NEAR-INFRARED PHOTOIMMUNOTHERAPY TARGETING OF CANCER-ASSOCIATED FIBROBLASTS By Raisa A. Glabman A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of Comparative Medicine and Integrative Biology – Doctor of Philosophy 2023 ABSTRACT Cancer-associated fibroblasts (CAFs) constitute a prominent cellular component of the tumor stroma, representing a heterogeneous group of activated fibroblasts. Within the tumor microenvironment (TME), CAFs play various pro-tumorigenic roles, including extracellular matrix remodeling, suppression of anti-tumor immunity, and modulation of tumor cell resistance to therapy. Fibroblast activation protein (FAP), a highly expressed marker on immunosuppressive CAFs, has been identified in several epithelial human cancers such as lung, colon, breast, and prostate cancer. Numerous attempts to target FAP+CAFs for inhibiting tumor progression and enhancing anti-tumor immunity have been reported, however, the translation of FAP-directed therapies into human clinical trials has been unsuccessful. Near-infrared photoimmunotherapy (NIR-PIT) is a highly selective tumor therapy that utilizes an antibody-photo-absorbing conjugate activated by near-infrared (NIR) light. In this study, we describe the therapeutic efficacy of anti- FAP near-infrared photoimmunotherapy (NIR-PIT) and subsequent immune activation in two immune-competent murine cancer models. Targeting FAP+ cells effectively suppressed tumor growth and reduced lung metastasis in a spontaneous mouse model of mammary cancer. These findings highlight a promising therapeutic approach for selectively and safely eliminating immunosuppressive FAP+ cells within the tumor microenvironment. Copyright by RAISA A. GLABMAN 2023 ACKNOWLEDGEMENTS I am extremely grateful to have had the opportunity to be a trainee at both Michigan State University (MSU) and the National Cancer Institute (NCI). I recognize that I am uniquely fortunate to have this experience learning from MSU faculty and NCI clinicians, scientists and investigators all working towards the common goal of improving human and animal health. Thank you to the Comparative Biomedical Scientist Training Program (CBSTP); Dr. Mark Simpson, Dr. Heather Shive, Jennifer Dwyer, Dr. Bih-Rong Wei, and the administrative staff for their invaluable support in ensuring the smooth operation of our fellowships. It has been an honor to work alongside the exceptionally talented CBSTP fellows, both past and present. Many thanks to the members of the Molecular Imaging Branch, as well as my colleagues in the Sato Lab – Colleen Olkowski, Dr. Qioaya Lin, Dr. Zuping Wang and Hannah Minor. I am deeply thankful to my committee members: Dr. Peter Choyke, Dr. Noriko Sato, Dr. Dalen Agnew, Dr. Margaret Petroff, Dr. Mark Simpson, and my major faculty advisor, Dr. Gisela Soboll Hussey. Their guidance, support, and encouragement throughout my PhD program have been instrumental in shaping my research journey. Thank you to Dr. Colleen Hegg and Dimity Palazzola in the CMIB department for your tireless support of graduate students. Lastly, I am eternally grateful to my family—Maureen, David, and Shira—and my extraordinary partner, Courtney. Your unwavering support has been my anchor and my strength during the most challenging moments of my journey. iv TABLE OF CONTENTS LIST OF ABBREVIATIONS ........................................................................................................ vi CHAPTER 1 INTRODUCTION AND LITERATURE REVIEW ................................................. 1 REFERENCES ......................................................................................................................... 23 APPENDIX 1: TABLES & FIGURES ..................................................................................... 42 CHAPTER 2 ANTI-FIBROBLAST ACTIVATION PROTEIN NEAR-INFRARED PHOTOIMMUNOTHERAPY TARGETING CANCER-ASSOCIATED FIBROBLASTS ........ 48 REFERENCES ......................................................................................................................... 72 APPENDIX 2: TABLES & FIGURES ..................................................................................... 78 CHAPTER 3 CONCLUSIONS AND FUTURE DIRECTIONS.................................................. 92 REFERENCES ......................................................................................................................... 98 v LIST OF ABBREVIATIONS CAF ECM FAP Cancer-associated fibroblast Extracellular Matrix Fibroblast activation protein NIR-PIT Near infrared photoimmunotherapy PDPN Podoplanin α-SMA alpha Smooth Muscle Actin vi CHAPTER 1 INTRODUCTION AND LITERATURE REVIEW 1 Cancer-associated fibroblasts: Tumorigenicity and targeting for cancer therapy Raisa A. Glabman1,2, Peter L. Choyke1, Noriko Sato1,* 1 Molecular Imaging Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA 2 Department of Pathobiology and Diagnostic Investigation, College of Veterinary Medicine, Michigan State University, East Lansing, MI 48824, USA * Corresponding author: N. Sato, saton@mail.nih.gov; Molecular Imaging Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA Tel.: 1-240-858-3079 2 ABSTRACT Cancer-associated fibroblasts (CAFs) are a heterogenous group of activated fibroblasts and major component of the tumor stroma. CAFs may be derived from fibroblasts, epithelial cells, endothelial cells, cancer stem cells, adipocytes, pericytes, or stellate cells. These complex origins may underlie their functional diversity, which includes pro-tumorigenic roles in extracellular matrix remodeling, suppression of anti-tumor immunity and resistance to cancer therapy. Several methods for targeting CAFs to inhibit tumor progression and enhance anti-tumor immunity have recently been reported. While preclinical studies have shown promise, to date they have been unsuccessful in human clinical trials against melanoma, breast cancer, pancreas cancer, and colorectal cancers. This review summarizes recent and major advances in CAF-targeting therapies, including DNA-based vaccines, anti-CAF CAR-T cells, and modifying and reprogramming CAF functions. Challenges in developing effective anti-CAF treatment are highlighted, which include CAF heterogeneity and plasticity, lack of specific target markers for CAFs, limitations in animal models recapitulating human cancer microenvironment, and undesirable off-target and systemic side effects. Overcoming these challenges and expanding our understanding of the basic biology of CAFs is necessary for making progress towards safe and effective therapeutic strategies against cancers in human patients. 3 Introduction Over 1.9 million new cancer cases are expected in the United States in 2022, and solid tumors comprise approximately 90% of these cases [1]. As we continue to expand our knowledge of cancer, we now recognize the tumor microenvironment as a heterogenous, intricate system composed of tumor cells and nonmalignant host components including immune cells, stroma, and vasculature, which shapes the nature of the tumor. In many epithelial tumors, including pancreatic, lung, breast and colorectal cancers, the stroma can comprise up to 90% of the cancer mass [2]. Within the tumor stroma are both cellular and noncellular components, including collagen, fibroblasts, and mesenchymal stromal cells which provide structure and remodel the tissue. Activated stromal tissue, in the pathological context, forms desmoplasia or fibrosis, resulting in increased mass and stiffness which are considered negative prognostic indicators. Fibroblasts constitute one of the most abundant and critical cell types in the tumor stroma and are the major producers of connective tissue extracellular matrix (ECM). Within the tumor microenvironment, various inflammatory cytokines produced by cancer cells, host immune and stromal cells induce activation of fibroblasts. These activated fibroblasts are termed cancer-associated fibroblasts (CAFs). Through their production of soluble factors, such as cytokines and chemokines, and ECM, CAFs strongly influence surrounding cells. They support tumor progression and metastasis by promoting cancer cell growth, enhancing pro-tumor immune responses, remodeling the ECM, influencing tumor cell drug resistance, and promoting angiogenesis [3, 4]. In this review, we focus on CAFs, discuss their biologic tumor-promoting functions and recent advancements in the development of CAF-targeting cancer therapies. 4 Definitions, origins, and basic biology of CAFs Definition of CAFs Fibroblasts are found in virtually all organs and normal tissues and contribute to inflammation and fibrosis during wound healing. CAFs are activated fibroblasts with a mesenchymal lineage associated with cancer and contribute to tumor-promoting inflammation and fibrosis. CAFs are defined by a combination of their morphology, association with cancer cells, and lack of lineage markers for epithelial cells, endothelial cells, and hematopoietic cells [4]. CAFs maintain key roles in regulating the biologic function of the tumor stroma and contribute to immune regulation, angiogenesis, and ECM remodeling of the tumor, as well as generation and maintenance of cancer stem cells, thereby promoting therapeutic resistance. Distinction of CAFs from resting fibroblasts CAFs differ in several respects from resting fibroblasts residing in normal tissues. CAFs are generally larger than resting fibroblasts, spindle-shaped, and have indented nuclei and branching cytoplasm. However, the difference between the two is largely a functional distinction. CAFs possess enhanced proliferative, migratory, and secretory properties. CAFs are more metabolically active than untransformed fibroblasts, producing increased extracellular matrix factors such as tenascin, periostin (POSTN), and secreted protein acidic and rich in cysteine (SPARC) [5]. Collagen production by CAFs is abnormal, characterized by increased production and often a more rigid and contractile pattern of collagen deposition [6-8]. Several signaling mechanisms are recognized in the transition from resting fibroblast to CAF, including activation of the Hippo pathway, loss of p53, and activation of heat shock factor protein 1 triggered by inflammation and changes in the structure and composition of the ECM [6, 9]. CAFs are even found in circulation, akin to circulating tumor cells (CTCs) - circulating CAFs [identified based on expression of 5 fibroblast activation protein (FAP) and alpha-smooth muscle actin (α-SMA)] were found in 88% of patients with metastatic breast cancer and in 23% of patients with nonmetastatic disease [9], suggesting a role in metastasis and formation of the pre-metastatic niche. Origin of CAFs CAFs can arise from myriad cell precursors, which can also vary between tissues. The origins of all CAFs are not entirely and fully elucidated. Regardless of origin, the transition to CAF is largely irreversible, and yet remains plastic with regard to CAF phenotype within or across tumor types. CAFs often develop from local resident fibroblast populations but can also differentiate from mesenchymal stromal cells or mesenchymal stem cells (MSCs). MSCs express a similar, less abundant set of surface markers, and possess the ability to differentiate into osteoblasts, chondrocytes and adipocytes [10-12]. Quiescent resident fibroblasts in the liver and pancreas, also known as pancreatic stellate cells, can acquire a CAF phenotype upon activation by tumor growth factor beta (TGF-β) and platelet-derived growth factors (PDGFs) [13, 14]. Outside of the fibroblast lineage, CAFs can transdifferentiate from epithelial cells, blood vessels, adipocytes, pericytes, and smooth muscle cells via endothelial to mesenchymal transition (EMT) and endothelial to mesenchymal transition (EndMT). Fibrocytes, circulating mesenchymal cells derived from monocyte precursors can also become CAFs [15]. Both noninvasive and invasive cancer cells can express EMT markers β-catenin and vimentin or S100A4, so these are also not unique to CAFs. Importantly, CAFs can secrete proinflammatory cytokines, such as interleukin (IL)-6, which promotes EMT of cancer cells [16-18], forming a positive feedback loop. Recruitment and activation of CAFs is mediated by hypoxic conditions, oxidative stress, and certain growth factors produced by tumor cells. TGF-β, epidermal growth factor (EGF), fibroblast growth factor type 2 (FGF2) and PDGF are known to act as key regulators of CAF recruitment and activation [19, 20]. 6 Additionally, IL-1β from innate immune cells triggers NF-kB activation and production of IL-6 in CAFs via the JAK-STAT pathway, contributing to CAF differentiation [21]. Lysophosphatidic acid produced by cancer cells synergizes with TGF-β to drive activation and increase contractility of CAFs [4]. Recent research has also shown that exosomes secreted by murine melanoma, human squamous cell carcinoma and human breast carcinoma can promote the differentiation of fibroblasts into CAFs, mediated by TGF-β and downstream SMAD signaling pathways [22, 23]. Overall, the precise origin and roles of fibroblast populations within the tumor microenvironment remain poorly understood. Further studies using lineage tracing for cell of origin [24, 25] will be essential in deepening our understanding on the origins of CAFs, as well as their evolution during tumorigenesis. CAF phenotypic and functional heterogeneity Tumors are spatially and functionally heterogeneous ecosystems [26], and the variety of sources from which CAFs can arise lend complexity to their phenotype, gene expression and function. Several biomarkers have been established to detect CAFs, however none are completely exclusive. To date, CAFs are defined as cells that lack expression of biomarkers for epithelial, endothelial, or hematopoietic cells but express mesenchymal biomarkers such as vimentin, α-SMA, FAP, and platelet-derived growth factor receptor alpha (PDGFR-α), and lack genetic mutations [27, 28]. As the phenotype of CAFs differs between tumor type, CAF studies necessitate the combined application of multiple biomarkers for detection and identification of these cells. As a result, CAFs are often identified by a combination of α-SMA, tenascin-C, periostin (POSTN), NG2 chondroitin sulfate proteoglycan, PDGFR-α/β and FAP expression. Other mesenchymal markers include vimentin, fibronectin, type I collagen, prolyl 4-hydroxylase, fibroblast surface protein, and 7 fibroblast specific protein-1 (FSP-1)/S100A4 [29]. Biomarkers expressed by CAFs are summarized in Table 1a and 1b. Historically, activated fibroblasts expressing α-SMA were termed ‘myofibroblasts’ but are now recognized to be only one subset among several within the tumor microenvironment. α-SMA+ CAFs predominantly produce and modulate the ECM, facilitate cell-ECM adhesion, and regulate adaptive immunity [30]. α-SMA+ CAFs are also located more distally to tumor cells. FAP+ CAFs are immunosuppressive with increased ECM alignment and stiffness, and this is hypothesized to be a major factor in the transition from a tumor-resistant to tumor-permissive microenvironment [31]. Stiffness of the tumor stroma influences invasion through tumor cell integrin-dependent mechanotransduction signaling [32], and is correlated with increased metastasis [33, 34]. Newer analytic methods such as single-cell RNA sequencing (scRNAseq) and cytometry by time of flight (cyTOF) have begun to help answer questions concerning functional subsets. Functional CAF subsets maintain unique cytokine expression profiles which variably shape the tumor microenvironment. While some CAF subsets do not seem to affect immune cell populations, others in fact, modulate the immune microenvironment, often in pro-tumorigenic ways. The most recent scRNAseq transcriptome data suggest there are between 3-7 major subsets of fibroblasts [35-37] but some of these groups may have overlapping features, as well as context-dependent and tumor- dependent variability. Nonetheless, there is growing evidence for similar or shared phenotypes across tumor types as discussed in the following sections. Functional CAF subsets in human cancers Analysis of distinct CAF subpopulations at the single cell level has largely been performed in the context of human pancreatic cancer, with several studies also examining these cells in other human tumor types (Table 2). In human pancreatic cancer, at least two major CAF phenotypes are defined 8 by their expression of α-SMA and IL-6. A more matrix-secreting, TGF-β–responsive, high-α-SMA and low-cytokine (e.g., IL-6, IL-11)-expressing myofibroblastic, myCAF population, and inflammatory-type, iCAFs, that exhibit high IL-6 and IL-11 production and low α-SMA expression.[35, 38-40]. Spatial distribution of these two populations also differs - myCAFs are often found adjacent to neoplastic cells whereas iCAFs localize within dense stromal regions distant from neoplastic cells [39]. Interestingly, pancreatic CAFs, formerly quiescent pancreatic stellate cells, are able to transition between the myCAF and iCAF states, although the mechanism by which this occurs is not well understood [39]. A third CAF phenotype, apCAFs, are characterized by major histocompatibility complex (MHC) class II and CD74 expression and capable of presenting antigen to CD4 T cells, but lack classical costimulatory molecules expressed by professional antigen-presenting cells [35]. MyCAF and iCAF subpopulations have also been identified in human cholangiocarcinoma [41] and bladder cancer [42]. Human triple negative breast [43, 44] and ovarian [45] cancer studies have yielded 3-4 CAF subtypes, designated CAF S1-S4 based on differential expression of six fibroblast markers (FAP, integrin β1/CD29, α-SMA, S100-A4/FSP1, PDGFR-β, and CAV1). Other phenotyping studies in human lung [37], prostate [46], head and neck [47] and colorectal [48, 49] cancers similarly classify CAF subpopulations based on high versus low α-SMA expression and/or functional characteristics. Functional CAF subsets in murine cancers The three CAF subsets described in human tumors are also found in murine pancreatic cancer models by scRNAseq analysis; ECM-producing myCAFs, inflammatory iCAFs, and a third smaller population of antigen presenting apCAFs. CAF subsets in spontaneous mouse mammary tumor models (the MMTV-PyVT mouse model) have been categorized into four main groups, vascular CAFs (vCAFs), cycling CAFs (cCAF), matrix CAFs (mCAF), and developmental CAFs 9 (dCAF) [50]. vCAFs are angiogenic, predominantly located near vessels and thought to arise from perivascular cell precursors. cCAFs are considered the proliferating fraction of vCAFs, with similar transcriptional profiles as vCAFs, exhibiting upregulated cell cycle genes (e.g. Nuf2, Mki67, Ccna2, Top2a, Cep55). mCAFs are descendents of resident fibroblasts, expressing fibulin- 1 and PDGFRα, which are often positioned at the invasive front of tumors. dCAFs express development-associated genes and are similar in phenotype and are proximal to cancer cells, suggesting they may originate from a malignant cell precursor. In 4T1 mouse mammary tumor models, eight subtypes of CAFs divided into in two main populations, pCAF and sCAF, are described based on selective expression of PDPN or S100A4. The ratio of pCAFs and sCAFs changes with tumor progression and is associated with disease outcome in triple negative breast cancer patients [51]. CAFs have been functionally categorized in other murine cancers, such as melanoma, as either immune (S1), desmoplastic (S2) or contractile (S3)[52], and in cholangiocarcinoma as either myCAF, iCAF, or mesothelial mesCAF [41]. Overall, the existence of both myofibroblastic and inflammatory CAF populations appears to be the most consistent observation in both human and mouse tumor models. Across cancer types, myCAFs are associated with high ECM production, whereas non-myofibroblastic iCAFs are generally characterized by a secretory, inflammatory phenotype. Lastly, CAFs can also be grouped based on location, e.g. primary tumor, circulation, or metastasis [53, 54]. Challenges in defining and detecting CAFs By far, one of the greatest challenges in defining CAFs is the lack of a pan-specific biomarker. In addition, no standardization nor consensus of biomarkers to identify CAFs currently exist, adding to the difficulty in differentiating CAFs from other mesenchymal cells (e.g. adipocytes or 10 pericytes). This lack of uniform analysis makes interpretation of previous studies and understanding of the full biological implications of these cells difficult. Standardized functional and molecular definitions of fibroblast subtypes also do not yet exist. There is inherent plasticity between CAF subtypes, suggesting these are functional fibroblastic states, as opposed to static fibroblast types, adding to their complexity [55]. CAFs continue to evolve over time and eventually differentiate into subpopulations that promote tumor development in ways that are not only tissue specific but tumor specific. Identifying what triggers this plasticity will also be invaluable in future research, as phenotypic or functional subsets may not function comparably across tumor types. It is increasingly clear that the tumor microenvironment changes throughout cancer progression, and likely so do CAFs. Longitudinal studies, particularly focused on CAF plasticity, are necessary for further insight. Pro-tumorigenic functions of CAFs Various components of the tumor microenvironment promote tumor progression and resistance to cancer therapy. For instance, mesenchymal stem cells can secrete vascular endothelial growth factor (VEGF), promoting vessel growth, and prostaglandin E2 (PGE2), impeding the anti-tumor immune response through suppression of T cell function. Pericytes and adipocytes can produce pro-tumorigenic growth factors and cytokines and even contribute to T cell anergy [56]. Finally, immune cells such as TAMs promote EMT, inflammation-associated angiogenesis through VEGF, TIE2, and CD31 expression [57], and therapeutic resistance. Here, we focus specifically on the roles of CAFs. Tumor promoting secretory factors In general, CAFs secrete far more cytokines and chemokines than their resting counterparts. These secreted factors include TGF-β, PDGF, FGF, hepatocyte growth factor (HGF), VEGF, tumor 11 necrosis factor α (TNF-α), interferon-γ (IFNγ), CXCL12, IL-6, connective tissue growth factor (CTGF-β), EGF, growth arrest-specific protein 6 (GAS6), galectin-1, secreted frizzled-related protein 1 (SFRP1), sonic hedgehog protein (SHH), and bone morphogenetic protein (BMP), which are tumor-promoting [6]. As the master regulator of fibrosis and a major secreted factor of CAFs, TGF-β predominantly mediates cross-talk between CAFs and cancer cells. Inhibition of TGF-β signaling using a number of approaches has been shown to significantly inhibit tumor growth and metastasis [58]. CAFs have also been demonstrated to induce EMT and promote the growth and migration of cancer cells via IL-6 [59, 60]. Elevated levels of CAF-derived IL-6 induces activation of the JAK/STAT3 signaling pathway, leading to tumor cell proliferation mediated by activation of cyclin D1, among other cell cycle mediators. Tumor survival is enhanced by activation of downstream BCL2-like protein 1 (BCL2-L1). STAT3 also induces expression of angiogenic factor VEGF. During tumor neovascularization, degradation of the basement membrane and ECM occurs, with contribution from matrix metalloproteinases (MMPs) [61], to allow for endothelial cells to migrate and generate new vessels. This process, in turn, enhances cancer invasion and metastasis. The hyperactivation of STAT3 in anti-tumor immune cells exerts a negative regulatory effect which also contributes to an immunosuppressive tumor microenvironment [62]. Other signaling pathways governing the tumor-promoting ability of CAFs include PDGF-PDGFR, which acts through paracrine signaling on cancer cells to drive tumor growth [29]. Resistance to chemotherapies and radiation Classic chemotherapy targets rapidly proliferating cells, but does not eliminate all CAFs, nor those cancer cells that become drug resistant. CAFs can also contribute to the development of resistant cancer phenotypes following cycles of chemotherapies. Several in vitro experiments demonstrate 12 that DNA damage induced by chemotherapies prompted increased cancer cell invasion and survival through stromal-derived paracrine signaling via cytokines and exosomes [6]. For example, this occurs via glial derived neurotrophic factor (GDNF) production in prostate cancer [63], IL-6 in lymphoma [64], and exosome secretion in colorectal cancer [65]. Chemotherapy-induced genotoxic stress can also trigger a DNA damage secretory program resulting in release of numerous inflammatory (IL-6/8), angiogenic (VEGF, CXCL1), mitogenic (amphiregulin) and pro- EMT (HGF) factors [55]. Several chemotherapy drugs have been reported to induce CAF-like phenotypes in resting fibroblasts and promote stemness in breast [66] and colorectal cancers [65]. This is thought to occur following an exposure of cancer cells to a hypoxic environment, which activates hypoxia- inducible factor (HIF-1α) and sonic hedgehog-GLI signaling [66, 67]. CAF-mediated TGF-β signaling synergizes with HIF-1α signaling and enhances the expression of GLI2 in cancer cells, inducing stemness. This results in resistance to chemotherapy. In fact, high expression of the HIF- 1α/TGF-β is associated with increased risk of colorectal cancer recurrence in patients undergoing chemotherapy [67]. Similarly, studies have found that CAFs contribute to drug resistance and reduce the efficacy of anti-EGFR cetuximab [68], gemcitabine [69], and tyrosine kinase inhibitor gefitinib [70]. As with the examples of chemotherapies described above, radiation therapy impedes cancer cell growth through DNA damage. Radiation affects not only cancer cells but also the tissue microenvironment surrounding cancer cells, which includes immune cells, endothelial cells, vasculature, and fibroblasts. Fibroblasts are highly resistant to radiation, even at high doses. Irradiated fibroblasts can overcome apoptotic signals and become senescent but have also been demonstrated to convert to a more activated CAF phenotype [71-73]. In one study, radiation 13 exposure activated CAFs and upregulated their expression of CXCL12, which directly acted on pancreatic cancer cells via CXCR4, promoting EMT and invasion in vitro and in vivo [74]. Enhanced expression of CXCL12, HGF, MMPs and TGF-β in irradiated fibroblasts was found to increase invasion and EMT in cancer cells as indicated by increased expression of vimentin, snail and beta-catenin, and decreased E-cadherin expression. [71-73]. CAF-directed resistance to radiotherapy and post-radiation recurrence of cancers is reported to be associated with activation of the autophagy pathway. It is likely this response is at least in part related to CAF-secreted IGF1/2, CXCL12 and β-hydroxybutyrate, leading to increased reactive oxygen species (ROS), enhancing protein phosphatase 2A (PP2A) activity, repressing mTOR activation, ultimately resulting in autophagy in cancer cells after irradiation [75, 76]. The IGF2 neutralizing antibody and autophagy inhibitor 3-MA consistently reduced the CAF-promoted tumor relapse in tumor-bearing mice after radiotherapy [75]. Combining CAF-targeted therapies and chemotherapy or radiation could yield a more powerful and robust anti-tumor response. Immunomodulatory role of CAFs Advances in immune checkpoint inhibitors, such as PD-1 and CTLA-4, have brought much attention to the immune cell-tumor crosstalk, however, less is known about the contribution of stromal components to the immune milieu. Recent studies suggest CAFs mediate the tumor immune landscape via the secretion of various cytokines, growth factors, chemokines, exosomes, and other effector molecules, ultimately shaping an immunosuppressive tumor microenvironment, enabling cancer cells to evade immune surveillance, and limiting immunotherapy strategies. In general, CAFs shape the tumor microenvironment by production of proinflammatory cytokines, including IL-1β and IL-6 [21, 77], and express the ligands CXCL12 [78], CXCL1 [79], and G- CSF [80] which can drive downstream immunosuppressive signaling pathways. For instance, 14 CXCL12 regulates interactions between tumor cells and surrounding cells in the tumor microenvironment, promoting tumor survival, proliferation, angiogenesis, and metastasis. It also promotes recruitment of immunosuppressive cells and their precursors, notably bone marrow mesenchymal stem cells and monocytes that differentiate into tumor-associated macrophages (TAMs). Inflammatory CAFs, or iCAFs, highly express CXCL12 which binds to CXCR4 [35]. Blocking the CXCL12-CXCR4 interaction can induce cancer regression in pre-clinical models [78, 81]. CAFs also interact with T cells, NK cells, dendritic cells (DCs), myeloid-derived suppressor cells (MDSCs), mast cells, TANs and TAMs in the tumor microenvironment generally resulting in an immunopermissive environment. CAFs prevent CD8+ cytotoxic T cell activity and recruitment within tumors, in part through TGF- β [82-84] and CXCL12 [85]. Both TGF-β cand CXCL12 are known to contribute to cytotoxic T cell exclusion by attenuation of the anti–PD-L1 response [78]. While limiting anti-tumor cytotoxic T cells, CAFs can also increase intratumoral Treg recruitment and scRNAseq revealed upregulation of PD-1 and CTLA4 in Tregs. CAFs appear to attract, help accumulate and promote the survival of FOXP3+Tregs in human triple negative breast cancer [44]. FoxP3+Tregs are known to restrain host-antitumor-immunity, and thereby lend an unfavorable prognosis in number of cancers. Although the precise mechanism of crosstalk between Tregs and CAFs remains unclear, high numbers of both cell types are found in stromal regions and are associated with low survival in cancers such as lung adenocarcinoma [86]. NK cells are well-known innate effector cells; however, their function can be impaired by CAFs through inhibition of NK receptor activation, cytotoxic activity, and cytokine production [87, 88]. Netrin G1 (NetG1) expression on CAFs can suppress the cytotoxic function of NK cells and support survival of cancer cells in nutrient-deprived environments, and is thus, linked to poor 15 prognosis in cancers such as pancreatic ductal adenocarcinoma [89]. Tumor-infiltrating DCs are also critical to the anti-tumor immune response, and their functionality can similarly be impaired by CAFs. By activating the IL-6-mediated STAT3 pathway, CAFs in hepatocellular carcinoma transdifferentiated DCs into regulatory DCs (rDCs) that produce inhibitory cytokines and enzymes such as indoleamine 2,3-dioxygenase (IDO) [90]. VEGF produced by CAFs is also involved in the abnormal differentiation and impaired antigen presenting function of DCs via inhibition of NF-κB activation [91]. MDSCs can be also be recruited to the tumor microenvironment by CAFs via CCL2 [92], thereby suppressing CD8 T cell proliferation and IFN-γ production [93]. Mast cells, which can be both tumor-suppressing and tumor promoting, can be recruited by CAFs via CXCL12 in a CXCR4- dependent manner [94]. In vitro, mast cells and CAFs can act together to induce the malignant transformation of benign epithelial cells [95]. Furthermore, N2, or protumorigenic, polarization of neutrophils within the tumor can be induced through CAF-derived cardiotrophin-like cytokine factor 1 (CLCF1), which upregulates CXCL6 and TGF-β on tumor cells [96]. Neutrophils may also be directly recruited by CAFs through secretion of CXCL12 or expression of CXCR2 thus becoming tumor associated neutrophils (TANs) [97, 98]. CAFs regulate the activation, survival, and function of TANs through the IL-6/STAT3-PDL1 signaling axis [97]. Like other cells in the tumor microenvironment, TAMs and CAFs have synergistic effects and are often detected in similar areas of tumor tissue. Their combined presence is a negative prognostic predictive indicator in human cancers [99]. Likewise, CAFs are involved in monocyte recruitment, macrophage differentiation and polarization toward tumor-promoting, or M2 phenotype [100, 101], through secretion of macrophage colony-stimulating factor 1 (M-CSF1), IL-6, CCL2 [102] and IL-8 [103]. M2 macrophages are reciprocally able to stimulate CAF activation through IL-6 16 and CXCL12 [100]. While research accumulates on the interactions of CAFs and immune cells in the tumor microenvironment, many ongoing questions remain unanswered. Undoubtedly, understanding CAF and immune cell interactions will provide the basis for novel strategies for targeted immunotherapies. Targeting CAFs: Anti-cancer therapies Significant advances have been made in CAF-targeted therapies in recent years. Predominantly, these methods aim to (1) directly or indirectly deplete CAFs, (2) reduce or eliminate the tumor- promoting and immunosuppressive functions of CAFs, or (3) normalize or reprogram CAFs to a more quiescent state. Those strategies are summarized here. Chemotherapy targeting CAFs As discussed previously, FAP is expressed on subsets of CAFs in various tumors. FAP is a membrane-bound serine postprolyl peptidase that differs from other dipeptidyl prolyl peptidases in that it also has endopeptidase activity [104]. A competitive inhibitor of prolyl peptidase, Val- boroPro (Talabostat) is an oral drug that showed some tumor growth control by degrading ECM in mice [105]. However, in human clinical trials for metastatic colorectal cancers, no therapeutic efficacy was observed [106]. Sibrotuzumab is a humanized anti-FAP monoclonal antibody (clone F19) that inhibits dipeptidyl peptidase activity of FAP [107]. Unlike F19, Sibrotuzumab did not demonstrate inhibitory activity and failed to suppress growth of pancreatic cancers in patients, despite documented evidence of accumulation of the antibody in the tumor using a radiolabeled version of the antibody (iodine-131-labeled Sibrotuzumab) imaged by single photon emission computed tomography (SPECT) [108]. Taking advantage of the unique enzymatic activity of FAP, anti-CAF prodrugs or protoxins contain cytotoxic agents coupled with a dipeptide containing a FAP cleavage site [104, 109]. These 17 prodrugs remain inactive when systemically delivered and are proteolytically activated upon cleavage by FAP, which is expressed on CAFs in the tumor. Intratumoral injection of these prodrugs produced tumor lysis and growth inhibition in human breast and prostate cancer xenografts [104, 109, 110]. Another class of drugs are the immunotoxins that use an antibody to specifically deliver a toxin to the target cells. Anti-FAP-PE39 demonstrated suppressed mammary tumor growth and increased recruitment of tumor infiltrating lymphocytes [111]. A monoclonal antibody conjugated with a tubulin binding drug maytrasinoid and a bispecific antibody simultaneously targeting FAP on CAFs and death receptor 5 on tumor cells has shown potent anti- tumor effects [111, 112]. In another strategy, nanoparticles such as FAP-targeted liposomes have been explored as carriers to specifically deliver therapeutic drugs (e.g. doxorubicin, anti-Tenascin C) to CAFs [113, 114] or to remodel the tumor microenvironment [115, 116]. Despite the success of preclinical strategies, including substantially attenuating the growth of tumor xenografts in various cancer models with minimal to no toxicity [110, 117-119], clinical translation is still in its early stages. Immunotherapy Various strategies to enhance immunity against FAP expressing cells (i.e. CAFs) and to suppress cancer growth have been explored. Vaccination against FAP using dendritic cells transfected with FAP mRNA led to suppressed growth of implanted and intravenously injected tumors [120]. The efficacy was enhanced when a co-vaccination against FAP and a tumor cell-associated antigen was used. These DC vaccines, synergistically combined with an anti-fibrotic agent, showed promising activation of both innate and adaptive immunity. Enhanced NK cell activity, anti-tumoral humoral immunity, and cytotoxic CD8+ T cell response was observed in three different tumor models [120]. Similarly, adenoviral anti-FAP vaccines are able to selectively deplete CAFs by stimulating a 18 CD8+ T cell response, leading to inhibition of tumor growth and metastasis in several murine cancer models [121-124]. In a landmark study using a transgenic mouse expressing the diphtheria toxin receptor under the FAP promoter, depleting FAP+ CAFs by diphtheria toxin administration improved anti-cancer vaccination efficacy [125]. An orally administered anti-FAP DNA vaccine notably suppressed neoangiogenesis, tumor growth and metastasis of orthotopically injected breast carcinoma cells [121]. Adding doxorubicin substantially increased intratumoral uptake of the drug and prolonged lifespans of vaccinated mice [126]. Adoptive chimeric antigen receptor (CAR)-T cell therapy can also be used to directly target CAFs [117, 127, 128]. FAP-specific CAR-T cells deplete most FAP+ cells, including CAFs, and restrict tumor stroma generation, resulting in the improved uptake and anti-tumor effects of chemotherapeutic drugs. Unfortunately, several studies have observed severe side effects using this approach, such as significant bone marrow toxicity and cachexia [129, 130]. More selective and yet unknown targets may improve the precision of CAF-based therapies, which remains an active field of research [131]. Finally, near-infrared photoimmunotherapy (NIR-PIT) is an innovative approach to CAF depletion that has been used to directly and specifically deplete FAP expressing cells, including CAFs in the tumor microenvironment. Tumor growth was inhibited using a co-culture xenograft model of human esophageal squamous cell carcinoma without adverse effects [132]. Anti-FAP+CAF therapy combined with 5-fluorouracil (5-FU) could overcome chemoresistance compared with 5- FU alone [133]. Functional Modification/Reprogramming Strategies that aim to revert activated CAFs to quiescence include use of all-trans-retinoic acid (ATRA) [134-136], minnelide (which de-regulates the TGF-β signaling pathway) [137, 138], and 19 calcipotriol, a vitamin D receptor ligand [139, 140]. The angiotensin receptor II antagonist losartan has been shown to decrease TGF-β-mediated activation of CAFs, reducing desmoplasia and increasing drug delivery and efficacy of immunotherapy [141-143]. Losartan in combination with other traditional chemotherapies to treat pancreatic cancer is currently under investigation in clinical trials [144]. Recent strategies seek to block immunosuppressive ligands of major CAF signaling pathways such as IL-6 [145, 146], LIF [147] and TGF-β [82, 84] in order to suppress or kill cancer cells. The CXCL12/CXCR4 axis is important in cancer progression and immunosuppression. CXCL12 produced by CAFs recruits CXCR4 expressing endothelial progenitor cells and immune suppressive Tregs, which contributes to angiogenesis and tumor growth [43, 85]. Abrogation of CXCR4 signaling in CAFs using the CXCR4 inhibitor Plerixafor significantly reduced fibrosis, leading to vasculature normalization, increased cytotoxic T cell infiltration, decreased immunosuppressive cell populations, and increased checkpoint inhibitor efficacy [81]. Other strategies which inhibit CAF functions include TGF-β blockade [148], NFkB inhibitors to overcome chemotherapy resistance [149], and Smoothened (SMO) hedgehog pathway inhibitors (IPI-926) [150]. Future Perspectives CAFs play an integral role in the promotion of tumor growth. However, the origin and functional roles of unique CAF subsets are yet to be fully understood. as well as their niche within various tumor types. Determining the spatial and temporal dynamics of CAFs and their cell-to-cell interactions in the tumor microenvironment will add critical information to our knowledge on these fascinating cells. While much of CAF biology has been modeled in vitro, it has been repeatedly demonstrated that CAFs in culture do not fully recapitulate the heterogeneity of CAFs in vivo [47, 20 151, 152]. Increasing the strategic use of animal models, including humanized and genetically engineered mouse models, is critical to further understanding the origin, plasticity and phenotypes of CAFs over time. To this end, the future of the field will undoubtedly include new and emerging technologies such as fate mapping and scRNAseq to assess changes in both stromal cells and immune cells through tumor progression, digital or multiplex spatial profiling of proteins or RNA in tissue to assess spatial changes in the tumor microenvironment, spatial transcriptomics, digital pathology and three-dimensional tissue clearing and 3D culture systems. Intravital microscopy will provide live visualization of cell-to-cell interactions in vivo. These technologies will bring breakthroughs, such as the identification of even more CAF subpopulations, their cellular interactions, and further insights into CAF heterogeneity and plasticity. In addition to these analytic methods, a consensus on CAF biomarkers will need to be reached, so that similar phenotypes may be compared across tumor types and preclinical models used in different laboratories. Improving therapeutic delivery methods, such as targeted CAF therapy, rather than stromal-directed therapy is now becoming more common. FAP shows promise as a CAF marker for CAR-targeted therapy. Recently emerged FAP imaging using gallium-68 labeled small-molecule FAP inhibitor (FAPI) as a tracer for positron emission tomography (PET) suggests superiority in detecting FAP+ cell containing cancers in patients compared with [fluorine- 18]fluoro-deoxy-glucose PET in some cancers [153]. FAPI PET could be used to predetermine the candidacy for anti-FAP CAF-targeted therapies as well as to evaluate the therapy efficacy. Conclusions This review summarizes key advances in CAF directed therapies and highlights new techniques for the molecular targeting of CAFs. 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Valdés-Mora F, Salomon R, Gloss BS, Law AMK, Venhuizen J, Castillo L, Murphy KJ, Magenau A, Papanicolaou M, Rodriguez de la Fuente L, Roden DL, Colino-Sanguino Y, Kikhtyak Z, et al. Single-cell transcriptomics reveals involution mimicry during the specification of the basal breast cancer subtype. Cell Rep. 2021; 35: 108945. doi: 10.1016/j.celrep.2021.108945. 41 References [78, 128, 154, 155] [27, 156, 157] [158-162] [163-166] [43, 167- 170] [131] APPENDIX 1: TABLES & FIGURES Table 1a: Surface biomarkers used to identify fibroblasts and cancer-associated fibroblasts. Expressed by Localizati on membrane Fibroblasts, immune cells Marker Fibroblast Activation Protein (FAP) PDGFRa/b membrane Fibroblasts, Role in tumor functionality/progression Tumor progression and metastasis, shaping the immunosuppressive TME, ECM remodeling, fibrogenesis M2 polarization, angiogenesis Podoplanin (PDPN) α11β1 integrin (ITGA11) Caveolin-1 (CAV1) CD10 CD74 Ly6C Thy-1 (CD90) vascular smooth muscle cells, pericytes membrane Endothelial cells membrane Mesenchymal cells membrane Many cells membrane Bone marrow mesenchymal stem cells, pre-B lymphocytes membrane Fibroblasts, monocytes, macrophages, epithelial cells Inflammatory CAFs, myeloid cells membrane membrane Fibroblasts, neurons, endothelial cells, tumor cells, immune cells Immunosuppression, tumor growth Cancer cell migration, adhesion, tumor cell invasion, desmoplasia Vascular and pleural invasion of cancer cells, metastasis Sustaining cancer stemness, cancer formation, chemoresistance Antigen presentation [35, 38] Protumorigenic inflammation [35, 38] Tumor cell invasion, migration, tumor-associated endothelial cells [171-174] TME: tumor microenvironment, ECM: extracellular matrix 42 Table 1b: Intracellular biomarkers used to identify fibroblasts and cancer-associated fibroblasts. Marker Localization Expressed by: Vimentin cytoplasmic α-SMA cytoplasmic FSP- 1/S100A4 cytoplasmic, nuclear Fibroblasts, mesenchymal cells Fibroblasts, smooth muscle cells Normal fibroblasts, epithelial and endothelial cells Tenascin- C ECM protein Tumor cells, stromal cells Periostin (POSTN, OSF-2) COL1 and COL11A1 Secreted ECM protein Many cells cytoplasmic Activated stromal cells Role in tumor functionality/progression: Tumor growth, invasion, migration, endothelial to mesenchymal transition Tumor cell proliferation, protection mechanism, impediment to drug delivery, ECM remodeling, desmoplasia, cancer stemness Promotion of metastasis, immune evasion, immune surveillance, cell motility, fibrosis Driver of metastasis, Epithelial-mesenchymal transition, desmoplasia, angiogenesis Cancer cell stemness, promotes tumor progression and metastasis Epithelial-mesenchymal transition, metastasis References [175, 176] [30, 39, 43] [157, 177- 179] [180-182] [183-186] [157, 187- 190] 43 Table 2: Cancer-associated fibroblast subtypes across different cancers. Species CAF subtype Tumor type Pancreatic cancer Patient samples, Murine tumors (KPC) Colorectal cancer Patient samples Head and neck cancer Patient samples Lung cancer Patient samples Melanoma Murine tumors (B16-F10) Patient samples Breast cancer and ovarian cancer Breast cancer Patient samples myCAF – ECM producing iCAF - inflammatory ApCAF – Ag presenting CAF-A CAF-B Myofibroblast Activated CAFs (2 subclusters; CAF1 and CAF2) Cluster 1 Cluster 2 Cluster 4 Cluster 5 Cluster 7 S1 – immune CAFs S2 – desmoplastic CAFs S3 – contractile CAFs CAF-S1 CAF-S2 CAF-S3 CAF-S4 iCAF myCAF Reference(s) [35, 36, 38, 39] [48, 49] [47] [37] [52] [43-45, 191] [192] Relevant Biomarker(s) or Major Feature(s) FAP, α-SMAhi, Thy1, TAGLN Ly6Chi, α-SMAlo, PDGFRαhi, IL-1, IL-6 MHCII α-SMAlo, FAP, MMP2, DCN, ECM remodeling α-SMAhi, TAGLNhi, PDGFRα, FAP-; activated myofibroblasts α-SMAhi, MYL9, MYLK, contractile FAP, PDPN, PDGFRα; ECM producing ECM-producing, TGF-β signature α-SMAhi Enriched at leading edge High mTOR; enriched at tumor core High mTOR; enriched at leading edge CD34hi, CXCL12, C3, immunosuppressive CD34lo, CTGF, TNC; PDGFRα, ECM producing α-SMAhi, RGS5 FAPhi, α-SMAhi, CXCL12, IL-6 Low/no marker expression; contractile α-SMAlo, FSP1, PDGFRβ+ CD29hi, α-SMAhi, FAPlo CXCL12 α-SMA, FAP, PDPN, COL1A1, COL1A2 44 Table 2 (cont’d) Breast cancer Murine tumors (MMTV- PyVT) Breast cancer Bladder cancer Murine tumors (4T1) Patient samples Vascular CAF (vCAF) Matrix CAF (mCAF) Cycling CAF (cCAF) Developmental CAF (dCAF) PDPN-CAF S100A4-CAF Myo-CAF iCAF Prostate cancer Patient samples CAF-S1 CAF-S2 Cholangio carcinoma CAF-S3 myCAF iCAF mesCAF Patient samples, Murine tumors (KRASG12 D/p19- induced, YAPS127A/ AKT- induced) [50, 193] [51] [42] [46] [41] α-SMA, PDGFRβ; angiogenesis α-SMAlo, PDGFRα; ECM producing PDGFRβhi, angiogenesis PDGFRβ-, SCRG1, SOX9; differentiation 6 subclusters 2 subclusters RGS5, MYL9, MYH11 PDGFRα, CXCL12, IL-6, CXCL14, CXCL1, CXCL2 α-SMA, PDGFRβ PDGFRα, PLAGL1 α-SMA, HOXB2, MAFB COL1A1, α-SMA COL8A1, COL15A1, SERPINF1 CXCL12, HGF, RGS5 Mesothelin TAGLN: transgelin, MHCII: major histocompatibility complex class II, DCN: decorin, MY: myosin, CTGF: connective tissue growth factor, TNC: tenascin-C , RGS5: regulator of G protein signaling 5, FSP1: fibroblast-specific protein-1, SCRG1: stimulator of chondrogenesis 1, SOX9: SRY-Box Transcription Factor 9, PLAGL1: pleomorphic adenoma gene 1, HOXB2: homeobox B2, MAFB: musculoaponeurotic fibrosarcoma oncogene homolog B, SERPINF1: serpin family F member 1 45 Figure 1. Schematic representation of selected pro-tumorigenic functions of CAFs. CAFs induce (1) angiogenesis and tumor growth, (2) invasion and metastasis of cancer cells, (3) modulation of the immune system, including recruitment and activation of immune suppressors and inhibition of anti-tumor effector cells, and (4) therapy-resistance through ECM production and remodeling (created with BioRender.com). 46 FUNDING This article was prepared with funding from the Intramural Research Programs of the National Cancer Institute at the National Institutes of Health. 47 CHAPTER 2 ANTI-FIBROBLAST ACTIVATION PROTEIN NEAR-INFRARED PHOTOIMMUNOTHERAPY TARGETING CANCER-ASSOCIATED FIBROBLASTS 48 Anti-fibroblast activation protein near-infrared photoimmunotherapy targeting cancer- associated fibroblasts Raisa A. Glabman1,2, Peter L. Choyke1, Noriko Sato1,* 1 Molecular Imaging Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA 2 Department of Pathobiology and Diagnostic Investigation, College of Veterinary Medicine, Michigan State University, East Lansing, MI 48824, USA * Corresponding author: N. Sato, saton@mail.nih.gov; Molecular Imaging Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA Tel.: 1-240-858-3079 49 ABSTRACT Cancer-associated fibroblasts (CAFs) constitute a prominent cellular component of the tumor stroma, representing a heterogeneous group of activated fibroblasts. Within the tumor microenvironment (TME), CAFs play various pro-tumorigenic roles, including extracellular matrix remodeling, suppression of anti-tumor immunity, and modulation of tumor cell resistance to therapy. Fibroblast activation protein (FAP), a highly expressed marker on immunosuppressive CAFs, has been identified in several epithelial human cancers such as lung, colon, breast, and prostate cancer. Numerous attempts to target FAP+CAFs for inhibiting tumor progression and enhancing anti-tumor immunity have been reported, however, the translation of FAP-directed therapies into human clinical trials has been unsuccessful. Near-infrared photoimmunotherapy (NIR-PIT) is a highly selective tumor therapy that utilizes an antibody-photo-absorbing conjugate activated by near-infrared (NIR) light. In this study, we examined the therapeutic efficacy of CAF depletion by anti-FAP NIR-PIT in two mouse models. Using CAF-rich syngeneic lung and spontaneous mammary tumors, anti-FAP NIR-PIT effectively depleted FAP+ CAFs, as well as FAP+ myeloid cells, and suppressed tumor growth. Activation of CD8+T and natural killer cells to produce interferon-gamma was induced within hours after anti-FAP NIR-PIT. Lung metastasis was reduced in the spontaneous mammary cancer model. These findings highlight a promising therapeutic approach for selectively and safely eliminating immunosuppressive FAP+ cells within the tumor microenvironment. 50 KEY WORDS Fibroblast Activation Protein Near-Infrared Photoimmunotherapy Cancer-Associated Fibroblast Tumor Microenvironment Cancer therapy 51 ABBREVIATIONS α-SMA: alpha Smooth Muscle Actin CAF: Cancer-Associated Fibroblast FAP: Fibroblast Activation Protein GCV: Ganciclovir NIR-PIT: Near-Infrared Photoimmunotherapy PDGFR-α: platelet derived growth factor receptor alpha PDGFR-β: platelet derived growth factor receptor beta PDPN: Podoplanin TME: Tumor Microenvironment TGF-β: Tumor Growth Factor beta 52 INTRODUCTION The tumor microenvironment (TME) contains various elements that contribute to both immune evasion and immune suppression. Among them, cancer-associated fibroblasts (CAFs) constitute a key cellular component of the tumor stroma, serving a number of immunosuppressive functions within the TME. Pro-tumorigenic roles of CAFs include remodeling of the extracellular matrix (ECM), suppressing anti-tumor immunity, and aiding tumor cells in resistance to therapy. Targeting CAFs presents several challenges owing to their diverse origins, plasticity, expression of heterogeneous markers and phenotypic variation across different cancer and tissue types. Regardless, controlling or reducing CAFs in the TME presents a promising approach to improve current cancer therapies. CAFs are more genetically stable compared with neoplastic cells, and less likely to develop resistant phenotypes due to high mutation rates and clonal selection. They maintain epigenetic differences compared with normal resting stromal cells and contribute to the physical structure and function of the extracellular matrix (ECM). CAFs support neoplastic cells throughout the disease spectrum, from early seeding to metastasis. Targeting or reducing CAFs has the potential to impact angiogenesis, epithelial-mesenchymal transition (EMT), and immune evasion, further augmenting cancer treatment outcomes [1]. Fibroblast activation protein (FAP) is a type II transmembrane serine protease family glycoprotein which is a member of the serine protease family [2]. FAP is minimally expressed by fibroblasts in health [3], but highly upregulated by CAFs in cancer as well as other fibroproliferative diseases (idiopathic pulmonary fibrosis, hepatic fibrosis, rheumatoid arthritis and myocardial infarction) [4, 5]. High FAP expression has been correlated to higher tumor grade, high recurrence rates and poor survival across a wide range of human cancers including breast [6-8], oral squamous cell carcinoma [9], gastric [10, 11], renal [12], colorectal [13, 14], lung [5, 15], ovarian [16], pancreatic 53 [17, 18] and melanoma [19, 20]. FAP promotes tumor growth by promoting angiogenesis and ECM remodeling [21] and facilitates the progression of tumors by suppressing the anti-cancer immune response [22, 23]. FAP is upregulated in vitro and in vivo by TGF-β and IL-1β [24]. Despite abundant evidence that FAP is critical in the TME, and FAP-targeted therapies have shown preclinical success [15, 25, 26], this has not translated into human clinical trials [27-30]. Near-infrared photoimmunotherapy (NIR-PIT) is a novel technique to selectively target and deplete cells locally within a tumor. Using an antibody conjugated to a phthalocyanine dye, IR700, followed by exposure to NIR-light, target cells rapidly undergo necrosis [31, 32]. Currently, epidermal growth factor receptor (EGFR)-targeted NIR-PIT is in phase 3 clinical trials in head and neck cancer (http://clinicaltrials.gov/ Identifier: NCT02422979) and has been approved for clinical use in Japan [33] (Rakuten Medical Inc.). In addition to directly targeting tumor antigens, immunosuppressive cells in the TME can be selectively depleted with NIR-PIT. For instance, CD25+ Treg cells have been locally depleted using NIR-PIT to augment the anti-tumor immune response [34]. In a similar manner, fibroblasts can be selectively targeted using anti-FAP NIR-PIT [35-37]. In this study, we investigated the therapeutic effect and subsequent immune response to FAP+ targeted NIR-PIT (Figure 1.1). Using CAF-rich syngeneic lung and spontaneous mammary tumors, we demonstrate that anti-FAP NIR-PIT can effectively deplete endogenous CAFs in the tumor microenvironment, induce anti-tumor effect cell activation and IFN-γ production and suppress tumor growth. 54 MATERIALS AND METHODS Synthesis of IR700-conjugated anti-FAP and anti-PDPN antibody Conjugation of IR700 with monoclonal antibodies was performed according to previous reports [32]. Briefly, 500 mg of anti-FAP (Clone 983802; R&D Systems) or anti-podoplanin (PDPN) (Clone 8.1.1; BioXCell) antibody was incubated with molar excess of IR700 (LI-COR Biosciences) in 0.1 mol/L sodium phosphate buffer (Sigma) at room temperature for 1 hour. The mixture was purified with a desalting column (PD-10 Sephadex column; GE Healthcare and Life Science) followed by protein concentration using a 500,000 MW spin column (Vivaspin™; Cytiva) and resuspended in PBS at 500 µg/mL. The quality of anti-FAP or anti-PDPN antibody- IR700 (FAP-IR700 or PDPN-IR700) was confirmed with UV-Vis (Agilent Technologies) where absorption of the elute was measured at a wavelength of 280 and 689 nm. The IR700 to antibody: dye ratio was 3:1 for FAP-IR700 and 4:1 for PDPN-IR700. Unconjugated antibody was used for the antibody control group. Cell culture NIH3T3 mouse fibroblasts, LL/2 Lewis lung carcinoma, MOC2 squamous cell carcinoma cells EL-4 T lymphoblast, EO771 mammary carcinoma, 4T1 mammary carcinoma, and PAN02 pancreatic adenocarcinoma cells were purchased from ATCC. MC38 colon adenocarcinoma cells were purchased from Kerafast. NIH3T3 cells were maintained in DMEM (Thermo Fisher Scientific) supplemented with 10 % fetal calf serum (FCS, Gemini), 100 IU/ml penicillin/streptomycin, and 0.05 mM 2-mercaptoethanol. LL/2, MOC2, EL-4, EO771, 4T1, PAN02 and MC38 cells were cultured in RPMI1640 (Thermo Fisher Scientific) supplemented with 0.05 mM 2-Mercaptoethanol, 10% FCS and 100 IU/mL penicillin/streptomycin. All cell lines were tested negative via Molecular Testing of Biological Materials by Frederick National Laboratory 55 for Cancer Research and Mycoplasma via PCR using a Mycoplasma PCR detection kit (ABM). All cells were cultured in a humidified incubator at 37°C with 5% CO2. In vitro NIR-PIT NIH3T3 cells (3x105 cells) were seeded into 12-well plates and incubated with TGF-β (20 ng/ml; Peprotech) in complete media at 37°C. After 48h, cells were washed and incubated with or without antibody conjugate (FAP-IR700 or PDPN-IR700) at 20 µl/mL in phosphate buffered saline (PBS) and incubated for 1h at 37°C. Cells were then washed with PBS and NIR irradiation performed (150 mW/cm2; ML7710 Laser System, Modulight). After 1h incubation at 37°C, cells were gently detached using PBS with 1 mM ethylenediaminetetraacetic acid (EDTA) and a cell scraper. Cell suspensions were then stained using fluorochrome-conjugated antibodies and analyzed using flow cytometry for NIR-PIT efficacy. Animal Experiments Mice All animals were housed in the NIH Clinical Center animal facility, and all procedures were performed in accordance with NIH guidelines and approved by the NIH Institutional Animal Care and Use Committee. Wild-type C57BL/6 (strain #000664), Ly 5.1 (B6.SJL-Ptprca Pepcb/BoyJ; strain # 002014), B6 MMTV-PyVT (B6.FVB-Tg(MMTV-PyVT)634Mul/LellJ; strain #022974) mice expressing the polyoma virus middle T oncoprotein (PyMT) under the Mouse Mammary Tumor Virus (MMTV) promoter in a C57BL/6 background, FAP-TK mice (B6.Cg-Tg(Fap-TK)MRkl/J; strain #034655), IFN-γ-enhanced yellow florescent protein (eYFP) reporter GREAT mice (C.129S4(B6)- Ifngtm3.1Lky/J; strain #017580), and green fluorescent protein (GFP) transgenic mice (C57BL/6- 56 Tg(CAG-EGFP)131Osb/LeySopJ; strain #006567) were purchased from The Jackson Laboratory and maintained in our facility. Subcutaneous tumors were generated by inoculating 3x105 LL/2, MOC2, EL-4, EO771, 4T1, PAN02 or MC38 tumor cells in 100 μl PBS subcutaneously into the right dorsum of mice. Tumor size was measured using electronic calipers (Mitutoyo) and tumor volume (V) was calculated as V = (major axis) x (minor axis)2 × ½ and followed until endpoint of V=4000 mm3. Mice with tumor size of approximately 100 mm3 were randomly grouped for subsequent experiments. In the MMTV-PyMT mouse, expression of the PyMT oncoprotein is restricted to the mammary epithelium, which results in the appearance of mammary tumors starting from 6-8 weeks after birth in C57BL/6 background mice and pulmonary metastases at 18 weeks in a C57BL/6 mouse background [38, 39]. GREAT mice (IFN-gamma reporter with endogenous polyA tail) [40] were used to evaluate IFNγ- eYFP expression using flow cytometry. FAP-TK mice [41] were used to achieve systemic depletion of FAP+ expressing cells by administration of ganciclovir (GCV; Sagent Pharmaceuticals) interperitoneally every 12 hours at 100 mg/kg of bodyweight (2.5 mg per 25 g mouse) for 2 days (total of 4 doses). In vivo NIR-PIT To evaluate the efficacy of FAP-targeted NIR-PIT, tumor-bearing mice were randomized into 4 groups as follows: (1) no treatment (untreated control); (2) 50 μg of anti-FAP antibody intravenously (IV), without NIR laser-light exposure (antibody alone); (3) 50 μg of anti-rat IgG1- IR700 antibody IV with NIR laser-light exposure (isotype control) or (4) 50 μg of anti-FAP-IR700 IV with NIR laser-light exposure (anti-FAP NIR-PIT). Anti-FAP-IR700, unconjugated anti-FAP or anti-rat IgG1-IR700 was IV administered when tumors reached 100 mm3 (Day 0). NIR laser-light 57 (690 nm, 150 mW/cm2, 50 J/cm2) exposure of the tumor occurred 24 hours later (Day 1). During NIR laser-light delivery, non-tumoral regions were covered with aluminum foil to prevent NIR exposure. Bone Marrow Chimeras Bone marrow chimera mice were generated by whole body lethal irradiation (9.5 Gy) of recipient mice (either MMTV-PyVT, FAP-TK or Ly5.1) using a Cesium-137 irradiator followed by intravenous injection of donor bone marrow cells within 3 hours of irradiation. Bone marrow was collected from donor mice (either FAP-TK or Ly 5.1) immediately after euthanasia by flushing the epiphysis of the femur and tibia with sterile PBS. MMTV-PyVT recipients (expressing Ly 5.2) received bone marrow from either FAP-TK (expressing Ly 5.2) mice (FAP-TKMMTV) or Ly5.1 mice (Ly5.1MMTV). FAP-TK and Ly5.1 recipients received bone marrow from Ly5.1 (Ly5.1FAP-TK) and FAP-TK (FAP-TKLy5.1) mice, respectively. Six weeks later, established chimerism was examined using peripheral blood, by distinguishing the recipient- and donor- derived cells by Ly5.2 and Ly5.1 markers using flow cytometry, where applicable. Mice with >95% chimerism in peripheral blood were used for subsequent experiments. In vivo depletion of FAP-TK+ cells by ganciclovir FAP-TK mice or bone marrow chimera mice generated using FAP-TK either as recipients or donors underwent depletion of FAP expressing cells by intraperitoneal administration of ganciclovir (GCV; Sagent Pharmaceuticals) every 12 hours at 100 mg/kg of bodyweight (2.5 mg per 25 g mouse) in PBS for 2 days (total of 4 doses). Flow Cytometry Tumors were harvested, minced using scissors, and digested using 5 µg/mL collagenase (Liberase TM™, Sigma) in 500 µL RPMI for 30 minutes at 37°C. Digestion was stopped by the addition of 58 FBS to neutralize protease activity. Digested tissues were then filtered through a 70 μm nylon mesh filter (BD Biosciences), centrifuged, washed, and incubated with Fc block (CD16, Thermo Fisher Scientific) for 10 minutes at 4°C. LiveDead™ (Invitrogen™) was used for dead cell exclusion. Single cell suspensions were stained with fluorochrome-conjugated antibodies and analyzed using a CytoFLEX (Beckman Coulter). Antibodies and secondary reagents were titrated to determine optimal concentrations. BD™ CompBeads were used for single-color compensation to create multi-color compensation matrices. Data was analyzed using FlowJo 10.8 (BD Biosciences). Antibodies used for flow cytometry can be found in Supplementary Table S1. Histologic and Multiplex Immunofluorescence Staining Whole tumors and endpoint MMTV-PyMT mouse lung tissue were harvested immediately following euthanasia and placed in 10% neutral buffered formalin (NBF) for 24-48 hours followed by 70% ethanol for paraffin embedding. Formalin-fixed, paraffin-embedded (FFPE) sections of 3- 5 µm thickness were baked for 30 min at 60°C and processed for immunohistochemical (IHC) and immunofluorescent (IF) staining. Opal™ Fluorescent Automation IHC Kits (Akoya Bioscience) were used on FFPE tissue according to the manufacturer’s instructions. FFPE tissue slides were stained using a Leica Bond RX autostainer and coverslipped using ProLong Diamond Antifade Mountant (Invitrogen). Antibodies used for histology can be found in Supplementary Table S2. Digital pathology image analysis IHC and IF slides were scanned using a Zeiss AxioScan Z1 whole slide scanner. Multiplex stained slides were scanned in their entirety using a 20x objective lens. Digital image analysis was performed using HALO® Imaging Analysis platform v3.5 (Indica Labs). A HALO® random forest classifier was used to train a classifier to segment epithelial, stromal, or necrotic tumor regions on H&E-stained whole tumor scanned slides (LL/2 and MMTV-PyVT). Specifically, the classifier 59 was trained based on 5-10 manual annotations of these regions. The classifier was visually and iteratively improved to prevent any inaccurate classification by manually adding additional training examples as needed. A HALO® AI DenseNet v2 classifier was trained to detect metastasis in lung tissue. Whole slide images taken every 20 µm of the entire lung were first annotated to exclude non-lung tissue (esophagus, thyroid, bronchial lymph nodes). Subsequent classified regions were validated by two board-certified veterinary pathologists in consensus. The percentage of each measure (tumor to lung ratio) was determined by dividing the total area classified as tumor by total area classified as lung. The HALO® High-Plex FL algorithm was used to analyze fluorescent cells and colocalization of markers. Thresholds of each stain were set using the real-time tuning window. User-defined cell phenotypes were created to make the algorithm quantify single, double, or triple positive cells. Cell segmentation was performed with the help of multiple parameters including minimum nuclear intensity, nuclear contrast threshold, and nuclear and membrane segmentation aggressiveness. Cell phenotype used to create heat maps was defined based on the antigen expressions as the following: DAPI+FAP+ = FAP+ cell, DAPI+PDPN+ = PDPN+ cell, DAPI+CD8+ = CD8+ T cell. To assess the validity of the unsupervised cell phenotyping algorithm, random areas were selected for manual visual counting of positive cell numbers. 60 Statistical Analysis Graphing and statistical analyses were carried out using GraphPad Prism 9 (GraphPad Software). P-values were calculated using two-tailed Student’s t-test when comparing two experimental groups, or one-way ANOVA when comparing more than two experimental groups. Parametric or non-parametric tests were applied accordingly. Error bars represent standard error of the mean unless specified in the figure legends. Asterisks indicate significant differences between experimental groups (* P value < 0.05, ** P value < 0.01, *** P value < 0.001) and N.S. = no statistically significant difference. Figures and schematics were created using BioRender (Biorender.com). 61 RESULTS CAFs are present in the TME across several tumor models at steady state. As CAFs are known to be variably abundant in syngeneic murine cancer models, we first examined the expression of five commonly reported CAF markers [42], including FAP, α-SMA, Podoplanin (PDPN), platelet derived growth factor receptor alpha (PDGFR-α) and platelet derived growth factor receptor beta (PDGFR-β) on seven murine cancer cell lines, EL-4, MC38, EO771, PAN02, LL/2, MOC2, 4T1 in vitro (Figure S1A-B). All cell lines examined highly expressed α-SMA. FAP and PDPN expression was low to absent. Among these cell lines, LL/2, 4T1 and MC38 demonstrated a steady subcutaneous tumor growth in mice (data not shown). To optimize downstream experiments, these three murine tumor models were compared for presence of the immunosuppressive CD45-α-SMA+FAP+ CAF subtype [43, 44]. Flow cytometry analysis indicated the highest frequency of the CD45-α-SMA+FAP+ fraction in the LL/2 tumor model compared with 4T1 and MC38 tumors (Figure 2A-B). Histological analysis of the LL/2 tumors confirmed the presence of α-SMA+ and FAP+ cells (Figure 2C), and a heat map analysis showed FAP+ cells were concentrated predominantly at the stromal margin near the tumor invasive front (Figure 2C). Because growth of subcutaneously inoculated tumors is more rapid than naturally occurring cancers, which affects CAF development and distribution, we performed similar expression analysis on a genetically engineered mouse model (GEMM) of spontaneous mammary cancer, the MMTV-PyVT mouse [38, 39]. Mammary tumors in these GEMMs have similar characteristics to human breast carcinoma including tumor progression [45] and CAF subsets [46]. Histologically, the MMTV-PyVT tumors also had high prevalence of α-SMA+FAP+ cells at the tumor periphery 62 (Figure S2A). We further analyzed Ki67 expression and found that these cells demonstrated Ki67+ staining, indicating their active proliferation (Figure S2B). Anti-FAP-IR700 NIR-PIT induces cell death of FAP expressing fibroblasts in vitro. To test the efficacy of anti-FAP NIR-PIT, we next performed depletion of FAP+ cells in vitro. Murine fibroblasts (NIH3T3) were stimulated with TGF-β to induce FAP expression [47, 48]. NIH3T3 cells upregulated FAP+ in a TGF-β dose-dependent manner observed via flow cytometry analysis (Figure 3A). In vitro anti-FAP NIR-PIT targeting of FAP-induced NIH3T3 cells resulted in decrease of live cells dependent on NIR light intensity (Figure 3B), confirming the efficacy of anti-FAP NIR-PIT. Based on these results, we chose 50J of NIR light exposure for subsequent in vivo PIT experiments. Anti-FAP NIR-PIT suppresses tumor growth and lung metastasis in vivo. In vivo anti-FAP NIR-PIT was performed in two murine tumor models, one subcutaneously inoculated (LL/2) and one spontaneously developed (MMTV-PyVT) to evaluate therapeutic efficacy on tumor growth. In both models, tumor-bearing mice were administered anti-FAP-IR700 conjugate (Day -1), NIR-PIT performed 24 hours later (Day 0), and tumors measured for 10-30 days until endpoint (Figure 4A). Anti-FAP NIR-PIT significantly suppressed LL/2 tumor growth compared with an anti-FAP Ab alone, rat IgG1 isotype control plus NIR-PIT light exposure, or an untreated control group (Figure 4B). Similarly, MMTV-PyVT tumor growth was significantly suppressed in the anti-FAP NIR-PIT group compared with an anti-FAP Ab alone, or an untreated control group (Figure 4C). Digital image analysis to segment tumor regions (as tumor, stroma, necrosis, muscle, skin or glass) was performed on H&E-stained scanned sections of MMTV-PyVT control and anti-FAP NIR-PIT treatment groups using a random forest classifier. Average stromal area (total stromal area divided by total classified area) was reduced by approximately 50% at 24 63 hours post NIR-PIT compared to untreated controls (Figure 4D). Moreover, in contrast to the multiple lung metastasis observed in untreated MMTV-PyVT tumors, lung metastasis was significantly reduced in the anti-FAP NIR-PIT group (Figure 4E). Anti-PDPN-IR700 NIR-PIT induces cell death of PDPN expressing fibroblasts in vitro, but did not suppress tumor growth in vivo. In addition to FAP, a second CAF marker, Podoplanin (PDPN), was tested for efficacy as an anti- CAF NIR-PIT target. As with FAP, PDPN expression increased on NIH3T3 cells in vitro after stimulation with TGF-β (Figure S3A). Anti-PDPN NIR-PIT demonstrated killing of NIH3T3 cells compared to untreated control cells (Figure S3B). PDPN expression levels varied among tumor types in vivo (Figure S3C) with highest expression in MOC2 tumors but absent in MOC2 tumor cells. PDPN-expressing cells were observed predominantly at the tumor periphery, near the invasive front (Figure S3D). Anti-PDPN NIR-PIT was performed on mice inoculated with subcutaneous MOC2 tumors, however, no difference in tumor growth was observed between the anti-PDPN NIR-PIT group, anti-PDPN Ab alone, or an untreated control group (Figure S3E). Anti-FAP NIR-PIT increases immune effector cells and their IFN-γ expression in the tumor microenvironment. To understand how tumor growth suppression was occurring, the frequency of key anti-tumor effector cells cytotoxic CD8+T and natural killer (NK) cells, as well as their IFN-γ production was measured within the tumor. As the primary anti-tumor effector cells, CD8+T and NK cells were enumerated in the tumor before and 24h after anti-FAP NIT-PIT. Flow cytometry showed an increase in frequency of CD8+ T cells after anti-FAP NIR-PIT for both LL/2 (Figure 5A). and MMTV-PyVT tumor models (Figure 5B). Multiplex immunohistochemistry revealed distribution of CD8+ T cells 24h after anti-FAP NIT-PIT was particularly increased in stromal regions 64 compared to untreated controls (Figure 5C). To examine IFN-γ production, ‘GREAT’ eYFP-IFN- γ reporter mice were inoculated with LL/2 tumors and analyzed for the induction of eYFP signal in intratumoral CD8+T and NK cells by flow cytometry. As early as 3h after treatment, CD8+ T cells and NK cells began to express eYFP, indicating activation of these anti-tumor effector cells and production of IFN-γ (Figure 5D). eYFP positivity in CD8+ T and NK cells increased from 3h to 24h (Figure 5D-E), suggesting IFN-γ production continues at least up to 24 hours after anti- FAP NIR-PIT. Because eYFP protein can remain within a cell after IFN-γ is no longer produced, it is difficult to determine the true peak of IFN-γ production using the GREAT eYFP mouse model (Figure S4). 65 Depletion of FAP+ hematopoietic cells contributes to tumor growth suppression. Flow cytometry characterization of the FAP+ population using GFP mice inoculated with LL/2 tumors demonstrated that many endogenous FAP+ cells also expressed CD45 (Figure 6A), a pan- leukocyte marker. Additional analysis of this FAP+CD45+ population in anti-FAP NIR-PIT treated LL/2 tumors suggested that FAP + macrophages (CD45+Ly6CintF4/80hi), circulating monocytes (CD45+Ly6ChiF4/80int), and resting monocytes (CD45+Ly6CloF4/80int), were depleted 1h after anti-FAP NIR-PIT (Figure 6B). To determine whether the tumor suppressive effect observed with anti-FAP NIR-PIT was due to ablation of FAP+CD45- mesenchymal stromal cells or FAP+CD45+ hematopoietic cells, a series of FAP-TK bone marrow chimeras were generated to allow for selective FAP+ cell depletion of either stromal or hematopoietic cells. GCV treatment depleted FAP+ cells in LL/2 tumors in FAP-TK mice (Figure S5A). Reconstitution of bone marrow by recipients was confirmed to be >95% by flow cytometry analysis using Ly5.1 and Ly5.2 congenic markers (Figure S5B). Generated bone marrow chimeras and control FAP-TK or wild type mice received 4 doses of 100 mg/ kg GCV intraperitoneal injections every 12 hours (Figure 6C). In the chimeras, GCV treatment selectively depleted actively dividing FAP+ cells in either the stromal (when FAP-TK mice were recipients) or hematopoietic compartments (when bone marrow from FAP-TK mice were transferred as donor bone marrow). Suppression of tumor growth was observed for the LL/2 stromal FAP+ depletion group (Ly5.1  FAP-TK) and, to a lesser extent, for the hematopoietic FAP+ depletion group (FAP-TK  Ly5.1) compared with PBS injected controls (Figure 6D). Tumor suppression was also observed for the MMTV-PyVT hematopoietic FAP+ depletion group (FAP-TK  MMTV) compared with a bone marrow transfer control group (Ly5.1  MMTV) receiving GCV, and an untreated control group (Figure 6E). This data indicates that depletion of FAP+ CAFs or FAP+ 66 hematopoietic cells alone can suppress tumor growth, and suggests that the tumor suppression of anti-FAP NIR-PIT, which depletes both the FAP+ CAFs and FAP+ hematopoietic cells, may occur through combined effects. 67 DISCUSSION In this study, we investigated the therapeutic and immune effects of FAP-targeted NIR-PIT in subcutaneously inoculated syngeneic tumor and spontaneously developing MMTV-PyVT mammary tumor mouse models. Previous studies have indicated that anti-FAP therapies such as binding of FAP‐α or blocking the enzymatic activity of FAP‐α are safe and effective in preclinical studies but do not translate into human clinical trial success [29, 49]. As NIR-PIT targeting EGFR- expressing cancer cells has been approved for use in Japan (Rakuten Medical Inc.) and currently in Phase 3 clinical trials in the US (ClinicalTrials.gov Identifier: NCT02422979) [33], there is clear safety and efficacy in using the NIR-PIT model in humans. Novel use of this established system to deplete immunosuppressive cells within the tumor has been established by targeting CD25 to deplete Treg cells [34, 50] and FAP to deplete CAFs [35, 37, 51] from the TME. As NIR light is carefully applied only at the tumor site, off-target effects are low in NIR-PIT [34, 50]. We demonstrate that local, anti-FAP NIR-PIT can successfully and selectively deplete FAP+ immunosuppressive cells, both CAFs and myeloid cells, in the TME which resulted in activation of CD8+ T and NK cells, production of IFN-γ, and suppression of tumor growth in both the subcutaneous LL/2 and spontaneous MMTV-PyVT tumors examined. Although anti-FAP NIR-PIT alone did not result in complete tumor remission, lung metastasis in MMTV-PyVT tumor mice was significantly reduced. To our knowledge, this work is the first to use anti-FAP NIR-PIT to deplete CAFFs physiologically differentiated in the TME. Moreover, our use of MMTV-PyVT mouse mammary tumors more closely mimic the human tumor microenvironment, including cellular and spatial heterogeneity, tumor growth, and CAF subsets [45]. It has been reported that higher PDPN expression is associated with poorer outcomes in human colorectal carcinomas [52] and is considered to be another promising CAF target [53]. Aside from 68 high expression on CAFs, PDPN is also highly expressed on lymphatic endothelium, both in normal tissues and during tumorigenesis. Additionally, PDPN serves important functions during development [54-56] and may not be an ideal target molecule for systemic depletion. We hypothesized that NIR-PIT could allow selective depletion of PDPN+ cells within the TME and examined the efficacy of anti-PDPN NIR-PIT in a syngeneic MOC2 tumor model. Despite being effective in vitro against murine fibroblasts (NIH3T3) with upregulated PDPN expression, anti- PDPN NIR-PIT was not successful in successfully reducing tumor volume in vivo in our study. Possible explanations include ineffective antibody distribution in the tumor, or less specificity of the PDPN-IR700 conjugate for CAFs in vivo. Taken together, from our data, we concluded that anti-PDPN NIR-PIT was a less favorable strategy for targeting CAFs compared with anti-FAP NIR-PIT. In this study, non-stromal, CD45+ cells within the tumor microenvironment expressed FAP. Our flow cytometry analysis data indicated that these FAP+CD45+ cells were likely myeloid, consistent with previous work demonstrating that macrophages, specifically M2 or tumor associated macrophages (TAMs), based on F4/80hi/CCR2+/CD206+ expression, also express FAP [57]. From our data bone marrow chimera mice, depletion of FAP+ hematopoietic cells by GCV had a suppressive tumor effect. This result supports the hypothesis that the FAP+ hematopoietic cell subset likely contributed to the total observed tumor suppression of anti-FAP NIR-PIT in non- chimeric mice. This hypothesis is also consistent with previous observations that ablation of FAP+/F4/80hi TAMs using a diphtheria toxin receptor (DTR) model results in suppression of tumor growth [57]. We observed a similar tumor suppressive effect of FAP-TK cell depletion by GCV injection between the bone marrow chimeras expressing FAP-TK in the stromal cells and the bone marrow chimeras expressing FAP-TK in the hematopoietic cell compartment. In the intratumoral 69 FAP+ cell depletion by anti-FAP NIR-PIT, it is likely that depletion of the stromal cells (CAFs) and that of hematopoietic FAP expressing cells (myeloid cells) both contributed to the observed therapeutic effect. This highlights a strength of anti-FAP NIR-PIT in targeting different immunosuppressive cell types in the TME with one treatment. A limitation to the chimera models using the FAP-TK/GCV system was toxicity of ganciclovir. To achieve FAP depletion in the FAP-TK chimeras, a near-toxic systemic dose (100 mg/kg IP twice daily for two days) was used, which likely caused off-target effects. Some studies have reported that systemic depletion of FAP+ cells induces bone marrow hypocellularity, anemia and cachexia in mice [58, 59]. With the dose of GCV used in our study, we cannot exclude the possibility of inducing some off-target effects in GCV-treated mice. In summary, this work provides evidence to support anti-FAP NIR-PIT as a viable method for depletion of immunosuppressive CAFs. The selective depletion of FAP+ cells using NIR-PIT successfully suppressed tumor growth in subcutaneous mouse tumor model and lung metastasis in a spontaneous mouse mammary tumor model. 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Following FAP+ NIR-PIT depletion, immunosuppression is decreased, and key anti-tumor immune cells (CD8+T and NK) are activated. 78 Figure S1. Tumor cell expression of CAF markers in vitro. Flow cytometry analysis of expression of five major CAF markers in murine tumor cell lines expressed as total percent frequency of live cells (A-B). FAP: fibroblast activation protein; SMA: alpha smooth muscle actin, PDPN: Podoplanin, PDGFR-α: platelet derived growth factor receptor alpha; PDGFR-β: platelet derived growth factor receptor beta. Data represent n=3 replicates per group. 79 Figure 2. CAFs are present in the TME across several tumor models at steady state. Representative flow cytometry plots comparing CAF subset marker expression in three murine tumor types (A) Frequency of SMA+FAP+ CAFs analyzed in (A) demonstrate significantly high CAF frequency in LL/2 tumors than the others (B). Data represent n=3 replicates per group. Means ± SEM are shown. p-values calculated using one-way ANOVA, *** p < 0.001, ns = not significant. Representative immunofluorescent image of an LL/2 tumor shows expression of the activated fibroblast markers α-SMA and FAP and generated heat map of FAP expression (C). Nuclei were counterstained with DAPI. Stromal boundary is represented by yellow line and tumor invasive front by red line. 80 Figure S2. CAFs are present in the MMTV-PyVT TME at steady state. Immunofluorescent histology of cancer-associated fibroblast (CAF) subset marker expression in the MMTV-PyMT tumor model at steady state (A-B). Representative images show expression of the activated fibroblast markers α-SMA (pink) and FAP (green), α-SMA and FAP co-expression (purple arrowheads) proliferative marker Ki67 (white; white arrowheads) and endothelial marker CD31 (red). Nuclei were counterstained with DAPI (blue). Stromal boundary represented by dashed yellow line and tumor invasive front by solid red line. 81 Figure 3. Anti-FAP NIR-PIT induces cell death of FAP+ expressing fibroblasts in vitro. Flow cytometry analysis of NIH3T3 cell stimulation with TGF-β expressed as total percent frequency of Live, FAP+ cells (A) and flow cytometry analysis of anti-FAP NIR-PIT in vitro expressed as total percent frequency of Live, FAP+ cells (B). Data represent n=3-4 replicates per group. Means ± SEM are shown. p-values calculated using one-way ANOVA, * p < 0.05, ns = not significant. 82 Figure 4. Anti-FAP NIR-PIT suppresses tumor growth and lung metastasis in vivo. Experimental timeline for in vivo NIR-PIT experiments (A). Experimental group mice were administered an intravenous injection of either unconjugated anti-FAP (Ab only), rat IgG1-IR700 (isotype control; rat IgG1 + NIR-PIT) or anti-FAP IR700 (anti-FAP + NIR-PIT) at Day -1, and both isotype control and anti-FAP groups were administered 50J NIR light exposure at 24h post- injection (Day 0). Tumor volume growth curve for LL/2 (inoculated) tumor experiment (B) and MMTV-PyVT (spontaneous) tumor experiment (C). Data presented as mean ± SEM. n=5-6 per group. p-values calculated using one-way ANOVA, *** p < 0.0001. H&E sections with analysis markup from random forest classified tissue regions for LL/2 control and anti-FAP NIR-PIT treatment groups (D). H&E sections with AI classified endpoint lung metastasis for MMTV-PyVT control and anti-FAP NIR-PIT treatment groups (E). Lung metastasis n=6 per group. p-values calculated using student’s t-test (two-tailed), * p < 0.05, ns = not significant. 83 Figure S3. Anti-PDPN NIR-PIT depletes PDPN+ cells in vitro but did not suppress tumor growth in vivo. Flow cytometry analysis of NIH3T3 cell stimulation with TGF-β expressed as total percent frequency of Live, PDPN+ cells (A) and flow cytometry analysis of anti-FAP NIR-PIT in vitro expressed as total percent frequency of Live, PDPN + cells (B). Data presented as mean ± SEM. n=3 per group. Flow cytometry analysis of total percent frequency of Live, PDPN + cells within MC38, LL/2 tumors and MOC2 tumors compared with MOC2 tumor cells (C). Representative image and generated heat map of PDPN expression in the MOC2 tumor model at steady state (D). Nuclei were counterstained with DAPI. Tumor volume growth curve for MOC2 (inoculated) tumor experiment (E). Experimental group mice were administered an intravenous injection of either unconjugated anti-PDPN (Ab only), or anti-PDPN IR700 (anti-PDPN + NIR-PIT) and the anti- PDPN IR700 group was administered 50J NIR light exposure at 24h post-injection. Data presented as mean ± SEM. n=4-6 per group. p-values calculated using student’s t-test (TGF-β stimulation) or one-way ANOVA (in vitro NIR-PIT and tumor growth curve), * p < 0.05, ** p < 0.005, ns = not significant. 84 Figure 5. Anti-FAP NIR-PIT increases immune effector cells and IFN-γ in the TME. Flow cytometry analysis of CD3+CD8+ T and CD3-NK1.1+ cells and 24h after anti-FAP NIT-PIT (A-B). Multiplex immunohistochemistry of CD8+ T cells 24h after anti-FAP NIT-PIT (C). Flow cytometry analysis of eYFP-IFN-γ reporter mouse CD8+T and CD3-NK1.1+ cells in LL/2 tumors at representative time points (3h, 24h) (D) Endogenous IFN-γ (IFN-γ-eYFP) production by CD3- NK1.1+ cells and CD3+CD8+ T cells from 0h to 24h (E). Data presented as mean ± SEM. n=3-5 per group. 85 Figure S4. Mechanism of IFN-γ eYFP timecourse The interferon gamma (IFN-γ) eYFP fluorescent reporter mouse produces eYFP as endogenous IFN-γ is produced. However, there is likely a discrepancy between eYFP signal, which is measured via flow cytometry, and true IFN-γ (unmeasured) due to the longer half-life of eYFP. 86 Figure 6. Depletion of FAP+ hematopoietic cells contributes to tumor growth suppression. Flow cytometry analysis of Live+GFP+FAP+SMA+ population, Live+GFP+CD45-FAP+SMA+ population (CAFs) and Live+GFP+CD45+FAP+SMA+ (leukocyte) population of LL/2 tumor (A). Histograms of Live+CD45+FAP+ macrophage population, circulating monocyte population and resting monocyte population of LL/2 tumor control (black line) of 1h after anti-FAP NIR-PIT depletion (blue line) (B). Bone marrow chimera experimental groups and experimental timeline for ganciclovir administration (C). Tumor growth curves for MMTV-PyVT chimera experimental groups (D) and LL/2 chimera experimental groups (E). Solid red line represents hematopoietic FAP+ depletion, solid purple line represents stromal FAP+ depletion. PBS = Phosphate Buffered Saline, GCV = Ganciclovir, FAP-TK = Fibroblast Activation Protein Thymidine Kinase. 87 Figure S5. Validation of FAP+ depletion in FAP-TK mice and bone marrow chimera mouse models. Representative histogram showing depletion of Live+FAP+ cells following ganciclovir administration in FAP-TK LL/2 tumor mouse via flow cytometry analysis (A). Data represents n=3 replicates. Chimera recipients were confirmed to have reconstituted >95% donor marrow using Ly5.1/Ly5.2 flow cytometry analysis on peripheral blood samples taken at least six weeks after bone marrow transfer (B). Data represent n=6-10 replicates per group. FAP-TK = Fibroblast Activation Protein Thymidine Kinase, WT= wild type. 88 Table S1: Antibodies used for flow cytometry Reagent Mouse anti-mouse FAP (clone 73.3) Source Sigma Identifier MABC1145 Rat anti-mouse FAP (clone 983802) R&D Systems AB9727 Mouse anti-mouse α-SMA-PE (clone 1A4) Novus NBP2-34522PE Mouse anti-mouse α-SMA-FITC (clone 1A4) Sigma Armenian Hamster anti-mouse CD3-BV421 (clone 145-2C11) Anti-mouse CD8a-PECy5 (clone 53-6.7) Rat anti-mouse CD11b-PECy7 (clone M1/70) Biolegend Thermo Fisher Scientific eBioscience F3777 100336 15-0081082 25-0112-82 Rat anti-mouse polyclonal CD16 Biolegend 101301 Mouse anti-mouse CD45.1-FITC (clone: A20) Thermo Fisher Scientific Thermo Fisher Scientific Mouse anti-mouse CD45.2-BV 650 (clone: 104) Biolegend Mouse anti-mouse CD45.2-PE (clone: 104) 11-0453-85 12-0454-83 50-402-986 Rat anti-mouse F4/80-APC Biolegend 123116 LiveDead Fixable Viability Dye eFlour™ 455 UV Rat anti-mouse Ly6C PE (clone: HK1.4) Syrian Hamster anti-mouse PDPN-PE Cy7 (clone 8.1.1) Rat anti-mouse PDGFR-α-Super Bright ™ 600 (clone APA5) Rat anti-mouse PDGFR-β-PE (clone APB5) Mouse anti-mouse NK1.1-PE (clone: PK136) Thermo Fisher Scientific Thermo Fisher Scientific Biolegend Thermo Fisher Scientific Thermo Fisher Scientific Thermo Fisher Scientific 65-0868-14 12-5932-82 25-5381-82 63-1401-82 14-1402-81 12-5941-83 89 Table S2: Antibodies used for histology Reagent Rabbit polyclonal anti-mouse FAP Source Abcam Rabbit anti-mouse α-SMA (clone EPR5368) Rabbit polyclonal anti-mouse CD3e Abcam Thermo Fisher Scientific Cell Signaling Rabbit anti-mouse CD8a (clone D4W2Z) Rat anti-mouse CD8a (clone C8/144B) Rabbit anti-mouse CD31 (clone D8V9E) Rabbit anti-mouse CD45 (clone D3F8Q) Rabbit anti-mouse Ki67 (clone SP8) Cell Marque Invitrogen Cell Signaling Cell Signaling Identifier 218164 Ab124964 PA1-29547 989415 MA5-13473 77699S 70257S 275R Rabbit anti-mouse Podoplanin (clone 66) Invitrogen MA5-29742 90 FUNDING This research was supported by the Intramural Research Program of the National Institutes of Health, National Cancer Institute, Center for Cancer Research (ZIA BC 010656 and ZIA BC 010657). RG is a Molecular Pathology Fellow in the NIH Comparative Biomedical Scientist Training Program supported by the National Cancer Institute in partnership with Michigan State University. 91 CHAPTER 3 CONCLUSIONS AND FUTURE DIRECTIONS 92 CONCLUSIONS AND FUTURE DIRECTIONS Cancer associated fibroblasts (CAFs) comprise a majority of the stromal cellular compartment in solid tumors, and serve significant functions in immunosuppression, invasion, and angiogenesis. One of the greatest challenges in targeting CAFs is the lack of a pan-specific biomarker as CAFs often express variable phenotypes across tumor and tissue types. As reviewed in Chapter 1, high expression of fibroblast activation protein (FAP) by CAFs is a negative prognostic indicator, and promising intratumoral target as it is most often expressed by immunosuppressive CAFs in several cancers. FAP itself also directly supports tumor growth, invasion, and metastasis as a through extracellular matrix remodeling [1]. We also observed expression of FAP in several murine cancer models examined. Therefore, we chose to use FAP as a CAF target for NIR-PIT. We chose two models, one subcutaneously inoculated (LL/2), one spontaneously occurring with frequent lung metastasis (MMTV-PyVT) to test this therapy. To our knowledge, this work is the first to use anti- FAP NIR-PIT entirely in vivo in an immunocompetent host, as well as the first within a spontaneous mouse tumor model. As discussed in Chapter 2, our bone marrow chimera modeling sought to untangle the contribution of stromal versus hematopoietic FAP-expressing cells. Although we observed a measurable effect from depletion of the FAP+ hematopoietic cells, additional work is required for more meaningful conclusions, as well as fully quantify the contribution of the FAP+ hematopoietic cell compartment towards tumor regression. We were also unable to see a measurable distinction between anti-PDPN NIR-PIT treated MOC2 tumor mice and controls. Because this was effective in vitro against murine fibroblasts (NIH3T3) with upregulated PDPN expression, this experiment might be considered for re-evaluation to increase antibody distribution in the tumor, or improving specificity 93 of the PDPN-IR700 conjugate for CAFs in vivo by increasing PDPN concentration bound to IR700, or considering alternative murine tumors which may express PDPN more highly. One limitation of NIR-PIT is that NIR light at a wavelength of 690 nm can penetrate and treat cancers at a maximum depth of approximately 1 cm. For our experiments, tumors were present in the subcutis or mammary gland in a mouse model. In clinical applications, for example, fibrotic tumors e.g. hepatocellular carcinoma, pancreatic or colon cancers, NIR light delivered through a catheter needle or endoscope [19, 20] can expand its use on these deeper tumors and also metastatic lesions. It is also possible that additional round(s) of PIT dose could improve tumor efficacy even further. A second round of NIR-PIT could be repeated to prevent tumor regrowth, which occurs months or years later in human patients, in contrast to the experimental mouse tumor models [5]. While much of our knowledge about CAF biology has come from in vitro modeling, it has been repeatedly demonstrated that CAFs in culture do not fully recapitulate the heterogeneity of CAFs in vivo [2-4]. Despite the popularity of human xenografts, immune compromised mice are unable to mount a comprehensive immune response. Moreover, in these models, human cells grow within a murine tumor microenvironment which raises the issue of species incompatibilities and a foreign murine microenvironment. While convenient, co-transplant of human stromal cells (fibroblasts) also do not accurately represent tumor progression or recapitulate metastasis [5]. Preclinical work in immune-competent tumor models including genetically engineered mouse models (GEMM), is critical for insight into clinically relevant cancer biology and CAF ecology in the context of the tumor microenvironment. To this end, we employed the MMTV-PyVT GEMM to evaluate the effects of FAP+ depletion using NIR-PIT. The KPC mouse, a spontaneous model of pancreatic ductal adenocarcinoma, could also be considered for future work examining the effects of FAP+ depletion, as it is a highly stromagenic cancer [6]. Possible targets which overlap between the 94 MMTV-PyVT GEMM and the KPC GEMM include FAP and PDGFR-α, which would require minimal changes from the already established protocols and analysis methods described here. Other Applications for anti-CAF NIR-PIT NIR-PIT is established as an innovative, safe, and effective tool, which can be used as a single or combination therapy aimed at restoring anti-tumor immunity. NIR-PIT offers a minimally invasive method whereby the antibody conjugate is administered systemically, but only activated at sites where target cells are bound and exposed to NIR light; both conditions need to be met for effective target killing. In addition to its therapeutic use, anti-FAP NIR-PIT could potentially expand our understanding of CAF biology through tumor progression at various stages of tumor development. Unlike tumor-specific antigens used in NIR-PIT, anti-FAP NIR-PIT is also more likely be effective across a range of tumors as FAP+ immunosuppressive cells are present in many tumor types [7]. In this study, the same anti-FAP IR700 conjugate was effective in both Lewis lung murine lung cancer and MMTV murine mammary cancer models. There are several potential future clinical applications to anti-CAF directed NIR-PIT. Anti-FAP NIR-PIT could be considered as an adjunctive therapy with other cancer drugs, such as cancer-cell directed treatment or immune checkpoint inhibitors. Anti-FAP NIR-PIT in combination with conventional cancer-cell directed therapies could potentially enhance the effect of NIR-PIT alone and overcome the limitations of monotherapy. In previous cancer-cell targeting NIR-PIT, a phenomenon known as the super enhanced permeability and retention (SUPR) effect was observed [8, 9]In this effect, tumors treated with NIR light undergo a rapid but significant period of increased vascular permeability after cell volume decreased, resulting in enhanced delivery of nano-sized therapeutic agents. By eliminating fibroblasts with anti-FAP NIR-PIT, we may see a similar phenomenon due to reduction of stromal cells in the tumor and subsequent permeability due to a 95 reduction in tumor pressure. Anti-CAF NIR-PIT could also be considered in the context of other fibrotic conditions. CAFs have been described to contribute to non-malignant disease conditions including cardiac fibrosis [10] and inflammatory bowel disease (IBD) [11] and selective depletion of these cells might help us better understand underlying the role of fibroblasts in the mechanism of disease [12]. One area of research with much recent interest is the use of FAP inhibitors (FAPi) as a PET imaging agent in cancer patients, whose tumors express FAP more highly than those in mice [13]. Radiolabeled FAPi tracers binds to FAP+ cells abundant in cancers and can deliver image- enhancing photons and/or ionizing particles directly into tumor stroma. The difference in FAPi expression between tumor stroma and normal tissue is leveraged to better distinguish the tumor from surrounding structures in imaging. Data from this emerging field is limited [14-16] yet highly promising [17], particularly in the detection of peritoneal ovarian and gastric carcinomatosis [18] FAPi PET to might also be beneficial for future diagnostics and identification of human cancer patients who might benefit from anti-FAP therapy. CAFs not a uniform population of cells, as they may be derived from several different cell types which can express other target markers depending on cell origin and tumor type. Although FAP and PDPN were used in targeting CAFs in our study, other tumor models expressing alternative immunosuppressive CAF markers such as PDGFR-α may also demonstrate efficacy in the NIR- PIT system. In this system, any antibody which can be successfully conjugated to IR700 and bind a target cell efficiently could potentially be investigated as a CAF-directed NIR-PIT therapy. The in vitro NIR-PIT modeling system using TGF-β stimulated NIH3T3 cells described in this work is also a valuable tool to quickly assess future CAF targets for efficacy. This system requires very few resources, outside of high quality and concentration antibody, IR700 photoactive dye, 96 NIR light and the target cells. As the quality and number of CAF-directed antibodies increases, this assay provides an excellent screening mechanism for additional CAF-directed NIR-PIT models. In summary, CAF targeting using anti-FAP NIR-PIT is a highly promising therapy. Recent research in the biology of CAFs in human tumors, as well as FAPi imaging field showing patient tumors expressing high levels of FAP [13] is further encouraging, as this therapy could demonstrate even more benefit in the human cancer clinical setting than preclinical murine studies. 97 REFERENCES Liu R, Li H, Liu L, Yu J, Ren X. Fibroblast activation protein: A potential therapeutic 1. target in cancer. 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