BREAST CANCER MULTIMODAL IMAGING AND THERAPEUTICS USING NANOTECHNOLOGY By Chia-Wei Yang A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of Chemistry – Doctor of Philosophy 2024 ABSTRACT Breast cancer is the leading cause of cancer associated death among women. Techniques for non-invasive breast cancer detection and imaging are urgently needed. Multimodality breast cancer imaging is attractive since it can integrate the advantages from several modalities enabling more accurate cancer detection. In order to accomplish this, Indocyanine Green (ICG) conjugated superparamagnetic Iron Oxide Nanoworm (NW-ICG) has been synthesized as contrast agents. When evaluated in a spontaneous mouse breast cancer model, the NW-ICG gave high tumor to normal tissue contrasts in multiple imaging modalities including magnetic particle imaging (MPI), near-infrared fluorescence imaging (NIR-FI), and photoacoustic imaging (PAI), providing more comprehensive detection and imaging of breast cancer. Thus, NW-ICGs are an attractive platform for non-invasive breast cancer diagnosis. A major contributing cause to breast cancer related death is metastasis. Moreover, breast cancer metastasis often shows few symptoms until a large area of the organs has been occupied by metastatic cancer cells. Breast cancer multimodal imaging is attractive since it integrates advantages from several modalities, enabling more accurate cancer detection. Glycoprotein CD44 is overexpressed on most breast cancer cells, and is the primary cell surface receptor for hyaluronan (HA). To facilitate breast cancer diagnosis, we report an ICG and HA conjugated iron oxide nanoparticle (NP-ICG-HA), which enabled active targeting to breast cancer by HA-CD44 interaction and detected metastasis with MPI and NIR-FI. When evaluated in a transgenic breast cancer mouse model, NP-ICG-HA enabled the detection of multiple breast tumors in MPI and NIR-FI, providing more comprehensive images and diagnosis of breast cancer. Furthermore, NP- ICG-HAs were evaluated in a breast cancer lung metastasis model. Upon NP-ICG-HA administration, MPI showed clear signals in lungs, indicating the tumor sites. This is the first time that HA based NPs have enabled MPI of cancer. NP-ICG-HAs are an attractive platform for non- invasive detection of primary breast cancer and lung metastasis. Cancer stem cells (CSCs) are a critical subset of cancer cells that contribute to tumor heterogeneity and resistance due to their self-renewal and tumor-initiating abilities. Targeting these cells, which often express elevated levels of CD44 receptors, is promising for developing effective cancer treatments. To better target the breast CD44-expressing cancer cells, we developed a novel nanodrug, G2-Sal-ICG, comprising a HA-like compound (G2) conjugated with the anticancer drug salinomycin (Sal) and the imaging agent ICG. This nanodrug targets CD44 receptors and allows for NIR-FI to track drug delivery in real-time. Binding assays with CD44- expressing 4T1 breast cancer cells showed that G2-Sal-ICG had significantly higher binding affinity than the positive control of HA conjugated with Sal and ICG (HA-Sal-ICG). Fluorescence microscopy imaging of cells incubated with G2-Sal-ICG revealed that the nanodrug was primarily localized in lysosomes, indicating successful cellular uptake. In vitro studies demonstrated delayed but effective cancer cell killing, suggesting that lysosomal degradation and hydrolysis are necessary for drug release. In vivo experiments using orthotopic breast cancer models highlighted the superior tumor-targeting capability of G2-Sal-ICG, which showed three times higher fluorescence signals in tumors compared to HA-Sal-ICG. Tumor volume measurements indicated significantly better suppression of tumor growth by G2-Sal-ICG. Flow cytometry and histological analyses confirmed a greater reduction in CD44-expressing cancer cells. Our findings demonstrated G2-Sal-ICG as a promising theranostic nanodrug for CSC-targeted therapy, combining efficient drug delivery with real-time imaging capabilities, thus highlighting its potential for clinical applications in breast cancer treatment. Copyright by CHIA-WEI YANG 2024 ACKNOWLEDGEMENTS I am extremely grateful to my supervisor, Dr. Xuefei Huang, for his support and guidance throughout my PhD study. He is a wonderful mentor and a role model for me. I am truly fortunate to have had the opportunity to work under his supervision. Thank you for your great support throughout these years. I would like to thank my dissertation committee, Dr Xiangshu Jin, Dr. Kevin Walker, Dr. Babak Borhan, and Dr. Zhen Qiu, for their guidance, suggestions, and constructive feedback, which have greatly improved the quality of this work. I am deeply appreciative of my former and current group members, colleagues, collaborators, and friends, who provided a supportive environment and offered encouragement during these challenging times. I would like to thank the support staff and specialists in the Department of Chemistry, the Institute for Quantitative Health Science and Engineering, and IQ core facilities for their help and service. I wouldn’t have been able to complete this work without your help. Thank you all for your support. My heartfelt thanks go to my family for their unconditional love and constant support. To my parents, who have always believed in me and encouraged me to pursue my goals, and to my siblings, for their unwavering support and understanding, which made this achievement possible. To everyone who has contributed to this journey in any way, I deeply appreciate your support and help. v LIST OF ABBREVIATIONS ....................................................................................................... vii Chapter 1. Recent Advances of Breast Cancer Stem Cell Imaging-guide Drug Delivery ............. 1 1.1 Introduction ......................................................................................................................... 1 1.2 Biomarkers of Breast Cancer Stem Cells .......................................................................... 3 1.3 CSC Biomarker-mediated Drug Delivery ......................................................................... 4 1.4 BCSC Image-guided Drug Delivery ................................................................................ 12 1.5 Conclusions and Perspectives ........................................................................................... 20 REFERENCES ............................................................................................................................. 23 Chapter 2. Indocyanine Green Conjugated Superparamagnetic Iron Oxide Nanoworm for Multimodality Breast Cancer Imaging .................................................................................... 29 2.1 Introduction ....................................................................................................................... 29 2.2 Results ................................................................................................................................ 31 2.3 Discussion ........................................................................................................................... 39 2.4 Conclusion .......................................................................................................................... 40 2.5 Experimental section ......................................................................................................... 41 REFERENCES ............................................................................................................................. 45 APPENDIX ................................................................................................................................... 50 Chapter 3. Active Targeting Hyaluronan Conjugated Nanoprobe for Magnetic Particle Imaging and Near-infrared Fluorescence Imaging of Breast Cancer and Lung Metastasis.................. 56 3.1 Introduction ....................................................................................................................... 56 3.2 Results ................................................................................................................................ 58 3.3 Discussion ........................................................................................................................... 70 3.4 Conclusion .......................................................................................................................... 71 3.5 Experimental section ......................................................................................................... 71 REFERENCES ............................................................................................................................. 77 APPENDIX ................................................................................................................................... 82 Chapter 4. Hyaluronan Derivative Self-assembled Nanodrugs for Breast Cancer Image-guided Drug Delivery ......................................................................................................................... 88 4.1 Introduction ....................................................................................................................... 88 4.2 Results ................................................................................................................................ 90 4.3 Discussion ........................................................................................................................... 99 4.4 Conclusion ........................................................................................................................ 101 4.5 Experimental section ....................................................................................................... 101 REFERENCES ........................................................................................................................... 107 APPENDIX ................................................................................................................................. 111 vi TABLE OF CONTENTS LIST OF ABBREVIATIONS 8-HQ: 8-hydroxyquinoline ALDH1: Aldehyde dehydrogenase1 ATRA: All-trans Retinoic acid BTZ: Bortezomib BCSCs: Breast Cancer Stem-like Cells CDMT: 2-chloro-4,6-dimethoxy-1,3,5-triazine CSCs: Cancer Stem-like Cells CMLVs: Cross-linked Multilamellar Liposomal Vesicles CT: X-ray Computed Tomography CUR: Curcumin CYC: Cyclopamine DCC: N,N-dicyclohexylcarbodiimide DIPEA: N,N-diisopropylethylamine DI: Deionized DMSO: Dimethyl Sulfoxide DTX: Docetaxel DOX: Doxorubicin DMEM: Dulbecco’s Modified Eagle Medium DMPG: 1,2-dimyristoyl-sn-glycero-3-phosphoglycerol DPBS: Dulbecco’s Phosphate-buffered Saline DLS: Dynamic Light Scattering EDX: Energy Dispersive X-ray Spectroscopy vii EPR: Enhanced Permeability and Retention ELISA: Enzyme Linked Immunosorbent Assay FBS: Fetal Bovine Serum FOV: Field of View FDA: Food & Drug Administration GEM: Gemcitabine H&E: Hematoxylin and Eosin HA: Hyaluronic Acid IHC: Immunohistochemistry ICG: Indocyanine Green ICP-OES: Inductively Coupled Plasma - Optical Emission Spectrometry CPT: Irinotecan IONPs: Iron Oxide Nanoparticles MPI: Magnetic Particle Imaging MRI: Magnetic Resonance Imaging MFI: Median Fluorescence Intensity MSNs: Mesoporous Silica Nanoparticles Met: Metformin NW: Nanoworm NIR: Near-infrared NIR-FI: Near-infrared Fluorescence Imaging NBF: Neutral Buffered Formalin NMM: N-methylmorpholine viii NOD/SCID: Nonobese Diabetic/Severe Combined Immunodeficiency PTX: Paclitaxel PFA: Paraformaldehyde PDX: Patient-derived Xenograft PAI: Photoacoustic Imaging PF127: Pluronic F127 PLGA: Poly(D,L-lactide-co-glycolide) PET: Positron Emission Tomography SAL: Salinomycin SPECT: Single-photon Emission Computed Tomography Sod: Sodium Salicylate SPIONs: Spherically Shaped Iron Oxide Nanoparticles SQUID: Superconducting Quantum Interference Device THZ: Thioridazine TPZ: Tirapazamine TEM: Transmission Electron Microscopy TNR: Tumor to Normal Tissue Ratio ix Chapter 1. Recent Advances of Breast Cancer Stem Cell Imaging-guide Drug Delivery 1.1 Introduction Cancer stem-like cells (CSCs) are a subset of cancer cells with unique characteristics contributing to tumor heterogeneity and resistance. These cells possess self-renewal capabilities and are believed to drive tumor growth, metastasis, and resistance to conventional therapies.1-4 Compared to the bulk of tumor cells, CSCs can better resist chemotherapy and radiation, leading to relapse and poor prognosis. Understanding the biology of CSCs is essential for developing targeted therapies that can effectively eradicate these cells and improve patient outcomes.5 Breast cancer remains one of the most prevalent and deadly cancers among women worldwide. In 2022, there were more than 2.3 million new cases of breast cancer (11.6% of all cancer cases) and more than 665,000 deaths globally.6-7 A critical factor contributing to its aggressiveness and recurrence is the presence of breast cancer stem-like cells (BCSCs), a subset of CSCs in breast cancer. Key biomarkers such as CD44, CD24, and aldehyde dehydrogenase1 (ALDH1) have been identified and are used to isolate and characterize BCSCs.8-11 These biomarkers are crucial for distinguishing BCSCs from other cancer cells and normal stem cells, aiding in the development of targeted therapies and diagnostic tools. The identification and characterization of BCSCs in vivo pose significant challenges due to their rarity and heterogeneity within tumors. Advances in imaging technologies have begun to address these challenges, enabling researchers to visualize and track BCSCs in real-time.12-13 Techniques such as fluorescence imaging, magnetic resonance imaging (MRI), and positron emission tomography (PET) have been used to label and monitor BCSCs.14-15 By integrating molecular markers specific to BCSCs with advanced imaging modalities, it has become possible 1 to study their behavior, track their response to treatment, and evaluate the effectiveness of new therapeutic strategies. Nanotechnology has been commonly used in the field of drug delivery, offering robust treatment for various diseases, including cancer. Nanomedicine utilizes nanoparticles to deliver therapeutic agents directly to the tumor site, enhancing drug accumulation and minimizing systemic toxicity. These nanoparticles can be engineered to carry multiple drugs, target specific cell populations, and release their payload in a controlled manner.16-17 In the context of breast cancer, nanomedicine offers a promising approach to overcome the limitations of conventional therapies by ensuring that potent anti-cancer agents reach and effectively target BCSCs.5, 18 Imaging-guided drug delivery combines the precision of advanced imaging techniques with the targeted therapeutic potential of nanomedicine. This approach allows for the real-time monitoring of drug distribution and the assessment of therapeutic efficacy at the cellular level.19- 20 By integrating imaging capabilities into drug delivery systems, it becomes possible to track nanoparticles, optimize their delivery to cancer cells, and adjust treatment regimens based on real- time feedback. This combination holds significant promise for improving the specificity and effectiveness of cancer treatments, ultimately leading to better clinical outcomes and reduced side effects.21-22 In this chapter, we introduced the commonly used biomarkers for BCSCs targeting in the next section and organized studies focused on drug delivery with these biomarkers in the following section. Additionally, we highlighted the studies focused on image-guided drug delivery toward BCSCs through different modalities and provided perspectives for advance of image-guided drug delivery. 2 1.2 Biomarkers of Breast Cancer Stem Cells BCSCs were first identified and isolated as CD44+CD24-/low from patients by Al-Hajj et al. in 2003. They demonstrated that 100 of cells with these phonotypes were able to form tumors in nonobese diabetic/severe combined immunodeficiency (NOD/SCID) mice, while tens of thousands of cells without these phenotypes did not form tumors.8 In 2007, Ginestier et al. demonstrated that human mammary cells, both normal and cancerous, with increased ALDH1 activity possess stem/progenitor properties.23 To date, the CD24, CD44, and ALDH1 are still the most used biomarkers for BCSC identification and isolation. However, when targeting the BCSCs with drug delivery systems, most common biomarkers used in literature were CD44, CD133, and HER2. 1.2.1 CD44 CD44 is a transmembrane glycoprotein protein involved in cell-cell interactions, cell adhesion, and migration. In breast cancer, CD44 has been extensively associated with CSC properties, including self-renewal, differentiation, and metastatic potential.24-25 The expression of CD44 in BCSCs is linked to poor prognosis, increased tumor invasiveness, and resistance to chemotherapy and radiation therapy. CD44 is a receptor of hyaluronic acid (HA) and the CD44- HA interaction has been well studied, leading to HA as a promising targeting molecule of CD44 overexpressed cancer cells.26-27 1.2.2 CD133 CD133, also known as prominin-1, is a transmembrane glycoprotein that has been widely recognized as a marker for both normal and cancerous stem cells. In the context of breast cancer, CD133+ cells have been shown to possess high tumorigenic potential, contributing to the aggressive behavior of the tumor. The presence of CD133 on BCSCs correlates with poor 3 clinical outcomes, increased resistance to chemotherapy, and enhanced metastatic ability.28 In 2008, Varticovski‘s group first described CD133 as a CSC marker in mouse breast cancer cells. The CD133+ cells showed increased colony formation and have a greater ability to form tumors in mice.29 Later, more studies indicated the CD133+ subpopulation in breast cancer cells showed higher stemness.28 This makes CD133 not only a marker for identifying BCSCs but also a promising target for therapeutic intervention. 1.2.3 HER2 HER2, a member of the ErbB family of receptor tyrosine kinases, is overexpressed in approximately 15-30% of breast cancers, which are often associated with aggressive disease, poor prognosis, and resistance to treatment.30 HER2+ breast cancer cells exhibit enhanced proliferative and survival capabilities, which are further augmented in the CSC subpopulation.31 Accumulated evidence showed that BCSCs are closely related to the development of HER2+ breast cancer.32 Thus, HER2 is a compelling target for BCSC targeting and BCSC-directed therapies. 1.3 CSC Biomarker-mediated Drug Delivery Traditionally, chemotherapy has been a cornerstone of cancer treatment, utilizing cytotoxic drugs to kill rapidly dividing cancer cells. However, despite its widespread use, chemotherapy meets several significant challenges, including low circulation time in the body, non-specificity, and the lack of ability of killing CSCs.33-34 To increase the circulating time of an anti-cancer drug, the free drug was often encapsulated in various types of carriers to form nanodrug and enable drug delivery. Doxil, a doxorubicin loaded liposome, is the first FDA-approved nanodrug.35 Encapsulation in liposome enables protection of the free drug and prolongs drug circulation time. Doxil is passively targeted to tumors and releases doxorubicin in the tumors. Passive targeting relies on the Enhanced Permeability and Retention 4 (EPR) effect, where long-circulating nanoparticles accumulate in tumors due to leaky vasculature and poor lymphatic drainage.36-38 However, without specific targeting, this method often results in insufficient drug levels at the target site, leading to ineffective treatment outcomes.39 Factors including tumor heterogeneity, complex tumor microenvironment, non-specific uptake, and patients’ variability contribute to poor efficiency of drug delivery. Despite improvements in drug stability and reduced toxicity (e.g., Doxil), passive targeting does not significantly enhance clinical response because it does not ensure adequate drug release within the tumor cells.21, 35 Additionally, passive targeting can still cause systemic side effects and damage to healthy tissues, limiting the dosage and duration of treatment. To better target CSCs and reduce side effects, CSC biomarker-mediated drug delivery was developed. CSC biomarker-mediated drug delivery enhances the precision of cancer therapy by attaching the targeting molecule on carriers to actively deliver drugs to CSCs in tumors.5, 18 This approach improves drug accumulation in the tumor microenvironment and reduces exposure to healthy tissues. This method can overcome the limitations of passive targeting, leading to more effective CSCs killing and reduced side effects. By enabling precision medicine, CSC biomarker- mediated drug delivery has the potential to significantly improve treatment outcomes. This section will introduce the CSC biomarker-mediated drug delivery for breast cancer (targeting BCSCs), the biomarkers include CD44, CD133, and HER2. CD44 Zhong’s group developed two types of nanoparticles: 8-hydroxyquinoline (8-HQ) loaded hyaluronan-modified mesoporous silica nanoparticles (HA-MSS) and docetaxel (DTX) loaded MSS for targeted drug delivery to BCSCs (Figure 1.1a).40 BCSCs were enriched from MCF-7 breast cancer cells by a spheroid formation method and confirmed with the CD44+/CD24- 5 phenotype. HA-MSS nanoparticles showed increased uptake in MCF-7 mammospheres via receptor-mediated endocytosis. DTX or DTX loaded MSS were more cytotoxic to MCF-7 cells, while 8-HQ or 8-HQ loaded HA-MSS were more cytotoxic to MCF-7 mammospheres. The combination therapy of DTX loaded MSS and 8-HQ loaded HA-MSS exhibited the strongest antitumor efficacy in MCF-7 xenograft mice with minimal systemic toxicity (Figure 1.1b, c). This combination therapy offers a potential strategy for effectively treating breast cancer by targeting both cancer cells and BCSCs. Yang’s group developed a thioridazine (THZ) and DOX encapsulated micelles, which self- assembled from specific diblock copolymers to co-deliver the drugs to target both cancer cells and CSCs.41 BCSCs were sorted from the BT-474 human breast cancer cell line and identified by CD44+/CD24- phenotype. In vitro results showed that DOX alone was less effective against CSCs compared to THZ and THZ-loaded micelles (THZ-MM). Co-delivery of DOX and THZ had a stronger inhibitory effect on CSCs compared to free drugs. In vivo, the co-delivery of DOX-MM and THZ-MM demonstrated the highest antitumor efficacy in BT-474 xenograft mouse model, significantly reducing the CSC population. This combination therapy offers a promising approach for treating breast cancer by targeting both non-stem cancer cells and CSCs. Wang’s group used an amphiphilic copolymer poly(ethylene glycol)-block-poly(D,L- lactide) (PEG-b-PLA) as a delivery carrier to deliver bortezomib (BTZ).42 BCSCs were enriched with a spheroid formation method and identified with ALDEFLUOR kit. The resulting BTZ loaded nanoparticles (NPBTZ) efficiently delivered BTZ to both CSCs and non-CSCs, inhibiting proliferation and inducing apoptosis. NPBTZ was particularly effective at reducing CSC stemness and showed a better suppression of tumor growth in the MDA-MB-468 breast tumor model compared to free BTZ. 6 Wang’s group developed cross-linked multilamellar liposomal vesicles (cMLVs) to co- deliver salinomycin (SAL) and DOX, targeting both CSCs and non-stem breast cancer cells.43 BCSCs were enriched with the mammosphere formation assay and identified with ALDEFLUOR kit. In vitro experiments demonstrated that cMLV(DOX + SAL) was more effective against breast cancer cells than either drug alone. In vivo tests showed that cMLV(DOX + SAL) suppressed breast tumors twice as effectively as single-drug cMLV treatments or combinations of separate cMLV(DOX) and cMLV(SAL). This study highlights cMLVs as a promising drug delivery platform for combination therapy targeting both breast cancer cells and CSCs. Chen’s group synthesized a new amphiphilic polymer, hyaluronic acid-cystamine- polylactic-co-glycolic acid (HA-SS-PLGA), then created nanoparticles to deliver DOX and cyclopamine (CYC), an inhibitor of the hedgehog signaling pathway in CSCs.44 These nanoparticles exhibited a redox-responsive drug release profile, specifically targeting CD44- overexpressing BCSCs and bulk cancer cells. In vitro tests showed that the dual drug-loaded nanoparticles significantly reduced the number and the size of tumor spheres. In vivo studies using an orthotopic mammary fat pad tumor model revealed that the combination therapy had a remarkable synergistic anti-tumor effect and prolonged survival compared to monotherapy. This co-delivery system offers a promising strategy for cancer treatment with controlled release and high efficacy. Al Faraj’s group combined the therapeutic drugs Paclitaxel and Sal, delivering them selectively via biocompatible single-walled carbon nanotubes conjugated with CD44 antibodies.45 This setup uses a hydrazone linker to enable pH-responsive drug release in the acidic tumor microenvironment. BCSCs in MDA-MB-231 cells were identified with the CD44+/CD24- phenotype. In vitro tests on MDA-MB-231 cells and in vivo evaluations on tumor-bearing mice 7 demonstrated the superior therapeutic efficacy of this combined treatment compared to individual drug-conjugated or free drugs. Kim’s group used HA-conjugated liposomes to deliver gemcitabine (GEM) specifically to BCSCs, leveraging HA's affinity for CD44 surface markers.46 BCSCs were enriched in MCF-7 cells by a spheroid formation method and identified with the CD44+/CD24- phenotype. The in vitro results showed that these liposomes significantly enhanced GEM's cytotoxicity, anti-migration, and anti-colony formation abilities by targeting CD44 on BCSCs. In an MCF-7 xenograft mouse model, the antitumor effect of the liposomal GEM was 3.3 times greater than free GEM, likely due to targeted CD44 receptor binding and increased drug stability. Overall, HA-conjugated GEM liposomes show potential for effectively targeting and treating BCSCs in breast cancer therapy. In another of Kim’s work, they developed negatively charged 1,2-dimyristoyl-sn-glycero- 3-phosphoglycerol (DMPG)-based liposomes and then incorporated with the neutral lipid 1- palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) to target MCF-7 breast cancer cells.47 The metformin (Met) and sodium salicylate (Sod) loaded DMPG-POPC liposomes significantly increased cytotoxicity and anti-colony formation abilities compared to individual drug- encapsulated liposomes or free drugs in BCSCs. Thus, DMPG-POPC liposomes containing Met and Sod present a promising approach for synergistic anti-cancer therapy by improving drug delivery efficiency to breast cancer cells and BCSCs. Kim’s group developed a drug-loaded liposome linked with two types of DNA aptamers targeting MUC1 on breast cancer cells and CD44 on CSCs.48 BCSCs were enriched in MCF-7 cells by the mammosphere formation method and identified with the CD44+/CD24- phenotype. DOX loaded dual-aptamer-conjugated liposomes (dual-Apt-DOX) enabled delivery of DOX to 3D-cultured breast cancer cells and CSCs and showing significantly higher toxicity compared to 8 liposomes without aptamers. Additionally, dual-Apt-DOX demonstrated inhibitory activity against the metastasis of BCSCs in nude mice. Therefore, the dual-aptamer-conjugated liposomal system is a promising drug delivery carrier for treating breast cancer, effectively targeting both cancer cells and CSCs. Figure 1.1. (a) The scheme of preparation of drugs-loaded HA-MSS. In vivo efficacy evaluation. 105 MCF-7 mammosphere cells were injected into the left side of mammary fat pad of mice on Day 0. Saline, HA-MSS, DTX (10 mg/kg), DTX-loaded MSS (10 mg/kg), 8-HQ (50 mg/kg) and 8-HQ-loaded HA-MSS (50 mg/kg), DTX (10 mg/kg) combined with 8-HQ (50 mg/kg), and DTX loaded MSS (10 mg/kg) combined with 8-HQ-loaded HA-MSS (50 mg/kg) were intravenously injected into mice respectively at days 15, 18, 22, and 25. (b) The tumor volume (V) was calculated by the following formula: V = (L x W2)/2 (L: length; W: width). Arrows indicate the day when the drugs were administrated. (c) The images of excised tumor at the end of treatment (day 43). The scale bar is 10 mm. This figure is reproduced with permission from the publisher. CD133 Li’s group used mesoporous silica nanoparticles (MSNs) encapsulating superparamagnetic iron oxide nanoparticles (Fe3O4 NPs) with the surface modified by a specific antibody and a nucleus-targeting agent (TAT peptide) (Figure 1.2).49 It has four layers: an antibody conjugated 9 with a thermo-sensitive azo linker for CSC targeting, the TAT peptide for nucleus targeting, an MSN shell loaded with the anticancer drug tirapazamine (TPZ) for hypoxic CSCs, and an Fe3O4 NP core that generates heat to trigger drug release under an alternating magnetic field. In vivo and in vitro tests using BCSCs and BCSC-xenograft nude mice demonstrated significant inhibition of CSC survival and tumor growth. Figure 1.2. Synthesis of CD133/TAT/TPZ-Fe3O4@mSiO2 NPs and scheme of the multistage targeting for CSCs targeting therapy. This figure is reproduced with permission from the publisher. 10 HER2 Wang’s group created Sali-NP-HER2 by conjugating anti-HER2 antibodies to Sal nanoparticles (Figure 1.3a).50 BCSCs were identified in BT-474 cells with ALDEFLUOR kit. In vitro studies showed that Sali-NP-HER2 effectively bound to HER2-positive cells, enhancing cytotoxic effects and inhibiting tumor growth more effectively than non-targeted nanoparticles or Sal alone. In vivo studies using mice bearing breast cancer xenografts demonstrated that the administration of Sali-NP-HER2 significantly inhibited tumor growth more effectively than non- targeted nanoparticles or salinomycin (Figure 1.3b, c). The treatment also reduced tumorsphere formation and the proportion of BCSCs. Thus, Sali-NP-HER2 presents a promising therapeutic strategy for HER2-positive breast cancer by simultaneously targeting CSCs and cancer cells. Overall, BCSC biomarker-mediated drug delivery showed promising results in CSC targeting and efficacy in suppression of tumor growth. However, there is still a lot of room for improvement, such as off-target drug accumulation and inefficient drug level in target site. Image- guided drug delivery is an appropriate approach to improve and optimize the drug delivery system. In the next section, I will review the recent literature on image-guided drug delivery for BCSCs. 11 Figure 1.3. (a) Preparation of Sali-NP-HER2. BT-474 cells were inoculated to mice to build the tumor mouse model.50 Mice were injected with nanoparticles (7.5 mg salinomycin/kg) through the tail vein, and salinomycin (7.5 mg salinomycin/kg) dissolved in ethanol was administered by intraperitoneal injection. Treatment was given nine times on alternate days (indicated by arrows), and tumor volume (V) was calculated with formula: V = (L x W2)/2 (L: length; W: width). (b) Tumor volume growth curve. (c) Photos of excised tumors. International Journal of nanomedicine 2017:12 6909-6921 Originally published by and used with permission from Dove Medical Press Ltd. 1.4 BCSC Image-guided Drug Delivery Drug delivery to cancers faces significant challenges due to factors such as drug type, administration procedure, and tumor characteristics. Key issues include insufficient drug levels at the target site, systemic toxicity, acquired drug resistance, and damage to healthy tissues.5, 17-18 These problems result in limited dosages, interrupted treatment, and the inability to treat in cases of recurrence. Therefore, improving drug delivery to the tumor microenvironment, enhancing 12 intra-tumoral drug accumulation, and minimizing exposure to healthy tissues are critical needs in drug delivery. Image-guided drug delivery addresses these challenges by using imaging techniques to enhance the precision and effectiveness of drug delivery to tumors. Image-guided drug delivery allows for real-time monitoring of therapeutic nanoparticles to the tumor site, ensuring higher drug availability at the target.19-21 Additionally, image-guided drug delivery facilitates precise tracking of drug pharmacokinetics, biodistribution, and accumulation, allowing dynamic adjustments to treatment protocols. By concentrating the drug's action within the tumor and minimizing systemic exposure, image-guided drug delivery significantly improves therapeutic outcome. In this section, I will review the BCSC image-guide drug delivery articles with the modalities including fluorescence imaging, MRI, and photoacoustic imaging. 1.4.1 Fluorescence imaging-guided drug delivery Fluorescence imaging has emerged as a powerful tool in cancer diagnostics and research due to its ability to provide high spatial resolution and contrast. This imaging technique involves the use of a fluorescent dye that emits light upon excitation, allowing for the visualization of cellular and molecular processes in real time. Despite its advantages, traditional fluorescence imaging faces significant limitations, such as low signal-to-noise ratios and autofluorescence when using short-wavelength UV radiation. These issues can affect the detection of fluorescent signals and reduce the accuracy of imaging. Near-infrared (NIR) fluorescence imaging offers several advantages over traditional fluorescence imaging, particularly when used for biological and medical applications.51-52 NIR fluorescence imaging significantly reduces background autofluorescence from biological tissues. Most biological tissues exhibit lower autofluorescence in the NIR region (700-900 nm) compared to the visible region, resulting in higher signal-to-noise 13 ratios and clearer images.53-54 Additionally, NIR light penetrates deeper into biological tissues than visible light. This is because NIR wavelengths experience less scattering and absorption by tissue components. This allows for more accurate detection and quantification of fluorescent probes. These advantages make NIR fluorescence imaging a powerful tool for a variety of applications, including image-guided drug delivery for BCSCs. He’s group prepared DOX, irinotecan (CPT), and ICG loaded nanoparticles (HAC-PFP) composed of four FDA-approved polymers: poly(D,L-lactide-co-glycolide) (PLGA), Pluronic F127 (PF127), chitosan, and HA. The HA is used not only for targeting CSCs, but also as a stabilizing agent to synthesize the nanoparticles. Electrostatic interactions between HA and chitosan can be broken in acidic conditions (late endosomes/lysosomes), leading to dissociation of HA and chitosan and drug release. Additionally, with the ICG encapsulation, HAC-PFP nanoparticles enabled NIR-FI for cancer imaging and biodistribution monitoring in vivo.55 In vitro and in vivo, these nanoparticles enabled acidic pH-triggered drug release and thermal responsiveness and effective destruction of CSCs, achieving up to 500 times greater efficacy compared to a mixture of the two drugs. This work demonstrates the potential of the co-delivery of DOX and CPT in one nanoparticle, which enables active targeting and dual responsiveness in overcoming drug resistance. In another work by the He group, they created C60 fullerene-silica nanoparticles decorated with HA to target CD44 receptors overexpressed on BCSCs.56 These nanoparticles encapsulate DOX and ICG with a 90% efficiency and high drug loading content (up to 48.5%). The multifunctional nanoparticles enable the combined chemo, photodynamic, photothermal therapy, and NIR-FI (Figure 1.4a), effectively destroying breast CSCs both in vitro and in vivo without systemic toxicity (Figure 1.4b). These nanoparticles improved drug delivery into tumor while 14 reduced drug accumulation in major normal organs such as the liver and kidney after intravenous injection. Yang’s group developed ultra-small magnetic iron oxide nanoparticles (IONPs) conjugated with peptides targeting both Wnt/LRP5/6 and urokinase plasminogen activator receptor.57 These dual-targeted IONPs were shown to inhibit breast cancer cell invasion and reduce Wnt/b-catenin signaling and the cancer stem-like phenotype. Additionally, IONP-DOX was conjugated with NIR-830 dye, enabling NIR fluorescence imaging to evaluate the target specificity. In vivo, systemic administration of these IONPs led to effective drug delivery to patient-derived xenograft (PDX) tumors, resulting in stronger tumor growth inhibition compared to non-targeted or single- targeted IONP-DOX treatments. The development of targeted nanoparticle drug carriers using multiplexed peptide targeting ligands demonstrated a new approach for delivery of therapeutic peptides and anticancer drugs into CSC population. Tian’s group developed a pH-sensitive polymer, poly(ethylene glycol)-benzoic imine- poly(ɣ-benzyl-L-aspartate)-b-poly(1-vinylimidazole) block copolymer (PPBV), creating a pH- responsive micellar system for co-delivery of paclitaxel (PTX) and curcumin (CUR).58 This system can change its surface charge, shed its PEG layer, and reduce its size in response to the tumor’s acidic environment, enhancing cellular uptake and deep tumor penetration. These properties enable the micelles to deliver PTX and CUR more effectively, maximizing their combined therapeutic efficacy against both CSCs and non-CSCs. In addition, DiR was loaded to micelles, enabling fluorescent imaging to estimate the in vivo bio-distribution. In vivo studies showed that these micelles achieved superior tumor inhibition and effective CSC elimination, demonstrating its potential as a powerful platform for combination cancer therapy. With the pH-responsive linkage and pH-sensitive charge-switching segment, the PPBV micelles overcame the drawbacks of 15 PEGylation design and increased the blood circulation time, improved cellular uptake and enhanced tumor accumulation. Kim’s group presents Nic-A, a prodrug combining a carbonic anhydrase IX inhibitor (acetazolamide) with a STAT3 inhibitor (niclosamide), targeting triple-negative breast cancer (TNBC) CSCs.59 Nic-A effectively inhibits both proliferating TNBC cells and CSCs by disrupting STAT3 signaling and suppressing CSC-like traits. It reduces ALDH1 activity, CD44high/CD24low stem-like subpopulations, and tumor spheroid formation. The Nic-A drug release design was evaluated by in vivo fluorescence imaging with its Analog Res-A. In TNBC xenograft models, Nic-A treatment decreased angiogenesis, tumor growth, Ki-67 expression (a prognostic factor for breast cancer), and increased apoptosis. Figure 1.4. In vivo tumor targeting and antitumor efficacy of HC60S-DI nanoparticles with NIR laser irradiation. (a) In vivo fluorescence imaging of ICG at 6 h after intravenous injection via the tail vein of free ICG and HC60S-DI nanoparticles with low and high drug loading content (DOX:ICG:HC60S nanoparticles = 1:1:20 and 1:1:1). The arrows indicate the locations of tumor. (b) Tumor growth curves for the different treatments (n = 5) and images of the tumors collected after sacrificing the mice on day 29. *p < 0.05 (n = 5). When tumors were established and reached ~5 mm in long diameter, mice were treated with various drug formulations with or without NIR laser irradiation. The tumor volume (V) was calculated as: V = (L x W2)/2 (L: length; W: width). This figure is reproduced with permission from the publisher. 16 1.4.2 MRI-guided drug delivery MRI is a widely used imaging technology in clinical medicine, renowned for its ability to provide detailed and high-resolution images of the internal structures of the body. The principle of MRI relies on the behavior of hydrogen atoms in the presence of an external magnetic field. When subjected to such a field, the hydrogen nuclei generate different relaxation times, which are then detected and processed by sophisticated computer algorithms to reconstruct detailed images.60 One of the key advantages of MRI is its non-invasive nature, and it does not involve ionizing radiation, making it a safer option compared to CT or PET scans.19, 61 MRI is often enhanced by contrast agents, and iron oxide nanoparticles are commonly used MRI contrast agents because of their good biocompatibility without toxic side effects. With these advantages, MRI has also been used for BCSC image-guided drug delivery. Moon’s group used DOX-loaded superparamagnetic iron oxide nanoparticles (SPIONs), conjugated with an extradomain-B of fibronectin (EDB-FN)-specific peptide (APTEDB), for detecting and treating BCSCs in a xenograft mouse model (Figure 1.5a).62 The Dox@APTEDB- TCL-SPIONs facilitated more efficient delivery of DOX to tumors compared to non-targeted SPIONs. Treatment with these targeted nanoparticles showed significant signals in tumors in MR images and resulted in significantly greater inhibition of BCSC tumor growth than either non- targeted SPIONs or free DOX (Figure 1.5b, c). This indicates that Dox@APTEDB-TCL-SPIONs can detect and target BCSCs within tumors, demonstrating their potential for both therapy and diagnostic imaging (theranostics) in breast cancer. 17 Figure 1.5. (a) Scheme of the preparation of Dox@APTEDB-TCL-SPIONs. (b) Representative T2*-weighted MR images of tumors (red circles) with the indicated SI ratios 7 days after three intravenous injections of Dox@APTEDB-TCL-SPIONs ([Dox]: 2 mg/kg; [APTEDB-TCL- SPIONs]: 20 mg Fe/kg). (c) Tumor volumes of mice treated with Dox@APTEDB-TCL-SPION, Dox@TCL-SPIONs, or free Dox compared to control mice. Data are expressed as the mean ± S.D (n = 5). *, p < 0.05. This figure is reproduced with permission from the publisher. 1.4.3 Photoacoustic imaging-guided drug delivery Photoacoustic imaging is an innovative biomedical imaging technique that leverages the photoacoustic effect to generate high-resolution images of biological tissues. This modality involves delivering non-ionizing laser pulses into tissues, where part of the laser energy is absorbed and converted into heat. This heat induces transient thermoelastic expansion, resulting in the emission of ultrasonic waves. These ultrasonic waves are detected by ultrasonic transducers. The detected signals are then analyzed to reconstruct detailed images of the tissue.63 Recent 18 advancements in photoacoustic imaging have seen significant progress in the development of nano photoacoustic probes, which include materials such as gold-based nanoprobes,64-65 carbon-based nanoprobes,66 and organic molecules, including ICG and NIR dyes.67-70 These probes have significantly enhanced the capabilities of photoacoustic imaging technology, and some of them have been used in image-guided drug delivery to target BCSCs. Zhang’s group developed a stimuli-responsive, tumor-targeted nanodrug composed of the hydrophobic differentiation-inducing agent all-trans retinoic acid (ATRA) and the hydrophilic anticancer drug irinotecan (IRI).71 These components self-assembled into nanoparticles that also encapsulated the photothermal agent IR825 then coated with DSPE-PEG-RGD(ARG-GLY-ASP) to form IR825@IRI-ATRA/RGD NPs. Upon uptake by cancer cells, the nanodrug releases its contents in response to acidic and esterase-rich environments, promoting CSC differentiation into non-CSCs and increasing chemotherapy sensitivity. Additionally, IR825 allows for in vivo fluorescence and photoacoustic imaging to track drug distribution (Figure 1.6a). In vivo, the nanodrug shows high tumor accumulation, good biocompatibility, and effectively inhibits tumor growth and metastasis in mouse models (Figure 1.6b). This design of the combination therapy holds great potential for eradication of CSCs and overcoming the chemotherapy resistance. 19 Figure 1.6. (a) In vivo photoacoustic images of subcutaneous 4T1 tumor-bearing mice at various time points (0, 1, 4, 8, 12, 24 and 48 h) after intravenous injection of IR825@IRI-ATRA/RGD NPs at the dose of IR825 (4.1 mg/kg). (b) Tumor volume growth for tumor-bearing mice treated with various formulations within 16 days of treatment. This figure is reproduced with permission from the publisher. 1.5 Conclusions and Perspectives This review highlights the significant advances and promising strategies in the field of image-guided drug delivery targeting BCSCs. Breast cancer remains a major global health concern, and the presence of BCSCs contributes to its aggressiveness, recurrence, and resistance to conventional therapies. By leveraging biomarkers such as CD44, CD133, and HER2, researchers have developed innovative drug delivery systems aimed at effectively targeting and eradicating BCSCs. 20 Most of the work discussed focused on CD44 and fluorescence imaging, demonstrating the potential of biomarker-mediated and imaging-guided approaches to enhance drug delivery precision and therapeutic outcomes. The primary ligand of CD44, HA, is significantly more affordable (approximately $200/g) compared to monoclonal antibodies, which can cost several hundred dollars per 100 μg. This cost difference makes the usage of HA a popular approach to target CD44+ BCSCs. The use of fluorescence imaging, especially NIR fluorescence, has provided valuable insights into the biodistribution and targeting efficiency of nanoparticles in real-time. These advancements highlight the importance of integrating imaging modalities with targeted drug delivery to achieve higher specificity and reduced systemic toxicity. However, despite these promising developments, there are still significant challenges and room for improvement. The issues of off-target drug accumulation and insufficient drug levels at the target site persist. The exploration of other biomarkers and imaging modalities to optimize drug delivery systems further is needed. MRI, CT, PET, and photoacoustic imaging have shown potential as complementary techniques to fluorescence imaging, offering deeper tissue penetration and high-resolution imaging capabilities. Future research are needed the following areas to advance image-guided drug delivery for BCSCs: (1) Diversification of biomarkers: Expanding the biomarkers beyond CD44 to include CD133, HER2, EpCAM, MUC1, GD2, and other emerging biomarkers could enhance the targeting specificity and effectiveness of drug delivery systems. (2) Advanced imaging modalities: Incorporating MRI, CT, PET, photoacoustic imaging, and other advanced imaging techniques can provide comprehensive insights into the pharmacokinetics, biodistribution, and real-time monitoring of therapeutic nanoparticles, enabling dynamic adjustments to treatment. (3) 21 Multimodal imaging: Developing multimodal imaging systems can offer synergistic benefits, providing detailed and complementary information to guide drug delivery. In conclusion, while significant progress has been achieved in the field of image-guided drug delivery for BCSCs, there is a need for continued research and innovation. By addressing the current challenges and exploring new biomarkers and imaging modalities, it is possible to develop more effective and precise therapeutic strategies to combat breast cancer and improve patient outcomes. 22 REFERENCES (1) Lapidot, T.; Sirard, C.; Vormoor, J.; Murdoch, B.; Hoang, T.; Caceres-Cortes, J.; Minden, M.; Paterson, B.; Caligiuri, M. A.; Dick, J. E., A cell initiating human acute myeloid leukaemia after transplantation into SCID mice. Nature 1994, 367, 645-648. Bonnet, D.; Dick, J. E., Human acute myeloid leukemia is organized as a hierarchy that (2) originates from a primitive hematopoietic cell. Nat. Med. 1997, 3, 730-737. Reya, T.; Morrison, S. J.; Clarke, M. F.; Weissman, I. L., Stem cells, cancer, and cancer (3) stem cells. Nature 2001, 414, 105-111. (4) Singh, S. K.; Clarke, I. D.; Terasaki, M.; Bonn, V. E.; Hawkins, C.; Squire, J.; Dirks, P. B., Identification of a Cancer Stem Cell in Human Brain Tumors. Cancer Res. 2003, 63, 5821- 5828. 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Copyright {2022} American Chemical Society 2.1 Introduction Among women, breast cancer is the most diagnosed cancer and cause most cancer related death. In 2020, it was estimated that there were 2.3 million new cases (11.7% of all cancer cases) and 685,000 deaths due to breast cancer in the world.1 Detection of breast tumor is crucial to guide the treatment and improve survival. Non-invasive imaging and detection of breast cancer is an attractive field of research.2 Various imaging modalities have been developed to diagnose breast cancer, including positron emission tomography (PET), single-photon emission computed tomography (SPECT), X-ray computed tomography (CT), magnetic resonance imaging (MRI), ultrasound, and fluorescence imaging.3-6 However, each modality has its own limitations such as sensitivity, specificity, background signals from normal tissues, and the depth of tissues that can be imaged, leading to a challenge for accurate breast cancer diagnosis by a single modality. Multimodal imaging is an emerging strategy to provide images co-registered from multiple modalities.7-11 It can potentially overcome the limitations of individual imaging methods by supplying complementary information from multiple imaging techniques. Herein, we report our efforts in multimodality imaging of breast cancer in the spontaneous tumor model of MMTV-PyMT transgenic mice by magnetic particle imaging (MPI), 29 photoacoustic imaging (PAI), and fluorescence imaging, which was enabled by a single platform, i.e., the iron oxide nanoworm (NW) platform functionalized with indocyanine green (ICG). MPI is a nascent imaging modality that detects superparamagnetic iron oxide tracers.13 MPI has multiple advantages including high-imaging contrast, high sensitivity, potential linear correlation between signal strength and tracer concentration, high imaging depth, no ionizing radiation, and nearly no background.14 MPI aided by magnetic tracers have been applied to various applications including cancer imaging.12, 15-16 To date, only a few of the MPI related multimodality imaging results were reported. The Krishnan group demonstrated a lactoferrin conjugated NPs that enabled tumor imaging via MPI and fluorescence imaging with a xenograft tumor mouse model.12 Rao and coworkers presented a nanoplatform that enabled MPI, MRI, PAI, and fluorescence imaging for detection of xenografted breast tumor.9 However, multimodal imaging for diagnosis of multiple tumors in a mouse model of spontaneous tumor have not been reported. PAI is an imaging method detecting the acoustic waves generated by a contrast agent, rather than the emitted fluorescence. As a result, PAI can enable detection at deeper tissue depth with high spatial resolution as compared to typical optical imaging techniques.17 A contrast agent such as ICG can absorb the energy from the incident laser in PAI. Part of the absorbed energy is converted to heat, causing a thermoelastic expansion, which generates an acoustic wave for detection.18-21 An advantage of ICG is that it is a water-soluble near-infrared (NIR) dye approved by the Food & Drug Administration (FDA) as a clinical imaging agent with a good safety profile.22- 29 For in vivo applications of nanoprobes, it is important that the probes are highly biocompatible. Iron oxide nanoworms (NWs)30-32 are associated with a much lower inflammatory response in vitro 30 and in vivo compared to the corresponding spherically shaped iron oxide nanoparticles (SPIONs).33 The stability of probes is crucial for in vivo diagnosis as well. Researchers developed the hybrid ICG-SPION approach through simple mixing34-35 or non-covalent encapsulation36-37 for multimodal imaging. However, ICG can leak out of those particles, complicating the interpretation of imaging results. To achieve better diagnosis of breast cancer, we covalently conjugated ICG to iron oxide nanoworms (NW-ICG), which could be passively targeted to breast tumor via the enhanced permeability and retention (EPR) effect.38-41 The new nanoprobes enabled noninvasive detection of breast tumors by integrating three imaging modalities into one platform. 2.2 Results Synthesis and Characterization of NW-ICG Synthesis of NW-ICG started from dextran-coated superparamagnetic iron oxide NWs, which were prepared through the coprecipitation method in the presence of dextran (40 kDa) (Scheme 2.1). The surface dextran on NWs was then cross-linked with epichlorohydrin followed by treatment with ammonia to introduce amine groups on the surface (NW-NH2).33 ICG-N- hydroxy succinimide (NHS) ester was then conjugated with NW-NH2 leading to NW-ICG. 31 Scheme 2.1. Synthesis of NW-ICG. The morphology of NW-ICG synthesized was characterized by transmission electron microscopy (TEM), which showed worm-liked shape of the NW-ICG (Figure 2.1a, Figure S2.1). The average length of NW-ICG’s iron oxide core was 68 ± 18 nm, corresponding to 15−30 sphere NPs forming a chain of each NW (Figure 2.1a). The zeta potential of NW-ICG was +3.6 mV and the average hydrodynamic diameter was 103 nm (Figure S2.2). The absorbance and emission maximum peaks of NW-ICG blue-shifted from 790 nm to 780 nm and from 810 nm to 800 nm respectively compared to the parent molecule ICG (Figure 2.1b). The blue shifts of the absorbance and fluorescence maxima could be due to the metal enhanced fluorescence effect or the nanoaggregation of ICG when conjugated to the NWs.42-44 The fluorescence signals of NW-ICG (excitation at 790 nm) correlated linearly with nanoparticle concentration (Figure 2.1c). The NW- ICGs were also imaged by PAI in test tubes placed in an agar phantom. Single wavelength (780 nm) anatomical photoacoustic (PA) images showed increasing PA signals with increasing sample concentrations (Figure 2.1d). PA spectrum of NW-ICG (Figure 2.1e) showed a distribution 32 profile consistent with its UV-Vis absorbance spectrum. This enabled us to use the specific wavelength with a higher absorbance for excitation in PAI, enhancing the strength of PA signals. Figure 2.1. (a) TEM images showed the worm-like morphology of NW-ICG. The scale bar is 20 nm. (b) Normalized UV-Vis absorption and emission spectra of NW-ICG and free ICG. (c) Linear correlation between the fluorescence signal intensity and Fe concentration of NW-ICG; (d) PA images of three concentrations of NW-ICG (diluted in water) loaded test tubes in agar phantom. Three samples: 1. iron concentration 1 mg/mL, 2. iron concentration 0.5 mg/mL, and 3. iron concentration 0.1 mg/mL. (e) The PA spectrum. (f) Linear correlation between MPI signal intensities and Fe concentration for NW-ICG and Vivotrax respectively. NW-ICG gave stronger MPI signals compared to Vivotrax as suggested by the steeper slope highlighting the advantage of NW-ICG as MPI contrast agents. The ability of NW-ICG to function as MPI contrast agents was analyzed. Increasing concentrations of NW-ICG in aqueous solutions were imaged by MPI in test tubes to determine the signal to Fe content sensitivity. The MPI signals of NW-ICG solution showed a linear correlation with the Fe concentration (Figure 2.1f). To benchmark the performance of NW-ICG in MPI, commercially available iron oxide nanoparticle-based contrast agent Vivotrax was used for head-to-head comparison. Vivotrax (Magnetic Insight Inc., CA, USA) is a carboxydextran coated SPION with a core size of 4.2 nm and a mean hydrodynamic diameter of 62 nm. As shown 33 in Figure 2.1f, NW-ICG exhibited 1.5 times higher MPI signal sensitivity compared to Vivotrax highlighting the advantage of NW-ICG. To evaluate the biocompatibility of NW-ICG, cell viability MTS assays were performed with Raw 264.7 cells (Figure S2.3). No significant changes in cell viability were observed after incubation with various concentrations (0.5, 0.25, and 0.13 mg Fe/mL) of NW-ICG. NW-ICG enabled multi-modality imaging of breast cancer To examine the cancer imaging ability of NW-ICG, we tested it in the MMTV-PyMT transgenic mice. MMTV-PyMT mice express the Polyoma Virus middle T antigen under the direction of the mouse mammary tumor virus promoter/enhancer,45-46 which leads to the spontaneous development of multiple palpable mammary tumors in 4-6 months. Compared to xenograft models of mouse breast cancer, the MMTV-PyMT mouse can mimic more closely the human breast cancer conditions with native tumor microenvironment. Five month-old female MMTV-PyMT mice were administered with NW-ICG (16 mg of iron /kg body weight) through the tail veins, which were followed by serial imaging with MPI, PAI, and fluorescence over 72 hours. Mice were also imaged by CT to provide anatomical background for the images. As a comparison, a control group of mice received Vivotrax at the identical level of iron. While there were no endogenous MPI signals in the mice before administration of NW-ICG, one hour post infection, strong signals were observed with the dominant location of signals from the liver area. Several tumors gave medium levels of MPI signals, indicating NW-ICG were delivered to tumor at 1 hour already (Figure 2.2a). Besides liver and tumor, other organs with MPI signals observed included spleen and bladder. Longitudinal imaging of the mouse showed increasing MPI signal strength in multiple breast cancer locales with concomitant reduction of liver signals. The relative % of MPI signals in tumor areas over the whole 34 mouse body was quantified (Figure 2.3b), which increased from 5% to 23% from 1 to 72 hours. In contrast, in control mice receiving the Vivotrax, MPI signals were mostly observed in the liver with little signals (~ 3%) from the tumor areas over the 72 hours span (Figures 2.2b and 2.3b). The signals from original MPI images (Figure S2.4) were quantified. To compare the signal levels of in vivo MPI images at different time points, the color bars of MPI images in NW-ICG and control group were all set as 0.1 to 2.0 (Figure 2.2). Since neither NW-ICG nor Vivotrax bore tumor targeting molecules on the surface, they were presumably passively targeted to tumors via the EPR effect. Mice receiving NW-ICG showed higher levels of MPI signals in tumor compared to those administered with Vivotrax. These results highlight the advantage of NW-ICG over Vivotrax for breast cancer imaging in this mouse model. Figure 2.2. Imaging of MMTV-PyMT mice bearing multiple mammary tumors. (a) Projection of 3D MPI volumes at indicated time points co-registered with a CT skeletal scan of mice injected with NW-ICG. T: tumor, Lv: liver, Bl: bladder, Sl: spleen (b) Projection of 3D MPI volumes at indicated time points co-registered with a CT skeletal scan of mice injected with Vivotrax. (c) Percentage of MPI signals from tumors in mice over time. 35 With ICG covalently attached, NW-ICG enabled fluorescence imaging and detection of breast cancer besides MPI. The fluorescence images (Figures 2.3a) showed increasing fluorescence signals of tumor areas over time from 1 to 72 h post injection of NW-ICG (Figure 2.3c), confirming the MPI results. Figure 2.3. (a) Fluorescence images of mice injected with NW-ICG at different time points. (b) Percentage of fluorescence signal from tumors in mice over time. We next compared the tumor images obtained using MPI, PAI and fluorescence imaging (Figure 2.4 and Figure S2.5) taken pre-injection and 24 h post-injection. The axial 2D MPI/CT frames pulled out from 3D MPI/CT images showed well-located positions of tumors, including tumors deep in the body (Figure 2.4a, axial view). In comparison, for PAI, strong signals were observed on the surface of tumors (Figure 2.4b). There were little PAI signals from interior of tumor, most likely due to the limited penetration depth of excitation light. The fluorescence images mostly showed signals from part of the superficial tumors (Figure 2.4c), presumably due to the similar limitation of penetration depth of light. Fluorescence imaging also detected small amounts of NW-ICG signals in the blood vessels, which were absent in MPI suggesting a better sensitivity of fluorescence imaging compared to MPI toward targets that were not deep inside the body. Next, quantitative analysis was performed on the images. Following NW-ICG administration, the MPI signals showed the highest tumor to normal tissue ratio (TNR) of 50.4. In comparison, the PAI 36 signals exhibited a TNR of 18.0. The fluorescence imaging signal showed a lower TNR of 2.9, which could be due to the higher background fluorescence signal intensities in normal tissues. Figure 2.4. (a) MPI/CT images and the corresponding axial images at 24 h post-injection. Integration of MPI signals of normal tissue (white oval) and tumor (yellow oval) allowed for quantification of signal ratios of tumor over normal tissue; (b) In vivo PAI scan. Biodistribution of NW-ICG multispectral unmixing signal (hot) co-registered with ultrasound signal (gray). Integration of NW-ICG PA signal of normal tissue (white oval) and tumor (yellow oval) enabled the calculation of signal ratios of tumor over normal tissue. (c) Fluorescence images of mice at 24 h post-injection and integration of fluorescence signals in normal tissue (white oval), tumor (yellow oval), and blood vessel (white arrows) enabled calculation of signal ratios of tumor over normal tissues. Confirmation of mouse imaging via ex vivo analysis of the tissues To confirm the in vivo imaging results, mice were euthanized 72 h post-injection, and their organs were extracted and imaged by MPI, PAI, and fluorescence (Figure 2.5). The biodistribution of NW-ICG was analyzed ex vivo by quantification of MPI (Figure 2.5a), with the percentage of MPI signal in excised tumors determined at 37% among the total signals in organs extracted. 37 Strong PA signals were observed distributed throughout the excised tumor (Figure 2.5b, Figure S2.6). This contrasts with the surface localization of signals observed from in vivo PAI images, supporting the idea that PAI signals in mice observed only on tumor surface (Figure 2.4c) was due to the limited depth of tissue penetration by light for PAI. Fluorescence signals were also present in the liver, kidney, spleen, and all tumors in fluorescence imaging (Figure 2.5c). Moreover, the excised tumors were imaged by confocal microscopy with large field of view (FOV) (Figure 2.5d, Figure S2.7), which showed strong fluorescence from majority of cells in the tumor tissues indicating the NW-ICG nanoparticles were able to access most cells in tumor.47 To further confirm the presence of NW-ICG in tumor, excised tumors were stained with Prussian blue stain to detect iron ions. The immediate adjacent slides were subjected to histological analysis via Hematoxylin and eosin (H&E) staining. As shown in Figure 2.5f, extensive blue color was observed in tumor tissues by Prussian blue stain, confirming the presence of iron in tumor. Figure 2.5. (a) Percentage of MPI signals measured ex vivo in main organs extracted from mice receiving NW-ICG. (b) Ex vivo MSOT scan of tumor. NW-ICG PA signal (hot) co-registered with ultrasound signal (gray). The scale bar is 5 mm. (c) Ex vivo fluorescence images of mice at 72 h post-injection. T: tumor, Lv: liver, K: kidney, Sl: spleen, H: heart, L: lung. (d) Confocal image of breast tumor acquired by a custom-made confocal microscope. The scale bar is 40 μm. (e, f) Histological analysis of tumor tissues from mice receiving NW-ICG. e) H&E stain of tumor slide 38 Figure 2.5. (cont’d) and f) the immediate adjacent tissue stained by Prussian blue (iron showed blue) followed by nuclear fast red counterstain. The scale bars are 10 μm. 2.3 Discussion Multimodality imaging is an emerging strategy for cancer imaging because every imaging modality has its own advantages and disadvantages, and complementary imaging can validate the location of tumors and enhance the accuracy of detection. In the synthesis of NW-ICG, ICG was covalently conjugated to surface of NW, bestowing NIR fluorescence and photoacoustic properties to NW-ICG.23 Moreover, NWs have been shown to be biocompatible30-33 and ICG has been approved by FDA for clinical imaging,22-23, 25 indicating the high translational potential of NW- ICG. For MPI study of mice, the observation of signals from the bladder indicated that NW-ICG could be excreted through the urinary system, which is consistent with previous in vivo study of iron oxide nanoparticles (IONPs).48-49 Liver uptake of the NW-ICG was also observed that is common for nanoprobe in vivo study.9, 11, 15-16, 50 NW-ICG accumulated in tumor for a longer time than in other organs including liver and spleen. Compared to the commercially available IONP Vivotrax, we found that NW-ICGs are 1.5 times brighter and their tumor uptake was higher than Vivotrax as observed in MPI. These observations suggest NW-ICGs are excellent MPI contrast agents for breast tumor imaging. Furthermore, we found the inconsistency between intensities of MPI and fluorescence imaging in ex vivo results. We suspect this was due to different depth of the particles in various tissues. Particles that are present closer to the organ surface would appear brighter than the same amount of particles residing deeper in the tissue. However, we do not have strong evidence to support this explanation 39 MPI is an imaging modality with several advantages, including nearly zero background, quantitative nature, no ionizing radiation, and not limited by tissue penetration depth. With these advantages, MPI showed a 2.8 times higher TNR compared with MSOT and a 17.4 times higher TNR over fluorescence imaging in this study. On the other hand, fluorescence imaging and PAI can lead to better sensitivity toward superficial tumor. There are several limitations to our studies. The NW-ICGs utilized in this study do not bear any ligands to selectively target tumor. As a result, the selective accumulation of the particles in tumor is most likely due to the EPR effect.38-41 There can be significant variations in homogeneity, vascularity, and pore size between tumor types. Even the same type of tumor could vary in development stage and size, which can impact the EPR effect. To increase the sensitivity and specificity of detection, NW-ICG could be modified with a targeting agent, including peptides, polysaccharides, and antibodies.51-53 Nanoprobes bearing targeting ligands may selectively bind to tumor and increase tumor uptake. Although we only demonstrated diagnostic cancer imaging in this work, this nanoprobe may also be developed for theranostic application, including image- guided drug delivery, photothermal therapy, and magnetic hyperthermia.11, 54-58 2.4 Conclusion New ICG conjugated superparamagnetic iron oxide nanoworm was synthesized for breast cancer diagnosis. The NW-ICGs integrated magnetic, optical, as well as photoacoustic properties in one nanoprobe, providing a multimodal imaging system. These nanoprobes generated excellent contrasts in MPI, NIR fluorescence imaging, and PAI, indicating their capacity as a multimodal imaging contrast agent. When evaluated in a clinically relevant spontaneous breast cancer mouse model, the NW-ICGs led to a high tumor to normal tissue contrast, especially in MPI. These results demonstrate that NW-ICGs are promising nanoprobes for breast tumor imaging and diagnosis. 40 2.5 Experimental section Materials Iron(III) chloride hexahydrate (FeCl3·6H2O), Iron(II) chloride tetrahydrate (FeCl2· 4H2O), dimethyl sulfoxide (DMSO), dextran (MW: 40 kDa), epichlorohydrin, ammonium hydroxide (30% NH4OH), sodium hydroxide (NaOH), Dulbecco’s Modified Eagle Medium (DMEM) were purchased from Sigma-Aldrich. CellTiter 96 Aqueous One solution containing 3-(4,5- dimethylthiazol-2-yl)-5-(3-arboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium (MTS) were purchased from Promega. Ultrafiltration disk (100 kDa) and centrifugal filter MWCO (100 kDa) were purchased from EMD Millipore. ICG NHS ester was ordered from Ruixibiotech. Synthesis of aminated NW FeCl3·6H2O (1.2 mmol), FeCl2.4H2O (0.65 mmol), and 2.35 g dextran (~ 40 kDa) were mixed in water (20 mL), vigorously stirred under nitrogen. A stream of nitrogen was flown over the reaction flask for 1 h to remove oxygen from the reaction flask and improve the magnetic properties of the iron oxide nanoparticles. 30% NH4OH solution (0.5 mL) was added dropwise to the above solution with rapid stirring. The resulting greenish suspension was heated to 70° C for 90 min under a constant stream of nitrogen. The mixture was then cooled forming black NWs. Ammonium chloride and excess dextran were removed by ultrafiltration through membrane filters with 100 kDa cutoff. After several washes, the colloidal product was concentrated by ultrafiltration to a total volume of 30 mL. The resulting colloidal solution of NW in distilled water (30 mL) was mixed with 5 M NaOH (10 mL) and epichlorohydrin (5 mL). The mixture was stirred at room temperature for 24 h to form cross-linked NW. Excess epichlorohydrin was removed by dialysis (14 kDa cutoff) against 3 changes of distilled water followed by ultrafiltration 5 times. The cross-linked NW was 41 then aminated by the addition of 30% NH4OH solution (10 mL) followed by incubation at 37° C for 36 h. The resulting mixture was dialyzed (14 kDa cutoff) against 3 changes of distilled water leading to amine functionalized NW-NH2. Synthesis of NW-ICG To prepare NW-ICG, ICG NHS ester (0.06 mg) in DMSO (1 mL) was mixed with NW- NH2 (4 mg/mL, 3 mL), and the mixture was stirred in the dark at room temperature for 48 hrs. The reaction mixture was diluted by water and purified by dialysis (14 kDa cutoff) and ultrafiltration (100 kDa cutoff). Characterization of NW-ICG For each step of NW synthesis, the size and charge of the NWs were monitored by dynamic light scattering (DLS) using a Zetasizer Nano zs apparatus (Malvern, U.K.). Absorption and emission of ICG and NW-ICG were measure by SpectraMax M3 plate reader. The prepared NWs were imaged under transmission electron microscope (TEM) (JEM-2200FM) operating at 200 kV using Gatan multiscan CCD camera with Digital Micrograph imaging software. The biocompatibility of NW-ICG To evaluate the biocompatibility of NW-ICG, Raw 264.7 cells were cultured in a 96-well plate with DMEM cell culture media containing of 10% of FBS at 37 oC and 5% CO2. The cells were incubated with different concentration of NW-ICG in cell culture media (0.50, 0.25, 0.13 mg Fe/mL) for 24 h at 37 oC and 5% CO2. The cells then incubated with MTS reagent (16.7% in media) for another 1 h at 37 oC until the brown color developed. The absorption of the 96-well plate was measured at 490 nm with SpectraMax M3 plate reader. 42 Mouse model MMTV-PyMT transgenic mice were purchased from The Jackson Laboratory. The female mice spontaneously develop palpable breast cancer in 4 months. All mice were kept in the University Laboratory Animal Resources Facility of Michigan State University. All the experimental procedures and guidelines for animal study were performed under approval of Institutional Animal Care and Use Committee (IACUC) of Michigan State University. Multimodality imaging MPI was performed on a MOMENTUM MPI scanner (Magnetic Insight Inc.). MPI scanning was performed with the following imaging parameters: the scan type: 3D scan; scan mode: Standard; Z FOV: 10.0 cm; number of projections: 21; 5.7 T/m gradient. CT imaging was performed on a Micro CT system (PerkinElmer) with a speed scan mode (Voltage: 90 kV). 3D MPI/CT data reconstruction was processed by VivoQuant software (Magnetic Insight Inc.). The MPI signal from tumor were integrated through ROI feature in VivoQuant. The percentage of MPI signal from tumor were calculated with formular: (tumor signal/total signal) *100%. Fluorescence imaging was performed on a Trilogy Pearl system (LI-COR Biosciences, Exposure time: 500 ms; Excitation: 785 nm; Signal detection: 820 nm). The fluorescence signal from tumor were integrated through ImageJ. The percentage of fluorescence signal from tumor were calculated with formular: (tumor signal/total signal) *100%. Photoacoustic imaging was performed on a MSOT inVision 256-TF small animal scanner (iThera medical GmbH). The PA images were reconstructed by a standard backprojection algorithm. Then, the reconstruction PA images were fit to a known NW-ICG absorption spectrum, producing NW-ICG unmixing PA images. All PA data were processed using the ViewMSOT software. Excised tissues were placed in an agar (1%, w/w) phantom for ex vivo MSOT. Confocal image was performed by a custom-made confocal 43 microscope with 3 mW 785 nm excitation Laser. Fluorescent signal was filtered by a 785 long- pass filter (Semrock, LP02-785RU-25) and obtained by a CMOS camera (Hamamatsu, C11440- 42U) with exposure time of 50 μs. Histological analysis Dissected tumors were fixed in 10% Neutral Buffered Formalin then processed and vacuum infiltrated with paraffin on the Sakura VIP 2000 tissue processor; followed by embedding. Paraffin blocks were finely sectioned at 5 μm. Slides were manually stained for Prussian Blue to detect ferric form iron. Hematoxylin and Eosin slides were stained on a Leica Autostainer XL. Slides were analyzed by a Nikon Eclipse Ci microscope with a Nikon DS-Fi3 camera (Nikon Instruments Inc.). 44 REFERENCES (1) Sung, H.; Ferlay, J.; Siegel, R. L.; Laversanne, M.; Soerjomataram, I.; Jemal, A.; Bray, F., Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. 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T.; Kaul, M. G.; Hansen, E. C.; Barch, M.; Wisniowska, A.; Chen, O.; Chen, Y.; Li, N.; Okada, S.; Cordero, J. M.; Heine, M.; Farrar, C. T.; Montana, D. M.; Adam, G.; Ittrich, H.; Jasanoff, A.; Nielsen, P.; Bawendi, M. G., Exceedingly small iron oxide nanoparticles as positive MRI contrast agents. Proc. Natl. Acad. Sci. U.S.A 2017, 114, 2325-2330. (50) Yu, E. Y.; Chandrasekharan, P.; Berzon, R.; Tay, Z. W.; Zhou, X. Y.; Khandhar, A. P.; Ferguson, R. M.; Kemp, S. J.; Zheng, B.; Goodwill, P. W.; Wendland, M. F.; Krishnan, K. M.; Behr, S.; Carter, J.; Conolly, S. M., Magnetic Particle Imaging for Highly Sensitive, Quantitative, and Safe in Vivo Gut Bleed Detection in a Murine Model. ACS Nano 2017, 11, 12067-12076. (51) Toy, R.; Bauer, L.; Hoimes, C.; Ghaghada, K. B.; Karathanasis, E., Targeted nanotechnology for cancer imaging. Adv. Drug Deliv. Rev. 2014, 76, 79-97. (52) Vaughan, H. J.; Green, J. J.; Tzeng, S. Y., Cancer-Targeting Nanoparticles for Combinatorial Nucleic Acid Delivery. Adv. Mater. 2020, 32, 1901081. (53) Marques, A. C.; Costa, P. J.; Velho, S.; Amaral, M. H., Functionalizing nanoparticles with cancer-targeting antibodies: A comparison of strategies. J. Control. Release 2020, 320, 180-200. (54) Kumar, C. S. S. R.; Mohammad, F., Magnetic nanomaterials for hyperthermia-based therapy and controlled drug delivery. Advanced Drug Delivery Reviews 2011, 63, 789-808. (55) Hensley, D.; Tay, Z. W.; Dhavalikar, R.; Zheng, B.; Goodwill, P.; Rinaldi, C.; Conolly, S., Combining magnetic particle imaging and magnetic fluid hyperthermia in a theranostic platform. Phys. Med. Biol. 2017, 62, 3483-3500. (56) Du, Y.; Liu, X.; Liang, Q.; Liang, X.-J.; Tian, J., Optimization and Design of Magnetic Ferrite Nanoparticles with Uniform Tumor Distribution for Highly Sensitive MRI/MPI Performance and Improved Magnetic Hyperthermia Therapy. Nano Lett. 2019, 19, 3618-3626. (57) Tay, Z. W.; Chandrasekharan, P.; Chiu-Lam, A.; Hensley, D. W.; Dhavalikar, R.; Zhou, X. Y.; Yu, E. Y.; Goodwill, P. W.; Zheng, B.; Rinaldi, C.; Conolly, S. M., Magnetic Particle Imaging- Guided Heating in Vivo Using Gradient Fields for Arbitrary Localization of Magnetic Hyperthermia Therapy. ACS Nano 2018, 12, 3699-3713. (58) Périgo, E. A.; Hemery, G.; Sandre, O.; Ortega, D.; Garaio, E.; Plazaola, F.; Teran, F. J., Fundamentals and advances in magnetic hyperthermia. Applied Physics Reviews 2015, 2, 041302. 49 APPENDIX TEM images of worm-like iron oxide NW; characterizations of NW-ICG; cell viability test by the MTS assay; raw data of NW-ICG biodistribution of mice; in vivo PAI scan; ex vivo PAI scan; and confocal image of a NW-ICG injected breast tumor Figure S2.1. TEM images of worm-like iron oxide NW. Scale bar are 50 nm in (a) and 20 nm in (b). (c) Energy-dispersive X-ray spectroscopy of NW-ICG. 50 Figure S2.2. Characterizations of NW-ICG (a) hydrodynamic size and (b) Zeta potential. NW- ICG was diluted to Fe concentration of 0.05 mg/mL in PBS for above measurements. Figure S2.3. Cells viability test by the MTS assay. Raw cells were incubated with different conc. of NW-ICG for 24 h at 37oC. The absorption at 490 nm were acquired as a measure of the number of live cells. 51 Figure S2.4. Raw data of NW-ICG biodistribution of mice. Maximum intensity projection of 3D MPI volumes co-registered with a CT skeletal scan at different time point. 52 Figure S2.5. In vivo PAI scan. Ultrasound anatomical frames of (a) liver and (b) tumor. PA (780 nm excitation) signal frames of (c) liver and (d) tumor. Biodistribution of NW-ICG multispectral unmixing signal (blue) co-registered with ultrasound signal of (gray) (e) liver and (f) tumor. Scale bars are all 5 mm. 53 Figure S2.6. Ex vivo PAI scan. Ultrasound frames of (a) liver and (b) tumor. PA (780 nm excitation) signal frames of (c) liver and (d) tumor. Biodistribution of NW-ICG multispectral unmixing signal (blue) co-registered with ultrasound signal of (gray) (e) liver and (f) tumor. Scale bars are all 5 mm. 54 Figure S2.7. A confocal image (FOV: 1200 um*1000 um) of a NW-ICG injected breast tumor acquired by a custom-made confocal microscope indicating most cells in tumor tissues took up the NW-ICG. A 3D stacking confocal image visualized by Amira Software. 55 Chapter 3. Active Targeting Hyaluronan Conjugated Nanoprobe for Magnetic Particle Imaging and Near-infrared Fluorescence Imaging of Breast Cancer and Lung Metastasis Reprinted (adapted) with permission from {Yang, C.-W.; Liu, K.; Yao, C.-Y.; Li, B.; Juhong, A.; Ullah, A. K. M. A.; Bumpers, H.; Qiu, Z.; Huang, X., Active Targeting Hyaluronan Conjugated Nanoprobe for Magnetic Particle Imaging and Near-Infrared Fluorescence Imaging of Breast Cancer and Lung Metastasis. ACS Appl. Mater. Interfaces. 2024, 16, 27055-27064.}, used under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/) 3.1 Introduction Breast cancer is the most diagnosed cancer type in woman with more than 2.3 million new cases in 2020 worldwide. Through the advances in early detection and treatment strategies, the survival rate of breast cancer patients has been significantly improved.1-2 On the other hand, breast cancer metastasis remains a major mortality factor. The locations of metastasis are often challenging to detect. While the lung, liver, and bone are common sites for breast cancer metastasis, they often show little symptoms until large areas of the organs have been occupied by metastatic cancer cells. Thus, it is critical that methods are available to detect primary and metastatic breast cancer.3-5 Non-invasive cancer imaging is an emerging field. Various scanning modalities have been utilized for cancer imaging in the lung including computed tomography (CT),6 positron emission tomography (PET),7-9 magnetic resonance imaging (MRI),10-11 and optical imaging.12 To better determine the presence of lung metastasis, multimodal imaging has been applied. 64Cu labeled interleukin 18 or a 89Zr labeled monoclonal antibody enable breast cancer lung metastasis imaging and evaluation with PET and CT/optical imaging.13-14 Moreover, PET and CT use ionizing radiation, which may be harmful to patients.15 56 Nanoparticle based contrast agents can significantly aid in cancer imaging. Nanoworms (NWs) bearing Indocyanine Green (ICG) (NW-ICGs) have been applied to primary breast cancer detection in mice.16-17 The accumulation of the nanoprobes in cancer was presumably due to the passive targeting of NWs through the enhanced permeability retention (EPR) effect.18-20 However, the breast cancer lung metastasis typically has small tumor masses compared to the primary tumor; thus less prominent EPR effect is expected.21-22 To enhance NP accumulation in metastatic sites, cell surface receptors on tumor cells may be targeted. CD44 is a glycoprotein that is overexpressed on various types of cancerous cells, including breast cancer.23-24 CD44 is known to play a key role player in metastasis and relapse of breast cancer.25-26 Hyaluronan (HA) is the major endogenous ligand of CD44.23, 27-29 Herein, we report an ICG and HA conjugated iron oxide nanoparticle (NP- ICG-HA), which can bind well with CD44. This can enable active NP targeting to metastatic breast cancer cells in the lungs and its detection with magnetic particle imaging (MPI) and near-infrared fluorescence imaging (NIR-FI). MPI is an attractive imaging modality, which detects superparamagnetic materials and does not require ionizing radiation. Compared to magnetic resonance imaging (MRI), MPI has multiple advantages such as high sensitivity, high imaging contrast with nearly no background, and the possibility for quantification of tracers while maintaining the high depth for imaging.30-32 Fluorescence imaging can complement the MPI results with the advantage of relatively high resolution. ICG is an NIR fluorescence dye approved by the Food & Drug Administration (FDA) as a clinical imaging agent.33-39 NIR fluorescence dyes have their emission windows at 700-900 nm enabling deeper tissue penetration when used in animal study. Thus, it could provide stronger signals compared to fluorescence dyes with emission maxima in the visible region. While ICG- 57 HA NPs have been reported before,40-41 they have not been tested for MPI based cancer and metastasis imaging. 3.2 Results Synthesis and Characterization of NP-ICG-HA The iron oxide nanoparticles (NPs) were synthesized by the modified co-precipitation method from Fe(III) and Fe(II) salts in the presence of dextran.42 The dextran on the surface of NPs was then cross-linked with epichlorohydrin followed by introduction of amine moieties by reacting with ammonium hydroxide to form aminated NP (NP-NH2). ICG was installed onto NP- NH2 with ICG-N-hydroxy succinimide (NHS) ester producing NP-ICG. HA was then conjugated to NP-ICG through amide bond formation leading to NP-ICG-HA (Scheme 1).43-45 Scheme 3.1. Synthesis of NP-ICG-HA. The nanomaterials were characterized first through dynamic light scattering (DLS). The average hydrodynamic diameter of NP, NP-ICG, and NP-ICG-HA was 67, 122, and 208 nm respectively, indicating the success conjugations of ICG and HA to the NP (Figure S3.1a). The 58 zeta potential values of the particles were also measured (Figure S3.1b). Aminated NP had a positive zeta potential (22.3 mV) likely due to the presence of ammonium ions on the surface. Upon conjugation of NP with ICG, the zeta potential of the resulting NP-ICG became less positive (16.9 mV) as some of the amine moieties were amidated. The immobilization of HA to NP-ICG further decreased the zeta potential to negative values (-14.2 mV) presumably due to the negatively charged nature of HA at neutral pH. The morphology of NP-ICG-HA was analyzed by transmission electron microscopy (TEM) (Figure 3.1a), which showed that the average diameter of iron oxide core was ~3 nm. The significantly larger sizes observed by dynamic light scattering compared to TEM were presumably due to the polysaccharides attached on the NP surface, which were not readily visible under TEM. When comparing the TEM images of NP, NP-ICG, and NP- ICG-HA (Figure S3.2a), no significant differences were observed in size as they were made of the same core. The element identification for the NP-ICG-HA was performed by energy dispersive X-ray spectroscopy (EDX) (Figure S3.2b). The fluorescence spectra of NP-ICG-HA were also acquired. Both the absorption and emission maximum peaks of NP-ICG-HA were blue-shifted by 5 nm as compared to the parent molecule ICG (Figure 3.1b). The blue shifts of the absorption and emission maxima could be due to the metal enhanced fluorescence effect46 or the nanoaggregation of ICG47-48 when conjugated with NPs. The intensities of fluorescence signals of NP-ICG-HA were linear to the nanoparticle iron concentration (Figure 3.1c). The iron concentration of NP-ICG-HA was determined by inductively coupled plasma - optical emission spectrometry (ICP-OES). The MPI signal strength of NP-ICG-HA was linearly correlated with the nanoparticle iron concentration (Figure 3.1d). The performance of NP-ICG-HA in MPI was evaluated by benchmarking against the commercially available carboxydextran coated superparamagnetic iron oxide nanoparticle (SPION): VivoTrax. The NP-ICG-HA was more sensitive than VivoTrax, 59 giving stronger MPI signals at the same level of iron. The potential magnetic hysteresis of the nanoparticles were measured by superconducting quantum interference device (SQUID) magnetometer at 300 k (Figure S3.3). No hysteresis loops were observed by SQUID, indicating the superparamagnetic property of NP-ICG-HA. The masses of iron in NP-ICG-HA and VivoTrax were determined by ICP-OES. The saturation magnetization of NP-ICG-HA (93.0 emu/g) is 2 times higher than that of VivoTrax (42.7 emu/g), explaining the higher sensitivity of NP-ICG-HA in MPI. Figure 3.1. (a) TEM images of NP-ICG-HA. (b) Normalized UV-Vis absorption and emission spectra of NP-ICG-HA and free ICG. Excitation: 730 nm. (c) Integrated fluorescence signal intensity vs. iron concentration of NP-ICG-HA (n=3). (d) MPI signal intensities vs. iron concentration for NP-ICG-HA and VivoTrax respectively (n=3). To ascertain HA immobilized on the NP-ICG-HA can bind with CD44, competitive enzyme linked immunosorbent assay (ELISA) was set up to measure the abilities of NP-ICG-HA 60 to compete with HA for CD44 binding.49 As shown in Figure S3.4, NP-ICG-HA significantly reduced the binding of HA with CD44. In contrast, NP-ICG did not have much effect on HA/CD44 binding confirming the important roles of HA in NP-ICG-HA/CD44 interactions (Figure S3.4). To evaluate the biocompatibility of NP-ICG-HA, cell viability assays were performed with RAW 264.7 cells (Figure S3.5). No major changes in cell viability were recorded when the cells were incubated with various concentrations (0.13-0.5 mg Fe/mL) of NP-ICG-HA, demonstrating the material has no significant toxicity to cells at the concentrations evaluated. Binding of NP-ICG-HA with CD44-expressing breast cancer cells in vitro To examine the ability of NP-ICG-HA to detect cancer cells, CD44 expressing 4T1 cells50 were incubated with NP-ICG-HA or NP-ICG or ICG at the same ICG fluorescence intensities for 2h at 37 oC followed by thorough washing with PBS to remove the unbonded particles. Cells were then imaged by confocal microscopy (Figure 3.2). The images showed much stronger ICG signals in cells incubated with NP-ICG-HA, suggesting that NP-ICG-HAs were taken up more by the cells as compared to NP-ICG and ICG. The incubated cells were further stained with Prussian Blue to detect iron present intracellularly (Figure S3.6). Cells incubated with NP-ICG-HA exhibited much stronger blue staining than those treated with NP-ICG, supporting that more NP-ICG-HA particles were present in 4T1 cells. 61 Figure 3.2. Fluorescence images measured by confocal microscopy. 4T1 cells were incubated with NP-ICG-HA then DAPI, followed by washing with PBS three times after each staining, and imaged (a) DAPI channel, (b) ICG channel, and (c) merge of both. 4T1 cells were incubated with NP-ICG then DAPI, followed by washing with PBS three times after each staining as the control group and imaged (d) DAPI channel, (e) ICG channel, and (f) merge of both. 4T1 cells were incubated with ICG then followed by the same washing procedure and imaged (g) DAPI channel, (h) ICG channel, and (i) merge of both. Scale bars are 10 μm. NP-ICG-HA enabled multi-modality imaging of breast cancer in the MMTV-PyMT spontaneous cancer model To evaluate the cancer imaging ability of NP-ICG-HA, the MMTV-PyMT transgenic mouse model is established.51-52 MMTV-PyMT mice spontaneously develop palpable mammary tumors in 4-6 months, which can mimic the human breast cancer with native microenvironment. 62 The breast tumor tissues dissected from MMTV-PyMT mouse were first subjected to CD44 Immunohistochemistry (IHC) staining confirming the expression of CD44 in these tissues (Figure S3.7). Five month-old female MMTV-PyMT mice (n = 4) were administered with NP-ICG-HA (8 mg of iron /kg body weight) through the tail vein. These mice were then imaged with MPI and fluorescence over 72 hours (Figure 3.3a). NP-ICG (8 mg of iron /kg body weight) without conjugated HA was injected to another batch (n = 4) of MMTV-PyMT mice as the control group (Figure 3.3b). 3D MPI images were co-registered with CT images to provide anatomical information (Figure 3.3). In the NP-ICG-HA group, pre-injection scanning showed no MPI signals indicating low endogenous iron concentration. In comparison, images acquired one-hour post-injection showed MPI signals all over the mouse body, suggesting NP-ICG-HA was in the vasculature system. In 24 h post-injection, strong MPI signals were observed in liver area as well as in the tumor area, showing NP-ICG-HA can accumulate in breast tumors. In contrast, for control mice receiving NP-ICG, particles were taken up by liver and stayed in liver for a shorter period. Moreover, no significant MPI signals were found in the tumor areas over the 72 h period in these mice. To confirm the MPI results, fluorescence imaging was performed enabled by the ICG attached on NPs. Consistent with MPI studies, in the NP-ICG-HA group, fluorescence images showed significant signals in liver and tumor areas (Figure 3.3c), with no fluorescence in tumor areas in mice administered with NP-ICG (Figure 3.3d). 63 Figure 3.3. Representative images of MMTV-PyMT mice bearing multiple mammary tumors (n=4 for each group). (a) 3D MPI images at indicated time points co-registered with a CT skeletal scan images of mice injected with NP-ICG-HA. (b) 3D MPI images at indicated time points co- registered with a CT skeletal scan images of mice injected with NP-ICG as a control group. (c) NIR-FI images of mice injected with NP-ICG-HA at various time points. (d) NIR-FI images of mice injected with NP-ICG as a control group at various time points. To further confirm the role of HA in targeting NP-ICG-HA to breast tumor, a mixture of NP-ICG-HA and free HA was injected intravenously to tumor bearing MMTV-PyMT mice. The free HA could bind with the HA receptor (CD44) in breast tumors, which could competitively inhibit the binding between NP-ICG-HA and CD44 in tumors. Compared to mice receiving NP- ICG-HA, the MPI and fluorescence images showed significantly lower signals in tumor areas in the presence of free HA (Figure S3.8a and S3.8c). The signals in tumors area were integrated and plotted for both NP-ICG-HA group and NP-ICG-HA + free HA group in MPI and NIR-FI results at 24 h post-injection (Figure S3.8b and S3.8d). A 95% reduction of signals in the MPI and an 88% reduction of signals in the fluorescence images were observed from NP-ICG-HA group to NP-ICG-HA + free HA group respectively, indicating that tissue accumulation of NP-ICG-HA in vivo was HA dependent. 64 Confirmation of MMTV-PyMT mouse imaging via ex vivo analysis of the tissues To confirm the in vivo imaging results, mice were euthanized 72 h post-injection, and the mouse organs were extracted and imaged by MPI and NIR-FI. The biodistribution of NP-ICG-HA was examined through quantification of MPI images of the organs acquired (Figure 3.4a). Significantly higher MPI signals (25.2% of the total signals from all organs extracted) were found in excised tumors. The ex vivo fluorescence signals (Figure 3.4b) corroborated MPI results. Biodistribution of nanoparticles in the control group of mice receiving NP-ICG was performed parallelly. Signal quantification showed only strong MPI/fluorescence signals from excised liver with little signals from the tumor (Figures 3.4c and 3.4d). To further confirm the accumulation of NP-ICG-HA in tumors, histopathological analysis was conducted in excised tissues. The CD44 expression of excised tissues were examined by immunohistostaining (Figure 3.4e) with the adjacent slides of tissues stained with Hematoxylin and eosin (H&E) and Prussian blue (Figures 3.4f and 3.4g). The dense nucleus stain area in H&E slide was co-localized with brownish area in CD44 IHC slide, indicating the CD44 expression in tumors. The extensive blue color observed in Prussian blue staining confirmed the presence of NP-ICG-HA in tumors. 65 Figure 3.4. MMTV-PyMT mice (n=4 for each group) bearing multiple mammary tumors injected with NP-ICG-HA or NP-ICG then sacrificed at 72 h post-injection. (a) Percentage of MPI signals measured ex vivo in main organs and (b) Ex vivo NIR-FI images of NP-ICG-HA group. (c) Percentage of MPI signals measured ex vivo and (d) Ex vivo NIR-FI images of NP-ICG control group. T: tumor, Lv: liver, K: kidney, Sl: spleen, H: heart, and L: lung. Histological analysis of tumor tissues from MMTV-PyMT mice receiving NP-ICG-HA. (e) Anti-CD44 IHC stain; (f) H&E stain; (g) Prussian blue (iron showed blue) followed by nuclear fast red counterstain. NP-ICG-HA enabled multi-modality imaging of breast cancer lung metastasis To test the ability of NP-ICG-HA to detect cancer metastasis, a breast cancer lung metastasis mouse model was built by injecting 4T1-Luc2 breast cancer cells into female BALB/c mouse through tail vein. Bioluminescence imaging showed that 4T1-Luc2 cells were accumulated in lung areas of mice, which could mimic metastasis of breast cancer to the lung. 66 NP-ICG-HA or NP-ICG was injected at the same doses (8 mg of iron /kg body weight) through tail vein to mice with 4T1 cancer cells in the lung, which was followed by MPI and fluorescence imaging over 72 hours. In the NP-ICG-HA group, MPI images showed strong signals in abdominal and chest areas at 1 h post-injection, indicating the particles were still in the circulation (Figure 3.5a). At 24 h, strong signals were observed in liver area and signals were found in both left and right lungs. However, in the NP-ICG control group, MPI signals were only visible in the liver area at all time points (Figure 3.5b). To exclude the possibility that NP-ICG- HA particles non-specifically accumulated in the lungs, BALB/c mice without tumor were administrated with NP-ICG-HA. No MPI signals were found in the lung areas of these mice (Figure S3.9). The results supported that NP-ICG-HA selectively accumulated in lungs of 4T1 lung metastasis mice. To confirm the MPI results, fluorescence images were measured at the corresponding time points (Figure S3.10). However, no significant signals were found in lung areas, which could be because the fluorescence signals were too weak to penetrate through the chest to be detected in vivo. In this in vivo dataset, MPI showed its superiority to fluorescence imaging when detecting the NP-ICG-HA in deeper tissues. 67 Figure 3.5. Imaging of 4T1 lung metastasis mice (n=4 for each group). (a) 3D MPI images at indicated time points co-registered with a CT skeletal scan images (left) of mice injected with NP- ICG-HA. The photo (middle) of the mouse and bioluminescence imaging (right) measured by IVIS. (b) 3D MPI images at indicated time points co-registered with a CT skeletal scan images of mice injected with NP-ICG as a control group. Confirmation of 4T1 lung metastasis mouse imaging via ex vivo analysis of the tissues The tracer administered 4T1 lung metastasis mice were sacrificed at 72 h post-injection, with their organs extracted and imaged by MPI and NIR-FI. The biodistribution of NP-ICG-HA was examined by quantification of MPI (Figure 3.6a) with the percentage of MPI signal in excised lung determined at 8.8% of the total signals in organs extracted. The ex vivo NIR-FI image (Figure 3.6b) showed a consistent result with MPI with significant intensities in lungs. In contrast, 4T1 lung metastasis mice receiving NP-ICG only gave significant MPI/NIR-FI signals from excised liver, but not from the tumor bearing lungs (Figures 3.6c and 3.6d). To further confirm the binding of NP-ICG-HA to metastatic sites in lung, the excised lungs were embedded with paraffin and 68 sliced to 5 µm of thickness for staining. The excised tissues were examined by CD44 immunohistostaining, H&E, and Prussian blue staining (Figures 3.6e, 3.6f, and 3.6g). The brownish area in CD44 IHC slide was co-localized with the dense nucleus stain area in H&E slide, indicating CD44 expression in tumor area. The extensive blue color observed in Prussian blue staining indicated the presence of NP-ICG-HA in metastatic sites in lungs. Figure 3.6. 4T1 lung metastasis mice (n=4 for each group) injected with NP-ICG-HA or NP-ICG then sacrificed at 72 h post-injection (a) Percentage of MPI signals measured ex vivo in main organs and (b) Ex vivo NIR-FI images of NP-ICG-HA group. (c) Percentage of MPI signals measured ex vivo and (d) Ex vivo NIR-FI images of NP-ICG control group. Lv: liver, K: kidney, Sl: spleen, H: heart, and L: lung. Histological analysis of lung from 4T1 lung metastasis mice receiving NP-ICG-HA. (e) Anti-CD44 IHC stain; (f) H&E stain; (g) Prussian blue followed by nuclear fast red counterstain. The scale bars are 20 μm. 69 3.3 Discussion Diagnosis of metastasis in addition to primary tumor is crucial to patients with breast cancer since a major cause of breast cancer related death is due to metastasis.3-5 While the EPR effects have been often utilized for NP aided cancer diagnosis studies,16, 22, 53 it is less applicable to breast cancer lung metastasis detection due to the small tumor mass in earlier stages of metastasis as compared to primary tumor.18-20 Active targeting can be an attractive approach for diagnosis of breast cancer lung metastasis. We report an ICG and HA conjugated IONP (NP-ICG-HA) that enable active targeting not only to solid tumor but also to cancer cells in lung. The results demonstrated that the breast tumor and breast cancer lung metastasis could be detected noninvasively by multimodality, including MPI and NIR-FI. The combination of NP, ICG, and HA was chosen for multiple reasons. Firstly, dextran coated iron oxide NPs are highly biocompatible and contain functional groups that enable conjugation with targeting molecules, including peptide, polysaccharide, and antibody. Secondly, ICG is an FDA approved water-soluble fluorescence dye.33-39 Compared to fluorophores excitable only by visible light, ICG enables NIR-FI, which has a better tissue depth penetration. Thirdly, HA is highly biocompatible and can target CD44 overexpressed on breast cancer, including metastatic breast cancer cells.54-56 In our study, NP-ICG-HA exhibited no significant toxicity to cells, indicating its good translational potential. Moreover, HA ($~200/g) is much less expensive compared to monoclonal antibody (hundreds of $ per 100µg) as a targeting agent. The NP-ICG- HA showed 2.4-fold stronger signals in MPI compared to those from commercially available SPION VivoTrax, indicating a better detection sensitivity. For in vivo imaging, we demonstrated that NP-ICG-HA detected breast tumor in MMTV-PyMT model and lung metastasis in breast 70 cancer lung metastasis model. The in vivo results were confirmed by ex vivo results and histological studies, showing accumulation of NP-ICG-HA in tumors and metastatic sites in lungs. There are limitations to the NP-ICG-HA multimodal imaging platform. Although CD44 is an exciting target and is overexpressed on breast cancer,26, 57 as tumor is highly heterogeneous, there may be populations of cancer cells low in CD44 expression, which will escape the detection. For more comprehensive detection of breast cancer, ligands targeting other biomarkers can be incorporated onto the NP-ICG platform in addition to HA for enhanced selectivity and specificity. 3.4 Conclusion ICG and HA conjugated SPION were synthesized for imaging of breast cancer at the primary site as well as in the lung. The NP-ICG-HAs integrated the magnetic and optical properties in a single tracer, providing a multimodal imaging platform. We demonstrated that NP-ICG-HAs can bind to 4T1 breast cancer cells through CD44/HA interactions. Moreover, NP-ICG-HAs target CD44 expressed breast tumors in the MMTV-PyMT mouse model and CD44 expressing breast cancer cells in the lung in 4T1 inoculated BALB/c mice. Thus, NP-ICG-HA is an excellent candidate for breast tumor and lung metastasis imaging. 3.5 Experimental section Materials: Ammonium hydroxide (30% NH4OH), 2-chloro-4,6-dimethoxy-1,3,5-triazine (CDMT), dextran (MW: 10 kDa), dimethyl sulfoxide (DMSO), epichlorohydrin, iron(III) chloride hexahydrate (FeCl3·6H2O), iron(II) chloride tetrahydrate (FeCl2·4H2O), fetal bovine serum (FBS), formalin solution neutral buffered 10%, N-methylmorpholine (NMM), sodium hydroxide (NaOH), Dulbecco’s Modified Eagle Medium (DMEM), Dulbecco’s phosphate-buffered saline (DPBS), RPMI 1640 medium, Penicillin-Streptomycin were purchased from Sigma-Aldrich. Sodium hyaluronan (16 kDa) was purchased from Lifecore Biomedicals. CellTiter 96 Aqueous One 71 solution containing 3-(4,5-dimethylthiazol-2-yl)-5-(3-arboxymethoxyphenyl)-2-(4-sulfophenyl)- 2H-tetrazolium (MTS) was purchased from Promega. Centrifugal filter MWCO (100 kDa) was purchased from EMD Millipore. ICG-NHS ester was purchased from Ruixibiotech. Synthesis of NP-NH2: FeCl3·6H2O (1.2 mmol), FeCl2.4H2O (0.65 mmol), and 4.5 g dextran (~10 kDa) were mixed in water (20 mL) and stirred with nitrogen purging the solution for 1 h to remove oxygen from the reaction flask and to improve the magnetic properties of the iron oxide nanoparticles. 30% NH4OH solution (0.9 mL) was added in a dropwise manner to the above solution under rapid stirring. The resulting dark greenish solution was heated to 70° C for 90 min under a nitrogen stream protection to form NPs. The mixture was cooled down to room temperature. Ammonium chloride and unreacted dextran were removed by centrifuge through centrifugal filters (MWCO 100 kDa). The colloidal solution of NP in distilled water (25 mL) was mixed with epichlorohydrin (5 mL) and 5 M NaOH (10 mL) then was stirred at room temperature for 24 h to form cross-linked NP. Unreacted epichlorohydrin was removed by centrifuge through centrifugal filters (MWCO 100 kDa). The cross-linked NP was then aminated by adding 30% NH4OH solution (10 mL) followed by stirring at 37° C for 36 h. The excess NH4OH in the mixture was removed by centrifuging through centrifugal filters (MWCO 100 kDa) leading to amine functionalized NP (NP-NH2). Synthesis of NP-ICG: NP-NH2 (4 mg/mL, 3 mL) was mixed with ICG-NHS ester (0.06 mg) in DMSO (1 mL), and the mixture was stirred at 25 oC for 48 h in the dark. The resulting mixture was centrifuged with centrifugal filters (MWCO 100 kDa) to remove the unreacted ICG- NHS ester. Synthesis of NP-ICG-HA: Sodium hyaluronan (~16 kDa, 100 mg) was dissolved in distilled water (20 mL), then the Amberlite H+ was added to the solution and stirred at 25 oC for 4 h. The 72 resulting solution was filtered and freeze-dried to obtain the protonated HA. HA (40 mg, 0.11 mmol of carboxylic acid), NMM (0.22 mmol), and CDMT (0.08 mmol) were dissolved in water and acetonitrile mixture (3:2, 6 mL) and stirred at 25 oC for 1 h. NP-ICG (4 mg/mL, 4 mL) was added to the mixture and stirred at 25 oC for 24 h. The unreacted reagents were removed by centrifuging with centrifugal filters (MWCO 100 kDa). Characterization of NP-ICG-HA: The hydrodynamic diameter and surface charge of NP- ICG-HA were measured by dynamic light scattering using a Zetasizer Nano zs apparatus (Malvern, U.K.). The morphology of NP-ICG-HA was imaged with an ultra-high resolution transmission electron microscope (JEOL 2200FS) operating at 200 kV using Gatan multiscan CCD camera with Digital Micrograph imaging software. The element identification was collected in the energy dispersive x-ray microanalysis (EDX) mode. Absorption and emission of ICG and NP-ICG-HA were measured by a SpectraMax M3 plate reader. The iron concentration of NP-ICG-HA was determined by Varian 710-ES ICP-OES (Varian Inc.). The NP-IGC-HA solution was digested with concentrated nitric acid at 60 oC for 2 h then placed at room temperature overnight. The digested solution was then diluted to a nitric acid concentration of 2% for ICP-OES analysis. Competitive ELISA: Competitive ELISA were performed following a literature procedure.49 The abilities of NP-ICG-HA and NP-ICG to compete with biotinylated-HA (b-HA) for CD44 binding were measured (n=3 for each group). The 96-wells plate was coated with IgG- Fc (3 µg/well) in the wells then blocked with 5% BSA. The wells were coated with CD44-Fcγ (0.2 𝜇g/well). b-HA (0.5 µg/well), b-HA + NP-ICG (0.5 µg iron/well), and b-HA + NP-ICG-HA (0.5 µg iron/well), were added. Avidin-HRP (1:2000 dilution) was added to all wells then chromogenic 3,3',5,5'-tetramethylbenzidine (TMB) solution (100 µL) was added to each well and incubated for 73 15 min, or until a blue color appeared. The reactions were then quenched by 0.5 M H2SO4 (50 µL). Optical absorbance was measured by the SpectraMax M3 plate reader at 450 nm. Cell Culture: 4T1-Luc2 mouse breast cancer cells were maintained with RPMI 1640 supplemented with 10% FBS, 1% Pen-Strep. RAW 264.7 mouse macrophage cells were maintained with DMEM supplemented with the same materials above. The cells were cultured with 5% CO2 at 37 oC. The biocompatibility of NP-ICG-HA: To evaluate the biocompatibility of NP-ICG-HA, MTS assays were performed (n=3 for each group). RAW 264.7 cells were cultured in a 96-wells plate with DMEM containing 10% FBS at 37 oC and 5% CO2. The cells were treated with various concentrations of NP-ICG-HA in 100 µL of RPMI-1640 media (0.50, 0.25, 0.13 mg Fe/mL) for 24 h at 37 oC and 5% CO2 followed by the addition of MTS reagent (20 µL) then incubated for another 1 h at 37 oC until the brown color developed. The absorption values of the wells were measured at 490 nm with the SpectraMax M3 plate reader. Verification of CD44 expression on 4T1 cells: To verify the CD44 expression levels on 4T1 cells, 4T1 (5×105 cells) were placed in flow cytometry tubes and washed twice with sterile PBS. The cells then incubated with anti-CD44 APC/Cy7 (IM7, BioLegend catalog # 103027) in serum-free media (1:200) for 1 h. The cells were washed with sterile PBS three times, then stored on ice till flow cytometry analysis. NP-ICG-HA uptake by CD44 expressing cells: To evaluate the binding between NP-ICG- HA and CD44 in vitro, 4T1 mouse breast cancer cells were used. Cells were cultured in Me-tek plate with RPMI-1640 media overnight at 37 oC and 5% CO2. The media were removed, and the plates were washed with PBS for three times. The cells were then incubated with NP-ICG-HA or NP-ICG for 1 h at 37 oC followed by three times of washes with PBS. The cells were fixed with 74 10 % formalin for 15 min then washed with PBS three times. For confocal analysis, the cells were stained with a DAPI solution (300 nM) for 10 min then washed with PBS for three times. The confocal images were performed with FluoView 1000 LSM (Olympus Corporation). For Prussian Blue staining, the cells were incubated with 1:1 mixture of 5% potassium ferrocyanide trihydrate and 10% HCl solution (in PBS) for 1 h at 37 oC then washed with PBS for three times. Images were taken by a Nikon Eclipse Ci microscope with a Nikon DS-Fi3 camera (Nikon Instruments Inc.). Mouse models and bioluminescence imaging: All mice were kept in the University Laboratory Animal Resources Facility of Michigan State University. All the experimental procedures and guidelines for animal study were performed under approval of Institutional Animal Care and Use Committee (IACUC) of Michigan State University (Protocol #: 202100095). MMTV-PyMT transgenic mice were purchased from the Jackson Laboratory. The female mice spontaneously develop palpable breast cancer in 4 months. BALB/c mice were purchased from Charles River Laboratories. To build a breast cancer lung metastasis model, 4T1-Luc2 cells (5x105) were injected through the tail vein. The 4T1-Luc2 cells accumulated in lungs. To confirm the cells distribution in mouse, BLI was acquired right after cell injection. D-luciferin (150 mg/kg) was injected abdominally to the mice 15 min before imaging with IVIS (PerkinElmer). Multimodality imaging: MPI images were acquired on a MOMENTUM MPI scanner (Magnetic Insight Inc.). MPI scanning was performed with the following imaging parameters: (1) the scan type: 2D scan; scan mode: Standard; Z FOV: 10.0 cm; 5.7 T/m gradient. (2) the scan type: 3D scan; scan mode: Standard; Z FOV: 10.0 cm; number of projections: 21; 5.7 T/m gradient. CT scan images were acquired on a Micro CT system (PerkinElmer) with a speed scan mode (Voltage: 90 kV). 3D MPI/CT data reconstruction and co-registration was processed by VivoQuant (Invicro). 75 The MPI signals from tumor were integrated through 3D ROI tool feature in VivoQuant. The percentages of MPI signal from tumor were calculated with the formula: (tumor signal/total signal) *100%. NIR-FI images were acquired on a Trilogy Pearl system (LI-COR Biosciences, Exposure time: 500 ms; Excitation: 785 nm; Signal detection: 820 nm). The fluorescence signals were integrated through NIR-FI images by ImageJ. Histological analysis: Dissected lungs and tumors were fixed in 10% Neutral Buffered Formalin then processed and vacuum infiltrated with paraffin on the Sakura VIP 2000 tissue processor followed by embedding. Paraffin blocks were sectioned at 5 μm. Hematoxylin and Eosin slides were stained on a Leica Autostainer XL. Slides were stained for Prussian Blue to detect ferric form of iron. 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Breast Dis. 2020, 39, 1. 81 APPENDIX DLS and zeta potential results; Additional TEM images, EDX results; The magnetic hysteresis curves; Competitive ELISA results and method detail; MTS assay results; in vitro Prussian Blue staining images; CD44 IHC staining; NP-ICG-HA and free HA mixture administrated group results; NP-ICG-HA administrated normal BALB/c group in vivo results; Fluorescence imaging of lung metastasis mice Figure S3.1. Characterizations of NP, NP-ICG, and NP-ICG-HA (a) hydrodynamic diameter and (b) Zeta potential. NP, NP-ICG, and NP-ICG-HA were diluted to Fe concentration of 0.05 mg/mL in PBS for these measurements. 82 Figure S3.2. The TEM images of (a) NP and (b) NP-ICG. (c) Energy-dispersive X-ray spectroscopy of NP-ICG-HA. Copper element was from the copper grid used for the measurement. Figure S3.3. The magnetic hysteresis curves of NP-ICG-HA and VivoTrax at 300K. 83 Figure S3.4. Competitive ELISA experiment showed that NP-ICG-HA competed with biotinylated-HA (b-HA) for CD44 binding while the corresponding NP-ICG did not (n=3). ELISA wells were coated with CD44. b-HA was added to the wells (no inhibition column), which bound with immobilized CD44. Upon removal of unbound ligand, streptavidin-HRP conjugate was added, which allowed the semi-quantification of the amount of bound b-HA based on the absorbance of the wells. For competitive ELISA, NP-ICG or NP-ICG-HA was added together with b-HA to CD44 coated wells (NP-ICG and NP-ICG-HA columns respectively). NP-ICG-HA could bind with CD44 reducing the amount of b-HA retained in the wells by CD44, thus significantly reducing the absorbance values of the wells. Statistical analysis was performed through one-way ANOVA analysis. ***, p < 0.001; ****, p < 0.0001. Figure S3.5. Cell viability test by the MTS assay. RAW 264.7 cells were incubated with various concentrations of NP-ICG-HA for 24 h at 37oC (n=3). The absorption values at 490 nm were acquired as a measure of the number of live cells. At the concentrations evaluated, the NP-ICG- HA did not significantly impact the cell viability. Statistical analysis was performed through one- way ANOVA analysis. ns, non-significant. 84 Figure S3.6. 4T1 cells were incubated with (a) NP-ICG-HA and (b) NP-ICG for 4 h at 37oC then stained with Prussian Blue, after being washed with PBS for three times following each staining. The significantly stronger blue color in panel a than that in panel b suggests the higher uptake of NP-ICG-HA as compared to NP-ICG. Scale bars are 20 μm. Figure S3.7. Excised breast tumor from MMTV-PyMT. Tumor slides were performed with CD44 IHC staining (brown color). The scale bar is 20 µm. 85 Figure S3.8. MMTV-PyMT mice were injected with NP-ICG-HA and free HA mixture (n=3). (a) 2D MPI images at coordinated time points. (b) Integration of MPI signals in tumors area at 24 h post-injection showed a 95% reduction of signals. (c) NIR-FI images indicating little NPs in the tumor. (d) Integration of fluorescence in tumors area at 24 h post-injection showed an 88% reduction of signals. Statistical analysis was performed through one-way ANOVA analysis. ***, p < 0.001 86 Figure S3.9. Normal BALB/c (n=3) were administrated with NP-ICG-HA. (a) 2D MPI images (b) fluorescence imaging at coordinated time points showing little NP signals from lung area. Figure S3.10. Fluorescence images of (a) lung metastasis mice (n=4 for each group) injected with NP-ICG-HA and (b) NP-ICG at different time points. 87 Chapter 4. Hyaluronan Derivative Self-assembled Nanodrugs for Breast Cancer Image- guided Drug Delivery 4.1 Introduction Cancer stem cells (CSCs) are a subset of cancer cells with unique characteristics contributing to tumor heterogeneity and resistance to therapy.1-4 These cells are associated with an epithelial-to-mesenchymal transition program in tumor progression and metastasis.5-6 Also known as tumor-initiating cells, CSCs constitute a small subpopulation within tumors, characterized by their ability to self-renew and initiate tumor. CSCs often exhibit elevated levels of CD44 receptors with their major endogenous ligand in the body being hyaluronic acid (HA).7-11 CD44 can be targeted with HA-grafted constructs for treating tumors by enhancing cellular uptake through CD44-mediated endocytosis.12-13 Traditional drug delivery systems, such as liposomes, micelles, exosomes, and polymeric nanoparticles, have encountered significant challenges, including limited drug loading capacity, premature drug leakage, and carrier-associated toxicity.14 Addressing these limitations requires the development of advanced nanocarriers capable of enhancing drug delivery efficiency while minimizing adverse effects. Polymeric prodrug approaches become more attractive because of its higher drug loading and controlled drug release. Drugs are covalently conjugated to the backbone of the polymers through a labile chemical linkage to form polymeric prodrugs. With specific stimuli, polymeric prodrugs release the drugs at the lesion area through the breakage of labile linkage.14-16 Salinomycin, an antibiotic initially used as an anticoccidial agent in veterinary medicine, has gained attention for its remarkable anticancer properties.17 Emerging research highlights salinomycin's ability to kill CSCs.18-21 Moreover, salinomycin demonstrates promise as a selective 88 anti-CSC agent, enhancing the effectiveness of radiation and various chemotherapy drugs.22-24 These results indicate that salinomycin might be a promising candidate for CSC targeting drug delivery. Image-guided drug delivery is an attractive approach for cancer therapy, merging the precision of imaging techniques with the targeted delivery of therapeutic agents. By integrating imaging modalities such as magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET), and optical imaging with nanocarrier-based drug delivery systems, researchers can precisely visualize tumor sites and monitor drug distribution in real time.25-29 Moreover, image-guided drug delivery facilitates early detection of treatment response or resistance, allowing timely adjustments in therapy.30-31 Additionally, by minimizing off-target effects and enhancing drug accumulation at tumor sites, image-guided drug delivery holds potential for improving therapeutic efficacy. CD44 is not only an elevating receptor in CSCs but also an overexpressed cell surface biomarker of various cancer types, including breast cancer. We recently reported the synthesis of HA like compounds and screened their abilities to bind with CD44.32 The lead compound (G2) was selected because of its significant enhanced binding affinity for CD44 receptors compared to native HA.32-34 Enhanced CD44 binding can potentially lead to higher cellular uptake and better anti-cancer efficacy. In this article, we extended the successful results to application of breast cancer targeting. Herein, we report a salinomycin and indocyanine green (ICG) conjugated HA like compound (G2) (G2-Sal-ICG), which can bind well to CD44. The conjugates were further ultrasonicated to form the nanodrugs. With the incorporation of ICG, the G2-Sal-ICG nanodrugs enable near-infrared fluorescence imaging (NIR-FI).35-38 Thus, the G2-Sal-ICG nanodrugs can potentially target breast cancer and enable NIR-FI guided drug delivery. 89 4.2 Results Synthesis and characterization of nanodrug: G2-Sal-ICG Synthesis of G2-Sal-ICG started from modification of carboxyl group in HA to form HA derivative: G2. HA (16 kDa) was reacted with 3-phenyl-1-propylamine, formaldehyde, and cyclohexyl isocyanide to form G2 through Ugi reaction (Scheme 4.1).32 The degree of carboxyl group modification in G2 was 36% per disaccharide repeating unit determined by 1H NMR (Figure S4.1). G2 was then conjugated to Sal through ester bond formation, leading to G2-Sal. The degree of drug conjugation in G2-Sal was 34% per disaccharide repeating unit, based on analysis of integrations of pertinent signals in 1H NMR spectrum of the conjugate (Figure S4.2). The 1H NMR spectrum of salinomycin, G2, and G2-Sal were stacked to confirm the salinomycin characteristic peaks in G2-Sal (Figure S4.3). To compare the affinity of G2-Sal to CD44, HA-Sal was synthesized as a control reagent using the same method with a similar degree of drug conjugation as G2-Sal (Figure S4.4). G2-Sal and HA-Sal were conjugated with ICG with a similar fluorescence amount, leading to G2-Sal-ICG and HA-Sal-ICG. 90 Scheme 4.1. The synthesis of G2-Sal-ICG. Nanodrug formation and characterization To form the nanodrug, G2-Sal-ICG or HA-Sal-ICG was dispersed in water at the concentration of 1 mg/mL, then was ultrasonicated at room temperature for 1 h. The morphology of G2-Sal-ICG nanodrug was characterized by scanning electron microscope (SEM), which showed a spherical shape with an average diameter of 265 nm (Figure 4.1a). The hydrodynamic size of G2-Sal-ICG nanodrugs was 272.2 nm (Figure 4.1b). The fluorescence emission maximum peak of G2-Sal-ICG was blue-shifted from 810 to 795 nm, compared to free ICG in solution (Figure 4.1c). The absorption peak of G2-Sal-ICG was found to be broader than the ICG. These observations could be due to the nanoaggregation of ICG with the formation of nanospheres.39-40 UV spectra of serially diluted G2-Sal-ICG nanodrug solutions showed a linear correlation between fluorescence signals and nanodrug concentrations (Figure 4.1d), suggesting the potential for 91 nanodrug quantification with NIR-FI. HA-Sal-ICG nanodrug was characterized in the same manner as G2-Sal-ICG (Figure S4.5). Figure 4.1. (a) TEM image of G2-Sal-ICG. (b) The hydrodynamic diameter of G2-Sal-ICG measured by DLS. (c) Normalized absorption and emission spectra of G2-Sal-ICG and free ICG. Excitation: 730 nm. (d) Integrated fluorescence signal intensity (from NIR-FI) vs concentration of G2-Sal-ICG (n = 3). Binding between G2-Sal-ICG and CD44-expressing breast cancer cells To examine the ability of G2-Sal-ICG nanodrug to target breast cancer cells, CD44- expressing 4T1 breast cancer cells were incubated with G2-Sal-ICG nanodrug and HA-Sal-ICG nanodrug respectively at 37 oC for 2 h followed by 3 times PBS washing to remove the unbonded nanodrugs. The cells were then examined by flow cytometry (Figure 4.2a). G2-Sal-ICG nanodrug treated cancer cells showed a significantly higher median fluorescence intensity (MFI) compared to the HA-Sal-ICG nanodrug group, indicating the stronger binding of G2-Sal-ICG by cancer cells in vitro. To confirm the role of HA (or HA derivative) in CD44 targeting, the 4T1 cells were incubated with a mixture of G2-Sal-ICG nanodrug and free HA. The presence of free HA during 92 incubation reduced the MFI of the cells as compared to the G2-Sal-ICG nanodrug group (Figure 4.2a, orange) likely because HA competed with G2-Sal-ICG for cell binding. To better quantify the binding of nanodrug, 4T1 cells were cultured in a 12-well plate overnight, then incubated with G2-Sal-ICG or HA-Sal-ICG nanodrug at 37 oC for 2 h. After thorough washing with PBS, the cells were detached with trypsin with the fluorescence intensities measured (excitation wavelength at 750 nm and emission wavelength at 795 nm). The G2-Sal- ICG nanodrug group showed 2.6 times higher fluorescence intensities compared to the HA-Sal- ICG nanodrug group (Figure 4.2b). When 4T1 cells were incubated with G2-Sal-ICG nanodrug at 4 oC, the amount of intracellular nanodrug was significantly reduced (Figure 4.2b), which was consistent with the idea of CD44 mediated uptake, an energy dependent process. Additionally, incubation of cells with G2-Sal-ICG or HA-Sal-ICG nanodrug for various durations showed that the nanodrug accumulation reached its maximum after around 8 h (Figure S4.6). To investigate the distribution of nanodrugs in the cells, 4T1 cells were incubated with G2- Sal-ICG nanodrug at 37 oC for 2 h, followed by lysotracker red and DAPI nuclear staining, and imaging by confocal microscopy (Figure 4.2). The ICG signals were co-localized with lysotracker red signals, indicating the presence of G2-Sal-ICG nanodrug in the lysosome (Figure 4.2c, first row). Furthermore, cells incubated with the HA-Sal-ICG nanodrug or the G2-Sal-ICG nanodrug with free HA were imaged following the same protocol under the same setting (Figure 4.2c, second and third row). As shown in Figure 4.2c, in the ICG channel, the G2-Sal-ICG nanodrug treated cells had stronger signals compared to the HA-Sal-ICG nanodrug and the G2-Sal-ICG nanodrug/free HA groups. These results supported the stronger binding of G2-Sal-ICG nanodrug compared to HA-Sal-ICG nanodrug as well as the CD44 dependence in cellular binding. Additionally, a drug release assay was performed to study the kinetics of drug release in conditions 93 mimicking lysosomes, including acidic pH and present of hyaluronidase (HAdase). In pH 5.5 group, the drug release percentage (51.7%) is significantly higher than the group in pH 7.4 (14.2%). The present of HAdase also increased the drug release percentage presumably due to enzymatic degradation of nanoparticles (Figure S4.7). Figure 4.2. (a) The averaged MFI of G2-Sal-ICG, HA-Sal-ICG, and G2-Sal-ICG/free HA group as measured by flow cytometry. (b) The averaged fluorescence signal intensities of G2-Sal-ICG, HA-Sal-ICG, and cell only group. (c) Fluorescence images of G2-Sal-ICG, HA-Sal-ICG, and G2- Sal-ICG/free HA group with DAPI (blue), Lysotracker (red), ICG (green), and merged channels. 94 Figure 4.2. (cont’d) Statistical analysis was performed through one-way ANOVA analysis. ***, p < 0.001; ****, p < 0.0001. Nanodrug efficacy against 4T1 cells To compare the efficacy of nanodrug, 4T1 cells were incubated with G2-Sal, HA-Sal, and salinomycin at different drug concentrations (1 µM and 10 µM) at 37 oC for 24 h followed by 3- (4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium (MTS) cell viability assays (Figure 4.3a). All the 10 µM groups showed slightly lower viabilities as compared to the 1 µM groups. The viabilities of salinomycin groups were 17% and 24% lower compared to the G2-Sal and HA-Sal groups at 10 µM; and was 23% and 22% lower compared to the G2-Sal and HA-Sal group at 1 µM at this time point, indicating free salinomycin killed more cancer cells within 24 h. Interestingly, when cells were incubated for 36 hours, G2-Sal and HA- Sal killed significantly more cancer cells as compared to the salinomycin only group (Figure 4.3b, blue). At 48 hours, almost all cells were dead for all groups (Figure 4.3b, orange). The delay of cell killing observed in both G2-Sal and HA-Sal groups could be because the nanodrugs need to be degraded in lysosome to release the drug for cell killing.41 Figure 4.3. (a) The viability of 4T1 cells, which incubated with G2-Sal, HA-Sal, or salinomycin at drug concentrations of 10 µM and 1 µM for 24 h. (b) The viability of 4T1 cells, which incubated 95 Figure 4.3. (cont’d) with G2-Sal, HA-Sal, or salinomycin at drug concentrations of 1 µM for 24 h, 36 h, and 48 h. Statistical analysis was performed through one-way ANOVA analysis. *, p < 0.05. Image-guided drug delivery with orthotopic breast cancer models With ICG conjugated, G2-Sal-ICG and HA-Sal-ICG nanodrugs could enable NIR-FI imaging in vivo for image-guided drug delivery. To evaluate the performance of nanodrugs, 4T1 cells (105) were orthotopically inoculated to the mammary gland of female BALB/c mice. The tumor bearing mice were randomized into four groups (n = 5 each) and the G2-Sal-ICG (8 mg/kg salinomycin), HA-Sal-ICG (8 mg/kg salinomycin), salinomycin (8 mg/kg, the same drug dose as nanodrug group), and PBS were administrated intravenously to each group at 7 day post- inoculation. To detect the accumulation of nanodrugs, the G2-Sal-ICG and HA-Sal-ICG nanodrugs group were imaged by the Trilogy Pearl system at 1 h, 4 h, and 24 h post injection (Figures 4.4a, 4.4c). For the G2-Sal-ICG nanodrug group, weak signals were observed in tumor area (indicated with white arrow) at 1h post injection and the signals increased at 4h then faded at 24h post injection (Figure 4.4a). Meanwhile, the integrated average fluorescence signals peaked at 4 h post injection (Figure 4.4b). However, for the HA-Sal-ICG group, only weak signals were observed in tumor area (indicated with white arrow) during the full imaging period (Figure 4.4c). In addition, quantification of average fluorescence signals showed no significant changes during the observing period (Figure 4.4d). The G2-Sal-ICG group showed 3 times stronger fluorescence signals than the HA-Sal-ICG group in tumor area at 4 h post injection, indicating that G2-Sal-ICG accumulated more in tumor sites in vivo. 96 Figure 4.4. (a) The fluorescence images of tumor bearing mice administrated with G2-Sal-ICG and imaged at indicated time points. (b) The integrated fluorescence intensities in tumor area from G2-Sal-ICG group at indicated time points. (c) The fluorescence images of tumor mice administrated with HA-Sal-ICG and imaged at indicated time points. (d) The integrated fluorescence intensities in tumor area from the HA-Sal-ICG group at indicated time points. Tumor analysis The estimated tumor volume of the mice in all groups were measured by caliper (length*width2 /2) every three days (Figure 4.5a). The G2-Sal-ICG nanodrug group showed a significantly lower tumor volume compared to the HA-Sal-ICG, salinomycin, and PBS groups, indicating better suppression of tumor growth by the G2-Sal-ICG nanodrug. To further investigate the effects of nanodrugs, the tumors from different study groups were collected and analyzed. The mice were sacrificed at 27-day post-inoculation and the tumors were dissected and disaggregated to single cells by triple enzyme digestion methods. The disaggregated cells from various study groups were stained with an anti-CD44 monoclonal antibody then 97 analyzed by flow cytometry. The tumor cells from G2-Sal-ICG nanodrugs treatment group showed a significantly lower CD44 expression compared to the tumor cells from HA-Sal-ICG nanodrug, salinomycin, and PBS group (Figure 4.5b), indicating the G2-Sal-ICG killed more CD44 expressing cancer cells as an anticancer drug. Figure 4.5. (a) The estimated tumor volume of tumor mice administrated with G2-Sal-ICG, HA- Sal-ICG, salinomycin, and PBS over 27 days (b) The MFI (from CD44 monoclonal antibody) of disaggregated tumor cells from G2-Sal-ICG, HA-Sal-ICG, salinomycin, and no treatment group by flow cytometry. Statistical analysis was performed through one-way ANOVA analysis. *, p < 0.05; **, p < 0.01. Histological analysis The tumor from the G2-Sal-ICG treatment group showed lower levels of CD44 expression in IHC tissue staining compared to HA-Sal-ICG, salinomycin free drug, and control groups (Figures 4.6 and S4.8). These results are consistent with the flow cytometry data, indicating the greater CD44 positive breast cancer cells killing ability of G2-Sal-ICG. Presumably the G2-Sal- ICG targets CD44 positive breast cancer and suppresses the growth of the cells, leading to the lower percentage of CD44 positive cells in tumors. 98 Figure 4.6. Expressions of CD44 in dissected tumors from different treatment groups (n=3). Statistical analysis was performed through one-way ANOVA analysis. **, p < 0.01; ***, p < 0.001. 4.3 Discussion CD44 is a major receptor of HA and has been found to be overexpressed in breast cancer cells. In our previous study, HA derivative: G2 has a stronger interaction with CD44 compared to HA.32 With this powerful G2 ligand in hand, we utilized the G2 as a targeting molecule for image- guided drug delivery toward CD44 expressing breast cancer. In the synthesis of G2-Sal-ICG, salinomycin was covalently conjugated to G2 through esterification and can be degraded and hydrolyzed under lysosomal conditions. We further conjugated ICG to G2-Sal, leading to the possibility of using NIR-FI for cancer diagnostic with the G2-Sal-ICG nanodrug. Moreover, ICG is an FDA approved clinical imaging35-38, 42-44 agent that increases the translational potentials for G2-Sal-ICG nanodrug. The G2-Sal-ICG gave 2.8 times better targeting than HA-Sal-ICG based on flow cytometry results. Pretreatment of cells with free HA resulted in the partial inhibition of G2-Sal-ICG nanodrug accumulation, which supports the involvement of the CD44 receptor-mediated mechanism of nanodrug uptake. Moreover, a reduced level of nanodrug accumulation was observed in HA-Sal-ICG in cell-based fluorescence assay, consistent with the observation of stronger binding of G2-Sal-ICG to cancer cells. 99 Cellular biodistribution of nanodrugs showed the nanodrugs were taken up by 4T1 cancer cells and accumulated in lysosomes. The G2-Sal-ICG group had stronger fluorescence signals in cells as compared to HA-Sal-ICG group. Moreover, the partial inhibition of G2-Sal-ICG nanodrug accumulation was observed in free HA pretreatment group, consistent with the receptor-mediated mechanism of nanodrug uptake. When evaluated in vitro for its toxicity, the nanodrugs showed delayed killing of cancer cells in the MTS assay. The reason could be the nanodrugs need to be degraded first to release the drug to kill the cancer cells.41 Presumably, nanodrugs were internalized by receptor-mediated endocytosis then transferred into lysosomes, where they were digested by the acidic pH and hyaluronidase and subsequently released intracellularly. Anti-cancer drugs commonly suffered from the solubility issue in water due to their hydrophobicity.14 The HA drug delivery system could not only be used to overcome the solubility issue for salinomycin but also possessed the ability to target CD44-expressing cancer cells. We utilized a HA derivative, G2, which has a stronger affinity to CD44 as the targeting molecules. In addition, the labile ester linkage between G2 and salinomycin allowed the drug to be released in the lysosome with acidic environment, potentially reducing the systemic toxicity. To target cancer precisely, a variety of drug delivery system has been developed.45-46 However, the typical drug delivery system could not track the drug in vivo. When comparing the targeting efficiency among different nanodrugs, pharmacokinetic study is necessary for each group in animal study.30-31 In this work, the nanodrugs were labeled with ICG and enabled the NIR-FI tracking in vivo, to help confirm that the nanodrugs were targeted to breast tumor in real time. 100 4.4 Conclusion Salinomycin and ICG conjugated G2-Sal-ICG nanodrug was synthesized for breast cancer image-guided drug delivery. The G2-Sal-ICG nanodrug enables CD44-expressing cancer cell targeting through the CD44/HA interaction and drug release under lysosomal conditions to kill the cancer cells. Moreover, we demonstrated that G2-Sal-ICG targets 4T1 breast cancer cells in the orthotopic mouse model for NIR-FI and drug delivery, enabling imaging and therapeutics simultaneously. Tumor volume measurements indicated significantly better suppression of tumor growth with G2-Sal-ICG administration. Flow cytometry and histological analyses confirmed a greater reduction in CD44-expressing cancer cells. Our findings present G2-Sal-ICG as a nanodrug for CSC-targeted therapy, combining efficient drug delivery with real-time imaging capabilities. Thus, G2-Sal-ICG nanodrug is a promising candidate for breast cancer image-guided drug delivery. 4.5 Experimental section Materials Sodium hyaluronan (16 kDa) was purchased from Lifecore Biomedicals. Dimethyl sulfoxide (DMSO), 3-phenyl-1-propylamine, hydrochloric acid, formaldehyde, N,N- diisopropylethylamine (DIPEA), N,N-dicyclohexylcarbodiimide (DCC), sodium carbonate, salinomycin, Dulbecco’s phosphate-buffered saline (DPBS), RPMI 1640, fetal bovine serum (FBS), Penicillin-Streptomycin, D-luciferin, and hyaluronidase (Type I-S, H3506) were purchased from Sigma-Aldrich. ICG-NHS ester was purchased from Ruixibiotech. CellTiter 96 Aqueous One solution was purchased from Promega. DAPI and lysotracker red were purchased from Thermo Fisher Scientific. The dialysis tube (MWCO: 3.5 kDa), centrifugal filter (MWCO 10 kDa), and centrifugal filter (MWCO 100 kDa) were purchased from EMD Millipore. Anti-CD44 APC/Cy7 (IM7, BioLegend catalog # 103027) was acquired from BioLegend. 101 Synthesis of HA derivative: G2 HA (100 mg, 16kDa), MilliQ water (6 mL), and ethanol (4 mL) were mixed and stirred until all solid dissolved. 3-Phenyl-1-propylamine in ethanol (200 µL, 0.25 mmol) was added then hydrochloric acid (1.4 M) solution was added to adjust the pH to 4. Formaldehyde in ethanol (100 µL, 0.125 mmol) and cyclohexyl isocyanide in ethanol (200 µL, 0.25 mmol) were added and the solution was stirred at 25 oC for 1 h. Sodium carbonate solution (2 M) was added to adjust the pH to 12 and the reaction was stirred at 25 oC for 48 h. The reaction mixture was then dialyzed with dialysis tube (MWCO: 3.5 kDa) against MilliQ water for 72 h over 9 times of water change. Syntheses of G2-Sal and HA-Sal G2 (100 mg, 0.25 mmol carboxyl groups) and N,N-diisopropylethylamine (DIPEA, 42 µL, 0.25 mmol) were dissolved in 5 mL of anhydrous DMSO. DMAP (2 mg) and N,N- dicyclohexylcarbodiimide (DCC, 16 mg, 0.075 mmol) were added and the solution was stirred at 25 oC for 1 h. Then, salinomycin (56 mg, 0.075 mmol) was added and the reaction was stirred at 25 oC for 72 h. The solution was dialyzed with dialysis tube (7.5 kDa) against MilliQ water for 24 h. The unreacted reagent in the mixture was removed by centrifuging through centrifugal filters (MWCO 10 kDa) leading to the G2 and salinomycin conjugate (G2-Sal). The HA and salinomycin conjugate (HA-Sal) was produced following the same synthetic method as G2-Sal. Synthesis of G2-Sal-ICG and HA-Sal-ICG G2-Sal (10 mg) was mixed with the ICG-NHS ester (0.06 mg) in water/DMSO (3 mL, 2:1), and the mixture was stirred at 25 oC for 24 h in the dark. The resulting mixture was centrifuged with centrifugal filters (MWCO 10 kDa) to remove the unreacted ICG-NHS ester, leading to G2- Sal-ICG. The HA-Sal-ICG was formed following the same synthetic method as G2-Sal-ICG. 102 Self-assembly of G2-Sal-ICG and HA-Sal-ICG nanoparticles and characterization G2-Sal-ICG or HA-Sal-ICG (1 mg) was dissolved in 1 mL of deionized (DI) water then sonicated with a bath sonicator for 1 h at 25 oC to form uniform nanoparticles. The hydrodynamic diameter and zeta potential were measured by dynamic light scattering (DLS) using Zetasizer Nano zs apparatus (Malvern, U.K.). The morphology of G2-Sal-ICG and HA-Sal-ICG was imaged with SEM JEOL 7500F (JEOL USA Inc., USA). Absorption and emission of ICG, G2-Sal-ICG and HA-Sal-ICG nanoparticles were measured by a SpectraMax M3 plate reader. Cell Culture RPMI 1640 cell culture media was supplemented with 10% FBS and 1% Pen-Strep. 4T1 mouse breast cancer cells were cultured with supplemented RPMI 1640 at 37 oC with 5% CO2. The 4T1 cells were detached by trypsin-EDTA (0.25%) solution when reached the 90% confluence. Nanodrug cell uptake by flow cytometry & fluorescence reading To compare cancer cell targeting ability of nanodrugs, 105 of 4T1 cells were cultured in each well of 12-well plate for overnight. The cells were incubated with G2-Sal-ICG or HA-Sal- ICG (0.2 mg salinomycin/mL of nanodrug, 1 mL) for 4 h at 37 oC then washed with PBS three times. The cells were detached by trypsin-EDTA solution then placed in flow cytometry tubes and stored on ice until flow cytometry analysis. For fluorescence reading, the detached cells were placed in 96-well plate and the fluorescence intensities were measured by a SpectraMax M3 plate reader with excitation at 700 nm and emission at 820 nm. Kinetic cell uptake of nanodrug To compare the kinetics of nanodrug uptake by cells, the 4T1 cells were cultured in 12- well plate for overnight. The cells were incubated with G2-Sal-ICG or HA-Sal-ICG (0.2 mg salinomycin/mL of nanodrug, 1 mL) at 37 oC for 1h, 2h, 4h, 8h, 12h, 24h, and 36h. The cells were 103 then washed with PBS three times and detached by trypsin-EDTA solution. The suspension cells were placed in a 96-well plate and the fluorescence intensities were measured by a SpectraMax M3 plate reader with the same setting. In Vitro cellular targeting To perform the cellular targeting, 104 of 4T1 cells were cultured in a Lab-Tek chamber slide overnight at 37 oC with 5% CO2. The cells were incubated with G2-Sal-ICG or Ha-Sal-ICG (0.2 mg salinomycin/mL of nanodrug, 1 mL) for 2 h at 37 oC with 5% CO2 followed by lysotracker red staining for 1 h. After two washes with PBS, the cells were fixed with 4% paraformaldehyde (PFA) then stained with DAPI for 30 min. The slides were covered with cover slips then sealed with nail paint. The cellular fluorescence images were measured by a Thunder microscope. Kinetic drug release of nanodrug in vitro To estimate the kinetics of drug release in different environments, the G2-Sal or HA-Sal nanodrugs (0.2 mg salinomycin/mL of nanodrug) were placed in a 5 mL Eppendorf tube and were dissolved in PBS (4 mL) with different conditions, including pH 7.4, pH 5.5, pH 7.4 with hyaluronidase (1 mg/mL, 400-1000 units/ mg solid, Type I-S, Sigma-Aldrich), and pH 5.5 with hyaluronidase. The tubes were placed on a rotator at room temperature and 200 µL of the solution was taking out for analysis at 1h, 2h, 4h, 8h, 12h, 24h, and 36h. The testing solution was filtered with centrifugal filter (MWCO: 10 kDa) to remove the nanodrug or degraded polymers. The released salinomycin in the filtrate was quantified by UV-Vis spectrometer through reading the absorption at 280 nm. Cytotoxicity of nanodrugs To evaluate the cytotoxicity of nanodrugs, 5,000 of 4T1 cells were placed in each well of 96-well plate and cultured for overnight at 37 oC with 5% CO2. The cells were then incubated with 104 G2-Sal-ICG, HA-Sal-ICG, or salinomycin at the same drug concentration (1 µM, 10 µM). To check the viability of each group, the cells were incubated with CellTiter 96 Aqueous One solution according to the manufacturer’s protocol. The absorption values were measured at 490 nm with the SpectraMax M3 plate reader. Orthotopic breast cancer models All mice were kept in the University Laboratory Animal Resources Facility of Michigan State University. All the experimental procedures and guidelines for animal study were performed under approval of Institutional Animal Care and Use Committee (IACUC) of Michigan State University (Protocol #: 202100095). Female 6-weeks old BALB/c mice were purchased from Charles River Laboratories. To build an orthotopic breast cancer model, 4T1 cells (5x105) were injected into mammary gland of the mouse under anesthesia. Near-Infrared Fluorescence Imaging In Vivo To acquire in vivo NIR-FI images, the mouse was mounted with tape on a Trilogy Pearl system (LI-COR Biosciences) under anesthesia. The parameter of Trilogy Pearl was set at Exposure time: 500 ms; Excitation: 785 nm; Signal detection: 820 nm. The in vivo NIR-FI images were processed by ImageJ. Therapeutic efficacy 4T1 cells were injected into mammary gland of female BALB/c mice on day 0. The nanodrugs (8 mg of salinomycin/kg of body weight, 100 µL), salinomycin (8 mg/kg of body weight, 100 µL), and PBS (100 µL) were injected to mice intravenously on day 7 (n =5 for each group). Tumor sizes were measured every 3 days with a caliper. Tumor volumes were calculated using the modified formular: (length*width2)/2. 105 Tumor disaggregation and analysis Mice were euthanized on day 27 and the tumors were dissected. The tumor was minced into small pieces then digested using 1 mg/mL collagenase, 10 mg/mL hyaluronidase, and 0.02 mg/mL DNase of 5 mL of Hank's balanced salt solution (HBSS) on a rotator for 2 h at 25 oC. The cells suspension was filtered with a 70 µm cell strainer and the solution was centrifuged at 1,200 rpm for 8 min. The supernatant was removed, and the cell pellet was washed with HBSS for three times. Tumor cells (105) from different groups were placed in V-bottom shape 96-well plate. To check the expression of cancer stem cell biomarker CD44, cells were stained with anti-CD44 APC/Cy7 according to the manufacturer’s protocol and washed with PBS for three times then analyzed by flow cytometry. Histological analysis Dissected tumors were fixed in 10% neutral buffered formalin (NBF) and then processed, and vacuum infiltrated with paraffin on the Sakura VIP 2000 tissue processor followed by embedding. Paraffin blocks were sectioned at 5 μm for all tissue staining. Hematoxylin and eosin (H&E) slides were stained on a Leica Autostainer XL. For CD44 IHC staining, slides were blocked for nonspecific binding with Rodent Block M for 20 min, followed by polyclonal rabbit anti-CD44 antibody (abcam, catalog #: ab157107) dilutions (1:200) incubations for 1 h at room temperature. Slides were then incubated with rabbit on rodent HRP micro polymer (Biocare Medical, catalog #: RMR 622 G, H, L) for 20 min with reaction developed utilizing Romulin AEC chromogen for 5 min. 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The level of modification was estimated as 36 % according to the integration value of phenyl ring peaks between 7.1 ppm and 7.3 ppm and the methyl group peak at 1.8 ppm. 111 Figure S4.2. 1H-NMR spectrum of G2-Sal in d-DMSO/D2O mixture (2:1). Peak at 1.8 ppm is from the methyl group. Peaks at chemical shift 5.8 and 6.0 ppm are from the vinyl group in salinomycin. The level of modification was estimated as 34 % according to the integration value of vinyl group peaks at 5.8 ppm and 6.0 ppm and the methyl group peak at 1.8 ppm. 112 Figure S4.3. Stacked 1H-NMR spectrum of salinomycin (blue), G2 (green), and G2-Sal (maroon). Salinomycin was dissolved in d-DMSO. G2 was dissolved in D2O. G2-Sal was dissolved in d-DMSO/D2O mixture (2:1). 113 Figure S4.4. 1H-NMR spectrum of HA-Sal in d-DMSO/D2O mixture (2:1). Peaks at chemical shift 5.8 and 6.0 ppm are from the vinyl group in salinomycin. Peak at 1.8 ppm is from the methyl group. Peaks at chemical shift 5.8 and 6.0 ppm are from the vinyl group. The level of modification was estimated as 34 % according to the integration value of vinyl group peaks at 5.8 ppm and 6.0 ppm and the methyl group peak at 1.8 ppm. Figure S4.5. Characterizations of HA-Sal-ICG nanodrug (a) SEM image and (b) hydrodynamic diameter. HA-Sal-ICG was diluted to 0.5 mg/mL in water for above measurements. 114 Figure S4.6. 4T1 cells were incubated with G2-Sal-ICG or HA-Sal-ICG nanodrug for 1, 2, 4, 8, 24, 36 h at 37oC then washed with PBS for three times then measured the fluorescence with excitation: 700 nm and emission: 820 nm. Figure S4.7. In vitro release rate (%) of salinomycin from G2-Sal in different conditions. ***P < 0.001. 115 Figure S4.8. Excised breast tumor from different treatment groups: (a) G2-Sal-ICG (b) HA-Sal- ICG (c) salinomycin (d) PBS. Tumor slides were performed with CD44 IHC staining (brown color). The scale bar is 1000 µm. 116