologous recombination with the BALB/c allele
of Mtor (C1977T) on a B6;129 background (as described in (Zhang, Readinger et al.
2011), Figure 4). In the initial construction of these mice, the neomycin cassette
disrupted the transcription of Mtor, leading to significantly reduced levels of mTOR
protein (approximately 70% decrease (Zhang, Readinger et al. 2011)). These mTOR
knockdown mice (KD) are 25% smaller than wild-type (WT) and heterozygous (HET)
littermates; they also have small spleens, smaller cell size, fewer thymic and splenic Tcells, and fewer splenic, lymph node, and bone marrow B220+ B-lymphocytes (Zhang,
Readinger et al. 2011). Protein levels of Raptor and Rictor (components of mTORC1
and mTORC2), as well as downstream phospho-targets of mTOR, such as phosphoS6K, were lower in several tissues from these mice (Zhang, Readinger et al. 2011).
The mTOR KD mice are more susceptible to mortality after inoculation with
Streptococcus pneumoniae, likely due to a decreased ability to form germinal centers in
lymphoid tissues and decreased immunoglobulin somatic hypermutation and class
switch recombination in B-cells, processes required for high affinity antibody responses
(Zhang, Pruitt et al. 2013). Interestingly, mTOR KD mice have been shown to have a
longer life span than mTOR WT mice (Wu, Liu et al. 2013). These mTOR KD mice
provide a unique model of decreased mTOR, as deletion of mTOR is embryonic lethal

10

(Gangloff, Mueller et al. 2004), and can be used as a model for the study of
pharmacologic mTOR inhibition.

Figure 4: Diagram illustrating the introduction of the SNP at nucleotide 1977 in
Mtor, originally found in the BALB/c and NZB mice, onto a B6;129 background
through homologous recombination, and the resulting amino acid substitution at
628.
Unlike the mTOR KD mice, B6;129 mice harboring the introduced Mtor SNP
(628C KI; crossed to cre mice to remove the disrupting neomycin cassette) are
phenotypically normal, with normal levels of mTOR, RICTOR, RAPTOR, and DEPTOR
(Zhang, Readinger et al. 2011). These mice have normal organ size, cell size, B-cell

11

development, splenic and thymic populations, and antibody formation (Zhang,
Readinger et al. 2011).
Because of the role of the SNP in mTOR as a susceptibility allele for plasma cell
tumor formation, we chose to evaluate the function of the altered protein in response to
cell stressors, such as inflammatory, genotoxic, and oncogenic stress, all of which
activate mTOR. Evaluating the function of the 628C variant of mTOR under stress
conditions illustrated the oncogenic nature of the variant and shed light on mTOR’s role
in stress responses.
Project goals
In this project, we utilized two unique mouse models with altered mTOR to better
understand the role of mTOR in cancer development, cancer cell signaling, and the
response to cell stressors likely to be encountered by neoplastic cells. To evaluate the
role of mTOR in cancer development and signaling, we studied the effects of mTOR
knock-down (KD) on the development of AKT-driven thymic leukemias/lymphomas and
on alterations of signaling pathways in these lymphomas. Using the mTOR KD mice as
a model for pharmacologic inhibition of mTOR, we identified this altered signaling as a
possible target for a combination therapy, and treated human T-cell lymphoblastic
leukemia/lymphoma (T-ALL/LBL) cell lines with the combination therapy, revealing a
cooperative combination therapy that may be efficacious in T-ALL/LBL treatment.
In a related project, we also studied the effects of the SNP (C1977T) in Mtor and
the resulting single amino acid substitution (628C) found in BALB/c mice on the function
of the mTOR protein using the 628C KI mice and cells derived from these mice. We
looked at transcriptional changes in tissues from 628C KI mice under inflammatory

12

conditions, and found that multiple DNA damage response (DDR) genes were
downregulated in KI cells. From this finding, we evaluated the response of mice and
cells with mTOR 628C KI to DNA damage through irradiation, and to mTOR WT and
628C KI cells in the face of oncogenic stress. Overall, this unique mouse model allowed
us to explore the effect of the SNP on the protein, and to explore mTOR’s role in the
stress response. Because of mTOR’s role in promoting the growth and maintenance of
cancer cells, a thorough understanding of mTOR signaling and the response of the
cancer cell to pharmacologic mTOR inhibition are important components in the
knowledge necessary to wisely approach targeted therapies.
Hypotheses
Chapter 3: Genetic and pharmacologic inhibition of mTOR will delay tumor growth in
mice with AKT-driven T-cell leukemia/lymphoma, and pathways concurrently inhibited
by decreased mTOR can be utilized as targets for combined therapy.
Chapter 4: The BALB/c variant of mTOR, C1977T, has an altered function compared to
the wild-type variant due to the single amino acid substitution at aa 628 (628C); this
altered function leads to a difference in survival, the phosphoproteome, the
transcriptome, and tumor formation in response to cell stressors.

13

CHAPTER 2: General Methods
The methods described in this section are general methods used throughout both
portions of the project (Chapters 3 and 4). For more detailed methods for each
individual project, see the methods section of the appropriate chapter.
Mice
All animal studies were performed in compliance with the NIH Animal Care and
Use Committee (Protocol LG009). The creation and preliminary characterization of the
mTOR KD and 628C KI mice are described by Zhang, et al. (Zhang, Readinger et al.
2011).
Collection of cells and tissues
Tissues were collected from mice at a pre-defined study endpoint or humane
endpoint and were either fixed in Telly’s Fixative (4% formaldehyde and 2% glacial
acetic acid in 70% EtOH) or 4% paraformaldehyde in PBS for 24 hours and transferred
to 70% ethanol for long term storage. Tissue was also flash frozen in liquid nitrogen or
was transported to the lab fresh on ice for downstream applications.
Fresh thymic tumors were crushed in a 40 µm sterile filter in 1X PBS to create a
single cell suspension. Depending on the downstream application, the single cell
suspension was spun down and cell pellets were flash frozen for future use.
Spleens and femur bones were collected from WT and 628C KI mice. Spleens
were crushed using the sterile end of a syringe plunger and cells were resuspended in
1X PBS and filtered through a 40 µm sterile filter. ACK lysis buffer (Lonza, Walkersville,
MD) was added to lyse remaining splenic red blood cells. B220+ splenocytes (splenic Bcells) were then isolated using MS MACS separation columns and B220+ beads
14

(Miltenyi Biotec, Auburn, CA) as recommended by the manufacturer. Bone marrow
cells were collected by cutting the ends of fresh femur bones and using a 30 ½ G
needle and 6 ml syringe to flush sterile, ice-cold PBS through the marrow cavity. The
bone marrow contents were incubated briefly with ACK lysis buffer to lyse red blood
cells. Cell pellets from B220+ splenocytes and bone marrow were flash frozen and
stored at -80oC for use in downstream applications.
To create mouse embryonic fibroblasts (MEFs), uteri containing 13.5 dpc (days
post conception) embryos were collected and individual embryos were separated. The
heads and internal organs were removed, and the remaining tissues were macerated in
5 ml Trypsin-EDTA (Gibco, Life Technologies, Grand Island, NY). The tissue was
incubated at 37oC in Trypsin-EDTA for 15 minutes, and remaining fragments were
pipetted up and down to break up the debris. Cells were cultured overnight in 10cm
dishes in Dubecco’s modified eagle medium (DMEM, Gibco) supplemented with 10%
fetal bovine serum (FBS) and 1% penicillin-streptomycin (Gibco). Media was changed
the following day, and MEFs were expanded for two passages and frozen for future use.
Flow cytometry and protein analysis
Single cell suspensions from thymi or spleens, or of mouse embryonic fibroblasts
(MEFs), were stained with the PE Annexin V Apoptosis Detection kit (Becton Dickson,
San Jose, CA) for evaluation of apoptotic cells; the cell cycle was analyzed using
propidium iodide (PI)/RNAse Staining Buffer (Becton Dickson). Stained cells were
analyzed using FACSCalibur (Becton Dickinson) and flow cytometry data was reviewed
using FlowJo software (Ashland, OR).

15

Protein was isolated for immunoblotting from thymi, T-cell lymphoma cell lines,
spleens, and bone marrow by lysing cell pellets in radioimmunopreciption assay buffer
(RIPA) plus protease and phosphatase inhibitors (Santa Cruz Biotech, Dallas, TX).
Lysates were passed through a 25 GA needle ten times and allowed to incubate on ice
for 1 hour. MEF samples were lysed in a freshly-prepared buffer composed of 10%
sodium dodecyl sulfate (SDS), protease and phosphatase inhibitors (Roche,
Indianapolis, IN), and 1% tris and were sonicated at 4oC on high for 7.5 minutes, with
0.5 minute on, 1 minute off intervals. These samples were also then allowed to
incubate on ice for 1 hour. Samples from both preparation methods were centrifuged at
12,000 rpm at 4oC for 20 minutes, and the supernatant, containing the proteins, was
saved for future analysis. Protein concentrations were measured using the bicinchoninic
acid (BCA) assay (Pierce™ BCA Protein Assay Kit, ThermoScientific; Rockford, IL).
Lysates were prepared with 4% lithium dodecyl sulfate (LDS) loading buffer and
approximately 12 µg of protein per sample was loaded onto 4-12% Bis-Tris or 4-20%
tris-glycine gels (Novex, Life Technologies, Grand Island, New York) and separated by
electrophoresis. Proteins were transferred to a nitrocellulose membrane via the iBLOT
system (Life Technologies, Grand Island, NY).
Membranes were incubated with primary antibodies at 4oC overnight in 5%
BSA/TBST (bovine serum albumin/tris buffered saline with 1% Tween-20), and the
following day were rinsed in TBST and incubated in the appropriate secondary antibody
at room temperature in 5% milk/TBST. Antibodies used throughout these projects are
listed below (Table 1). Membranes were incubated for 1 minute with Super Signal West
Dura or Femto Extended Duration Substrate (Life Technologies) and were imaged using

16

a Syngene Imager and the GeneSnap program from Syngene (Frederick, MD). Digital
quanitifcation of bands (densitometry) was performed using GeneTools (Syngene).

Table 1: Antibodies used in this project, including company and
catalog number.
Target Antigen
Catalog #
Company
Phospho-4E-BP1 (T37/46) 2855
Cell Signaling
4E-BP1
9452
Cell Signaling
Phospho-AKT (S473)
9271
Cell Signaling
AKT
9272
Cell Signaling
ATM
2873
Cell Signaling
CDK4
2906
Cell Signaling
CDK6
3136
Cell Signaling
Cleaved Caspase 3
9661
Cell Signaling
Cyclin D1
2926
Cell Signaling
Cyclin D3
2636
Cell Signaling
FANCD2
ab108928
Abcam
Mtor
2972
Cell Signaling
c-MYC
ab32072
Abcam
P21
sc-397
Santa Cruz
P16
sc-1207
Santa Cruz
P27
2552
Cell Signaling
Phospho-PKCα (T638)
ab32502
Acbam
Phospho-PKCα (T497)
ab76016
Abcam
Phospho-PKCα (S657)
12356
Cell Signaling
PKCα
ab32376
Abcam
Phospho-P53 (Ser15)
9284
Cell Signaling
Phospho-RB ( S780)
8180
Cell Signaling
RB
9313
Cell Signaling
Phospo-rpS6 (S240/244)
2215
Cell Signaling
RpS6
2217
Cell Signaling
Phospho-p70SK6 (T389)
9205
Cell Signaling
P70-S6K (S6K)
9202
Cell Signaling

Protein expression for phospho and total S6, 4E-BP1, and AKT was also
evaluated using a size-based, automated, capillary immunoassay system [Simple
Western, Protein Simple, Santa Clara, CA; (Chen JQ 2013)]. This analysis was

17

performed by the Center for Cancer Research Collaborative Protein Technology
Resource group.
Genotyping
DNA was prepared by the HotSHOT method [(hot sodium hydroxide and Tris;
(Truett 2000)] from cell pellets, ear punches, or tail tips. PCR reactions were composed
of buffer 2 and components from the Expand High Fidelity Kit (Roche) or of the GoTaQ
Green master mix (Promega, Madison, WI) per the manufacturer’s instructions, as well
as 1 µL each of the appropriate forward and reverse primers. Cycling conditions were
optimized based on primer. Primers for determining the mTOR 628C KI or mTOR KD
status (Zhang, Readinger et al. 2011) and for genotyping based on sex (McClive and
Sinclair 2001) are previously described.
Microarray and RT-PCR
RNA was isolated using Trizol reagent (Invitrogen, Life Technologies), followed
by purification using the Qiagen RNeasy MiniElute Cleanup kit (Qiagen, Vinlo, Limburg).
1 µg of RNA was labeled and amplified using the Message Amp-11-Biotin Enhanced Kit
(Ambion, Life Technologies, Carlsbad, CA). RNA was hybridized to Affymetrix Mouse
Genome 430 2.0 array cartridges while rotating at 45oC for 16 hours. Chips were
washed in a GeneChip Fluidic wash station (Affymetrix, Santa Clara, CA) and scanned.
Microarray analyses were performed using Affymetrix GCOS software (Santa Clara,
CA), Partek software, and BRB-ArrayTools (developed by Dr. Richard Simon and BRBArrayTools Development Team). Data were normalized to internal controls. Significantly
different genes were selected with p-values >0.05 and a fold change of >1.5 or <-1.5.

18

cDNA for real time PCR (RT-PCR) was created from RNA samples using
TaqMan ® Reverse Transcription Reagents (Life Technologies, Grand Island, NY) and
RT-PCR was performed using SYBR-Green PCR Master Mix (ABI, Foster, CA, USA) on
a 7500 Fast Real-Time PCR System (Applied Biosystems, Foster City, CA, USA) with
the following primers for CDK6: 3’-CCAAATCTGCTCAACCCATCG-5’ and 3’CAGGTTGTCCTTGTATCTCTCCAG-5’, FANCD2 forward 3’- AGTATGGCCGTCGCTT
TGTGG-5’, FANCD2 reverse 3’-GCAGCAAGCTCAGAACATCTTCC-5’, FANCC forward
3’-CTGCTGTGGCTCTTGGTGTTC-5’, FANCC reverse 3’-AATACCTTCAGCTCCACCA
TGC-5’, FANCG forward 3’-CTCTTTCGGACCCTGCCTGAGG-5’, FANCG reverse 3’ACTCCAGTCCACGACTGATCAG-5’. Cycle threshold values (CT) were normalized to
B-Actin or rRNA levels for each sample.
RNA including microRNAs (miRNA) was prepared from B220+ splenocytes from
untreated and pristane-treated mice using the mRNeasy kit (Qiagen), per the
manufacturer’s instructions. RNA samples were shipped to Nanostring (Seattle, WA) for
barcoded Nanostring array analysis of miRNA expression. Results were analyzed in
nSolver (Nanostring) and in Microsoft Excel. MiRNAs with p-value >0.05, a fold change
>1.5 and <-1.5, and FDR<5 were selected. RT-PCR for miRNA was performed on RNA
samples containing miRNA using primers and a kit specific for detection of miRNA
(Applied Biosystems). Samples were normalized to U6 expression levels.
Glycolysis analysis
Glycolysis in the WT, KI, and KD transformed and primary mouse embryonic
fibroblasts was analyzed using the Seahorse XF Glycolysis Stress Test Kit (Seahorse,
MA) and the XF analyzer per the manufacturer’s instructions.

19

Statistical Analysis
Mouse survival was assessed using the Kaplan-Meier survival curve and the Log
Rank Test (Graph Pad Prism, La Jolla, CA) analyses. RT-PCR results were analyzed
using the 2-∆CT method, and values were compared using a Student’s T-test. Flow
cytometry, RT-PCR, proliferation, IHC results were also compared using Student’s Ttest.

20

CHAPTER 3: Constitutive mTOR inhibition in mouse thymic pre-T LBL
identifies Cdk6 as a target for combination treatment of T-ALL/LBL

Abstract
The PI3K/AKT/mTOR pathway is frequently hyperactivated in T-cell acute lymphoblastic
leukemia/lymphoma (T-ALL/LBL). To model inhibition of this pathway in lymphoma,
mice with T-lymphocyte-specific, constitutively-active AKT (Lck-MyrAkt2) were crossed
to mice with genetically reduced mTOR expression (mTOR knock down, KD). Mice with
genetic reduction of mTOR had increased survival relative to wild-type mTOR mice
(average survival of 24 versus 14 weeks, respectively), though both groups eventually
developed thymic pre-T-cell lymphoblastic leukemia/lymphoma (pre-T LBL). A similar
phenotype was observed when mTOR wild-type Lck-MyrAkt2 mice were treated for 8
weeks with the rapamycin analog, everolimus, an inhibitor of the mTORC1 complex.
Transcriptional profiling of thymic lymphomas from the mice uncovered decreased
expression of Cdk6, a critical proliferative control node in T-cell development and
oncogenic transformation, in mTOR KD mice. Pharmacologic inhibition of mTOR in
tumor cells also decreased CDK6 protein levels, suggesting the two proteins have a
mechanistic relationship in the tumors. The combination of a mTOR inhibitor
(rapamycin) and a CDK4/6 inhibitor (PD-0332991) cooperatively decreased the overall
viability and signaling downstream of drug targets in mouse lymphoma cells and in
human T-ALL/LBL cell lines. Our results suggest that this drug combination may be
beneficial in the treatment of T-ALL/LBL.

21

Introduction
T-cell acute lymphoblastic leukemia/lymphoma (T-ALL/LBL) accounts for 15% of
childhood and 25% of adult lymphoblastic leukemia and is often characterized by
hyperactivation of the PI3K/AKT/mTOR pathway (Pui, Relling et al. 2004). In one study,
deletion or mutational inactivation of PTEN or activating PI3K or AKT mutations were
found in approximately half of primary T-ALL samples (Gutierrez, Sanda et al. 2009). In
vitro pharmacologic inhibition of the PI3K/AKT/mTOR pathway decreased the viability of
human T-ALL/LBL cell lines and caused G1 cell cycle arrest (Chan, Weng et al. 2007,
Batista, Barata et al. 2011, Bressanin, Evangelisti et al. 2012). The frequent activation
of this pathway and its role in cell growth has suggested mTOR as a target for
pharmacologic inhibition, leading to clinical trials of mTOR inhibitors in ALL
(https://clinicaltrials.gov). However, first-generation mTOR inhibitors, such as
rapamycin, efficiently target only one of the two complexes formed by mTOR (TORC1)
(Loewith, Jacinto et al. 2002), and can be associated with feed-back loops and
eventual resistance (Carew, Kelly et al. 2011). While newer mTOR inhibitors target both
complexes (TORC1/2), suppression of resistance mechanisms by combining them with
additional drugs could further improve treatment efficacy.
To explore the effects of mTOR inhibition in a T-cell neoplasm with a
hyperactivate PI3K/AKT pathway, we utilized the Lck-MyrAkt2 (Lck-Akt) mice, in which
the T-lymphocyte-specific proximal Lck promoter drives a constitutively-active,
myristoylated AKT2 protein (Ahmed, Franke et al. 1993, Malstrom, Tili et al. 2001).
These mice spontaneously develop thymic pre-T cell lymphoblastic leukemia/lymphoma
(pre-T LBL) between 75-200 days of age (Rathmell, Elstrom et al. 2003, Tan, Timakhov

22

et al. 2008, Timakhov, Tan et al. 2009). To diminish the hyperactive PI3K/AKT
signaling, we inhibited mTOR both genetically and pharmacologically in these mice.
This study highlights the modulation of CDK6 levels by mTOR and the use of mTOR
inhibition in mouse models to explore molecular responses in T-ALL/LBL and to identify
targets for combination therapy.
Methods
Mice. Animal studies were in compliance with NIH Animal Care and Use Committee
Protocol LG009. Lck-Akt (Founder line 72; C57BL/6 background) transgenic mice were
crossed with heterozygous Mtortm1. Lgm mice [mTOR KD mice, approximately 70%
reduction in mTOR expression, B6;129 background; Figure 5 (Zhang, Readinger et al.
2011)] for two generations; offspring positive for Lck-Akt and homozygous for wild-type
or knock down mTOR were selected. Mouse survival was assessed by a Kaplan-Meier
survival curve and a Log Rank test (GraphPad Prism, San Diego, CA). In a separate
experiment to control for the allelic variant (628C) of mTOR in the KD mice,
Mtortm1.1Lgm mice with the allelic variant and normal mTOR levels [ mTOR KI mice
(Zhang, Readinger et al. 2011)] were crossed with Lck-Akt mice; no differences in
survival were observed between Lck-Akt mice with or without the allelic variant (data not
shown). Mice were genotyped for the Lck-Akt transgene (primers 5’ AGG CAC TGC
CCT CTT GAA GC-3’ and 5’ TTT GGG GTT CTG AAT GTG AG-3’), and for the
disrupted mTOR gene as described (Zhang, Readinger et al. 2011). Tumors were
collected at humane endpoint; a portion was fixed in Telly’s fixative for 24 hours (h) and
the remainder was frozen. Lck-Akt transgenic mice from founder line 55 (C57BL/6
background) (Timakhov, Tan et al. 2009) were given RAD001 (everolimus, 20mg/kg) or
23

vehicle (50µl) by gavage twice weekly, beginning at 8 weeks of age and continuing for 8
weeks. Mice from founder line 55 have a similar incidence of tumor formation as mice
from founder line 72, though tumors arise more quickly in line 55 (~10wks compared to
16wks) (Timakhov, Tan et al. 2009).

Figure 5: Schematic summarizing the characteristics of the strains bred to
produce the Lck-Akt/mTOR WT (WT) and Lck-Akt/mTOR KD (KD) mice. LckMyrAkt2 mice have constitutively-active AKT due to myristoylation exclusively in Tlymphocytes, which is driven by a proximal LCK promoter; these mice spontaneously
developed thymic lymphomas. mTOR knockdown mice have decreased mTOR
expression due to a neomycin cassette inserted in the Mtor gene in cells throughout the
body. The resulting offspring are referred to throughout as WT and KD based on mTOR
status, but are positive for the Lck-Akt transgene.
Flow cytometry and protein analysis. Single cell suspensions from thymi of 4-weekold WT and KD mice and from murine thymic pre-T LBL were stained for CD4 and CD8
to determine double (CD4+,CD8+) and single (CD4+ or CD8+) positive T-cell
populations by flow cytometry. Double negative (CD4-, CD8-) T-cells were identified as
previously described (Hu, Deshpande et al. 2011). Viably frozen WT thymic pre-T LBL
were transplanted into nude mice, then collected and cultured in vivo with either 1 nM of
rapamycin or 625 nM of PD-0332991 (CDK4/6i, Pfizer) for 48 hours. Apoptosis of
24

treated cells was evaluated using the PE Annexin V Apoptosis Detection Kit 1 and cell
cycle was analyzed using PI/RNAse staining buffer (Becton Dickson, San Jose, CA).
Cells were analyzed using FACSCalibur (Becton Dickinson) and FlowJo software
(Ashland, OR).
Protein was isolated with RIPA lysis buffer plus protease inhibitors (Santa Cruz
Biotech, Dallas, TX). Lysates were electrophoresed on 4-12% Bis-Tris gels (Novex, Life
Technologies, Grand Island, NY) and were transferred to nitrocellulose membranes via
the iBLOT system (Life Technologies). Antibodies were acquired from Abcam (cMYC:ab32072, Cambridge, MA), Santa Cruz (p21:sc-397,p16:sc-1207; Dallas, TX), or
Cell Signaling (mTOR:2972; CDK6:3136; CDK4:2906; Cyclin D3:2936; Cyclin D1:2926;
p27:2552; and phospho-4E-BP1Thr37/46:2855, 4E-BP1:9452; phospho-AKTS473:9271,
AKT:9272; phospho-RBS780:8180, RB:9313;phopsho-S6S240/244:2215, and S6:2217;
Danvers, MA). A size-based, automated, capillary immunoassay system [Simple
Western, Protein Simple, Santa Clara, CA (Chen, Heldman et al. 2013)] was utilized by
the Center for Cancer Research Collaborative Protein Technology Resource group to
measure phospho/total 4E-BP1 and AKT protein expression.
Pre-T LBL clonality. Analysis for T-cell clonality was performed on genomic DNA
extracted from eight paraffin-embedded tumor tissue sections using the QIAamp DNA
FFPE Tissue Kit (Qiagen, Valencia, CA). PCR amplification was performed using a twostep nested PCR that detects intralocus TCRG rearrangement (Knapp 2003) utilizing
previously-described primers (Lista, Bertness et al. 1997). PCR reactions were
prepared in 25μl total volume, with 3μl DNA, 5pmol of each primer, 0.5U of Taq
polymerase (Invitrogen, Carlsbad, CA), and final concentrations of 80μM DNTP, 2mM
25

magnesium chloride, 20mM Tris-hydrogen chloride, and 50μl potassium chloride.
Cycling conditions were: 94°C for 4 minutes (m); 40 cycles at 94°C for 1m, 55°C for 1m,
and 72°C for 1m; and 72°C for 5m. All PCR reactions were run in duplicate. Amplicons
were visualized by high-resolution capillary electrophoresis using the QIAxcel Advanced
Instrument (Qiagen) and QIAxcel Screengel Software. Two samples from mouse spleen
and lymph node were amplified as polymorphic controls.
Pre-T LBL cell culture and fluorescence in situ hybridization (FISH). Thymic pre-T
LBL single cell suspensions were cultured in Iscove’s Modified Dulbecco Medium
(IMDM; Life Technologies; plus 10% FBS, 1% penicillin-streptomycin, L-glutamine, nonessential amino acids, and sodium pyruvate, and 0.1% β-mercaptoethanol). A subset of
cells were cultured with 0.2% colcemid for 2h, lysed with 0.075M KCL, and fixed with
3:1 methanol/glacial acetic acid. Probes for TCRα (BAC probe kindly provided by
Thomas Reid, NCI) and c-Myc were labeled and hybridized overnight to metaphase
spreads from fixed cells. Slides were incubated with FITC-labeled anti-DIG and avidinAlexa 568 and stained with DAPI. Metaphase spreads were imaged on an inverted
fluorescent microscope at 100X. At least 50 cells were assessed for the presence of
t(14;15) translocations/sample (Timakhov, Tan et al. 2009).
Microarray and RT-PCR. RNA (1µg) was isolated from WT and KD thymic pre-T LBL
using Trizol reagent (Invitrogen, Life Technologies), followed by purification with Qiagen
RNeasy MiniElute Cleanup Kit (Qiagen). RNA was labeled and amplified with Message
Amp-11-Biotin Enhanced Kit (Ambion, Life Technologies) and hybridized overnight to
Affymetrix Mouse Genome 430 2.0 array cartridges (Santa Clara, CA). Chips were
washed in a GeneChip Fluidic wash station (Affymetrix) and scanned. Microarray

26

analyses (ArrayExpress accession E-MTAB-3242, www.ebi.ac.uk/arrayexpress) were
performed using Affymetrix GCOS, Partek, and BRB-ArrayTools (Richard Simon;BRBArrayTools Development Team). Data were normalized to internal controls. Genes
expressed at significantly different levels between WT and KD mice had p<0.05, FDR of
<0.1, and 30% of expression data values had at least a 1.5-fold change in either
direction from the gene’s median value.
To assess levels of Cdk6, cDNA was prepared using TaqMan® RT Reagents
(Life Technologies) and real-time PCR (RT-PCR) was performed using SYBR-Green
master mix (ABI, Foster City, CA) on a 7500 Fast RT-PCR System (Applied
Biosystems) with the following primers for Cdk6:3’-CCAAATCTGCTCAACCCATCG-5’
and 3’-CAGGTTGTCCTTGTATCTCTCCAG-5’ and for p16 as described (Zhang, Qian
et al. 2003). Values were normalized to β-actin.
Drug treatment of murine pre-T LBL cells. Thymic pre-T LBL cells (100,000 cells/200
µL, 96-well plates) were treated with 1nM rapamycin and/or 5nM-5µM PD-0332991
(SelleckChem, Houston, TX), each dissolved in DMSO. Cell viability was assessed after
24h (CDK4/6 inhibitors-Figure 4C) and 48h (mTOR inhibitor, CDK4/6 inhibitors, and
combination) using CellTiter96® Aqueous One Solution (MTS Assay, Promega,
Madison, WI). Experiments were performed in duplicate.
Matrix dose response screen in human T-ALL/LBL cell lines. Human T-ALL/LBL
cell lines (CEM, CUTLL1, HALL, P12-ICHIKAWA, Jurkat, TIB-153, J.CaM1.6, and
MOLT-3) were grown in RPMI (0.2% Normocin, 1% penicillin-streptomycin and Lglutamine, 10% FBS). To assess the activity of the drugs in combination, cell lines
(25,000 cells/well in 96-well plates) were treated with a range of five doses of rapamycin

27

(0–100nM) and the CDK4/6 inhibitor, PD-0332991(0-1µM) individually and in
combination [matrix dose response screen (Simmons, Patel et al. 2014)]. Viability at
48h post-treatment was assessed by MTS assay. Each screen was repeated twice, with
duplicated plating/experiment. In addition, each cell line (6-well plates,
1.5x106cells/well) was treated with 500nM PD-0332991, 1nM rapamycin, or the
combination for 48h and collected for protein isolation. Drug activity of rapamycin and
PD-0332991 was evaluated using Excess over Highest Single Agent (EOHSA) (Borisy,
Elliott et al. 2003) and synergy scores were calculated using Combination Index (CI)
methods [CompuSyn software http://www.combosyn.com/;CI<1 is synergistic (Chou
2005, Chou 2006, Chou 2010)]. Heat maps and CI plots for the dose matrices were
generated with R v2.15.1 (Team 2011). Four T-ALL/LBL cell lines were treated with a
range of PP242 (dual mTORC inhibitor; 0–2.5µM) and PD-0332991 doses (0–1000nM)
in combination and assessed for viability.
Results
Pre-tumor thymocytes from mTOR KD mice have decreased mTOR activity. LckMyrAkt2 (Lck-Akt) mice spontaneously develop thymic pre-T LBL by 10-20 weeks of
age (Tan, Timakhov et al. 2008, Timakhov, Tan et al. 2009), although their thymi are
histologically normal at 4 weeks of age (Tan, Timakhov et al. 2008). mTOR signaling
and T-cell development were evaluated in thymocytes from 4-week-old Lck-Akt/mTOR
WT (WT) and Lck-Akt/mTOR KD (KD) mice prior to tumor formation. The downstream
targets of mTOR, phospho-4E-BP1Thr37/46 and phospho-AKTS473, were decreased in
KD compared to WT thymocytes (Figure 6A and B). Total thymocyte number and size
were similar in WT (n=3) and KD (n=3) pre-tumor thymi by flow cytometry. There was
28

no difference in the absolute number of double positive CD4+, CD8+ and single positive
CD4+ or CD8+ thymocytes (Figure 7A, B, and C). Four stages of double negative (DN)
thymocyte maturation are recognized, DN1-4. In thymi from 4-week-old mice there were
fewer DN1 thymocytes in KD thymi (p=0.031), though all other double negative stages
were similar between WT and KD thymi (Figure 8A, B, and C). Only a mild delay in
development was observed in KD thymocytes at the DN1 stage, but this delay resolved
and thymocyte populations were similar between KD and WT through remaining
developmental stages, indicating the mTOR KD did not disrupt T-cell development in
the thymi of these mice. A similar population of CD4 and CD8 single positive
thymocytes has been reported in mTOR WT and KD mice that were not crossed to LckAkt mice (Zhang, Readinger et al. 2011).
A

Figure 6A: Digital bands from a capillary-based immunoassay assessing levels of
downstream targets of mTOR in pre-tumor thymocytes (4 weeks) in two
representative mice. Phospho-4E-BP1T37/46 and phospho-AKTS473 were assessed
Figure 6 (cont’d). for WT and KD thymocytes from 4-week-old mice (before tumor
formation). Vinculin served as the loading control.

29

B

Figure 6B: Chemiluminescence peaks from a capillary-based immunoassay
assessing levels of downstream targets of mTOR in pre-tumor thymocytes (4
weeks) in two representative mice. Phospho-4E-BP1T37/46 and phospho-AKTS473
were assessed for WT and KD thymocytes from 4-week-old mice (before tumor
formation). Vinculin served as the loading control.

30

A

B

C

Figure 7: Flow cytometry scatter plots for thymic CD4 and CD8 labeling (A), with
bar graphs of absolute numbers (B) and percents (C) of each cell type. 3 WT and
3 KD thymi were assessed, and error bars represent standard error of the mean.
Absolute numbers of cells for each population were compared between WT and KD by
Student’s T Test.

31

A

B

C

Figure 8: Flow cytometry scatter plots (A) and bar graphs of absolute numbers
(B) and percentages of cells (C) for CD44 and CD25-labeled, lineage-depleted Tlymphocytes from pre-tumor thymi. Non-T-cells were depleted from thymi of 4-weekold mice, and remaining cells were labeled for CD25 and CD44. These markers define
different populations of developing, double negative (DN), thymocytes. DN1 cells were
significantly decreased in KD thymi (p=0.031). 3 WT and 3 KD thymi were assessed,
and error bars represent standard error of the mean. Absolute numbers of cells for
each population were compared between WT and KD by Students T Test.

Genetic and pharmacologic mTOR inhibition prolonged survival of Lck-Akt mice.
Over a period of >400 days, a similar proportion of 45 WT (75%) and 20 KD (71%) mice
32

developed pre-T LBL, which had a similar appearance in photomicrographs (Figure 9).
However, the KD mice had a notably increased survival time compared to WT mice
(Log Rank Test, p=0.002, Figure 10); KD mice survived an average of 168 days
(median survival: 151d), while WT mice survived an average of 99 days (median: 92d).
As in the pre-tumor thymocytes, phospho-4E-BP1Thr37/46 and phospho-AKTS473 levels
were decreased in thymic pre-T LBL from KD mice (Figure 11). Pre-T LBL cells from
WT mice (n=2) were a mixture of CD8+ and CD4+,CD8+ neoplastic T-cells, while cells
from KD mice (n=3) were predominately CD8+ (representative tumors, Figure 12). PCR
for T-cell antigen receptor rearrangement revealed that six of eight tumors were clonal
(3/4 WT, 3/4 KD); pseudoclones were observed in the remaining two samples, likely a
result of PCR failure in these samples (representative tumors, Figure 13).

Figure 9: Photomicrographs of thymic lymphomas from WT and KD mice.
Hematoxylin and Eosin, Imaged at 20X magnification.

33

Figure 10: Survival curve for Lck-Akt/mTOR WT and Lck-Akt/mTOR KD mice.
Survival associated with thymic pre-T cell lymphoblastic leukemia/lymphoma (pre-T
LBL) was evaluated in KD (n=20) and WT mice (n=45) by Kaplan Meier survival
analysis and a Log Rank test.
A

Figure 11A: Digital bands from a capillary-based immunoassay assessing levels
of downstream targets of mTOR in pre-T LBL from two representative mice.
Phospho-4E-BP1T37/46 and phospho-AKTS473 were assessed for WT and KD pre-T
LBL cells. Vinculin served as the loading control.
34

B

Figure 11B: Chemiluminescence peaks from a capillary-based immunoassay
assessing levels of downstream targets of mTOR in pre-T LBL from two
representative mice. Phospho-4E-BP1T37/46 and phospho-AKTS473 were assessed
for WT and KD pre-T LBL cells. Vinculin served as the loading control.

35

Figure 12: Flow cytometry scatter plots of CD4 and CD8-labeled populations in
thymic pre-T LBL from WT and KD mice. The CD4, CD8 status of WT (n=2) and KD
(n=3) thymic pre-T LBL was assessed by flow cytometry (representative scatterplots
shown for WT and KD).

Figure 13: Clonality of pre-T LBL assessed by nested PCR for T- cell receptor
rearrangement. WT (n=3) and KD (n=3) pre-T LBL thymic tumors were assessed by
nested PCR for T-cell antigen receptor rearrangement (PARR: PCR reactions were run
in duplicate). The normal spleen samples have the expected polymorphic (non-clonal)
pattern. Negative control = water and positive control = known clonal T-cell lymphoma.
Two representative tumors are shown.
36

As Lck-Akt mice frequently develop a t(14;15) translocation involving T-cell
receptor α/Myc (Timakhov, Tan et al. 2009), we hypothesized that the increased
survival in KD mice could be associated with a decrease in translocation frequency.
FISH screening for t(14;15) in thymic pre-T LBL cells from 11 WT and 8 KD mice
(Figure 14) revealed a slight increase in translocations in KD cells (50% versus 45% in
WT; Figure 15). Four (36%) WT pre-T LBL and 4(50%) KD pre-T LBL did not have the
translocation and two WT tumors (18%) had three Myc signals (trisomy 15). MYC
expression levels were similar in WT and KD tumor cells without the translocation, and
were lower in pre-tumor thymocytes (Figure 15). The similar proportion of t(14:15)
observed in the WT and KD tumors suggests that the increased survival in the KD mice
is not associated with a decrease in Myc translocation.

Figure 14: TCRα/Myc translocations in WT and KD mice. Representative metaphase
spreads from WT and KD tumor cells with the t(14;15) at 100X magnification. Myc
signals are green and Tcra signals are red. Juxtaposed green and red signals (yellow)
were indicative of the t(14;15) recombinant chromosomes.

37

Figure 15: Proportions of TCRα/Myc translocations and MYC protein levels in WT
and KD pre-T LBL. Percentages of WT (n=11) and KD (n=8) tumors with or without
Tcra/Myc translocation by FISH. MYC protein levels in representative WT and KD pretumor thymi (from 4-week-old mice) and pre-T LBL are shown.
In parallel, Lck-Akt mice with WT mTOR were treated biweekly with 20mg/kg
everolimus (RAD001, n=12) or vehicle (n=10), beginning at 8 weeks of age and
continuing for 8 weeks or until signs of tumor progression. Mice treated with everolimus
had significantly improved survival (p<0.001, Log Rank Test, median survival:155d
versus 73.5d in vehicle-treated, Figure 16), echoing results seen in the genetic mTOR
KD mice. As the everolimus treatment was begun after neoplastic transformation
occurred in these mice, this result suggests that mTOR inhibition delayed tumor
progression, but did not alter the populations from which the tumor arose (as supported
by the thymic flow cytometry results in the genetic mTOR KD mice).

38

Figure 16: Survival curve from Lck-Akt mice treated with a mTOR inhibitor
(everolimus). Lck-Akt transgenic mice were treated by gavage with everolimus (20
mg/kg twice weekly; n = 12) or vehicle (50 μl PBS; n = 10) starting at 8 weeks of age.
Treatment of both groups continued for 8 weeks or until mice showed signs of illness.
Arrows indicate start and completion dates of the drug treatment. Survival was
evaluated by Kaplan-Meier survival analysis and a Log Rank test (p<0.001).

CDK6 is decreased in KD thymic pre-T LBL. To elucidate possible mechanisms
explaining the increased survival in KD mice, we performed gene expression profiling
on thymic pre-T LBL tumors from both WT and KD mice. Transcriptional profiling
revealed 98 differentially-expressed genes; 49 up-regulated and 49 down-regulated
(p<0.05, fold change >1.5 or <-1.5, and FDR<0.1; Figure 17A). Cdk6 was one of the
most down-regulated genes in lymphomas from KD mice (p=0.001, fold change= -7.7,
FDR=0.06); both Cdk6 transcripts (Figure 17B) and CDK6 protein levels (Figure 17C,D)
were decreased in lymphomas from KD mice. By contrast, WT tumors had increased
levels of CDK6, and pre-tumor thymi from WT and KD mice had similar, low levels of
CDK6 protein (Figure 17D), suggesting that the decrease in CDK6 occurred during
tumor development in KD mice. The reduced CDK6 expression in KD pre-T LBL was
39

not attributable to differential expression of the Cdk6 regulator p16Ink4a (Cdkn2a), as
its expression was similar at the RNA and protein level in WT and KD tumors (Figure
18). In contrast, expression of cyclin D1 and cyclin D3 (the main activator of CDK6)
proteins were higher in KD compared to WT lymphomas, and like CDK6, CDK4 and
cyclinD3 were not differentially expressed in the WT and KD pre-tumor thymocytes
(Figure 19). Levels of the cell cycle inhibitors, p21 and p27 (CDKN1A and B) were also
increased in the KD pre-T LBL cells (p27 increased in 2 out of 3 KD tumors, Figure 17C,
Figure 19); increased levels of p21 have previously been reported with pharmacologic
CDK4/6 inhibition (Paternot, Colleoni et al. 2014), and p27 phosphorylation and
localization are reported to be regulated by mTOR (Hong, Larrea et al. 2008). The
results suggest a possible mechanistic relationship between chronically low levels of
mTOR and subsequently low levels of CDK6 during tumor development/maintenance.

40

A

B

C

D

Figure 17: Transcript and protein levels of CDK6 and protein expression of other
cell cycle regulators in WT and KD thymic pre-T LBL.
41

Figure 17 (cont’d): A. 98 genes were differentially expressed between WT (n=4) and
KD (n=3) thymic lymphomas, as shown in a heat map from microarray results
(green=down regulated, red=up regulated). One gene, Cdk6, is highlighted. B. Levels
of Cdk6 transcripts were evaluated in WT (n=4) and KD (n=3) pre-T LBL cells by RTPCR. C. Also shown are CDK6, CDK4, cyclin D3, RB, and p27 protein levels in 3 WT
and 3 KD pre-T LBL cells. D. CDK6 and cyclin D3 protein expression levels were
compared between pre-tumor thymi and pre-T LBL in representative WT and KD mice.

Figure 18: Protein and transcript levels ofCdkn2a (p16) in WT (n=4) and KD (n=3)
tumors. Levels ofCdkn2a (p16) mRNA by RT-PCR, as well as CDKN2A (p16) protein
levels in representative WT and KD pre-T LBL tumors by immunoblot.

Figure 19: Levels of CDKN1A (p21) and cyclin D1 protein in a representative KD
tumor compared to a WT tumor.

Murine pre-T LBL is sensitive to inhibition of mTOR and/or CDK4/6. To test
whether pharmacologic reductions in mTOR in pre-T LBL tumor cells mimicked the
effects of reduced CDK6 expression seen in KD tumors, we treated pre-T LBL cell lines
derived from WT and KD mice with the mTOR inhibitor, rapamycin (1nM, 48h). Both
42

WT and KD cells were sensitive to rapamycin (post-treatment viability: WT=20%,
KD=30%; Figure 20A), suggesting that chronically low mTOR levels did not lead to
rapamycin resistance in the KD tumors. Notably, CDK6 levels were decreased in
rapamycin-treated WT cells, showing that acute inhibition of mTOR signaling decreases
CDK6 levels in neoplastic T-cells (Figure 20B), providing further support for a
mechanistic relationship between low mTOR and low CDK6 levels. Because the pre-T
LBL tumors in the WT and KD mice differentially expressed CDK6 (Figure 17), we
explored the consequences of inhibiting both CDK6 and CDK4 in cell lines from these
tumors (no specific CDK6 inhibitor is available). We treated WT and KD pre-T LBL cells
with increasing doses of the CDK4/6 inhibitor PD-0332991(palbociclib, Pfizer) for 24
hours. Both WT and KD tumor cells showed similar decreases in viability with increased
doses of the CDK4/6 inhibitor (Figure 21). Treatment of WT pre-T LBL cells with both
rapamycin and PD-0332991 led to a G1 arrest (approximately 80% of cells in G1,
compared to approximately 65% in G1 in untreated cells, Figure 23), while rapamycin
treatment induced a higher rate of apoptosis than PD-0332991 treatment
(approximately 50% compared to 20% in untreated cells and 30% in cells treated with
PD-0332991, Figure 22).

43

A

B

Figure 20: Viability and CDK6 protein levels from WT and KD thymic pre-T LBL
cells treated with rapamycin. A. WT and KD thymic pre-T LBL cells (n=3/group) were
treated in culture with 1 nM rapamycin, and percent cell viability in relation to untreated
cells was assessed at 48 hours. The experiment was repeated twice, with four technical
replicates per experiment. Representative data from one experiment is shown, with
error bars indicating the standard error of technical replicates. B. Levels of CDK6
protein were evaluated after 48 hours of treatment with 1nM rapamycin in cell lines
established from WT and KD pre-T LBL tumors. Representative WT and KD cells lines
are shown.

Figure 21: Viability of WT and KD pre-T LBL cells with increasing doses of a
CDK4/6 inhibitor (PD-0332991). WT and KD pre-T LBL cells were treated for 24 hours
with a CDK4/6 inhibitor (Pfizer PD-0332991) over a range of doses. The experiment
was performed twice, and a representative experiment is shown.
44

Figure 22: Cell cycle and apoptosis were analyzed post treatment with a mTORi
and a CDK4/6i in mTOR WT pre-T LBL cells. WT thymic pre-T LBL cells were treated
with 1 nM rapamycin (mTORi) and 625 nM PD-0332991 (CDK4/6i) for 48 hours, and
cell cycle and apoptosis were evaluated by flow cytometry. Technical replicates are
shown in this figure.
Given that decreased mTOR and CDK6 levels in KD pre-T LBL were associated
with prolonged survival in the KD mice, we treated WT pre-T LBL cells with a
combination of rapamycin (1nM) and PD-0332991(500nM), as well as each individual

45

drug. WT tumor cell viability was decreased to a greater extent by the combination than
by each single agent (Figure 23).

Figure 23: Percent viability of WT thymic pre-T LBL cells treated with a mTORi, a
CDK4/6i, and a combination of the two inhibitors. WT thymic pre-T LBL cells were
treated for 48 hours with 1 nM rapamycin (mTORi), 500 nM PD-0332991 (CDK4/6i), and
the combination of the two compounds. Percent viability shown is in comparison to
untreated cells. The experiment was repeated twice, with four technical replicates per
compound (Error bars=SEM for technical replicates in the representative experiment).

The combination of CDK4/6 and mTOR inhibition is cooperative in human TALL/LBL cell lines. Genetic and pharmacologic inhibition of mTOR in murine pre-T
LBL had an associated decrease in CDK6 and delayed tumor progression; the
combination of a mTOR inhibitor and a CDK4/6 inhibitor also decreased viability in
murine pre-T LBL cells. As a result, we examined the combined effect of these two
inhibitors in a series of human T-ALL/LBL cell lines. Human T-ALL and T-LBL fall under
the same WHO classification, and have minor variations based on bone marrow
involvement and differential gene expression; these tumors share morphological,
immunophenotypic and genetic similarities (Hoelzer and Gökbuget 2009). We treated TALL/LBL cell lines with PD-0332991 and rapamycin in a combination dose matrix. Dose

46

responsive combination activity on cell viability was evident in all of the cell lines (Figure
24A) and was reinforced by positive excess of inhibition as shown by Excess over
Highest Single Agent graphs (EOHSA; Figure 24B). Synergy Combination Index scores
were calculated and are available in Figure 25 (CI<1 is synergistic). Phospho-RBS780,
the downstream target of CDK6, was reduced to a greater extent in the presence of the
combination compared with its reduction when the lines were treated with PD-0332991
alone (Figure 26A). This result suggests that the concentration of PD-0332991 used did
not fully inhibit CDK4/6 activity and that rapamycin cooperated with PD-0332991 in
reducing the level of phospho-RB. Rapamycin has also been reported to decrease
phospho-RB in breast cancer cell lines that express HER-2 (García-Morales, Hernando
et al. 2006). Total RB levels were also decreased by PD-0332991 and the combination
in all of the cell lines (except for Jurkat), as previously reported [Figure 26B, (Fry,
Harvey et al. 2004, Dean, Thangavel et al. 2010)]. Levels of CDKN1B (p27) protein
were similar across treatments for all cell lines, except for an increase in p27 in P12 cell
line with combination treatment (Figure 26B).

47

Figure 24: Activity of the combination of a CDK4/6 inhibitor (PD-0332991) and a
mTOR inhibitor (rapamycin) evaluated in human T-ALL/LBL cell lines. A. Heat
maps of 48-hour viability relative to control in 8 T-ALL/LBL cell lines (CUTTL1, CEM,
Jurkat, J.CaM1.6, TIB153, HALL, MOLT3, and P12 Ichikawa) treated in matrix format
with a range of five doses of rapamycin (mTORi, 0nM to 100nM, increasing 10-fold for
each dose) and five doses of PD-0332991 (CDK6i, 0nm-1µM, starting at 62.5nM and
increasing 2 fold for each dose) individually and in combination (matrix dose response
screen). Lighter blue squares represent lower viability, while darker blue is high percent
viability. Values are averaged results from 4 replicate experiments. B. Graphs showing
the Excess over Highest Single Agent (EOHSA) for T-ALL/LBL cell lines treated with
increasing doses of PD-0332991 and rapamycin, representing the difference in viability
between cells treated by the single agent and the combination at each dose.

48

Figure 25: Combination index of T-ALL/LBL cell lines treated with a mTORi
(rapamycin), a CDK4/6i (PD-0332991), and a combination of the two agents. The
IC50 normalized isobolograms generated with CompuSyn (Chou 2005) based on the
median-effect and Combination Index (CI) equations for the nonconstant ratio
combination design (Chou 2006). The diagonal line represents the additive effects of
drugs (CI=1); data points below and above the additivity line correspond to synergistic
(CI<1) and antagonistic (CI>1) effects of specific dose combinations, respectively.

49

A

B

Figure 26: Cell cycle proteins from six T-ALL/LBL cell lines treated with PD0332991, rapamycin, and the combination of the two agents. Western blots from six
T-ALL/LBL cell lines treated with 500nM PD-0332991 and 1 nM rapamycin, or the
combination of the two agents for 48 hours. Samples were run on two different gels due
to space restrictions on the gel. Figures A and B represent duplicate experiments.
Although rapamycin induced lower levels of CDK6 in the mouse lymphoma cells
(Figure 20), it did not do so consistently in the human T-ALL/LBL lines (Figure 26A and
B). PD-0332991 alone and in combination led to increased CDK6 levels in the human
lines. As expected, treatment of the T-ALL/LBL lines with 1nM rapamycin or the
combination decreased the phosphorylation of mTOR target, ribosomal protein
S6S240/244 (Figure 27). Phospho-AKTS473, however, was also increased in some of the
T-ALL/LBL lines treated with PD-0332991 or combination treatment (Figure 27).
50

Figure 27: Downstream targets of mTOR, phospho-ribosomal S6S240/244 and
phospho-AKTS473 were evaluated in T-ALL/LBL cell lines treated with 1 nM
rapamycin, 500 nM PD-0332991, and the combination of the two agents. Average
percent cell viability over 4 replicates when treated with the combination of 1nM
rapamycin and 500nM PD-0332991 is listed below the immunoblot images for each cell
line.
To determine whether pharmacologic inhibition of both mTORC1/2 might
abrogate the effects seen on phospho-AKT, the dual TORC1/2 kinase inhibitor PP242
was evaluated in combination with PD-0332991 in a subset of the T-ALL/LBL cell lines
(CEM,TIB-153,Jurkat, and MOLT-3; Figure 28). Treatment with 1nM rapamycin alone or
in combination with 500nM PD-0332991 served for comparison. With increasing doses
of PP242 (0-2.5µM), viability was decreased in all cell lines compared to treatment with
PD-0332991 alone (Figure 28). However, compared with the combination of rapamycin
plus PD-0332991, the dual inhibitor was only mildly more potent in two (CEM and TIB153) of the four lines tested. When signaling was examined in TIB-153, the most
notable difference was the absence of phospho-AKTS473 in cells treated with the
PP242/PD-0332991 combination, and its presence in cells treated with the
rapamycin/PD-0332991 combination (Figure 29). In addition, phospho-RB was also

51

decreased to a greater extent by this combination. This difference is likely attributable to
the suppression of mTORC2 by PP242.

Figure 28: Four representative T-ALL/LBL cells lines treated with increasing
doses of a dual mTOR inhibitor, PP242, or a mTORC1 inhibitor, rapamycin, in
combination with increasing doses of a CDK4/6 inhibitor (PD-0332991) for 48
hours. Percent viability is in comparison to untreated cells. These results are the
average of two replicate experiments.

52

Figure 29: Immunoblot analysis of one T-ALL/LBL cell line (TIB-153), evaluating
phospho-RB, RB, CDK6, cyclin D3, and phospho-AKTS473 after treatment with the
combination of PP242 (1.25 µM) and the CDK4/6 inhibitor (500 nM), as well as the
combination of rapamycin (1 nM) and the CDK4/6i (500nM). Average percent cell
viability from duplicate experiments for each treatment condition are listed below the
immunoblot images.
Discussion
As the constitutive ablation of mTOR in mice leads to embryonic lethality,
development of a viable mTOR knock-down mouse has made it possible to study the
genetic effects of mTOR knock-down in vivo. Previously described phenotypes of this
mouse include an increased lifespan, provided the animals are protected from infectious
stressors, as their B-cell development is impaired (Zhang, Readinger et al. 2011, Wu,
Liu et al. 2013, Zhang, Pruitt et al. 2013). Here, we used a constitutively-active Akt2
allele under control of a T-cell-specific promoter (Lck) to examine susceptibility of the
mTOR knock-down mouse to development of pre-T LBL. Lck-Akt/mTOR KD mice lived
substantially longer (2mo.) than their Lck-Akt/mTOR WT littermates. As a similar
proportion of the WT and KD mice died with thymic lymphoma (75% vs. 71%,
53

respectively), it may be inferred that, compared with the WT mice, lymphoma
development in the KD mice may have been delayed and/or that the lymphomas were
less aggressive.
Although mTORC1 and mTORC2 are both continuously inhibited in the mTOR
KD mouse, pharmacologic treatment of the Lck-Akt/mTOR WT mice with the mTORC1
inhibitor, everolimus, before and during lymphoma development was able to phenocopy
the increased lifespan of the Lck-Akt/mTOR KD mouse, although the KD mice lived
longer than the everolimus treated mice. The importance of mTORC1 activity was also
recognized in a different mouse model with inactivated mTORC1 and mTORC2 (Hoshii,
Kasada et al. 2014). In that report, a mutant K-ras gene that induced both T-cell
leukemia and a myeloproliferative neoplasm (MPN) was evaluated in mice whose
mTORC1 component Raptor or mTORC2 component Rictor was genetically disrupted.
Raptor disruption prevented the T-cell leukemia, but not MPN, while Rictor disruption
did not prevent either disease (Hoshii, Kasada et al. 2014). mTORC1 inactivation
through deletion of Raptor also suppressed death in a Notch-driven mouse model of TALL/LBL (Hoshii, Kasada et al. 2014). Our findings here, which evaluate AKT-driven
pre-T LBL, strengthen the inference that development of thymic pre-T LBL may depend
on mTOR.
CDK6 protein was reduced in the mTOR KD lymphomas and treatment of WT
pre-T LBL with rapamycin also led to reduced CDK6, highlighting the mechanistic role of
mTOR in affecting CDK6 levels in the tumors. In contrast to CDK6, expression cyclin
D3 was lower in WT tumors compared with KD tumors. These differences were limited
to lymphomas, as the two proteins had similar expression in the WT and KD pre-tumor

54

thymi. It is tempting to speculate that the differences in CDK6 and cyclin D3 expression
were selected during lymphomagenesis. Since pre-T LBL from the WT and KD mice
were susceptible to pharmacologic inhibition of mTOR and CDK4/6 and they share
similarities with human T-ALL/LBL, including upregulation of the PI3K/AKT pathway, we
tested the sensitivity of human T-ALL/LBL lines to combined inhibition of mTOR and
CDK4/6 pathways. CDK4/6 inhibitors, including PD-0332991, are in clinical trial for a
variety of cancers, including acute leukemias (Choi and Anders 2014). CDK4/6
inhibition is particularly relevant because primary human T-ALL/LBL samples have high
levels of CDK6 protein by immunohistochemistry (Chilosi, Doglioni et al. 1998), and
cyclin dependent kinase inhibitors such as Cdkn1a (p21), 1b (p27) and Cdkn2a (p16)
are often deleted or absent by immunohistochemistry in T-ALL/LBL (Yamada, Hatta et
al. 1997). In addition, Notch activating mutations, which occur commonly in T-ALL/LBL,
can induce the expression of cyclin D3, which, when it interacts with CDK6, leads to
aberrant cell cycle progression (Hu, Deshpande et al. 2011, Sawai, Freund et al. 2012).
In this study, the human T-ALL/LBL cell lines evaluated had relatively high baseline
levels of CDK6 and phospho-RB proteins. Furthermore, we found that the combination
of the mTOR inhibitor, rapamycin, and the CDK4/6 inhibitor, PD-0332991, was active
and cooperative in all eight T-ALL/LBL cell lines examined. In breast cancer, combined
treatment with PI3K and CDK4/6 inhibitors has been found to be synergistic, especially
in tumors that harbor PIK3CA mutations (Vora, Juric et al. 2014), underlining the
potential relevance of combination treatment of neoplasms with hyperactive
PI3K/ATK/mTOR and CDK4/6 signaling. One potentially important signaling effect of the
combination of mTOR and CDK4/6 inhibitors in the T-ALL/LBL lines was the decreased

55

levels of phospho-RB. In addition, our data suggest that, when used in combination
with the CDK4/6 inhibitor, PD-0332991, a dual mTORC1/mTORC2 inhibitor, PP242,
may reduce the levels of phospho-RB and phospho-AKT as well as the viability of
some, but not all, T-ALL/LBL lines to an even greater degree than the combination of
PD-0332991 and the mTORC1 inhibitor, rapamycin. The potential therapeutic
advantage of adding an mTORC1/TORC2 inhibitor in combination with CDK4/6
inhibition should be considered in the treatment for T-ALL/LBL.

56

CHAPTER 4- A rare, naturally occurring SNP in Mtor (C1977T) is
associated with increased sensitivity to stress at the cellular and
organismal level
Introduction
mTOR, the mechanistic target of rapamycin, is a serine/threonine kinase at the
center of numerous cell signaling pathways involved in cell growth, energy metabolism,
protein and lipid synthesis, and autophagy. mTOR belongs to a family of
serine/threonine kinases (Phosphatidylinositol 3-kinase-related kinases (PIKKs)) that
includes ataxia-telangiectasia mutated (ATM), ataxia- and Rad3 related (ATR), and
DNA-dependent protein kinase catalytic subunit (DNA-PKcs) [(Lempiainen and
Halazonetis 2009), (Hardt, Chantaravisoot et al. 2011)], which are integral members of
the stress and DNA damage repair (DDR) signaling pathways. The role of mTOR in
DDR, however, has not been clearly elucidated. In yeast, TORC1 signaling is needed
for cells to progress through S-phase and for cell viability after genotoxic stress (Shen,
Lancaster et al. 2007). In mammals, mTOR has been shown to incorporate stress
signals, including low energy, hypoxia, and DNA damage, often through TSC1/2
[reviewed in (Laplante and Sabatini 2012)]. DNA damage, in particular, has been shown
to signal mTORC1 through p53-dependent transcription, including induction of TSC2
and PTEN expression [(Feng, Zhang et al. 2005), (Stambolic, MacPherson et al.)],
though the interactions between mTOR and p53 have proven to be complex and
redundant. Evidence of mTOR’s role in DDR is also found in neoplasia, where mTOR
inhibitors have been reported to have a radiosensitizing effect, allowing the tumors to
57

respond more completely to radiation treatment, including soft tissue sarcomas
(Murphy, Spalding et al. 2009), breast cancer (Albert, Kim et al. 2006), and pituitary
adenomas (Vender, Dhandapani et al. 2011). The association between mTOR
inhibition and increased sensitivity to irradiation supports the role of mTOR in DNA
damage and cell stress responses.
Increased sensitivity to DNA damage can be an inherited phenotype. Many
tumor syndromes are associated with mutations or alterations in genes involved in
DDR, including Fanconi Anemia, Bloom’s syndrome, and breast cancer families with
BRCA1 mutations (Ford, Easton et al. 1994, Jackson and Bartek 2009). In mice,
BALB/c mice, in particular, are hypersensitive to irradiation, with decreased survival
post-irradiation (Roderick 1963, Okayasu, Suetomi et al. 2000), and a higher rate of
radiation-induced mammary tumors (Yu, Okayasu et al. 2001). Mammary cells from
BALB/c mice exposed to 3 Gy irradiation exhibited higher rates of chromosomal
aberrations than cells from C57Bl/6 mice, especially in later passages (Ponnaiya,
Cornforth et al. 1997). Similarly, skin fibroblast lines from a variety of mouse strains
were evaluated for radiation-induced chromatin damage; fibroblasts from BALB/cAN
had the highest number of chromatid breaks, and continued to have the most breaks 4hours post irradiation (Potter, Sanford et al. 1988). Differences in chromatid breaks
seen in skin fibroblasts from BALB/c mice versus DBA mice were linked to genes on
chromosomes 1 and 4. Lower levels and activity of DNA-PKs associated with a
polymorphism in the gene Prkdc (DNA-dependent protein kinase catalytic subunit) have
also been proposed as a cause for decreased DDRs in BALB/c mice (Okayasu,
Suetomi et al. 2000, Yu, Okayasu et al. 2001). In this study, we propose that a rare SNP
58

in the Chr 4 gene, Mtor, found in BALB/c and NZB mice is another possible cause for
decreased DDRs in BALB/c mice.
Using our mouse model containing the BALB/c allele of Mtor (C1977T; R628C),
we evaluated the effect of the altered variant of mTOR, which has an amino acid
substitution at aa628 (628C). Specifically, we compared the role of the allelic variants
R628 and 628C in response to three different types of stress (capable of putting
selection pressure on neoplastic cells): inflammatory, genotoxic and oncogenic.
Materials and Methods
Mice. All animal studies were in compliance with NIH Animal Care and Use Committee
Animal Study Protocol LG009. To explore the consequences of the single nucleotide
polymorphism in mTOR naturally found in BALB/c mice, transgenic mice were created
with a SNP (C1977T) in the Mtor gene through homologous recombination on a B6;129
background [knock in (Zhang, Readinger et al. 2011)]. These knock in mice were
genotyped as previously described (Zhang, Readinger et al. 2011).
3 WT mice and 3 628C KI mice were injected intraperitoneally with 0.4 ml
pristane and were euthanized after 7 days. Untreated WT and KI mice (3/group) served
as controls and were collected at the same time. Spleens and bone marrow were
collected fresh from these mice and processed for transcriptional analyses.
Six WT, 7 heterozygous (HET), and 7 628C KI male mice were irradiated at 8 Gy
at approximately 60 to 75 days of age in a Gammacell 40 irradiator (Best Theratronics,
Ottowa, ON, Canada). Mice were observed over time, and were collected at a humane
endpoint. Survival was analyzed by a Kaplan-Meier survival curve and a Log Rank Test.

59

Another cohort of male WT (n= 57) and 628C KI (n= 39) mice were irradiated starting at
5 weeks of age with 1.75 Gy gamma irradiation, once weekly for 4 weeks. These mice
were also observed over time for survival and for the formation of thymic lymphomas.
Because the mice began to develop rectal prolapses, the feed was supplemented with
metronidazole (138 mg/kg of chow, fed ad libitum) to eliminate causative infections.
Isolation of keratinocytes from newborn WT and 628C KI pups, expansion and
Ras transformation of these keratinocytes, and grafting of the keratinocytes onto nude
mice was performed by Christophe Cataisson of Stuart Yuspa’s Laboratory (Laboratory
of Cancer Biology and Genetics, NCI), as previously described (Lichti, Anders et al.
2008).
Microarray and RT-PCR. B220+ splenocytes and bone marrow cells were collected
from WT and 628C KI mice. Three WT mice (2 females and 1 male) were untreated,
three (2 females and one male) were treated with 0.4 ml pristane intraperitoneally and
were harvested 7 days later. Spleens were crushed using the sterile end of a syringe
plunger and dissociated cells were resuspended in cold 1X PBS and filtered through a
0.40 µm sterile filter. ACK lysis buffer (Lonza, Walkersville, MD) was added to lyse red
blood cells. B220+ splenocytes were then isolated using MS MACS separation columns
and B220+ beads (Miltenyi Biotec, Auburn, CA) as recommended by the manufacturer.
Bone marrow cells were collected by cutting off the ends of the femur bones and using
a 30 ½ G needed and 6 ml syringe to flush sterile, ice-cold PBS through the marrow
cavity. ACK lysis buffer was used to remove red blood cells from the collected marrow
contents. Cell pellets from B220+ splenocytes and bone marrow were flash frozen and
stored at -80oC until RNA isolation.

60

RNA was isolated using Trizol reagent and the Qiagen RNeasy MiniElute
Cleanup kit (Qiagen). 1 μg of RNA was labeled and amplified using the Message Amp11-Biotin Enhanced Kit (Ambion, Life Technologies, Carlsbad, CA) per the
manufacturer’s instructions. RNA was hybridized to Affymetrix Mouse Genome 430 2.0
array cartridges at 45oC for 16 hours. Chips were washed in a GeneChip Fluidic wash
station (Affymetrix, Santa Clara, CA) and scanned.
Partek software was used to analyze the .Cel files obtained when the arrays
were scanned. Data were normalized to internal controls and an ANOVA comparing
WT and 628C KI was performed. Significantly different genes between WT and 628C KI
mice were selected with values for WT + KI signals > 100 (higher than background), pvalues <0.05, and a fold change >1.5 or <-1.5. Principal component analyses were also
performed in Partek.
Cell culture. Mouse embryonic fibroblasts (MEFs) were created from 13.5 day post
conception WT and 628C KI embryos. The embryos were separated, the heads and
internal organs removed, and the remaining tissues were macerated in 5 ml TrypsinEDTA (Gibco, Life Technologies, Grand Island, NY). The dissociated tissue was
incubated at 37oC in the Trypsin-EDTA for 15 minutes, and then the remaining
fragments were pipetted up and down to break up the cell debris. Cells were cultured
overnight in 10cm dishes in DMEM (Gibco) supplemented with 10% fetal bovine serum
(FBS) and 1% penicillin-streptomycin (Gibco). Media was changed the following day,
and MEFs were expanded for two passages and frozen for future use.
A subset of MEFs were transformed using the SV40 Large T Antigen. The
pBAB2 -SV40 plasmid (shared by Dr. Andre Nusswenzweig) was amplified in OneShot

61

TOP10 Chemically Competent E. Coli (Invitrogen, Life Technologies, Grand Island, NY)
and isolated using the HiSpeed Plasmid Purification Midi and Maxi Kit (Qiagen, Venlo,
Netherlands). The plasmid was first passaged through BOSC packaging cells cotransfected with the PCL2-eco- retrovirus packaging vector (shared by Dr. Andre
Nusswenzweig) with the addition of Fugene6 (Promega, Madison,WI). The BOSC cells
produced virus for 48 hours, at which point viral supernatant was collected and mixed
with 10 µg/ml polybrene (EMD Millipore, Billerica, MA). The polybrene-spiked viral
supernatant was placed over plated MEFs, which were spun at 2500 rpm for 90
minutes. Selection was performed by the inclusion of 1 mg/ml G418 sulfate (Corning;
Cellgro, Manassas, VA) in the media over several days. Transformed MEFs were
expanded under antibiotic selection and viably frozen for downstream applications.
Transformed MEFs were used in colony formation assays, in which cells were
plated in a 10cm dish, allowed to grow to confluency, and were irradiated at 2, 4, 6, or 8
Gy in a cesium sealed source irradiator (Shepherd model 68, dose rate approx 3
Gy/min). Irradiated cells were trypsinized and 1000 cells of each genotype treated with
each dose were plated in 10cm dishes in triplicate. Colonies allowed to form over 10
days were fixed in ice cold methanol and stained with a 0.5% crystal violet solution in
25% methanol. Colonies of greater than 50 cells were counted. Colony counts for
untreated and treated cells were used to calculate the plating efficiency [average # of
colonies for the three untreated dishes per sample/1000 (the number of cells plated)]
and the surviving fraction [average # of colonies for three dishes per
sample/(1000*plating efficiency for sample)].

62

Comet Assay. Fresh bone marrow cells from WT and 628C KI mice were collected and
samples were split in half. One half of the sample was irradiated at 6 Gy, and the other
served as a control. Cells were spun down and resuspended in 37 degree low melting
agarose (CometAssay LMAgarose, Trevigen, Gaithersburg, MD) following the
manufacturer’s instructions and were replated onto CometSlides (Trevigen). After lysis
(in Lysis Solution, Trevigen) and unwinding (in an alkaline unwinding solution, 0.4g
NaOH and 250 μl of 200 mM EDTA), slides were placed into an alkaline electrophoresis
solution (pH>13) in the CometAssay Electrophoresis II unit (Trevigen) and were
electrophoresed for 30 minutes at 21 V, per the manufacturer’s instructions. Slides were
rinsed in 70% EtOH and deionized water and dried overnight. The following day, slides
were stained with 1X Sybr Gold (Life Technologies) and imaged at 10X on a fluorescent
scope. In captured images, at least 50 comets were scored using CometScore (TriTek
Corporation). Comet analysis results are here reported as Tail moment, which is a
measurement of tail migration distance as well as the percent DNA in the tail.
Immunoblotting, immunohistochemistry, and immunofluorescence. Primary MEFs
were plated into 10cm dishes and allowed to expand for 1 passage. Cells were then
plated in T25 flasks, which were irradiated once confluent. Media was removed and
flasks were frozen at the appropriate time points. Lysis buffer, composed of 10% SDS,
1% tris, phosphatase inhibitor (PhosStop, Roche), and cOmplete protease inhibitor
(Roche), was pipetted directly onto frozen cells, and a rubber scrapper was used to
remove cells. The samples were then sonicated on high for 7.5 minutes, with 0.5
minutes on, 1 minute off intervals and were allowed to incubate on ice for 1 hour.
Samples from both preparation methods were centrifuged at 12,000 rpm at 4oC for 20

63

minutes, and the supernatant, containing the proteins, was saved. Protein
concentration was measured by BCA assay and 12 µg protein for each sample was
electrophoresed on 4-12% Bis-Tris gels (Novex). Proteins were transferred to
nitrocellulose membranes using the iBLOT (Invitrogen), and membranes were blocked
in 10% milk/TBST (TBS plus .1% Tween-20) for 30 minutes at room temperature,
incubated with primary antibody overnight in 5% BSA/TBST at 4oC, and incubated with
secondary antibody in 5% milk/TBST for 1 hour. Rinsed membranes were incubated for
1 minute with Super Signal West Dura or Femto Extended Duration Substrate and were
imaged using a Syngene Imager and the GeneSnap program from Syngene (Frederick,
MD).
Immunohistochemical staining for cleaved caspase 3 was performed on 4%
paraformaldehyde-fixed, paraffin embedded sections of small intestine and bone
marrow from 3 irradiated WT and 3 irradiated 628C KI mice (irradiated at 8 Gy starting
at 8 weeks of age). Slides were deparaffinized in xylene and rehydrated through graded
alcohols. The slides were blocked in 3% hydrogen peroxide in methanol, and antigen
retrieval was performed in a bath of pH 9.0 Target Retrieval solution (Dako, Atlanta, GA)
incubated in a hot vegetable steamer (steam retrieval) for 15 minutes. Slides were
allowed to cool, and then incubated with Background Buster (Innovex Biosciences,
Richmond, CA). The primary antibody was used at a concentration of 1:300 in antibody
diluent (Dako) overnight at 4oC. After rinsing in 1X PBS with .02% Tween-20 (SigmaAldrich), slides were incubated with goat-anti rabbit secondary antibody (Dako)
conjugated with biotin. The slides were incubated with ABC reagents (Vector
Laboratories, Burlingame, CA), rinsed, and then incubated with DAB for 7 minutes

64

(diaminobenzidine, Dako). Slides were counterstained with hematoxylin. The stained
slides were dehydrated through graded alcohols and xylene, cover slipped, and imaged
with the AT2 slide scanner (Aperio, Leica Biosystems, Buffalo Grove, IL). The
ImageScope color deconvolution algorithm (Aperio, Leica Biosystems) was used to
analyze the amount of positive pixels from DAB labeling (categorized as strong,
moderate, and weak labeling) in the bone marrow and in the crypts of the small
intestine.
Primary WT and KI MEFs were plated onto chamber slides pre-treated with Llysine and allowed to adhere overnight. Slides were irradiated and media was removed
at the appropriate time point. Cells were fixed in 4% paraformaldehyde, rinsed, and
blocked with 1X PBS containing 1% BSA. MEFs being stained for F-actin were
incubated with Texas red-conjugated phalloidin (Life Technologies) and mounted with
Vectashield mounting media containing DAPI (Vector Laboratories). MEFs to be
labeled for PKCα were permeablized with 0.01% TritonX-100, blocked with 10% goat
serum in 1X PBS, and labeled with the PKCα antibody (1 to 400 dilution) overnight at
4oC. The slides were rinsed and incubated with the secondary antibody, conjugated to
FITC, and coverslips were mounted with Vectashield mounting media + DAPI. Slides
were imaged with an Olympus Fluorescent scope at 40X.
Flow cytometry and proliferation. Apoptosis of irradiated MEFs was evaluated at 3
hours and 18 hours post 4 Gy irradiation using the PE Annexin V Apoptosis Detection
Kit 1 and cell cycle was analyzed using PI/RNAse staining buffer (Becton Dickson, San
Jose, CA). Cells were analyzed using FACSCalibur (Becton Dickinson), and FlowJo
(Ashland, OR).

65

Irradiated embryonic fibroblasts were plated at 10,000 cells/well in a 96 well plate
and imaged every 6 hours starting 4 hours after 4 Gy irradiation in the intra-incubator
imaging system, Incucyte (Essen Biosciences, Ann Arbor, MI).
Results
Characterization of 628C KI mice. To predict the effect of the rare single nucleotide
polymorphism (SNP, C1977T) in Mtor found in BALB/c mice, which leads to an amino
acid substitution (R628C), the SNP was introduced onto a B6;129 background through
homologous recombination and the affects of injection with pristane were evaluated.
CBC/chemistry panels and histology of multiple tissues before and after pristane
treatment were within normal limits (Figure 47, Appendix A). Evaluation of downstream
targets phospho-4E-BP1, phospho-S6, and phospho-AKT revealed inconsistent
differences in the ability of mTOR to phosphorylate downstream targets in the spleen of
both untreated and pristane-treated WT and 628C KI mice (Figure 48, Appendix A). As
such, the consequences of the 628C amino acid substitution on the function of protein
remained unclear.
The expression levels of microRNAs in the B220+ splenocytes of untreated and
pristane-treated WT and 628C KI mice were also evaluated. Nanostring microRNA
analysis (which uses molecular barcodes for individual miRNAs similar to a microarray)
was performed on RNA isolated from B220+ splenocytes of both 628C KI and WT mice.
Three microRNAs, miR-30a, miR-101, and miR-423-5p, were significantly increased in
splenocytes of untreated KI versus WT mice by Nanostring (Figure 49, Appendix B). No
differences were found in these miRNAs in the pristane-treated animals. All three
miRNAs were predicted to regulate members of the mTOR pathway by Ingenuity

66

Pathway Analysis (IPA, Qiagen). The trend of up regulation of these miRNAs in KI mice,
as seen by Nanostring, was similar in RT-PCR evaluation in multiple animals, but was
not statistically significant, bringing into question the role of miRNAs for this model
(Figure 49, Appendix B).
Finally, because mTOR is involved in cellular metabolism, we assessed the
levels of glycolysis in mouse embryonic fibroblasts (MEFs) using Seahorse XF
Glycolysis Stress Test, both primary and immortalized by SV40 (transformed) in WT,
mTOR KD, and 628C mTOR KI fibroblasts. In transformed fibroblasts, glycolysis (as
measured by the glycolytic capacity) was significantly decreased in mTOR KD cells
compared to mTOR WT cells (Figure 50, Appendix C), though there was no difference
in glycolysis in untransformed MEFs. Further experiments were not pursued since
differences were not noted between untransformed WT and KI MEFs.
Predicted effects of 628C allele. To predict the effect of the 628C aa substitution on
the function of the protein mTOR, two computer algorithms were used. The algorithms
used by the site Polyphen [http://genetics.bwh.harvard.edu/pph/ (Adzhubei, Schmidt et
al. 2010)] reported a 99% probability that the mutation is damaging to the protein.
Similarly, the algorithm used at the Panther database [http://www.pantherdb.org;
(Huaiyu Mi 2012)] describes a probability of 93% that the mutation is deleterious.
Based on modeling performed by Aron Marchler-Bauer and Gabi Marchler, in the
Conserved Domain Database group (NCBI, NIH), the amino acid substitution is
predicted to fall within a HEAT domain of the protein. HEAT domains are sites in
proteins that tend to form curves; they are also often sites of protein-protein interaction
(Perry and Kleckner 2003), suggesting that this amino acid substitution may affect

67

protein-protein binding. A SNP leading to an amino acid substitution at the same
location in the protein mTOR (amino acid 628) has been reported in human colon
cancer [COSMIC, Catalog of the Somatic Mutations In Cancer,
http://cancer.sanger.ac.uk/cancergenome/projects/cosmic/ (Forbes, Bindal et al. 2011)];
the arginine was replaced by a histidine, and was again predicted to be deleterious to
protein function (Polyphen, Panther).
Transcriptional differences in cells exposed to inflammatory stress. Because
mTOR has been associated with plasma cell tumor formation in BALB/c mice after
intraperitoneal (IP) pristane injection, we examined the transcriptional profile of bone
marrow and B220+ splenocytes (splenic B-cells) 7 days after IP pristane injection.
Microarray analysis revealed 268 differentially expressed genes between pristanetreated wild-type mTOR mice (WT), and knock in 628C mTOR mice (KI) in B220+
splenocytes (141 upregulated and 127 downregulated in KI), and 2511 differentially
expressed genes between WT and KI whole bone marrow (902 upregulated and 1609
downregulated in KI). Principal component analysis of differentially expressed genes
indicated the largest difference between WT and KI cells in the bone marrow from
pristane-treated mice (Figure 30), so we chose to focus on the bone marrow. Ingenuity
Pathway Analyses (IPA, Qiagen), a knowledge-based network analysis tool, identified
enriched networks in differentially expressed genes from the bone marrow of pristanetreated mice (Table 2 and Appendix D). DNA replication, recombination, and repair was
a top enriched pathway (number of molecules = 182, p-value range = 1.87 E -02 to
2.31E-06; subnetworks and individual p-values displayed in Appendix D). We chose to
focus on DNA replication, recombination, and repair because of mTOR’s association

68

with the DNA damage response (DDR), the sensitivity of BALB/c mice to DNA damage,
and the relevance of DNA damage to cancer.
A

B

C

Figure 30: Principal components analyses of genes from tissues of the nonpristane-treated animals (A), pristane-treated animals (B), and bone marrow of
pristane-treated animals (C); the genes are most different in the pristane-treated
bone marrow. KI is short for 628C knock in mice, and WT is short for wild-type
animals.

69

Table 2: Top enriched molecular and cellular function networks in bone marrow
from pristane-treated animals identified by Ingenuity Pathway Analysis. P-values
are listed as a range because each network includes subnetworks, which have
individual p-values. Subnetworks and individual p-values displayed in Appendix D.
Top Enriched Networks in BM
P-Values
# of Molecules
1

Cell Morphology

1.91E-02 to 2.09 E-08

184

2

Small Molecule Biochemistry

1.78E-02 to 5.35E-06

108

3

1.87E-02 to 2.31 E-06

182

4

DNA Replication, Recombination, and
Repair
Molecular Transport

1.38E-02 to 8.39E-06

59

5

Gene Expression

1.15E-02 to 1.02E-05

49

Of the differentially expressed genes identified by IPA in the DNA replication,
recombination, and repair network, several genes fell under the category of DDR (Table
3, Appendix D, Table 6). Many of these genes were downregulated in the 628C KI mice.
Of these genes, loss of Fancd2, Fancg, Wrn, and Brca1 are associated with decreased
DDR and increased tumor formation in human patients (Ford, Easton et al. 1994,
Niedernhofer, Lalai et al. 2005, Jackson and Bartek 2009). FANCD2 in particular, is a
hub in the network of Fanconi Anemia proteins, which are involved in interstrand
crosslinking DDR (Niedernhofer, Lalai et al. 2005). A decrease in expression of
Fanconi anemia genes Fancd2, Fancc, and Fancg was confirmed by real time PCR
(RT-PCR) in samples from the bone marrow of pristane-treated mice used in the
microarray, but was not consistently different in bone marrow from additional pristanetreated animals (Figure 31).

70

Table 3: Differentially expressed genes associated with DNA damage response (z
score = 0.864, p-value of overlap = 0.002) identified by Ingenuity Pathway
Analysis in bone marrow from pristane-treated mice. Fold change is for KI gene
expression in relation to WT expression.
Gene
Fold Change Gene
Fold Change Gene
Fold Change
ALKBH8

-1.5

FANCD2

-1.892

RAD23A

-2.804

ATF2

-2.5

FANCC

- 2.0

RBM38

-1.762

ATRX

-2.4

FANCG

-1.894

SIRT2

2.602

BRCA1

-1.941

HIPK1

-2.437

SOX10

-2.100

BTG2

-2.672

IKBKG

-1.926

STRA13

1.9

CASP9

-1.808

IRF3

1.823

STXBP4

-1.8

CHCHD6

1.8

MAPKAPK2

-1.6

TAOK1

-2.158

CHEK1

-1.878

MBD4

1.661

TLK2

-2.040

CIB1

1.741

MIF

1.874

TOP1

-3.933

CUL4A

-1.882

NEK1

-1.794

TRIP12

-1.6

DCK

-2.1

Paxip1

-1.652

UBE2T

1.531

DDIAS

-1.9

POLH

-4.417

WRN

-2.398

DTL

-2.4

PSME4

-2.2

YY1

-1.669

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Figure 31: Fancd2, Fancc, and Fancg transcripts are lower in bone marrow from
pristane-treated KI mice by RT-PCR in samples from microarray analysis, but not
in additional animals. 2^-ΔCT values for 3 individual WT and 4 KI samples are shown
for each gene from the microarray, and 3 WT and 3 KI samples are shown for additional
bone marrow samples. P-values are based on Student T-test.

Phenotypic changes associated with DNA damage. Because of the differential
expression of DNA replication, repair, and response genes identified by transcriptional
profiling in mTOR 628C KI mice, and because BALB/c mice, which carry the SNP in
Mtor, are hypersensitive to DNA damage, we evaluated the response of the mTOR WT
and 628C KI mice to DNA damage through a lethal total body irradiation (TBI) dose of 8
Gy. WT, heterozygous (HET), and KI mice were irradiated in 3 separate studies and
were evaluated for survival. The KI mice had significantly decreased survival, with 20%
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of KI mice surviving compared to approximately 80% of WT mice (Figure 32,
representative experiment). Tissues collected at 18 days post irradiation revealed
hemorrhage and severe pancytopenia in the bone marrow in both WT and KI mice
(Figure 33). CBC revealed severe anemia (15 to 20%, normal range = 33-52%) and
pancytopenia. Additional findings included testicular degeneration, lympholysis in
lymph nodes, marked extramedullary hematopoesis in the spleen with a large
population of atypical, highly-proliferative round cells, likely erythroid or myeloid
precursor repopulating the spleen and compensating for loss of bone marrow
precursors.

Figure 32: Kaplan-Meier survival curve for mTOR WT, heterozygous (Het), and
628C KI mice treated with 8 Gy gamma irradiation. P-value is from the Log-Rank
test. A representative experiment is shown.

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A

B

Figure 33: Severe bone marrow depletion (pancytopenia) in irradiated mice
collected 18 days post 8 Gy total body irradiation (A), in comparison to untreated,
aged-matched mice (B). Images taken at 10 X. Representative mice shown (findings
are similar for WT and KI mice).

Apoptotic cells, characterized by pyknosis and karyorrhexis, were apparent in
bone marrow and crypts of the small intestine, 3 hours post 8 Gy TBI, from both WT and
628C KI mice (n = 3 each). Immunohistochemical staining for cleaved caspase 3, a
marker of apoptosis, and analysis by color deconvolution in Aperio ImageScope,
showed no difference in levels of cleaved caspase 3 labeling between WT and KI mice
in the bone marrow, and slightly less labeling in small intestinal crypts of KI mice,
indicating a similar level of apoptosis in WT and KI mice at this time point postirradiation (Figure 34).

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Figure 34: Cleaved caspase 3 labeling in WT and KI bone marrow and small
intestines, with quantification of labeling by color deconvolution (% positive
pixels). Sections of bone marrow and small intestine counterstained with hematoxylin
and labeled with DAB. Lableing was characterized as strong positive, medium, and
weak positive. Images captured at 20X on Aperio ImageScope.

Assessing DNA damage by Comet Assay in bone marrow treated ex vivo. Bone
marrow cells from WT and 628C KI mice were collected. Each sample was divided in
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two, and one half was irradiated ex vivo at 6 Gy and collected at 2.5 hours postirradiation for analysis by Comet Assay (the untreated cells served as individual controls
for each sample). The Comet Assay assesses the amount of DNA damage present in
individual cells by suspending the cells in agarose and subjecting them to an electrical
current. In cells with greater damage, fragmented DNA migrates farther through the
agarose, creating a longer comet tail. In this assay, KI bone marrow cells had a greater
average tail moment (p = 0.1) than WT cells, indicating greater DNA damage than WT
bone marrow cells (Figure 35A,B).
A

Untreated

6 Gy

WT

KI

Figure 35A: Representative comets from untreated and irradiated (6 Gy) WT and
628C KI bone marrow cells 2.5 hours post irradiation.

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B

Figure 35B: Comparison of the average tail moment from WT and KI irradiated
bone marrow cells. Error bars represent standard error and the average is for >50
comets/sample. Tail moments were normalized to untreated controls for each sample.
Assessing DNA damage by Comet Assay and micronuclei in mouse embryonic
fibroblasts. Mouse embryonic fibroblasts (MEFs) were created from mTOR WT and
628C KI mice. MEFs were irradiated at 4 Gy and collected for Comet Assay directly
after irradiation (5 minutes) and one hour post irradiation. Like the KI bone marrow, KI
MEFs had a significantly greater average tail moment at 5 minutes (p=0.001, Student’s
T-test) and one hour (p<0.001) after irradiation, indicating increased damage and
suggesting decreased repair of the damage (Figure 36).

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Untreated
A

5 Minutes

60 Minutes
C

B

WT
D

E

F

KI

*

**

Figure 36: Representative comets from untreated and treated WT and KI MEFs at
5 minutes and one hour after 4 Gy gamma irradiation, and comparison of average
tail moment from WT and KI MEFs at these time points. Time points with
significantly different tail moments are marked with stars. Error bars represent the
standard error of the mean from 50 assessed comets for each time point.

Finally, micronuclei are fragments of DNA that break off from the chromosomes
during cell division when there is DNA damage in a cell (Fenech, Kirsch-Volders et al.
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2011). Percent cells with multinuclei can be used as a measurement of DNA damage,
and thus genotoxicity. Micronuclei were counted in 500 DAPI-stained nuclei from WT
and 628C KI MEFs at each time point post 4 Gy gamma irradiation. At all time points
post irradiation, KI MEFs had a greater percentage of cells with micronuclei, with the
greatest difference between WT and KI occurring at later time points (12 and 24 hours,
Figure 37), again suggesting greater DNA damage and less repair in 628C KI cells.

Figure 37: Percent cells with micronuclei for WT and KI MEFs irradiated at 4 Gy
and collected at time points post irradiation. Percent cells with micronuclei out of
500 observed cells, normalized to untreated controls. Also pictured are representative
DAPI stained nuclei with micronuclei (40X magnification). Blue arrows point to example
micronuclei.

Assessing DNA damage by colony formation in transformed MEFs.

Mouse

embryonic fibroblasts (MEFs) from both WT and KI mice were immortalized with SV40
large T antigen and were exposed to a range of doses (0-8 Gy) of gamma irradiation. A
low number of cells irradiated at each dose were plated and colonies were allowed to
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form over 10 days. Stained colonies were counted and the surviving fraction was
calculated for WT and KI MEFs. Fewer colonies developed in KI plates at each dose of
irradiation (2 Gy, 4 Gy, and 6 Gy; Figure 38A). As such, KI MEFs had significantly lower
surviving fractions at each dose of irradiation (2 Gy, p =0.007; 4 Gy, p = 0.001; 6 Gy, p
=0.006; Student’s T-test, Figure 38B).

A

B

Figure 38: Colony formation and surviving fraction of transformed WT and KI
MEFs 10 days after 2, 4, 6, and 8 Gy gamma irradiation. A. Colonies of transformed
MEFs, stained with crystal violet, grown from 1000 cells/dish in the 10 days post
irradiation at 2, 4, and 6 Gy. Also shown is the untreated control (0). B. Surviving
fraction of transformed MEFs, calculated from colony formation at 10 days post
irradiation. Significant difference between WT and KI was determined by Student T-test
and is indicated by a star and p-value. Error bars represent standard error of the mean.
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DNA damage response proteins following irradiation in MEFs. DNA damage
response proteins and downstream signaling of mTORC1 and mTORC2 were evaluated
by immunoblotting at different time points up to 6 hours post 4 Gy irradiation in primary
MEFs. ATM, which is in the same protein family as mTOR and is one of the first
proteins activated in DDR was decreased at all time points in KI MEFs. Levels of
FANCD2 were increased by 30 minutes until 3 hours post-irradiation in WT MEFs;
FANCD2 levels in the KI MEFs were not detectable until 1 hour post irradiation and
remained low (Figure 39). These results were consistent with the low levels of Fancd2
transcripts in bone marrow from pristane-treated KI mice. Phospho-p53 levels at Serine
15 and total p53 levels (data not shown) were similar both before and after treatment.

Figure 39: Immunoblot of DDR proteins at 30 minutes, 1 hour, 3 hours, and 6
hours post 4 Gy gamma irradiation in mTOR WT and 628C KI primary MEFs.
Untreated samples are included as controls.

Downstream targets of mTOR following irradiation in MEFs. Interestingly, while
phospho-p70-S6K was increased in WT MEFs with time post irradiation, indicating

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increased mTOR activity in irradiated cells, it was in low abundance in both untreated
and irradiated KI MEFs, showing no change following irradiation. A similar, more
dramatic pattern was apparent for all three phosphorlyation sites in PKCα (PRKCα),
which increased in WT MEFs with time post irradiation, but were low and did not change
in KI MEFs (Figure 40). The main role of PKCα is in maintaining cytoskeletal structure
(Sarbassov, Ali et al. 2004), though PKCα is also involved in apoptosis (Lista, Bertness
et al. 1997). As such, PKCα localization and cytoskeletal structure (F-actin) were
assessed in WT and KI MEFs by immunofluorescence post irradiation. PKCα remained
localized within the cytoplasm of MEFs after irradiation (Figure 41) and F-actin patterns
were unaltered by irradiation in WT and KI MEFs at all time points (Figure 42, untreated
and 6 hours post irradiation, representative images). Apoptosis and cell cycle were
assessed by flow cytometry at 3 and 18 hours post 4 Gy irradiation, and no differences
were noted in post-irradiation apoptosis or cell cycle at either time point (See Appendix
E, Figure 51, 52)

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Figure 40: Downstream targets of mTORC1 and mTORC2 at time points post 4 Gy
irradiation in WT and 628C KI MEFs. Representative diagrams of the main targets of
mTORC1 and 2 are also included for reference.

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WT

KI
Untreated

6 Hrs post
4 Gy

Figure 41: PKCα labeling in untreated and 4 Gy-irradiated WT and 628C KI MEFs 6
hours post irradiation. Green fluorescent signal is PKCα, while the blue signal is
DAPI. Images are taken at 40X magnification.

Figure 42: Labeling for F-actin in untreated WT and 628C KI MEFs, and in WT and
KI MEFs 6 hours post 4 Gy irradiation. F-actin is in red, while nuclei are blue (DAPI).
Images were taken at 40X magnification.

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Proliferation. PKCα has also been shown to play in role in cell proliferation in
endometrial cancer (Haughian and Bradford 2009), colon cancer cells (ScaglioneSewell, Abraham et al. 1998) and human osteoblasts (Lampasso, Marzec et al. 2002).
Proliferation was assessed in primary WT and KI MEFs by observing cell growth and
confluency every 6 hours in the Incucyte (Essen Bioscience) post irradiation at 2 Gy and
at 4 Gy. At 2 Gy, proliferation was suppressed post irradiation in comparison to
untreated cells in the WT MEFs (Figure 43), but not in the KI MEFs (p <0.001 , Student
T-Test). Proliferation was mildly suppressed at 4 Gy in WT MEFs compared to KI MEFs
(p = 0.003).

Figure 43: Proliferation based on percent confluence in untreated and irradiated
WT and 628C KI MEFs. Red lines are for KI MEFs, while blue lines are for WT MEFs.
Percent confluence values are the average of 45 wells/sample and error bars represent
standard error of the mean. P-values are by Student’s T-test.

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Irradiation-induced thymic lymphoma. To further evaluate the role of the altered
628C mTOR protein in the DDR and in neoplasia, we used a well-known model of tumor
formation in mice, in which mice are exposed to fractionated doses of irradiation starting
at 5 weeks of age and continuing to receive small doses once weekly for four weeks.
This schedule of fractionated irradiation induces the formation of thymic lymphomas in
many strains of mice (Kominami and Niwa 2006, Zhao, Zhou et al. 2011). We irradiated
our mTOR WT (n=51) and 628C KI (n=37) mice following this dosing scheme. Both WT
and KI mice developed thymic lymphomas that spread to multiple tissues throughout the
body including liver, spleen, kidneys, lymph nodes, and occasionally heart. However, KI
mice developed thymic lymphomas at a higher rate and more rapidly than WT mice
(70% survival in KI versus 90% survival in WT mice, p=0.05, Log rank test, Figure 44).
These findings, in conjunction with the proliferation data and the susceptibility of BALB/c
mice with this allele to plasma cell tumor formation, suggested that the 628C allele of
mTOR can function as an oncogene in an environment of inflammatory or genotoxic
stress, perhaps by allowing the accumulation of DNA damage.

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p=0.05

Figure 44: Survival curve of WT and 628C KI mice exposed to fractionated doses
of 1.75 Gy, once weekly for 4 weeks, that developed thymic lymphomas. Survival
was assessed by Kaplan-Meier survival analysis and Log Rank Test.

Ras-transformed 628C KI keratinocytes form larger papillomas more rapidly than
WT keratinocytes. To test the response of the 628C variant of mTOR to oncogenic
stress in a tumor model, we isolated keratinocytes from newborn WT and KI mice. The
keratinocytes were transformed with a mutant RAS and grafted onto the backs of nude
mice. Nude mice with KI cells developed significantly more papillomas and developed
them at a quicker rate (Figure 45) then nude mice with grafts of transformed WT cells.
In addition, papillomas were larger on the KI mice than the WT mice (Figure 45). As in
irradiated MEFs, protein levels of FANCD2 and all three phosphorylation sites for PKCα
were decreased in KI keratinocytes, including those that were RAS transformed (Figure
46); phospho-PKCαT638 had the greatest decrease in KI keratinocytes. As with the
MEFs, this indicated that mTOR signaling downstream of mTORC2 is decreased under
stress conditions, in this case, oncogenic stress.
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Figure 45: Papilloma volume from WT and 628C KI Ras-transformed
keratinocytes grafted onto nude mice.

Figure 46: Immunoblots of FANCD2 and phospho-PKCα (PRKCa) in WT and 628C
KI keratinocytes, both untreated (Un) and Ras-transformed (ras).

Under different types of cellular stress, including inflammatory, genotoxic, and
oncogenic stress, DDR genes and proteins were down-regulated in 628C KI mice and
cells, and 628C KI mice were more sensitive to DNA damage. In addition, downstream
targets of mTOR, specifically phopsho-PKCα, were decreased in KI cells exposed to
irradiation. KI cells proliferated at a greater rate post irradiation and formed larger
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papillomas, and KI mice developed post-irradiation thymic lymphomas, suggesting that
the 628C allelic variant of mTOR is oncogenic under conditions of genotoxic and
oncogenic stress, perhaps due to accumulation of DNA damage.
Discussion
mTOR is a crucial hub at the core of numerous signaling pathways in cells. We
studied the role of an altered form of mTOR in response to stress. To better understand
this role, we used a mouse model with a naturally-occurring single nucleotide
polymorphism in Mtor (C1977T) that leads to a single amino acid substitution (R628C)
in the HEAT domain of the protein, a region which is not well studied. Though mice with
this SNP, such as BALB/c mice, appear to have normal survival under baseline
conditions, these mice have decreased survival and a higher incidence of tumor
formation under conditions of cell stress [(Okayasu, Suetomi et al. 2000) (Yu, Okayasu
et al. 2001) (Ponnaiya, Cornforth et al. 1997)]. In conjunction, several prediction
methods, including online algorithms and protein modeling programs suggest the 1977T
SNP is likely to be damaging to the function of the protein.
Using transcriptional profiling under pristane-induced inflammatory conditions, we
identified DNA replication, recombination, and repair as major enriched pathways in
differentially expressed, often downregulated, genes in mTOR 628C KI mice. The
association of inflammation induced by the oil pristane and DNA damage has been
previously shown, as co-culturing neutrophils with B-cells exposed to pristane induces
DNA strand breaks in the B-cells (Shacter, Lopez et al. 1991). In addition, the mTOR
inhibitor, rapamycin, has been shown to reduce papilloma formation in inflammatory

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skin cancer models by decreasing DNA damage (Dao, Pandeswara et al. 2015) and
subsequently reducing the rate of Ras mutations.
Mice and cells with the 628C allelic variant of mTOR were more sensitive to
irradiation, with decreased survival. Greater damage in KI cells at later time points
suggests a potential decrease in DDR, as well. mTOR has been associated with DDR,
most commonly through interactions with p53 [(Feng, Zhang et al. 2005), (Feng 2010),
(Akeno, Miller et al. 2015), (Cam, Bid et al. 2014)]. However, phospho-p53 was similar
between WT and KI irradiated MEFs, suggesting that in this system, signaling through
mTOR onto DNA damage pathways may be mediated by other genes.
Of the down-regulated genes in the 628C KI bone marrow, a cluster of genes
were associated with the Fanconi anemia pathway, which is involved in interstrand
crosslink repair (Niedernhofer, Lalai et al. 2005), including FANCD2, FANCC, FANCG,
and BRCA1. In both the irradiated KI MEFs and the untreated and Ras-transformed KI
keratinocytes, FANCD2 was decreased compared to WT cells. FANCD2 has been
reported to be regulated by mTOR through a variety of mechanisms, including the NFκB pathway (Guo, Li et al. 2014) and transcriptional regulation (Guo, Li et al. 2014), and
thus is a possible link between the altered mTOR and decreased DDR.
While mTOR inhibition through rapamycin has been shown to decrease the
incidence of tumor formation in inflammatory skin tumor models (Dao, Pandeswara et
al. 2015), and aging mTOR knock down mice (KD) have a lower incidence of tumor
formation (Wu, Liu et al. 2013), mice with the 628C allelic variant in mTOR express
normal levels of mTOR but are more sensitive to tumor formation with perturbation.
Specifically, BALB/c mice develop pristane-induced plasma cell tumors (Potter and

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Wiener 1992) and irradiation-induced mammary tumors (Yu, Okayasu et al. 2001). In
this study, genetically engineered mice with the allelic variant of mTOR were more
susceptible to developing irradiation-induced thymic lymphomas and cells from these
mice lead to larger papillomas when grafted onto nude mice. These findings, in addition
to the sustained proliferation seen in irradiated KI MEFs (compared to suppressed
proliferation in irradiated WT MEFs), suggests that the 628C allelic variant may be
oncogenic under genotoxic stress conditions. Several activating mutations in mTOR
have been described, suggesting that mTOR is a proto-oncogene [(Hardt,
Chantaravisoot et al. 2011) (Grabiner, Nardi et al. 2014)]; typically these mutations are
in the C-terminal region of the protein.
In yeast, TORC2 signaling has been associated with maintaining genomic
stability (Shimada, Filipuzzi et al. 2013), perhaps pointing to a mechanism of decreased
DDR in our model, which had significantly decreased phospho-PKCα downstream of
mTORC2. However, a cursory examination of cytoskeleton structure by ICC and
apoptosis by flow cytometery, which are two cell processes regulated by PKCα, did not
reveal differences in irradiated KI MEFs. Another potential mechanism for decreased
DDR in our model is decreased DNA damage sensing as well as repair mechanisms, as
suggested by the decrease in FANCD2 and other DDR signaling proteins. Given that
studies have found that FANCD2 is controlled by mTOR (Shen, Oswald et al. 2013),
this is a likely connection to pursue. Interestingly, proliferation in the KI MEFs was only
minimally inhibited by irradiation and associated DNA damage, allowing the cells to
continue to grow despite unrepaired mutations. Studies in yeast (Searle, Schollaert et
al. 2004) and cancer suggest that inactivation of Pkcα may contribute to this phenotype.

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These accumulated mutations could lead to further signaling disruption within the cell
and eventually tumorigenesis. Clearly, additional experiments are needed to determine
the mechanism by which the allelic variant is oncogenic.
mTOR signaling is complex and has many different roles in the cell depending on
environmental signals and the input from other signaling pathways. It is likely that the
effect of the 628C allelic variant of mTOR on downstream signaling is multifaceted, and
can have a variety of affects depending on the cellular environment. However, we have
shown that the allelic variant is associated with increased sensitivity to irradiation,
increased DNA damage, a decrease in certain DDR proteins, and that this allelic variant
may serve as an oncogene in situations of genotoxic or oncogenic stress. These
findings support the need for further research into mTOR inhibitors as cancer therapy,
and into mTOR’s role in the DNA damage response.

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CHAPTER 5: Synthesis and Conclusions
mTOR is a crucial cellular switch at the hub of numerous pathways. A variety of
upstream signals such as energy, metabolites, and cell stress can moderate mTOR
signaling, which the cell uses to maintain a delicate balance between catabolic and
anabolic processes, such as growth and autophagy, and proliferation and apoptosis. To
further complicate mTOR signaling, other cell signaling pathways feed into the
PI3K/AKT/mTOR signaling at multiple levels, and a variety of feedback loops fine tune
this signaling. Thus, in evaluating the mTOR pathway, we are gaining insight into a
complicated, multifactorial system that responds dynamically to various cellular inputs;
responses may vary temporally and spatially and among cell types. Mouse models of
decreased and/or altered mTOR protein provide valuable tools to assist in
understanding the consequences of this complicated pathway in vivo.
In these studies, novel mouse models of decreased mTOR (KD) and an allelic
variant of mTOR (KI) were used to explore the role of mTOR in neoplasia and under
stress conditions. The mTOR KD mouse has 70% less functional mTOR protein (Zhang,
Readinger et al. 2011) and can be used as a model of pharmacologic inhibition of
mTOR signaling. Because complete inhibition of mTOR in mice is embryonic lethal,
most genetic models of mTOR inhibition use genetic knock outs of different components
of mTORC1 or 2, such as Rictor or Raptor (Hoshii, Kasada et al. 2014). These models,
however, are only specific to complex 1 or 2, and not to loss of mTOR itself.
By crossing the mTOR KD mice with mice that have T-cell specific hyperactivation
of the PI3K/AKT/MTOR pathway, we were able to determine how cell signaling differed
in T-cell acute lymphoblastic leukemias/lymphomas (T-ALL/LBL) with decreased mTOR
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signaling, and use this information to identify a possible target for chemotherapy in
combination with mTOR inhibitors. The identification of possible combination therapies
is crucial because of the resistance developed by many cells treated with targeted
therapies, which can be lessened by targeting multiple pathways or steps in the same
pathway. Combination therapies are also useful because lower doses of individual
drugs can be given to patients, often with the benefit of lessening side effects. The
cooperative combination of a dual mTOR kinase inhibitor and a CDK4/6 inhibitor that we
found in this study has been shown to be effective in other tumors with hyperactive
PI3K/AKT/mTOR signaling, such a breast cancers with PI3K mutations (Vora, Juric et
al. 2014). However, this combination has not yet been evaluated clinically in T-ALL/LBL.
Future directions for this arm of the project are many fold. An in vivo experiment,
whereby nude mice that received subcutaneous pre-T LBL transplants from WT and KD
mice are being treated with single agents and the combination of an mTOR inhibitor
with a CDK4/6 inhibitor is in progress. Tumors from these mice will be assessed for
apoptosis (by flow cytometry), cell cycle arrest (by flow cytometry), and proliferation (by
immunohistochemistry for KI67 or BRDU). Cell signaling will also be evaluated in these
tumors by immunoblots. Additional steps would include testing this combination on
additional tumor types, both human cell lines and mouse models, and especially those
with hyperactive PI3K/AKT/mTOR pathway signaling to better understand the spectrum
of activity of the combination. Finally, evaluating the biologic effects (apoptosis and
proliferation) of CDK6 knock out and over expression would help elucidate the
mechanism of delayed tumor formation in the mTOR KD mice, which also had
decreased CDK6 levels.

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To evaluate the role of a naturally-occurring single nucleotide polymorphism in
mTOR (C1977T) that leads to an amino acid substitution in the protein (R628C), we
used a mouse engineered to carry the BALB/c variant on a B6;129 mixed genetic
background. This SNP was originally identified in BALB/c mice as one susceptibility
allele for peritoneal plasma cell tumor formation after intraperitoneal injection with the
oil, pristane (Bliskovsky, Ramsay et al. 2003). mTOR mutations were initially thought to
be rare in human cancers, but more mutations have been reported as a result of the
current TCGA projects to sequence collections of different types of tumors. In addition,
mutations in upstream effectors of the mTOR pathway are quite common. Thus, a better
understanding of mTOR mutations and their affects on the protein may shed light on
mTOR’s role in tumorigenesis. In addition, the 628C amino acid alteration occurs in a
HEAT domain of the mTOR protein, a region near the N-terminus that is not well
studied. Further understanding of the function of this region will help us better
understand mTOR’s role in protein interactions.
To emphasize the importance of exploring the role of the SNP in Mtor, we found
that DNA damage response (DDR) genes were down regulated in the bone marrow
cells from pristane-treated 628C KI mice. mTOR has previously been described as
having roles in DDR, though the exact connections are unclear, often through signaling
interactions with the p53 signaling pathway or through specific DDR proteins. We have
found that decreased DDRs in cells with the 628C allelic variant of mTOR is likely
multifactorial, with decreases in DDR proteins such as FANCD2 and ATM, as well as
downstream targets of mTOR such as phospho-PKCα. The combined effects from
each alteration downstream of the 628C variant of mTOR add up to increased

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sensitivity to irradiation, increased formation of thymic lymphomas following repeated
exposure to low dose irradiation as well as larger skin papillomas from RAStransformed keratinocytes.
Future directions for this project are to understand the connections between
FANCD2 and the allelic variant of mTOR in our system. A likely starting point for this
exploration is to examine the bone marrow hematopoteic stem cells from 628C KI mice
and their response to inflammation and genotoxic stress. Also, because the heat
domains are reported to be regions of protein-protein interaction, exploring the binding
of mTOR partners with the allelic variant may open the door to understanding the
mechanism of increased sensitivity to DNA damage. Finally, a more complete
understanding of the biologic consequences of decreased PKCα under stress
conditions would complete the picture of the allelic variant’s effect.
Mtor’s role in numerous pathways, the dysregulation of the PI3K/AKT/mTOR
pathway in numerous cancers, and its ability to be targeted by specific compounds,
such as rapamycin, clearly highlight the importance of understanding the protein and its
roles. Herein, we have evaluated mTOR’s signaling in T-cell acute lymphoblastic
leukemia, and the effects of downregulating mTOR in this setting. Through this study,
we were able to identify CDK6, a crucial cell cycle signaling protein, as an indirect target
of mTOR signaling in this cancer, and as a target for combined therapy. In a separate,
but related, study we also explored the role of a naturally-occurring single nucleotide
polymorphism (SNP) in mTOR. We identified the DDR pathway as down regulated in
cells with this SNP, and explored the mechanism and consequences of this down
regulation both in cells and mice. Because of mTOR’s dysregulation in cancer, its role in

96

the DDR is crucial, as many cancer therapies induce DNA damage in rapidly dividing
cells. In all of these studies, we used mouse models with altered mTOR, allowing us to
assess the consequences of mTOR at both the cellular and organismal level.

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APPENDICES

98

APPENDIX A: Additional results from mTOR WT and 628C KI mice
that are not significantly different by genotype

Inflammatory response by complete blood count (CBC)
mTOR WT and 628C KI mice are phenyotypically normal when not perturbed.
Seven days after intraperitoneal pristane injection, WT and 628C KI mice have similar
neutrophil (PMN) and lymphocyte counts by CBC (Figure 47). Neutrophil counts were
increased in both pristane-treated groups.

Figure 47: Polymorphonuclear cells (PMNs) and lymphocytes from untreated (WT
and KI) and pristane-treated (designated WTP and KIP) mTOR WT
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Figure 47 (cont’d). and 628C KI mice by CBC. Each point represents a value for an
individual mouse. Included are both percent and absolute values.
Downstream protein phosphorylation
The phosphorylation of the main downstream targets of mTOR, 4E-BP1, S6, and
AKT, shown as a ratio of phospho – to total protein by immunoblot or size-based
capillary electrophoresis [(Peggy, Protein Simple; (Chen, Heldman et al. 2013)] showed
variable differences based on tissue and with or without pristane-treatment (Figure 48).
The biggest differences in phospo/total ratios between WT and KI were in untreated
tissues, but these differences were not statistically significant (Student T-test, n per
group =3). Differences were apparent between B220+ (splenic B-cell) and B220populations in spleens from pristane-treated mice, indicating different phosphorylation
patterns in different cell subtypes within a tissue (Figure 48).

100

Figure 48: Average protein expression levels by quantification of western blot
bands or by size-based, automated, capillary immunoassay system (peak area),
showing levels of downstream targets of mTOR. Levels of phospho-4E-BP1,
phospho-S6, and phospho-AKT in the bone marrow and spleen from untreated and
pristane-treated mice. Error bars represent standard error of the mean from three
animals. N.D. signifies that indicated ratios were not tested for this cell/treatment type.

101

APPENDIX B: Levels of three miRNAs are differentially expressed
between WT and 628C KI B220+ splenocytes by Nanostring; the
magnitude of the differences by Real Time PCR were not significant

Nanostring arrays (Nanostring, Seattle, WA) were performed on B220+
splenocytes (B-cells) isolated from untreated mice or mice 7 days after pristane
treatment. Analysis of the Nanostring results indicated that three microRNAs were
significantly different between untreated WT and KI cells: miR30a, mir101, mir423-5p
(no microRNAs were different in cells from pristane-treated mice, Figure 49). However,
there was no significant difference between WT and 628C KI cell miR expression levels
by real time PCR (RT-PCR).

102

Figure 49: Spot intensity by Nanostring array for miR30a, miR101, and mir423-5P,
and transcript levels by RT-PCR for each miR in WT and KI bone marrow cells. All
miRs were significantly up regulated in the KI cells by Nanostring array. However, by
RT-PCR (reported as 2^-Δ CT) in additional animals, none of the miRs had differential
expression between WT and KI mice; although for each miR, the trend was similar.

103

APPENDIX C: Glycolysis is similar in primary and transformed mTOR
WT and 628C KI, and mTOR WT and KD mouse embryonic fibroblasts
Glycolysis was measured in transformed (by SV40 Large T antigen) and primary
WT, KI, and KD mouse embryonic fibroblasts (MEFs) by the XF Glycolysis stress test
on the Seahorse XF (Seahorse Bioscience, MA). In this test, baseline pH, (measured by
ECAR: mpH/min), glycolysis after glucose introduction, and glycolytic capacity and
reserve after oligomycin (ATP Synthase inhibitor) and then 2 Deoxy-D-glucose
(glycolysis inhibitor) was measured. Glycolytic capacity, which is the area under the
curve from 50 minutes to 75 minutes was compared between groups by ANOVA.
Experiments were repeated in triplicate. Transformed KD MEFs had significantly lower
glycolytic capacity than transformed WT MEFs, though WT and 628C KI transformed
MEFs had similar glycolytic capacity. There was no significant difference in glycolytic
capacity between primary WT, KI, and KD MEFs, indicating that glycolysis was not
different between WT and KI MEFs under these conditions (Figure 50, representative
experiment).

104

Figure 50: Curves representing glycolytic function in SV40-transformed and
primary mTOR WT, KI, and KD mouse embryonic fibroblasts. Each line represents
a different cell line. Error bars represent standard error of the mean of 4 technical
replicates. Glucose, oligomycin (ATP Synthase inhibitor), and then 2 Deoxy-D-glucose
(glycolysis inhibitor) are added to the cells as pH (a measure of glycolytic byproducts) is
measured in the media adjacent to the cells.
105

APPENDIX D: Top Molecular and Cellular Functions identified by
Ingenuity Pathway Analysis in genes from bone marrow of pristanetreated animals
Table 4: Cell morphology-associated top molecular functions as identified by
Ingenuity Pathway Analysis. Sub-category of Disease or Functions Annotation, pvalue, activation z-score, molecules involved, and numbers of molecules are included.
Diseases or
Functions
Annotation
morphology of
red blood cells

p-Value

2.09E-08

abnormal
morphology of
red blood cells

4.29E-08

morphology of
blood cells

3.56E-06

volume of blood
cells
volume of cells

1.29E-05
2.32E-05

morphology of
bone marrow
cells

1.52E-04

morphology of
hematopoietic
progenitor cells

3.60E-04

Activation
z-score

Molecules

ADD1,ADD2,Ahsp,ARHGEF12,BNIP3L,EIF2AK
1,EPB41,EPB42,EPOR,GATA1,GFI1B,Gypa,H
BA1/HBA2,Hbb-b2, IREB2, KLF1, MPP1,
PRDX2, RB1, SCARB1, SIN3B, SLC11A2,
SLC4A1, SPI1, STEAP3, TFRC, THBS1,
TSPAN33
ADD1,ADD2,Ahsp,ARHGEF12,BNIP3L,EIF2AK
1,EPB42,EPOR,GATA1,GFI1B,Gypa,HBA1/HB
A2,Hbb-b2, IREB2, KLF1, PRDX2, RB1,
SCARB1, SIN3B, SLC11A2, SLC4A1, SPI1,
STEAP3,TFRC,TSPAN33
ABHD5,ADD1,ADD2,Ahsp,ANO6,ARHGEF12,A
RID3A,ATF2,BAD,BCL11B,BCL2L1,BNIP3L,CC
DC86,CCND2,CD36,CD8A,CP,CSF1,CTSZ,DC
K,EBI3,EIF2AK1,EPB41,EPB42,EPOR,EPS15,
EPX,FANCC,FCGR2B,FLT3LG,FOXO3,GATA1
GBA,GFI1B,Gypa,HBA1/HBA2,Hbb-b2, ICAM2,
ID1, IKBKG, IL5RA, IL7R, IREB2, KLF1, KLF13,
LIPA, MAPKAPK2, MCL1, MPP1, MST1, Mt1,
MXD1,MYB,NFKBIZ,PARL,PIK3CD,PPM1D,PP
P3CB,PRDX2,PRG2,PSMB10,PSMB9,RB1,RB
L1,RC3H1,S1PR4,SCARB1,SELP,SENP1,SIN3
B,SLA,SLC11A2,SLC4A1,SOX4,SPI1,STEAP3,
TAL1,TAP1,TFRC,THBS1,TLR4,TNFAIP8L2,T
NFSF14,TRIB1,TSPAN33,TSTA3,ZBTB46,ZFP
M1
ADD1,ADD2,GATA1,GP1BA,Hbb-b2,
SLC12A4, SPTA1, SPTB,ST3GAL6
ADD1,ADD2,ADRB2,AQP1,BCL2L1,COL18A1,
GATA1,GP1BA,Hbb-b2, IL1RL1, KCNN4,
SLC12A4, SLC6A9, SPTA1,SPTB,ST3GAL6
ANO6,ARID3A,ATF2,CCND2,CSNK2A1,FANC
C,FLT3LG,GATA1,ICAM2,IKBKG,MXD1,RBL1,
S1PR4,SELP,SENP1,SPI1,TAL1,TRIB1,TSTA3
,ZFPM1
ANO6,ARID3A,ATF2,CCND2,CD8A,DCK,EPB4
1,EPOR,FANCC,FLT3LG,FOXO3,GATA1,ICAM
2,IKBKG,KLF1,MCL1,MXD1,MYB,PRDX2,RBL1
S1PR4,SELP,SENP1,SLA,SLC4A1,SOX4,SPI1,
STEAP3,TAL1,TRIB1,TSTA3,ZFPM1

106

#
Molecules
28

25

88

9
16

20

32

Table 4 (cont’d)
morphology of
lymphatic
system cells

6.27E-04

volume of red
blood cells
shape change of
tumor cell lines

6.75E-04
2.57E-03

-2.584

cell spreading of
tumor cell lines

2.91E-03

-2.081

abnormal
morphology of
hematopoietic
progenitor cells
morphology of
nucleus

3.46E-03

initiation of
autophagy of
cells
cell spreading of
leukemia cell
lines
autophagy of
neuroblastoma
cell lines
volume of blood
platelets
abnormal
morphology of
myeloid
progenitor cells
shape change of
vascular
endothelial cells
abnormal
morphology of
dopaminergic
neurons
cell flattening of
bone cancer cell
lines
cellularity of bone
marrow
abnormal
morphology of
megakaryocyte/er
ythrocyte lineagerestricted
progenitor cells
cell spreading of
colon cancer cell
lines

4.89E-03

3.47E-03

6.54E-03

0.152

7.10E-03

-0.655

ANO6,ARID3A,ATF2,CCND2,CSNK2A1,EPS15
FANCC,FLT3LG,GATA1,ICAM2,IKBKG,MXD1,
RBL1,S1PR4,SELP,SENP1,SPI1,TAL1,TRIB1,
TSTA3,ZFPM1
ADD2,Hbb-b2,SLC12A4,SPTA1,SPTB

21

AKAP12,ANXA5,BCL10,CCNE1,CDH11,CLIP1,C
SF1,EDNRA,FERMT3,GFAP,HOOK1,ITGA4,ITG
B1,PARVB,PIP5K1A,PPFIA1,PRNP,RAP1B,RB1
RBL1,SDC2,SRC,TAOK1,THBS1,TIAM1,TMBIM
4,TNC
BCL10,CDH11,CLIP1,FERMT3,GFAP,HOOK1,IT
GA4,ITGB1,PARVB,PPFIA1,PRNP,RAP1B,RB1,
SDC2,SRC,THBS1,TIAM1,TMBIM4,TNC
ANO6,ARID3A,ATF2,CCND2,CD8A,DCK,FANC
C,FLT3LG,FOXO3,GATA1,ICAM2,MCL1,MXD1,
MYB,PRDX2,RBL1,S1PR4,SELP,SENP1,SLA,S
LC4A1,SPI1,STEAP3,TRIB1,TSTA3,ZFPM1
AIFM1,BRCA1,BUB3,CHEK1,EIF4E,EP300,GAD
D45A,GMCL1,KIF22,LMNA,LMNB1,MAP4,MCP
H1,MST1,NCAPG,NET1,PLSCR1,SIRT2,SMC2,
SRC,TOR1A,VIM
BECN1,SH3GLB1,WIPI1

27

5

19

26

22

3

BCL10,FERMT3,ITGA4,ITGB1,TNC

5

DNM1L,PRNP,ROCK1,SNCA

4

7.10E-03

ADD1,GATA1,GP1BA,ST3GAL6

4

8.10E-03

ATF2,CCND2,FLT3LG,GATA1,MXD1,RBL1,SEL
P,SPI1,TRIB1,TSTA3

10

ANG,ANGPT1,CRK,CTBP2,CTTN,DICER1,DRO
SHA,GP1BA,HS6ST1,ITGB1,SRC,TNC

12

1.11E-02

-1.6

1.12E-02

SLC18A2,SNCA,SPR

3

1.12E-02

CCNE1,RB1,RBL1

3

1.12E-02

CLEC11A,CSF1,RNF2

3

1.17E-02

GATA1,ICAM2,SENP1,ZFPM1

4

PPFIA1,RAP1B,SDC2,SRC

4

1.17E-02

-2

107

Table 4 (cont’d)
abnormal
morphology of
eosinophils
osmotic water
permeability of
red blood cells
ruffling of
endothelial cell
lines
transmembrane
potential of
epithelial cells
volume of
nucleus
formation of
invadopodia
cell spreading of
kidney cell lines
morphology of
erythroid
progenitor cells
permeability of
mitochondrial
membrane
cell rounding of
tumor cell lines
morphology of
cerebral cortex
cells
shape change of
bone cancer cell
lines
permeabilization
of mitochondria

1.21E-02

EPX,PRG2

2

1.21E-02

AQP1,SLC14A1

2

1.21E-02

SRC,TIAM1

2

1.21E-02

CASP9,KCNN4

2

1.21E-02

TMPO,TOP1

2

1.24E-02

-0.896

ARF6,BTG2,CTTN,DIAPH3,ITGB1,RELN,SRC

7

1.35E-02

-0.254

ANTXR1,CRK,ITGB1,SORBS1,THBS1,VIM

6

1.35E-02

EPB41,EPOR,GATA1,KLF1,PRDX2,SLC4A1,S
PI1,STEAP3

8

1.37E-02

ATF2,BAD,BCL2L1,BNIP3L,PLEKHF1

5

AKAP12,EDNRA,PARVB,PIP5K1A,TAOK1,TIA
M1,TNC
ACHE,CLCN3,CPEB3,DYRK1A,FMR1,KALRN,
KLK8,PAFAH1B1,SYNCRIP

7

CCNE1,RB1,RBL1,TMBIM4

4

1.56E-02

-2

1.66E-02

1.78E-02

0

1.91E-02

0.549

AIFM1,BAD,BCL2L1,CLIC4,DNM1L,ITSN1,MC
L1,PLEKHF1,RB1,SMPD4

9

10

Table 5: Small Molecule Biochemistry-associated top molecular functions as
identified by Ingenuity Pathway Analysis. Sub-category of Disease or Function
Annotation, p-value, activation z-score, molecules involved, and numbers of molecules
are included.
Diseases or
Functions
Annotation
metabolism of
porphyrin

p-Value

Activation
z-score

5.35E-07

-0.97

synthesis of
porphyrin

9.55E-07

-1.432

synthesis of heme

2.56E-04

-1.387

metabolism of
phosphatidic acid

4.06E-04

-0.921

Molecules

ABCB6,ALAD,ALAS2,ANK1,BCL2L1,BLVRB,EI
F2AK1,FECH,IREB2,PPOX,PRDX2,SLC11A2,S
LC25A38,SPTA1,SPTB,UROD,UROS
ABCB6,ALAD,ALAS2,ANK1,BCL2L1,FECH,IRE
B2,PPOX,SLC11A2,SLC25A38,SPTA1,SPTB,U
ROD,UROS
ABCB6,ALAD,ALAS2,BCL2L1,FECH,PPOX,SL
C11A2,SLC25A38,UROD,UROS
ABHD5,ADRB2,AGPAT2,ALOX15,ARF6,CHPT
1,CTBP2,DPM1,DPM2,FABP5,FCGR2B,GPAA
1,INPP5E,ITGB1,PCYT1A,PIGA,PIGQ,PIK3CD,
PIK3R1,PIP5K1A,PIP5K1B,PLA1A,PLA2G4C,P
LEK,PLSCR1,PNPLA6,PRDX2,PTDSS2,SH3G
LB1,SH3YL1,SMPD4,SPI1

108

#
Molecules
17

14

10
32

Table 5 (cont’d)
homeostasis of
transition metal
ion
incorporation of
sphingomyelin
metabolism of
protoporphyrinoge
n
uptake of
arachidonic acid
synthesis of
phosphatidic acid

8.20E-04

1.61E-03

-1.618

metabolism of
phospholipid

2.12E-03

-0.872

transport of
phospholipid

2.22E-03

translocation of
phospholipid
synthesis of
phospholipid

2.94E-03

homeostasis of
Cu2+
synthesis of
polyamines
metabolism of
dolichol
synthesis of
spermidine
catabolism of
hydrogen peroxide
metabolism of
glutamine
accumulation of
porphyrin
catabolism of
glycerophospholip
id
formation of
farnesyl
pyrophosphate
hydrolysis of 1oleoyl-2acetylglycerol

4.19E-03

ABHD5,ADRB2,AGPAT2,ALOX15,ARF6,CHPT
1,CTBP2,DPM1,DPM2,FABP5,GPAA1,INPP5E,
ITGB1,PCYT1A,PIGA,PIGQ,PIK3CD,PIK3R1,PI
P5K1A,PIP5K1B,PLSCR1,PNPLA6,PRDX2,PT
DSS2,SH3GLB1,SH3YL1
ABHD5,ADRB2,AGPAT2,ALOX15,ARF6,CHPT
1,CLN8,CTBP2,DPM1,DPM2,FABP5,FCGR2B,
GPAA1,INPP5E,ITGB1,LPCAT1,PCYT1A,PIGA
,PIGQ,PIK3CD,PIK3R1,PIP5K1A,PIP5K1B,PLA
1A,PLA2G16,PLA2G4C,PLEK,PLSCR1,PNPLA
6,PRDX2,PTDSS2,PTGS2,PTPMT1,SGMS1,S
H3GLB1,SH3YL1,SMPD4,SNCA,SPI1
ABCB4,ABCG4,ANO6,ATP11C,ATP8A1,ATP8
A2,KCNN4,OSM,PLSCR1,PRELID1,SCARB1,T
MEM30A
ABCB4,ATP11C,ATP8A1,ATP8A2,KCNN4,PLS
CR1,TMEM30A
ABHD5,ADRB2,AGPAT2,ALOX15,ARF6,CHPT
1,CTBP2,DPM1,DPM2,FABP5,GPAA1,INPP5E,
ITGB1,LPCAT1,PCYT1A,PIGA,PIGQ,PIK3CD,P
IK3R1,PIP5K1A,PIP5K1B,PLA2G16,PLSCR1,P
NPLA6,PRDX2,PTDSS2,PTGS2,PTPMT1,SGM
S1,SH3GLB1,SH3YL1
APLP2,ATOX1,ATP7B,COMMD1,PRNP

4.19E-03

AMD1,AZIN1,ODC1,SMOX,SRM

5

4.89E-03

DPM1,DPM2,SRD5A3

3

4.89E-03

AMD1,ODC1,SRM

3
6

9.68E-03

ABCG2,CAT,HBA1/HBA2,PRDX2,PRDX3,PTG
S2
GLS,GLUL,ME1,NIT2,PHGDH

1.21E-02

UROD,UROS

2

1.21E-02

PLA2G4C,SMPD4

2

1.21E-02

FDPS,GGPS1

2

1.21E-02

PAFAH1B1,PAFAH1B2

2

1.33E-03

ABCB7,ALAS2,APLP2,ATOX1,ATP7B,COMMD
1,IREB2,Mt1,NUBP1,PRNP,SLC30A5,TFR2,TF
RC
GBA,SCARB1,SGMS1

1.33E-03

EIF2AK1,FECH,IREB2

3

1.33E-03

APOD,FAT1,SCARB1

3

2.94E-03

7.46E-03

-1.517

-2

109

13

3

26

39

12

7
31

5

5

Table 5 (cont’d)
hydrolysis of 1palmitoyl-2arachidonyl-snglycero-3phosphorylcholine
hydrolysis of 1palmitoyl-2linoleoyl-snglycero-3phosphocholine
quantity of
vinblastine
uptake of myristic
acid
quantity of
bilirubin
reduction of
hydrogen peroxide

1.21E-02

PLA2G16,PNPLA6

2

1.21E-02

PLA2G16,PNPLA6

2

1.21E-02

ABCB4,UGCG

2

1.21E-02

CD36,THBS1

2

1.38E-02

2.121

1.78E-02

-1.732

ABCB4,ABCG2,ADD2,GFER,Hbbb2,PFKM,RDX,SLC51A,SPTA1,SPTB
CAT,PRDX2,PRDX3,PTGS2

10
4

Table 6: DNA Replication, Recombination, and Repair-associated top molecular
functions as identified by Ingenuity Pathway Analysis. Sub-category of Disease or
Function Annotation, p-value, activation z-score, molecules involved, and numbers of
molecules are included.
Diseases or
Functions
Annotation
initiation of
replication of DNA
DNA replication

p-Value

Activation Molecules
z-score

2.31E-06

0

9.73E-06

-0.582

segregation of
chromosomes

5.25E-05

-0.181

metabolism of
DNA

6.19E-05

0.382

CCNE1,CCNE2,CDC6,CDC7,CDK2AP1,CHEK
1,EP300,ORC1,ORC2,ORC4,ORC5,PURA
ABCB6,ABCB7,ACHE,BECN1,BRCA1,CCDC88
A,CCNA2,CCNE1,CCNE2,CDC6,CDC7,CDK2A
P1,CHEK1,CUL4A,CUL4B,DBF4,E2F2,E4F1,E
NDOG,EP300,ESCO2,HELB,ID1,IGHMBP2,KIN
,MAPKAPK2,NAP1L1,NASP,NRF1,OBFC1,OR
C1,ORC2,ORC4,ORC5,Paxip1,PLK1,POLH,PT
GS2,PURA,RB1,RNF2,SLA,SRC,SSBP1,SUPT
16H,THRA,TMPO,TOP1,WAPAL,WRN
ATRX,BRCA1,BUB3,CCNA2,CDC6,CENPE,CE
NPF,CENPH,EBNA1BP2,ECT2,ESCO2,FAM96
B,GPSM2,KIF2C,KNSTRN,LMNA,NCAPG,NEK
2,NINL,NUSAP1,PLK1,RIOK3,SKA2,SMC2,SM
C4,STAG1,TLK2,TPX2,WAPAL
ABCB6,ABCB7,ACHE,AGTR1,AIFM1,ANTXR1,
BCL2L1,BECN1,BRCA1,CASP9,CCDC88A,CC
NA2,CCNE1,CCNE2,CDC6,CDC7,CDK2AP1,C
HEK1,CSF1,CUL4A,CUL4B,DBF4,DHX9,DUSP
1,E2F2,E4F1,ENDOG,EP300,ESCO2,EXO5,HE
LB,HSD17B10,ID1,IGHMBP2,ISG20,JUN,KIN,L
MNA,MAPKAPK2,MCL1,NAP1L1,NASP,NRF1,
OBFC1,ORC1,ORC2,ORC4,ORC5,Paxip1,PIK3
R1,PLK1,POLH,PPIB,PRNP,PTGS2,PURA,RB
1,RNF2,SERINC3,SLA,SNCA,SRC,SSBP1,SU
PT16H,THRA,TIAM1,TMPO,TNFRSF19,TOP1,
TREX1,WAPAL,WRN

110

#
Molecules
12
50

29

72

Table 6 (cont’d)
checkpoint
control

8.68E-05

-0.906

chromosomal
congression of
chromosomes
organization of
kinetochores
alignment of
chromosomes
DNA damage
response of cells

9.04E-04

-0.64

segregation of
sister chromatids
segregation of
mitotic sister
chromatids
spindle
checkpoint of
tumor cell lines
synthesis of DNA

2.94E-03

quantity of
centrosome
re-replication of
DNA
quantity of
chromosomes
degradation of
plasmid
formation of
spindle pole
DNA replication
checkpoint of
cells
mitotic exit DNA
damage
checkpoint of
cells
spindle
checkpoint of
colon cancer cell
lines

1.33E-03
1.71E-03

-1.912

2.54E-03

0.864

5.31E-03

5.31E-03

-0.97

5.32E-03

-1.565

6.87E-03

1.404

7.46E-03

-0.64

8.74E-03

1.109

BCL2L1,BRCA1,BUB3,CCNE2,CDC20,CDC6,C
DC7,CHEK1,CUL4A,DBF4,E2F2,EIF4E,FANCC
,FANCD2,FANCG,FOXO3,GTF2H5,HELB,MBD
4,MCPH1,MXD1,PLK1,POLH,PSME3,RB1,SIN
3B
CENPE,KIF18A,KIF22,KIF2C,NET1,PLK1

26

6

CENPH,SMC2,SMC4

3

CCNA2,CENPE,DLGAP5,KIF18A,KIF22,KIF2C,
NCAPG,PLK1,SMC4
ALKBH8,ATF2,ATRX,BRCA1,BTG2,CASP9,CH
CHD6,CHEK1,CIB1,CUL4A,DCK,DDIAS,DTL,
FANCD2, FANCC,FANCG,HIPK1, IKBKG,
IRF3, MAPKAPK2, MBD4, MIF, NEK1,Paxip1,
POLH, PSME4, RAD23A, RBM38, SIRT2,
SOX10,STRA13,STXBP4,TAOK1,TLK2,TOP1,T
RIP12,UBE2T,WRN,YY1
BUB3,CCNA2,KNSTRN,NEK2,NUSAP1,PLK1,
SMC4
BUB3,KNSTRN,NEK2,NUSAP1,PLK1,SMC4

9

AXIN2,CENPI,DLGAP5,ERCC6L,NET1,PLK1

38

7
6

6

AGTR1,Alox12e,ARRB1,BAD,BRCA1,CAT,CC
DC88A,CCL5,CCNA2,CCND2,CCNE1,CCNE2,
CDC7,CDK2AP1,CHEK1,CRK,CSF1,DUSP1,E
P300,F10,FANCD2,GFER,GJA1,GTF2H5,HEL
B,HIRA,HSPA8,ID1,IRF3,ITGB1,JUN,LGALS1,
MAPKAPK2,MCL1,MIF,MINPP1,MST1,MYBL2,
ODC1,OSM,PIK3CD,PIK3R1,PLK1,POLH,PPA
T,PRKAR2B,PRNP,PTGS2,PTPRF,RAP1B,RB
1,RBL1,SKP2,SLC29A1,SPI1,SRC,SUPT4H1,T
FR2,TIMP2,TNC,UHRF1,WRN,YY1
BECN1,CDC25B,CHMP3,DHX9,GADD45A,ID1,
KIF23,LMO4,PLK1,SKP2,TACC3
CCDC88A,CCNA2,CDC6,CUL4A,CUL4B,DBF4

63

8

1.12E-02

BRCA1,BUB3,CENPE,DICER1,GADD45A,KIF2
C,SPI1,WAPAL
AIFM1,PPIB,TREX1

1.12E-02

CKAP2,DLGAP5,PLK1

3

1.21E-02

CENPE,CHEK1

2

1.21E-02

CHEK1,PLK1

2

1.21E-02

AXIN2,PLK1

2

111

11
6

3

Table 6 (cont’d)
conformational
modification of
DNA
spindle
checkpoint of
cervical cancer
cell lines
catabolism of
DNA

1.39E-02

-2.418

DNAJB1,GATA1,JUN,MCM4,MYB,PURA,TOP1
,WRN,YY1

9

1.78E-02

-0.152

CENPI,DLGAP5,ERCC6L,NET1

4

AIFM1,ENDOG,EXO5,ISG20,TREX1

5

1.87E-02

Table 7: Molecular Transport-associated top molecular functions as identified by
Ingenuity Pathway Analysis. Sub-category of Disease or Function Annotation, pvalue, activation z-score, molecules involved, and numbers of molecules are included.
Diseases or
Functions
Annotation
quantity of heavy
metal

p-Value

8.39E-06

#
Molecules
23

14

4.89E-03

ABCB10,ATOX1,ATP7B,COMMD1,CP,IREB
2,Mmgt2,SLC11A2,SLC25A37,SLC30A5,SL
C39A8,STEAP3,TFRC,TRPM7
ABCB4,ABCG4,ANO6,ATP11C,ATP8A1,AT
P8A2,KCNN4,OSM,PLSCR1,PRELID1,SCA
RB1,TMEM30A
ABCB10,ATP1B2,ATP7B,SLC11A2,SLC25A
37,STEAP3,TFRC
ABCB4,ATP11C,ATP8A1,ATP8A2,KCNN4,P
LSCR1,TMEM30A
Mmgt2,SLC11A2,SLC30A5

4.89E-03

AQP1,CA2,RHAG

3

4.89E-03

ABCC5,CD14,SCARB1

3

6.54E-03

ATOX1,ATP7B,Mmgt2,SLC11A2,STEAP3

5

1.21E-02

UROD,UROS

2

1.21E-02

PRNP,SNCA

2

1.21E-02

ABCB4,UGCG

2

1.21E-02

CD36,THBS1

2

2.50E-04

transport of
phospholipid

2.22E-03

import of metal

2.94E-03

translocation of
phospholipid
transport of Co2+

2.94E-03

accumulation of
porphyrin
exocytosis of Lglutamic acid
quantity of
vinblastine
uptake of myristic
acid
quantity of
bilirubin

Molecules

ADD2,ALAS2,APLP2,ATP7B,COMMD1,CP,
EIF2AK1,EPB42,Hbb-b2, HMOX2, IREB2,
KCNN4, Mt1, OSM, PRNP, RHAG,
RHCE/RHD,SLC11A2,STEAP3,TFR2,TFRC,
TRIB1,UROD
ABCB10,ATP7B,SLC11A2,SLC25A37,STEA
P3,TFRC
APOD,FAT1,SCARB1

import of heavy
metal
uptake of
arachidonic acid
transport of heavy
metal

transport of
carbon dioxide
transport of
polysaccharide
transport of Cu2+

Activatio
n zscore
3.004

1.33E-03
1.38E-03

1.38E-02

-1.976

2.121

ABCB4,ABCG2,ADD2,GFER,Hbb-b2, PFKM,
RDX, SLC51A,SPTA1,SPTB

112

6
3

12

7
7
3

10

Table 8: Gene Expression-associated top molecular functions as identified by
Ingenuity Pathway Analysis. Sub-category of Disease or Function Annotation, pvalue, activation z-score, molecules involved, and numbers of molecules are included.
Diseases or
Functions
Annotation
translation of
mRNA

p-Value

Activation
z-score

1.02E-05

1.289

expression of
mRNA

1.97E-03

0.379

initiation of
expression of
RNA

3.55E-03

-1.269

activation of
chromosome
components
initiation of
translation of
mRNA

4.89E-03

1.15E-02

Molecules

#
Molecules

AGO2,BTG2,CPEB3,EIF2AK1,EIF2S3,EIF3G,E
IF4B,EIF4E,EIF4EBP1,EIF4G2,EIF5,ELAVL1,F
ARSB,FMR1,FOXO3,GAPDH,HBS1L,IREB2,KL
HL25,MRPL15,MRPL17,MRPL19,MRPL39,MTI
F3,PABPC4,PRG3,PURA,RPL23,RPL30,RPL3
9,RPS17,RPS9,SAMD4A,SYNCRIP
AGO2,ATF2,BTG2,CPEB3,EIF2AK1,EIF2S3,EI
F3G,EIF4B,EIF4E,EIF4EBP1,EIF4G2,EIF5,ELA
VL1,FARSB,FMR1,FOXO3,GAPDH,HBS1L,IRE
B2,IRF3,JUN,KLHL25,MRPL15,MRPL17,MRPL
19,MRPL39,MTIF3,PABPC4,PRG3,PURA,RPL
23,RPL30,RPL39,RPS17,RPS9,SAMD4A,SYN
CRIP,TIMP3
AGO2,BRCA1,CDK7,E2F2,EIF2S3,EIF3G,EIF4
B,EIF4E,EIF4EBP1,EIF4G2,EIF5,EP300,FMR1,
KLHL25,MED13,MTIF3,NCOA4,PTRF,SRC,YY
1
ATF2,NCAPG,SMC2

34

AGO2,EIF2S3,EIF3G,EIF4B,EIF4E,EIF4EBP1,
EIF4G2,EIF5,FMR1,KLHL25,MTIF3

11

113

38

20

3

APPENDIX E: Apoptosis and cell cycle in WT and 628C KI MEFs 3
hours and 18 hours post irradiation
WT and 628C KI mouse embryonic fibroblasts (MEFs) were irradiated at 4 Gy,
and were collected at 3 hours and 18 hours post irradiation. Flow cytometry was used
to assess apoptosis and cell cycle in these MEFs. A similar increase in % apoptotic
cells (both early and late apoptosis) was seen in WT and KI MEFs post irradiation
(Figure 51). The cell cycle in WT and KI MEFs was not altered at 3 hours post 4 Gy
irradiation. A slight G1 arrest was present in both WT and KI MEFs 18 hours post 4 Gy
irradiation (Figure 52).

Figure 51: Percent cells in early and late apoptosis 3 hours and 18 hours post 4
Gy irradiation in WT and KI MEFs by flow cytometry.

114

Figure 52: Cell cycle by flow cytometry in WT and KI MEFs 3 hours and 18 hours
post 4 Gy irradiation.
115

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