FAP+ cells restrict antibody drug delivery and promote an immunosuppressive environment in head and neck squamous cell carcinoma.

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Candace Grisham, Hidenori Tanaka, Ashtyn McAdoo, Georgii Vasiukov, and 12 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6228925/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Antibody-based therapies (such as anti-EGFR and anti-PD1/L1 agents) have altered the landscape of cancer treatment to improve patient outcomes in formerly unresponsive tumor types. However, this robust response is not ubiquitous for all patients or cancer subtypes. Head and neck squamous cell carcinoma continues to have reduced response in many patient populations regardless of target expression (e.g. EGFR or PDL1). The role of microenvironmental proteins, such as fibroblast activation protein (FAP), may hold the key to improving antibody drug delivery and efficacy. We explore the role of FAP in restricting antibody drug therapies and the subsequent impact of targeting FAP to improve immunotherapy response. Methods Our study uses fluorescently- labeled panitumumab (anti-EGFR) to dissect the impact of FAP on drug delivery in HNSCC patients. Through spatial transcriptomic analysis on these patient samples, we explored the effects of FAP expression on another highly relevant subset of antibody-based drugs- immunotherapy. Based on our patient findings, we used a flank syngeneic mouse model to corroborate the role of FAP in responsive (MOC1) and unresponsive (MOC2) tumor types. Our work culminated in a therapeutic proof-of concept using combination anti-FAP therapy with anti-PDL1. Results Our patient samples revealed that high FAP areas had significantly reduced panitumumab compared to regions with lower FAP expression. Furthermore, depth of penetration within tumor nest was reduced in high FAP areas. Our spatial transcriptomic analysis segmented by FAP, PanCK (tumor), and CD31 (vasculature) showed reduced immunotherapy responsiveness (via TIDE scores) in FAP segments. We confirmed that high-FAP expression was associated with reduced immunotherapy (anti-PDL1) response in our MOC2 tumor-bearing model. We also saw reduced anti-PDL1 drug delivery within MOC2 tumors. However, concurrent administration of an anti-FAP monoclonal antibody improved anti-PDL1 response and overall survival. The administration of anti-FAP agents simultaneously enhanced CD8 T cell infiltration while inducing collagen reorganization (both mechanisms previously linked to improved cancer therapeutic efficacy). Conclusion Our study used human and in vivo data to support a clinically implementable approach for improving antibody-based drug efficacy and response. These findings suggest targeting FAP improves drug penetration and alters the microenvironment to result in higher drug efficacy. Head and neck squamous cell carcinoma immunotherapy drug delivery Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Targeted antibody therapies have improved outcomes in many cancer types, but only 20–25% of patients benefit. Unfortunately, response cannot be predicted by expression of the therapeutic target (e.g. EGFR, PD-L1) or tumor-intrinsic factors, such as tumor genetics. Inadequate drug engagement with antigen is probably the largest unexplored area of resistance for antibody therapies. Both incomplete and heterogenous antibody delivery also limit drug efficacy 1 , 2 . Overcoming cancer therapeutic resistance may require developing synergistic combinations with non-overlapping toxicities to improve antibody targeting of the tumor microenvironment (TME) and increase therapeutic efficacy. Stromal cells commonly contribute to therapeutic resistance, particularly due to fibroblasts promoting tumor growth through remodeling of the extracellular matrix (ECM), secreting pro-tumor factors, and suppressing anti-tumor immune cell functions 3 . Subsets of cancer associated fibroblasts (CAFs) have been extensively characterized in multiple tumor types and found to correlate with patient response to different therapies 4 , 5 . Although the exact mechanistic substrates and pro-tumorigenic qualities of fibroblast activation protein (FAP) remain understudied, its expression is consistently linked to worse overall survival in patients with cancer 6 – 8 . FAP expression by CAFs is thought to remodel the ECM, potentially creating barriers to delivery of large molecules such as antibodies. Furthermore, FAP expression induces immunosuppressive cell phenotypes characterized by reduced CD8 + T cells and increased immunosuppressive macrophages 9 , 10 . Both mechanisms negatively impact responsiveness to antigen-targeted therapies, most notably immune checkpoint inhibitors. To inhibit growth-inducing behavior of the surrounding stroma, non-specific anti-stromal therapies have been previously tested in several studies 11 . Unfortunately, the failure of anti-fibrotic agents to enhance drug response may be a result of poor targeting or combination with other drugs that do not mutually enhance efficacy 12 . Optimal timing, dosing and drug combinations remain largely unexplored for anti-stromal agents. Anti-FAP drugs were explored as a single agent therapy in 2004 13 . They were found to be safe and minimally toxic in patients with cancer, but ineffective as a monotherapy. FAP has been shown to induce immune system suppression, suggesting that targeting FAP would facilitate immune checkpoint blockade 14 , 15 . Furthermore, FAP inhibition may promote improved delivery of antibodies by facilitating a more penetrable ECM. We sought to evaluate the relationship between FAP expression and antibody delivery in samples from patients with head and neck squamous cell carcinoma (HNSCC) and in a preclinical syngeneic mouse model. We hypothesize that FAP + cells restrict antibody drug delivery and promote an immunosuppressive environment, collectively reducing efficacy of immune checkpoint blockade. Using specimens from a clinical trial in which patients received infusions of optically-labeled anti-EGFR antibody (panitumumab), we employed spatial proteomics and transcriptomics to correlate stromal FAP with reduced antibody delivery into tumor nests. To support this correlative work, we used a mouse model to measure the effect of FAP inhibition on antibody delivery in a syngeneic mouse model of head and neck cancer. This study has widespread implications for improving immunotherapy response. Methods HNSCC Patient Samples Patient samples were obtained from two separate clinical trials (NCT04511078 and NCT02415881) with panitumumab-IRdye800 (Pan800) delivery in patients with HNSCC. After samples were processed as previously published, 16 they were cut into 5 um sections, deparaffinized, and stained with DAPI for initial drug imaging studies. Slides were scanned using an Olympus Slide Scanner VS200. Following image acquisition, the coverslip was removed using PBS, and slides were stained for markers of interest using the BondRX automated stainer. After staining was completed, the slides were scanned and analyzed on Qupath software. Tumor nests were identified on histology and outlined in Qupath (v 0.5.1). We created a specialized segmentation algorithm which was applied to create 30 µm regions of interest from the edge of the nest inward and outward. Fluorescent measurements were analyzed for each annotation. For the delineation of high and low FAP or Pan800 regions, median values were used for cutoffs. Spatial Transcriptomic Analysis NanoString GeoMX platform was used to acquire spatial transcriptomic data. A HNSCC tissue microarray was stained for PanCK, CD31, and FAP overnight. Twenty-four regions of interest were identified and subcategorized by protein expression (PanCK+, CD31+, FAP+, or pan-negative). All subsequent processing and sequencing was conducted by Technology Access Program at NanoString. Probe measurements and quality control was provided by Nanostring. Raw counts were processed using the standR package. The RNA transcription data was analyzed for tumor immune dysfunction and exclusion scores (TIDE) on the TIDE website ( http://tide.dfci.harvard.edu/ ) 17 . Cytokine activity levels for individual segments were imputed using the NIH web application Cytosig ( https://cytosig.ccr.cancer.gov/ ) 18 . All samples were normalized to average gene counts for TIDE and Cytosig analysis. Atezolizumab-IRdye800 Conjugation A mouse version of atezolizumab (anti-PD-L1) was obtained from Genentech and labeled using previously documented techniques 19 . Conjugation was executed according to the manufacturer’s instructions for IRdye800CW-NHS-Ester (LI-COR Biosciences, Inc., NE, cat. 929-70020). Briefly, anti-PD-L1 was diluted to 1mg/mL and incubated with the dye for 2 hours at room temperature in the dark. Spin columns were used for purification and removal of unbound dye. MOC1 and MOC2 Immunotherapy Model MOC1 (1x10 6 /100 µL PBS) or MOC2 (1x10 5 /100µL PBS) cells were injected into the subcutaneous flank of 6–8 week old C57BL/6 female mice after culturing in DMEM media (Thermofisher, cat. 11965118). For baseline characterization studies of MOC1 and MOC2 (e.g. PD-L1, FAP, CD8 + T cell expression), tumors were resected after reaching ≥ 150 mm 3 . Volume was calculated using L x W 2 x 0.5. In all immunotherapy efficacy studies, tumors reached 50 mm 3 before beginning any drug administrations. For drug delivery studies using anti-PD-L1-IRdye800, mice were injected with drug (10 ug/mg intraperitoneal injection) after reaching 150 mm 3 . Imaging of labeled antibodies was conducted 48 and 72 hours after initial injection, and mice were sacrificed. After harvesting the organs, ex vivo imaging (the Pearl Trilogy imaging system, LI-COR Biosciences) was obtained to determine fluorescent drug uptake. Additionally, samples were fixed in formalin and paraffin-embedded for histologic analysis. In immunotherapy response experiments, mice were given three doses of anti-PD-L1 with concurrent InVivoMab anti-mouse FAP (BioXcell, cat. BE0374) or its InVivoMab IgG1 isotype control (BioXcell, cat. BE0083) at 2.5 ug/mg after tumors were reached ≥ 50 mm 3 . All mouse experiments were approved by the Vanderbilt University Institutional Animal Care and Use Committee (IACUC) and were conducted in accordance with American Association for Laboratory Animal Science (AALAS). Immunofluorescent staining Immunohistochemical staining for CD31 and alpha-smooth muscle actin (α-SMA) was completed at Vanderbilt’s Translational Pathology Staining Resource. After 5 µm sections were prepared, samples were stained using the BondRx automatic stainer. For immunofluorescent studies involving patient samples with Pan800, slides were dewaxed, stained for DAPI, and scanned. After this initial step, coverslips were removed (soaked in PBS for 20 minutes) and multiplexing was conducted using the Opal automatic staining system according to manufacturer protocols (Akoya Biosciences, Marlborough, MA, USA, cat. NEL820001KT) 20 . The following antibodies were used: FAP (1:400, ab207178, Abcam), CD8 (1:500, ab316778, Abcam), CD68 (ab303565, Abcam), CD206 (ab64693, Abcam), COL1A1 (72026, Cell Signaling), PDL1(ab213480, Abcam). Statistical Analysis All statistical analyses were completed using GraphPad Prism version 9.0 software. For direct comparisons between two groups (e.g. MOC1 vs. MOC2 or IgG1 isotype control vs. anti-FAP), unpaired t-test was performed. For survival analysis, Kaplan-Meier analysis with log-rank test was conducted to compare experimental groups. Mice were monitored for tumor growth, mortality, and humane endpoints based on criteria delineated in IACUC-approved protocols. TCGA data and analysis was obtained from TIMER 2.0 ( http://timer.cistrome.org ). Results were deemed statistically significant if p < 0.05 (*: p < 0.05, **: p < 0.01 and ***: p < 0.001). Results Fibroblast activation protein expression is correlated to reduced antibody drug delivery. We obtained patient samples previously infused with optically labeled antibodies (NCT04511078 and NCT02415881) in order to visualize the relationship between FAP and drug distribution. Drug concentrations of panitumumab-IRdye800 (pan800) were fluorescently measured and then samples stained for FAP using the Opal staining technique (Fig. 1 A). Immunofluorescent staining identified FAP + cells heterogeneously throughout the TME (Fig. 1 B). Using automated co-localization tile analysis, we determined that areas of high drug delivery had significantly lower expression of FAP (Fig. 1 D). Furthermore, Pan800 accumulation was measured within the tumor nest at 30 um increments to assess drug penetration (Fig. 1 E). In tumor nests surrounded by lower amounts of FAP (by median), there was increased drug intensity at 30, 60, 90, and 120 um (Fig. 1 F). These results highlight the negative relationship between increased FAP expression and reduced drug accumulation, which illuminates the potential targeting of FAP for drug response. Spatial transcriptomics identifies FAP segments as poorly activated. We conducted differential gene expression analysis of human tumor samples which confirmed upregulation of stromal markers in FAP rich segments compared to PanCK and CD31 ( Supplementary Fig. 1A ). Furthermore, GO biological pathway analysis confirmed upregulation of ECM remodeling pathways in FAP positive areas (Supplementary Fig. 1B). To determine if the presence of FAP + cells correlates with immunosuppression, we used a computational analysis tool that incorporates expression signatures of T cell activity to predict immunotherapy response 21 . With our transcriptomic data, we performed TIDE analysis to determine if FAP expression correlated with reduced responsiveness to immune checkpoint blockaded or a “cold tumor” 22 . CAF populations in the TME negatively correlate to immunotherapy response 23 , 24 , and as expected, our TIDE analysis revealed a significantly higher CAF score in FAP high expression segments of the tumor (Fig. 2 A). The CD8 T cell signature revealed that FAP segments demonstrated the highest exhaustion score ( Supplementary Fig. 2A ). Our analysis also confirmed FAP expression’s positive association with CD8 T cell exclusion (Fig. 2 B ). Although FAP has previously been linked to immunosuppressive macrophage polarization, we did not see a significant increase in TAMs in FAP segments ( Supplementary Fig. 2B ). These characteristics culminated in a significantly higher tumor immune dysfunction and exclusion (TIDE) score in FAP + areas signifying reduced immunotherapy efficacy (Fig. 2 C ) . Compared to a predicted 71% and 47% segment response rate in PanCK and CD31 areas, respectively, only 27% of FAP segments are predicted to respond ( Supplementary Fig. 2C ). These data suggest FAP rich areas are less likely to respond to immunotherapy. The cytokine signaling in the tumor microenvironment is an important factor for immune cell driven response. To evaluate the signaling profile in different tumor areas, we performed a Cytosig analysis 25 . Based on prior studies, we evaluated four cytokines commonly associated with reduced immunotherapy efficacy: TGF-beta, CXCL12, IL10, and MCSF 26 – 30 . The activity levels of these four cytokines were significantly elevated in FAP segments (Fig. 2 E-H). In conjunction with our TIDE analysis, these data emphasized the immunosuppressive environment created by FAP + cells and the correlation to broader immunotherapy response. FAP expression in MOC1 and MOC2 tumors correlates to immunotherapy response Our human data suggests that FAP has a strong relationship with the tumor immune microenvironment and FAP-directed therapies could improve antibody drug delivery. To this end, we evaluated a FAP-targeting antibody to test our hypothesis in a syngeneic mouse model to trial the effects of concurrent immune-checkpoint blockade and anti-FAP therapy. We used an established mouse model the using two cell lines – one resistant to immune checkpoint inhibition (ICI) (MOC1) and one responsive (MOC2) 31 . To confirm response, we treated mice with 3 doses of mouse atezolizumab or IgG 1 control (10mg/kg) and tracked subsequent tumor growth (Fig. 3 A). MOC1 had a robust response to anti-PDL1 therapy whereas MOC 2 tumor growth was not significantly altered although both models had similar PD-L1 expression (Fig. 3 B). This result was independent of PD-L1 expression since both mouse models demonstrated similar protein expression levels ( Supplementary Fig. 3A, p = 0.08 ). Similar to our patient samples, the increased ICI responsiveness was associated with a significantly lower expression of FAP in the immunotherapy responsive MOC1 tumors (Fig. 3 C). Furthermore, CD8 T cell recruitment was reduced in the high FAP expressing MOC2 phenotype (Fig. 3 D). We assessed for disparity in drug delivery by administering a fluorescently labeled atezolizumab to mice bearing tumors of 150 mm 3 (Fig. 3 E). We confirmed tumor specific drug uptake in both models in vivo ( Supplementary Fig. 3B) and predominant tumor localization (Fig. 3 F). However, MOC2 had significantly reduced drug accumulation (Fig. 3 G). These results support our correlative findings from the patient samples and confirmed a similar relationship between FAP, drug delivery and the associated immunotherapy efficacy. Anti-FAP antibodies with Atezolizumab induces tumor responsiveness in MOC2 model. To evaluate the potential of anti-FAP therapy to improve ICB efficacy, MOC2 cells were subcutaneously injected as previously described 32 . After allowing tumors to reach 50 mm 3 , mice were treated with three doses of atezolizumab (10 mg/kg, 3x per week) in combination with either anti-FAP (FAP-i) monoclonal antibodies or non-specific IgG 1 antibodies (2.5 mg/kg) 33 . Mice treated with nonspecific control IgG 1 antibodies and atezolizumab had reduced overall survival with all mice deceased by day 18 (Fig. 4 A). Furthermore, mouse tumor volumes demonstrated a significant reduction starting at day 10 and continuing the duration of the study (Fig. 4 B). This significant improvement corresponded with increased drug accumulation in anti-FAP treated mice (Fig. 4 C), although expression levels of PD-L1 remained unchanged ( Supplementary Fig. 4A ). These results correlate with the responsive phenotype seen in MOC1 tumor bearing mice and demonstrate the synergistic effects of anti-FAP therapy with immune checkpoint blockade. To confirm the activity of the FAP antibodies, we confirmed an overall increase in COL1A1 expression and structural reorganization, similar to those previously reported in FAP-inhibited samples (Fig. 4 D, 4 E) 34 . In spite of these ECM changes, we saw no significant difference in a-SMA + cells indicating that these effects may be isolated to FAP + fibroblasts ( Supplementary Fig. 4C-D ). These data support our hypothesis that specific targeting of FAP improves antibody drug delivery and efficacy through potential ECM remodeling mechanisms. To assess other FAP-driven microenvironmental changes, we stained for vascularity, T cell, and tumor associated macrophage (TAM) markers. We saw an increase in CD31 staining and lumen vessel area which may provide an explanation for the improved drug delivery through vasculature normalization mechanisms (Fig. 4 F-H) 35 , 36 . Based on our prior knowledge of the FAP/CD8 T cell relationship, we assessed CD8 T cell infiltration following FAP treatment and found increased CD8 T cell infiltration (Fig. 4 I). An immunosuppressive macrophage phenotype has also been found to be altered by FAP expression and is implicated in reduced immunotherapy response. Our studies demonstrated that CD68 + cells and CD68+/CD206 + cells infiltration (immunosuppressive subpopulation TAM) was reduced in FAPi treated mice, however, the fraction of CD68+/CD206 + cells remained the same between the two treatment groups ( Supplementary Fig. 4F ). This FAP-immune microenvironment analysis identified t favorable changes to the environment supporting more robust immunotherapy response. These data highlight the synergistic effects and potential of dual anti-FAP/anti-PD-L1 therapy. Discussion In addition to being frontline treatment for some diseases, monoclonal antibody therapy offers many patients with cancer a therapeutic option when disease progresses despite traditional radiation therapy and/or chemotherapy. However, tumor response rates are heterogeneous and difficult to predict, including in HNSCC. Here, we evaluated poor delivery of monoclonal antibody therapy as one mechanism of reduced targeted drug efficacy 37 . In our study, we demonstrate FAP expression correlated with reduced antibody drug delivery in humans with HNSCC and improved drug delivery when FAP is inhibited in a HNSCC mouse model. Spatial transcriptomic data from patient samples and our syngeneic mouse model highlight FAP’s role in promoting an immunosuppressive TME. In the mouse model, we found co-administration of inhibitory anti-FAP antibodies and immune checkpoint blockade (anti-PD-L1) improved the response to immunotherapy in a notoriously ICI-resistant mouse model 38 , 39 . The increased responsiveness correlated with collagen reorganization, increased tumor vascularity, more CD8 + T cell infiltration, and reduced TAM recruitment. Our study builds upon previous work evaluating anti-FAP monoclonal antibodies for use in cancer treatment 40 – 43 . The role of stromal cells in the tumor microenvironment has recently garnered increasing interest 3 . Our study focused on collagen and vasculature changes, based on prior characterizations in the literature. Collagen deposition reduced therapeutic efficacy by decreasing drug distribution in a study of patients with cancer taking losartan 44 , 45 . FAP + cells have specifically been implicated in ECM reorganization to promote tumor progression by enhanced matrix accumulation and promoting a thick desmoplastic stroma 34 , 46 . Consistent with previous studies, we found that inhibition of FAP in vivo decreased alignment of collagen and reduced coherent directionality 47 . Tumor vasculature has received attention due to many of its paradoxical cancer progression mechanisms. Previous findings supported the idea that increased tumor vasculature conveys a more aggressive, metastatic phenotype 35 . However, more recent studies have focused on vessel normalization (or the transformation of vessels into more organized, open, and stable structures) as the ideal TME feature 48 . This idea arose after clinical trials with anti-VEGF agents failed to improve overall survival. 49 , 50 Although there is no literature commenting on FAP’s role in vasculature collapse, we saw a significant increase in lumen vessel area after treatment with anti-FAP antibody, consistent with improved vasculature normalization 35 . Increased vasculature collapse is a proposed mechanism of reduced drug delivery in tumor types characterized by high FAP expression 1 , 51 . In addition to the effects that tumor vasculature may have on drug delivery, these vessels serve as the highway system for infiltration of immune cells necessary for immunotherapy efficacy 52 . The presence of FAP + fibroblasts is thought to promote an immunosuppressive landscape, as evidenced by reduced infiltrating CD8 + T cells and increased immunosuppressive TAMs. From our spatial transcriptomic samples, we assessed cytokine activity levels with Cytosig 25 . We focused on cytokines linked to reduced immunotherapy response. IL10 and TGF-beta were elevated in FAP-rich segments. CAF expression of these cytokines has been linked to accumulation of protumor macrophages 53 . Macrophage colony stimulating factor is also secreted by CAFs, promoting immunosuppressive macrophage polarizations 14 . Others have shown that FAP + cells can secrete CXCL12, leading to exclusion of CD8 + T cells and potentially limiting immunotherapy effectiveness 54 . In our study, high CXCL12 activity scores were co-located with FAP-rich segments on spatial transcriptomic analysis. This was further corroborated by the improvement in CD8 + T cell infiltration in our mouse models with anti-FAP therapy. The infiltration of CD8 + T cells is a key TME change which improves immunotherapy response and serves a positive prognostic factor for HNSCC patients 55 – 57 . Furthermore, developing evidence supports a role for TAMs in immunotherapy response 58 . Cancer associated fibroblasts have a unique relationship with TAMs and commonly induce phenotypic shifts toward an immunosuppressive phenotype 15 . Additionally, specific targeting of FAP has been shown to reduce M2 or immunosuppressive macrophage phenotypes 59 . Our immune studies from both patient samples and in vivo mouse models highlights the complex relationship and impact that FAP + cells have on the immune microenvironment, which ultimately culminates in reduced immunotherapy response in HNSCC. Anti-FAP monoclonal antibodies have been used in clinical trials previously. These studies confirmed the safety and specificity of these antibodies 60 . However, complete or partial responses were not achieved in phase II studies 61 . At this time in the early 2000s, researchers were limited in their understanding of FAP’s mechanistic effects, especially in relation to the immune system. Furthermore, the advent of immunotherapy had not emerged. In more recent clinical trials with FAP, the focus has been on harnessing the specific targeting effects of anti-FAP molecules in PET imaging 62 . A potential theranostic (combined therapy and diagnostic tool) use is emerging for FAP-targeted radionuclides, but none of these studies pair an anti-FAP antibody with immunotherapy 63 . Our findings introduce an additional clinical use of FAP-targeted therapy with the added benefit of previously confirmed safety and specificity. Although we were able to demonstrate FAP’s ability to limit immunotherapy response in an immune competent mouse model of HNSCC, we were limited by use in a single mouse strain (C57BL/6). Furthermore, we opted for a heterotopic model rather than an oral tumor to reduce mortality and allow for larger tumor volumes for analysis. Subcutaneous models have reduced lymphatics and vasculature, which is limitation and potentially blunted drug delivery and immune cell infiltration 64 – 66 . However, this model may recapitulate less vascular sites seen in HNSCC such as the larynx which are notoriously unresponsive. Additionally, we provided evidence for the role of CD8 + T cells and immunosuppressive macrophages in FAP-rich environments, but further studies should be conducted to characterize the exhaustive and effector functions of these cells. Many of these functions could be examined with additional proteomic-level studies on both human and mouse samples. Furthermore, we focused on anti-PD-L1 therapy due to frequent therapeutic resistance observed in mouse models and patients. However, we would be remiss not to mention the potential for co-administration with anti-PD-1 therapies, which are clinically approved but display limited benefit to many patients with HNSCC 67 . Additionally, recent trials have focused on small molecule FAPi in radiomic studies, which may also offer another anti-FAP therapeutic option 68 , 69 . Our human samples provided a unique look into drug delivery and important spatial transcriptomic factors, but downstream protein analysis can be asynchronous with the RNA spatial analysis. Large scale proteomic studies, such as CODEX, may provide additional clarity on the interactions of FAP + cells in the tumor-stroma interface. The presence of FAP expression within the stroma influences collagen organization and drug delivery, while also promoting an immune suppressive environment. Extensive data supports the pro-tumor role of FAP in other tumor types (e.g., pancreatic adenocarcinoma, glioblastoma), which implies anti-FAP therapies could be applied in other tumors 68 , 70 , 71 . However, these studies have not explored the combination of anti-FAP therapy with immunotherapy. Our findings suggest that FAP-targeted therapies could be combined with immunotherapy to improve patient outcomes in FAP + cancers. Abbreviations CAF Cancer associated fibroblast cLN Contralateral lymph node ECM Extracellular matrix FAP Fibroblast activation protein FAP-i Fibroblast activation protein inhibitor HNSCC Head and neck squamous cell carcinoma ICI Immune checkpoint inhibitor iLN Ipsilateral lymph node TAM Tumor associated macrophage TIDE Tumor immune dysfunction and exclusion TME Tumor microenvironment Declarations Ethics approval and consent to participate Patient samples were obtained from ongoing clinical trials assigned to NCT04511078 and NCT02415881. Trials were approved by IRB committees at Stanford University and Vanderbilt University Medical Center (respectively) and their respective institutional Scientific Review Committees. All animal studies were approved by Vanderbilt University/ VUMC IACUC and were conducted in accordance with American Association for Laboratory Animal Science (AALAS). Consent for publication Not applicable. Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interest. Funding This work was supported by Barry Baker Biorepository Fund and two institutional training grants (T32GM007347 and T32GM152284). Authors' contributions CG, EL conceived and designed the study; HT, AM, NM, MH, SG, BB engaged in sample collection and processing of human samples; CG, AN completed spatial transcriptomics and analysis; CG, HT, AM, GV, SMAZ assisted with mouse husbandry and tissue processing; CG, HT, GV, SMAZ, CO, SG engaged in protein immunofluorescent and IHC staining and analysis; GV. developed tumor nest analysis algorithm; HT, GV, MH, VW, JC, YM, MR assisted with methodology, data analysis, and critically evaluating the study. All authors reviewed the manuscript. Acknowledgements We would like to thank all of the patients who have offered their support and participation in our clinical trials. We hope this work will continue to benefit these patients and many others in the future. References Gellerman MAFANDG. Targeted drug delivery for cancer therapy: the other side of antibodies. BioMed Cent. 2012;5(1). 10.1186/1756-8722-5-70 . Provenzano KYEGANDMCANDJZANDPP. 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Fibroblast activation protein targeted therapy using [177Lu]FAPI-46 compared with [225Ac]FAPI-46 in a pancreatic cancer model. Eur J Nucl Med Mol Imaging. 2022;49(3):871–80. 10.1007/S00259-021-05554-2 . Puré E, Blomberg R. Pro-tumorigenic roles of fibroblast activation protein in cancer: back to the basics. Oncogene. 2018;37(32):4343–57. 10.1038/S41388-018-0275-3 . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6228925","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":431468569,"identity":"9d3ccdd6-cc5e-44eb-8aa9-6293d56fd0dc","order_by":0,"name":"Candace Grisham","email":"","orcid":"","institution":"Vanderbilt University","correspondingAuthor":false,"prefix":"","firstName":"Candace","middleName":"","lastName":"Grisham","suffix":""},{"id":431468570,"identity":"4eccdecf-7394-4c0b-8cd9-5c216cb974d6","order_by":1,"name":"Hidenori Tanaka","email":"","orcid":"","institution":"Vanderbilt University Medical 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19:53:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6228925/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6228925/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":79173695,"identity":"5f1b73fc-9a03-4333-bc4f-371da340c879","added_by":"auto","created_at":"2025-03-25 09:47:10","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":502531,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFAP rich areas are correlated with reduced drug delivery. A \u003c/strong\u003eSchematic of patients sample acquisition and spatial transcriptomic analysis (made with Biorender). \u003cstrong\u003eB \u003c/strong\u003eOverview image demonstrating fibroblast activation protein is expressed in areas of reduced drug accumulation (scale bar= 800µm) . \u003cstrong\u003eC. \u003c/strong\u003eDrug accumulation is reduced as proximity to FAP is increased. \u003cstrong\u003eD. \u003c/strong\u003eIn tumor areas with high drug delivery as determined by a median cutoff (n=3 patients), there was significantly lower FAP+ expression (scale bar = 200µm). \u003cstrong\u003eE. \u003c/strong\u003eUsing a contour analysis, drug accumulation was measured from the tumor nest edge (scale bar = 100µm). \u003cstrong\u003eF. \u003c/strong\u003eAt every distance from the tumor edge, low FAP areas had higher amounts of Panitubumab-800 accumulation. All data are mean ± SEM. Significance calculated using the unpaired \u003cem\u003et\u003c/em\u003e test. *p\u0026lt;0.05, **p\u0026lt;0.01, ***p\u0026lt;0.001\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6228925/v1/ab8de5dcc5384a79142d11fb.jpg"},{"id":79173692,"identity":"15105fef-77e0-4bec-9b9d-bf26847902f3","added_by":"auto","created_at":"2025-03-25 09:47:10","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":57295,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFAP rich segments demonstrate immunosuppressive cell signatures which may reduce antibody drug response, specifically immunotherapy. A.\u003c/strong\u003e TIDE analysis of areas of interest confirmed highest CAF score in FAP rich segments. \u003cstrong\u003eB.\u003c/strong\u003e T Cell exclusion is significantly higher in areas of FAP expression. \u003cstrong\u003eC. \u003c/strong\u003eFAP regions have a significantly higher TIDE score implying reduced likelihood of immunotherapy responsiveness. \u003cstrong\u003eD. \u003c/strong\u003eSimilar to prior studies, CAFs (from FAP rich segment) are positively correlated with T cell exclusion scores (r\u003csup\u003e2\u003c/sup\u003e= 0.81, p \u0026lt;0.0001). \u003cstrong\u003e\u0026nbsp;E-H. \u003c/strong\u003eBased on previous studies, four cytokines linked to FAP driven immunosuppressive microenvironment mechanisms were evaluated and found to be significantly upregulated in FAP environments compared to predominantly tumor or vasculature segments\u003cstrong\u003e. \u003c/strong\u003eAll data are mean ± SEM. Significance calculated using the unpaired\u0026nbsp;\u003cem\u003et\u003c/em\u003e\u0026nbsp;test or a one-way ANOVA followed by post-hoc Tukey test for individual comparisons. *p\u0026lt;0.05, **p\u0026lt;0.01, ***p\u0026lt;0.001, **** p\u0026lt;0.0001\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6228925/v1/57789dc479686439b6bfa49b.jpg"},{"id":79175680,"identity":"29f0b506-6a31-416e-854f-8aa5fb3d375a","added_by":"auto","created_at":"2025-03-25 09:55:10","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":303212,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMOC1 and MOC2 syngeneic tumors have variations in immunotherapy response rates that are inversely correlated to their FAP expression . A. \u003c/strong\u003eTimeline of the immunotherapy administration for response trial, starting when tumors reach \u003cu\u003e\u0026gt;\u003c/u\u003e50 mm\u003csup\u003e3\u003c/sup\u003e. \u003cstrong\u003eB. \u003c/strong\u003eAlthough MOC1 shows a robust response to anti-PD-L1 therapy, mice inoculated with MOC2 are unresponsive to therapy. \u003cstrong\u003eC. \u003c/strong\u003e\u0026nbsp;The responsive phenotype in MOC1 parallels with reduced FAP expression compared to MOC2 tumors. \u003cstrong\u003eD. \u003c/strong\u003eIn MOC2 samples, there is a significantly reduced fraction of CD8+ T cells compared to the responsive MOC1 phenotype. \u003cstrong\u003eE. \u003c/strong\u003eTimeline of drug delivery studies, which includes administration of labeled anti-PD-L1 after tumors reach \u003cu\u003e\u0026gt;\u003c/u\u003e150 mm\u003csup\u003e3 \u003c/sup\u003eand Pearl imaging at 72 hours. \u003cstrong\u003eF. \u003c/strong\u003e\u003cem\u003eEx vivo\u003c/em\u003e fluorescent imaging of organs (including tumor, ipsilateral lymph node [iLN] and contralateral LN [cLN]) confirms highest uptake in the tumor compared to muscle controls. \u003cstrong\u003eG. \u003c/strong\u003eMOC1 tumors have significantly higher anti-PD-L1-IRdye800 present compared to MOC2 tumors of the same size (scale bar = 5 mm). Results are representative of two separate experiments. All data are mean ± SEM, n=5-8 mice/group. Significance was calculated using the unpaired\u0026nbsp;\u003cem\u003et\u003c/em\u003e\u0026nbsp;test or a one-way ANOVA followed by post-hoc Tukey test for individual comparisons.\u003cstrong\u003e \u003c/strong\u003eAll scale bars = 100 µm unless otherwise noted. *p\u0026lt;0.05 and **p\u0026lt;0.01\u003c/p\u003e","description":"","filename":"Picture3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6228925/v1/cdf3dd0548efaabd1f8794d2.jpg"},{"id":79173700,"identity":"7ddb88b7-e143-4bcb-87ac-cb11f6a46ad6","added_by":"auto","created_at":"2025-03-25 09:47:10","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":307195,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTargeting FAP alters tumor microenvironment to improve immunotherapy delivery and efficacy. A. \u003c/strong\u003eThe addition of FAPi to atezolizumab treatment improved survival by 17 days. \u003cstrong\u003eB.\u003c/strong\u003e Tumor volumes were significantly reduced starting at day 10 until the end of the study (day 18). \u003cstrong\u003eC. \u003c/strong\u003eAtezolizumab-IRdye800 has significantly improved accumulation in anti-FAP therapy samples (scale bar = 2 mm). \u003cstrong\u003eD. \u003c/strong\u003eRepresentative images of COL1A1 staining of whole samples with and without DAPI (two left panels, scale bar = 1mm) and images of the tumor border showing increased collagen disorganization with fiber analysis overlay (two right panels, scale bar = 100 µm). \u003cstrong\u003eE. \u003c/strong\u003eCOL1A1 expression and deposits is increased after FAPi treatment (scale bar = 1 mm).\u003cstrong\u003e F. \u003c/strong\u003eRepresentative images of CD31 staining in IgG (left) and FAPi (right) samples (scale bar = 200µm). \u003cstrong\u003eG. \u003c/strong\u003eThe percent of CD31+ cells (marker of tumor vasculature) is significantly elevated in FAPi samples compared to IgG isotype control. \u003cstrong\u003eH. \u003c/strong\u003eIn addition to increased overall CD31 expression, the lumen vessel area is significantly increased in anti-FAP samples. \u003cstrong\u003eI. \u003c/strong\u003eAfter FAP-inhibition, there is a signficant increase in the percent of CD8+ T cells as seen in the representative images (scale bar = 100 µm). Results are representative of two separate experiments. All data are mean ± SEM, n= 5-8 mice/group. Significance calculated using the log-rank test, unpaired \u003cem\u003et\u003c/em\u003e test, or a one-way ANOVA followed by post-hoc Tukey test for individual comparisons. *p\u0026lt;0.05 and **p\u0026lt;0.01\u003c/p\u003e","description":"","filename":"Picture4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6228925/v1/a48bef911e2a3457190c882e.jpg"},{"id":80199660,"identity":"8683d679-0cf0-421c-a5b1-e09d353447b9","added_by":"auto","created_at":"2025-04-09 06:31:51","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2162390,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6228925/v1/e5fbfaca-01d8-456c-9151-8aedd2f363f6.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"FAP+ cells restrict antibody drug delivery and promote an immunosuppressive environment in head and neck squamous cell carcinoma. ","fulltext":[{"header":"Introduction","content":"\u003cp\u003eTargeted antibody therapies have improved outcomes in many cancer types, but only 20\u0026ndash;25% of patients benefit. Unfortunately, response cannot be predicted by expression of the therapeutic target (e.g. EGFR, PD-L1) or tumor-intrinsic factors, such as tumor genetics. Inadequate drug engagement with antigen is probably the largest unexplored area of resistance for antibody therapies. Both incomplete and heterogenous antibody delivery also limit drug efficacy\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Overcoming cancer therapeutic resistance may require developing synergistic combinations with non-overlapping toxicities to improve antibody targeting of the tumor microenvironment (TME) and increase therapeutic efficacy.\u003c/p\u003e \u003cp\u003eStromal cells commonly contribute to therapeutic resistance, particularly due to fibroblasts promoting tumor growth through remodeling of the extracellular matrix (ECM), secreting pro-tumor factors, and suppressing anti-tumor immune cell functions\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Subsets of cancer associated fibroblasts (CAFs) have been extensively characterized in multiple tumor types and found to correlate with patient response to different therapies\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Although the exact mechanistic substrates and pro-tumorigenic qualities of fibroblast activation protein (FAP) remain understudied, its expression is consistently linked to worse overall survival in patients with cancer\u003csup\u003e\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. FAP expression by CAFs is thought to remodel the ECM, potentially creating barriers to delivery of large molecules such as antibodies. Furthermore, FAP expression induces immunosuppressive cell phenotypes characterized by reduced CD8\u0026thinsp;+\u0026thinsp;T cells and increased immunosuppressive macrophages\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Both mechanisms negatively impact responsiveness to antigen-targeted therapies, most notably immune checkpoint inhibitors.\u003c/p\u003e \u003cp\u003eTo inhibit growth-inducing behavior of the surrounding stroma, non-specific anti-stromal therapies have been previously tested in several studies\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Unfortunately, the failure of anti-fibrotic agents to enhance drug response may be a result of poor targeting or combination with other drugs that do not mutually enhance efficacy\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Optimal timing, dosing and drug combinations remain largely unexplored for anti-stromal agents. Anti-FAP drugs were explored as a single agent therapy in 2004\u003csup\u003e13\u003c/sup\u003e. They were found to be safe and minimally toxic in patients with cancer, but ineffective as a monotherapy. FAP has been shown to induce immune system suppression, suggesting that targeting FAP would facilitate immune checkpoint blockade\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Furthermore, FAP inhibition may promote improved delivery of antibodies by facilitating a more penetrable ECM.\u003c/p\u003e \u003cp\u003eWe sought to evaluate the relationship between FAP expression and antibody delivery in samples from patients with head and neck squamous cell carcinoma (HNSCC) and in a preclinical syngeneic mouse model. We hypothesize that FAP\u0026thinsp;+\u0026thinsp;cells restrict antibody drug delivery and promote an immunosuppressive environment, collectively reducing efficacy of immune checkpoint blockade. Using specimens from a clinical trial in which patients received infusions of optically-labeled anti-EGFR antibody (panitumumab), we employed spatial proteomics and transcriptomics to correlate stromal FAP with reduced antibody delivery into tumor nests. To support this correlative work, we used a mouse model to measure the effect of FAP inhibition on antibody delivery in a syngeneic mouse model of head and neck cancer. This study has widespread implications for improving immunotherapy response.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eHNSCC Patient Samples\u003c/h2\u003e \u003cp\u003ePatient samples were obtained from two separate clinical trials (NCT04511078 and NCT02415881) with panitumumab-IRdye800 (Pan800) delivery in patients with HNSCC. After samples were processed as previously published,\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e they were cut into 5 um sections, deparaffinized, and stained with DAPI for initial drug imaging studies. Slides were scanned using an Olympus Slide Scanner VS200. Following image acquisition, the coverslip was removed using PBS, and slides were stained for markers of interest using the BondRX automated stainer. After staining was completed, the slides were scanned and analyzed on Qupath software. Tumor nests were identified on histology and outlined in Qupath (v 0.5.1). We created a specialized segmentation algorithm which was applied to create 30 \u0026micro;m regions of interest from the edge of the nest inward and outward. Fluorescent measurements were analyzed for each annotation. For the delineation of high and low FAP or Pan800 regions, median values were used for cutoffs.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSpatial Transcriptomic Analysis\u003c/h3\u003e\n\u003cp\u003eNanoString GeoMX platform was used to acquire spatial transcriptomic data. A HNSCC tissue microarray was stained for PanCK, CD31, and FAP overnight. Twenty-four regions of interest were identified and subcategorized by protein expression (PanCK+, CD31+, FAP+, or pan-negative). All subsequent processing and sequencing was conducted by Technology Access Program at NanoString. Probe measurements and quality control was provided by Nanostring. Raw counts were processed using the standR package. The RNA transcription data was analyzed for tumor immune dysfunction and exclusion scores (TIDE) on the TIDE website (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://tide.dfci.harvard.edu/\u003c/span\u003e\u003cspan address=\"http://tide.dfci.harvard.edu/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e)\u003csup\u003e17\u003c/sup\u003e. Cytokine activity levels for individual segments were imputed using the NIH web application Cytosig (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cytosig.ccr.cancer.gov/\u003c/span\u003e\u003cspan address=\"https://cytosig.ccr.cancer.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e)\u003csup\u003e18\u003c/sup\u003e. All samples were normalized to average gene counts for TIDE and Cytosig analysis.\u003c/p\u003e\n\u003ch3\u003eAtezolizumab-IRdye800 Conjugation\u003c/h3\u003e\n\u003cp\u003eA mouse version of atezolizumab (anti-PD-L1) was obtained from Genentech and labeled using previously documented techniques\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Conjugation was executed according to the manufacturer\u0026rsquo;s instructions for IRdye800CW-NHS-Ester (LI-COR Biosciences, Inc., NE, cat. 929-70020). Briefly, anti-PD-L1 was diluted to 1mg/mL and incubated with the dye for 2 hours at room temperature in the dark. Spin columns were used for purification and removal of unbound dye.\u003c/p\u003e\n\u003ch3\u003eMOC1 and MOC2 Immunotherapy Model\u003c/h3\u003e\n\u003cp\u003eMOC1 (1x10\u003csup\u003e6\u003c/sup\u003e/100 \u0026micro;L PBS) or MOC2 (1x10\u003csup\u003e5\u003c/sup\u003e/100\u0026micro;L PBS) cells were injected into the subcutaneous flank of 6\u0026ndash;8 week old C57BL/6 female mice after culturing in DMEM media (Thermofisher, cat. 11965118). For baseline characterization studies of MOC1 and MOC2 (e.g. PD-L1, FAP, CD8\u0026thinsp;+\u0026thinsp;T cell expression), tumors were resected after reaching\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026ge;\u003c/span\u003e\u0026thinsp;150 mm\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Volume was calculated using L x W\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e x 0.5. In all immunotherapy efficacy studies, tumors reached 50 mm\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e before beginning any drug administrations. For drug delivery studies using anti-PD-L1-IRdye800, mice were injected with drug (10 ug/mg intraperitoneal injection) after reaching 150 mm\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Imaging of labeled antibodies was conducted 48 and 72 hours after initial injection, and mice were sacrificed. After harvesting the organs, \u003cem\u003eex vivo\u003c/em\u003e imaging (the Pearl Trilogy imaging system, LI-COR Biosciences) was obtained to determine fluorescent drug uptake. Additionally, samples were fixed in formalin and paraffin-embedded for histologic analysis. In immunotherapy response experiments, mice were given three doses of anti-PD-L1 with concurrent InVivoMab anti-mouse FAP (BioXcell, cat. BE0374) or its InVivoMab IgG1 isotype control (BioXcell, cat. BE0083) at 2.5 ug/mg after tumors were reached\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026ge;\u003c/span\u003e\u0026thinsp;50 mm\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. All mouse experiments were approved by the Vanderbilt University Institutional Animal Care and Use Committee (IACUC) and were conducted in accordance with American Association for Laboratory Animal Science (AALAS).\u003c/p\u003e\n\u003ch3\u003eImmunofluorescent staining\u003c/h3\u003e\n\u003cp\u003eImmunohistochemical staining for CD31 and alpha-smooth muscle actin (α-SMA) was completed at Vanderbilt\u0026rsquo;s Translational Pathology Staining Resource. After 5 \u0026micro;m sections were prepared, samples were stained using the BondRx automatic stainer. For immunofluorescent studies involving patient samples with Pan800, slides were dewaxed, stained for DAPI, and scanned. After this initial step, coverslips were removed (soaked in PBS for 20 minutes) and multiplexing was conducted using the Opal automatic staining system according to manufacturer protocols (Akoya Biosciences, Marlborough, MA, USA, cat. NEL820001KT)\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. The following antibodies were used: FAP (1:400, ab207178, Abcam), CD8 (1:500, ab316778, Abcam), CD68 (ab303565, Abcam), CD206 (ab64693, Abcam), COL1A1 (72026, Cell Signaling), PDL1(ab213480, Abcam).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eAll statistical analyses were completed using GraphPad Prism version 9.0 software. For direct comparisons between two groups (e.g. MOC1 vs. MOC2 or IgG1 isotype control vs. anti-FAP), unpaired t-test was performed. For survival analysis, Kaplan-Meier analysis with log-rank test was conducted to compare experimental groups. Mice were monitored for tumor growth, mortality, and humane endpoints based on criteria delineated in IACUC-approved protocols. TCGA data and analysis was obtained from TIMER 2.0 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://timer.cistrome.org\u003c/span\u003e\u003cspan address=\"http://timer.cistrome.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Results were deemed statistically significant if p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (*: p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, **: p\u0026thinsp;\u0026lt;\u0026thinsp;0.01 and ***: p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eFibroblast activation protein expression is correlated to reduced antibody drug delivery.\u003c/span\u003e \u003c/p\u003e \u003cp\u003eWe obtained patient samples previously infused with optically labeled antibodies (NCT04511078 and NCT02415881) in order to visualize the relationship between FAP and drug distribution. Drug concentrations of panitumumab-IRdye800 (pan800) were fluorescently measured and then samples stained for FAP using the Opal staining technique (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). Immunofluorescent staining identified FAP\u0026thinsp;+\u0026thinsp;cells heterogeneously throughout the TME (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). Using automated co-localization tile analysis, we determined that areas of high drug delivery had significantly lower expression of FAP (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD). Furthermore, Pan800 accumulation was measured within the tumor nest at 30 um increments to assess drug penetration (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE). In tumor nests surrounded by lower amounts of FAP (by median), there was increased drug intensity at 30, 60, 90, and 120 um (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF). These results highlight the negative relationship between increased FAP expression and reduced drug accumulation, which illuminates the potential targeting of FAP for drug response.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eSpatial transcriptomics identifies FAP segments as poorly activated.\u003c/span\u003e \u003c/p\u003e \u003cp\u003eWe conducted differential gene expression analysis of human tumor samples which confirmed upregulation of stromal markers in FAP rich segments compared to PanCK and CD31 (\u003cb\u003eSupplementary Fig.\u0026nbsp;1A\u003c/b\u003e). Furthermore, GO biological pathway analysis confirmed upregulation of ECM remodeling pathways in FAP positive areas (Supplementary Fig.\u0026nbsp;1B). To determine if the presence of FAP\u0026thinsp;+\u0026thinsp;cells correlates with immunosuppression, we used a computational analysis tool that incorporates expression signatures of T cell activity to predict immunotherapy response\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. With our transcriptomic data, we performed TIDE analysis to determine if FAP expression correlated with reduced responsiveness to immune checkpoint blockaded or a \u0026ldquo;cold tumor\u0026rdquo; \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. CAF populations in the TME negatively correlate to immunotherapy response \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e, and as expected, our TIDE analysis revealed a significantly higher CAF score in FAP high expression segments of the tumor (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). The CD8 T cell signature revealed that FAP segments demonstrated the highest exhaustion score (\u003cb\u003eSupplementary Fig.\u0026nbsp;2A\u003c/b\u003e). Our analysis also confirmed FAP expression\u0026rsquo;s positive association with CD8 T cell exclusion (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB\u003cb\u003e).\u003c/b\u003e Although FAP has previously been linked to immunosuppressive macrophage polarization, we did not see a significant increase in TAMs in FAP segments (\u003cb\u003eSupplementary Fig.\u0026nbsp;2B\u003c/b\u003e). These characteristics culminated in a significantly higher tumor immune dysfunction and exclusion (TIDE) score in FAP\u0026thinsp;+\u0026thinsp;areas signifying reduced immunotherapy efficacy (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC\u003cb\u003e)\u003c/b\u003e. Compared to a predicted 71% and 47% segment response rate in PanCK and CD31 areas, respectively, only 27% of FAP segments are predicted to respond (\u003cb\u003eSupplementary Fig.\u0026nbsp;2C\u003c/b\u003e). These data suggest FAP rich areas are less likely to respond to immunotherapy.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe cytokine signaling in the tumor microenvironment is an important factor for immune cell driven response. To evaluate the signaling profile in different tumor areas, we performed a Cytosig analysis\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Based on prior studies, we evaluated four cytokines commonly associated with reduced immunotherapy efficacy: TGF-beta, CXCL12, IL10, and MCSF\u003csup\u003e\u003cspan additionalcitationids=\"CR27 CR28 CR29\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. The activity levels of these four cytokines were significantly elevated in FAP segments (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE-H). In conjunction with our TIDE analysis, these data emphasized the immunosuppressive environment created by FAP\u0026thinsp;+\u0026thinsp;cells and the correlation to broader immunotherapy response.\u003c/p\u003e\n\u003ch3\u003eFAP expression in MOC1 and MOC2 tumors correlates to immunotherapy response\u003c/h3\u003e\n\u003cp\u003eOur human data suggests that FAP has a strong relationship with the tumor immune microenvironment and FAP-directed therapies could improve antibody drug delivery. To this end, we evaluated a FAP-targeting antibody to test our hypothesis in a syngeneic mouse model to trial the effects of concurrent immune-checkpoint blockade and anti-FAP therapy. We used an established mouse model the using two cell lines \u0026ndash; one resistant to immune checkpoint inhibition (ICI) (MOC1) and one responsive (MOC2)\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. To confirm response, we treated mice with 3 doses of mouse atezolizumab or IgG\u003csub\u003e1\u003c/sub\u003e control (10mg/kg) and tracked subsequent tumor growth (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). MOC1 had a robust response to anti-PDL1 therapy whereas MOC 2 tumor growth was not significantly altered although both models had similar PD-L1 expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). This result was independent of PD-L1 expression since both mouse models demonstrated similar protein expression levels (\u003cb\u003eSupplementary Fig.\u0026nbsp;3A, p\u0026thinsp;=\u0026thinsp;0.08\u003c/b\u003e). Similar to our patient samples, the increased ICI responsiveness was associated with a significantly lower expression of FAP in the immunotherapy responsive MOC1 tumors (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). Furthermore, CD8 T cell recruitment was reduced in the high FAP expressing MOC2 phenotype (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD). We assessed for disparity in drug delivery by administering a fluorescently labeled atezolizumab to mice bearing tumors of 150 mm\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e(Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE). We confirmed tumor specific drug uptake in both models \u003cem\u003ein vivo\u003c/em\u003e (\u003cb\u003eSupplementary Fig.\u0026nbsp;3B)\u003c/b\u003e and predominant tumor localization (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eF). However, MOC2 had significantly reduced drug accumulation (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eG). These results support our correlative findings from the patient samples and confirmed a similar relationship between FAP, drug delivery and the associated immunotherapy efficacy.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eAnti-FAP antibodies with Atezolizumab induces tumor responsiveness in MOC2 model.\u003c/span\u003e \u003c/p\u003e \u003cp\u003eTo evaluate the potential of anti-FAP therapy to improve ICB efficacy, MOC2 cells were subcutaneously injected as previously described\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. After allowing tumors to reach 50 mm\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e, mice were treated with three doses of atezolizumab (10 mg/kg, 3x per week) in combination with either anti-FAP (FAP-i) monoclonal antibodies or non-specific IgG\u003csub\u003e1\u003c/sub\u003e antibodies (2.5 mg/kg)\u003csup\u003e33\u003c/sup\u003e. Mice treated with nonspecific control IgG\u003csub\u003e1\u003c/sub\u003e antibodies and atezolizumab had reduced overall survival with all mice deceased by day 18 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Furthermore, mouse tumor volumes demonstrated a significant reduction starting at day 10 and continuing the duration of the study (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). This significant improvement corresponded with increased drug accumulation in anti-FAP treated mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC), although expression levels of PD-L1 remained unchanged (\u003cb\u003eSupplementary Fig.\u0026nbsp;4A\u003c/b\u003e). These results correlate with the responsive phenotype seen in MOC1 tumor bearing mice and demonstrate the synergistic effects of anti-FAP therapy with immune checkpoint blockade. To confirm the activity of the FAP antibodies, we confirmed an overall increase in COL1A1 expression and structural reorganization, similar to those previously reported in FAP-inhibited samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD, \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE)\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. In spite of these ECM changes, we saw no significant difference in a-SMA\u0026thinsp;+\u0026thinsp;cells indicating that these effects may be isolated to FAP\u0026thinsp;+\u0026thinsp;fibroblasts (\u003cb\u003eSupplementary Fig.\u0026nbsp;4C-D\u003c/b\u003e). These data support our hypothesis that specific targeting of FAP improves antibody drug delivery and efficacy through potential ECM remodeling mechanisms.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo assess other FAP-driven microenvironmental changes, we stained for vascularity, T cell, and tumor associated macrophage (TAM) markers. We saw an increase in CD31 staining and lumen vessel area which may provide an explanation for the improved drug delivery through vasculature normalization mechanisms (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF-H)\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e,\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. Based on our prior knowledge of the FAP/CD8 T cell relationship, we assessed CD8 T cell infiltration following FAP treatment and found increased CD8 T cell infiltration (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eI). An immunosuppressive macrophage phenotype has also been found to be altered by FAP expression and is implicated in reduced immunotherapy response. Our studies demonstrated that CD68\u0026thinsp;+\u0026thinsp;cells and CD68+/CD206\u0026thinsp;+\u0026thinsp;cells infiltration (immunosuppressive subpopulation TAM) was reduced in FAPi treated mice, however, the fraction of CD68+/CD206\u0026thinsp;+\u0026thinsp;cells remained the same between the two treatment groups (\u003cb\u003eSupplementary Fig.\u0026nbsp;4F\u003c/b\u003e). This FAP-immune microenvironment analysis identified t favorable changes to the environment supporting more robust immunotherapy response. These data highlight the synergistic effects and potential of dual anti-FAP/anti-PD-L1 therapy.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn addition to being frontline treatment for some diseases, monoclonal antibody therapy offers many patients with cancer a therapeutic option when disease progresses despite traditional radiation therapy and/or chemotherapy. However, tumor response rates are heterogeneous and difficult to predict, including in HNSCC. Here, we evaluated poor delivery of monoclonal antibody therapy as one mechanism of reduced targeted drug efficacy\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn our study, we demonstrate FAP expression correlated with reduced antibody drug delivery in humans with HNSCC and improved drug delivery when FAP is inhibited in a HNSCC mouse model. Spatial transcriptomic data from patient samples and our syngeneic mouse model highlight FAP\u0026rsquo;s role in promoting an immunosuppressive TME. In the mouse model, we found co-administration of inhibitory anti-FAP antibodies and immune checkpoint blockade (anti-PD-L1) improved the response to immunotherapy in a notoriously ICI-resistant mouse model\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e,\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. The increased responsiveness correlated with collagen reorganization, increased tumor vascularity, more CD8\u0026thinsp;+\u0026thinsp;T cell infiltration, and reduced TAM recruitment. Our study builds upon previous work evaluating anti-FAP monoclonal antibodies for use in cancer treatment\u003csup\u003e\u003cspan additionalcitationids=\"CR41 CR42\" citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe role of stromal cells in the tumor microenvironment has recently garnered increasing interest\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Our study focused on collagen and vasculature changes, based on prior characterizations in the literature. Collagen deposition reduced therapeutic efficacy by decreasing drug distribution in a study of patients with cancer taking losartan\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e,\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. FAP\u0026thinsp;+\u0026thinsp;cells have specifically been implicated in ECM reorganization to promote tumor progression by enhanced matrix accumulation and promoting a thick desmoplastic stroma\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. Consistent with previous studies, we found that inhibition of FAP \u003cem\u003ein vivo\u003c/em\u003e decreased alignment of collagen and reduced coherent directionality\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. Tumor vasculature has received attention due to many of its paradoxical cancer progression mechanisms. Previous findings supported the idea that increased tumor vasculature conveys a more aggressive, metastatic phenotype\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. However, more recent studies have focused on vessel normalization (or the transformation of vessels into more organized, open, and stable structures) as the ideal TME feature\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. This idea arose after clinical trials with anti-VEGF agents failed to improve overall survival.\u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e,\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003eAlthough there is no literature commenting on FAP\u0026rsquo;s role in vasculature collapse, we saw a significant increase in lumen vessel area after treatment with anti-FAP antibody, consistent with improved vasculature normalization\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. Increased vasculature collapse is a proposed mechanism of reduced drug delivery in tumor types characterized by high FAP expression\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e. In addition to the effects that tumor vasculature may have on drug delivery, these vessels serve as the highway system for infiltration of immune cells necessary for immunotherapy efficacy\u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe presence of FAP\u0026thinsp;+\u0026thinsp;fibroblasts is thought to promote an immunosuppressive landscape, as evidenced by reduced infiltrating CD8\u0026thinsp;+\u0026thinsp;T cells and increased immunosuppressive TAMs. From our spatial transcriptomic samples, we assessed cytokine activity levels with Cytosig\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. We focused on cytokines linked to reduced immunotherapy response. IL10 and TGF-beta were elevated in FAP-rich segments. CAF expression of these cytokines has been linked to accumulation of protumor macrophages\u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e. Macrophage colony stimulating factor is also secreted by CAFs, promoting immunosuppressive macrophage polarizations\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Others have shown that FAP\u0026thinsp;+\u0026thinsp;cells can secrete CXCL12, leading to exclusion of CD8\u0026thinsp;+\u0026thinsp;T cells and potentially limiting immunotherapy effectiveness\u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e. In our study, high CXCL12 activity scores were co-located with FAP-rich segments on spatial transcriptomic analysis. This was further corroborated by the improvement in CD8\u0026thinsp;+\u0026thinsp;T cell infiltration in our mouse models with anti-FAP therapy. The infiltration of CD8\u0026thinsp;+\u0026thinsp;T cells is a key TME change which improves immunotherapy response and serves a positive prognostic factor for HNSCC patients\u003csup\u003e\u003cspan additionalcitationids=\"CR56\" citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e. Furthermore, developing evidence supports a role for TAMs in immunotherapy response\u003csup\u003e\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e. Cancer associated fibroblasts have a unique relationship with TAMs and commonly induce phenotypic shifts toward an immunosuppressive phenotype\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Additionally, specific targeting of FAP has been shown to reduce M2 or immunosuppressive macrophage phenotypes\u003csup\u003e\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u003c/sup\u003e. Our immune studies from both patient samples and \u003cem\u003ein vivo\u003c/em\u003e mouse models highlights the complex relationship and impact that FAP\u0026thinsp;+\u0026thinsp;cells have on the immune microenvironment, which ultimately culminates in reduced immunotherapy response in HNSCC.\u003c/p\u003e \u003cp\u003eAnti-FAP monoclonal antibodies have been used in clinical trials previously. These studies confirmed the safety and specificity of these antibodies\u003csup\u003e\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e. However, complete or partial responses were not achieved in phase II studies\u003csup\u003e\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e. At this time in the early 2000s, researchers were limited in their understanding of FAP\u0026rsquo;s mechanistic effects, especially in relation to the immune system. Furthermore, the advent of immunotherapy had not emerged. In more recent clinical trials with FAP, the focus has been on harnessing the specific targeting effects of anti-FAP molecules in PET imaging\u003csup\u003e\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e. A potential theranostic (combined therapy and diagnostic tool) use is emerging for FAP-targeted radionuclides, but none of these studies pair an anti-FAP antibody with immunotherapy\u003csup\u003e\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u003c/sup\u003e. Our findings introduce an additional clinical use of FAP-targeted therapy with the added benefit of previously confirmed safety and specificity.\u003c/p\u003e \u003cp\u003eAlthough we were able to demonstrate FAP\u0026rsquo;s ability to limit immunotherapy response in an immune competent mouse model of HNSCC, we were limited by use in a single mouse strain (C57BL/6). Furthermore, we opted for a heterotopic model rather than an oral tumor to reduce mortality and allow for larger tumor volumes for analysis. Subcutaneous models have reduced lymphatics and vasculature, which is limitation and potentially blunted drug delivery and immune cell infiltration\u003csup\u003e\u003cspan additionalcitationids=\"CR65\" citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u003c/sup\u003e. However, this model may recapitulate less vascular sites seen in HNSCC such as the larynx which are notoriously unresponsive. Additionally, we provided evidence for the role of CD8\u0026thinsp;+\u0026thinsp;T cells and immunosuppressive macrophages in FAP-rich environments, but further studies should be conducted to characterize the exhaustive and effector functions of these cells. Many of these functions could be examined with additional proteomic-level studies on both human and mouse samples. Furthermore, we focused on anti-PD-L1 therapy due to frequent therapeutic resistance observed in mouse models and patients. However, we would be remiss not to mention the potential for co-administration with anti-PD-1 therapies, which are clinically approved but display limited benefit to many patients with HNSCC\u003csup\u003e\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e\u003c/sup\u003e. Additionally, recent trials have focused on small molecule FAPi in radiomic studies, which may also offer another anti-FAP therapeutic option\u003csup\u003e\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e,\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e\u003c/sup\u003e. Our human samples provided a unique look into drug delivery and important spatial transcriptomic factors, but downstream protein analysis can be asynchronous with the RNA spatial analysis. Large scale proteomic studies, such as CODEX, may provide additional clarity on the interactions of FAP\u0026thinsp;+\u0026thinsp;cells in the tumor-stroma interface.\u003c/p\u003e \u003cp\u003eThe presence of FAP expression within the stroma influences collagen organization and drug delivery, while also promoting an immune suppressive environment. Extensive data supports the pro-tumor role of FAP in other tumor types (e.g., pancreatic adenocarcinoma, glioblastoma), which implies anti-FAP therapies could be applied in other tumors\u003csup\u003e\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e,\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e,\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e\u003c/sup\u003e. However, these studies have not explored the combination of anti-FAP therapy with immunotherapy. Our findings suggest that FAP-targeted therapies could be combined with immunotherapy to improve patient outcomes in FAP\u0026thinsp;+\u0026thinsp;cancers.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eCAF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 539px;\"\u003e\n \u003cp\u003eCancer associated fibroblast\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003ecLN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 539px;\"\u003e\n \u003cp\u003eContralateral lymph node\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eECM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 539px;\"\u003e\n \u003cp\u003eExtracellular matrix\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eFAP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 539px;\"\u003e\n \u003cp\u003eFibroblast activation protein\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eFAP-i\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 539px;\"\u003e\n \u003cp\u003eFibroblast activation protein inhibitor\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eHNSCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 539px;\"\u003e\n \u003cp\u003eHead and neck squamous cell carcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eICI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 539px;\"\u003e\n \u003cp\u003eImmune checkpoint inhibitor\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eiLN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 539px;\"\u003e\n \u003cp\u003eIpsilateral lymph node\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eTAM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 539px;\"\u003e\n \u003cp\u003eTumor associated macrophage\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eTIDE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 539px;\"\u003e\n \u003cp\u003eTumor immune dysfunction and exclusion\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eTME\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 539px;\"\u003e\n \u003cp\u003eTumor microenvironment\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cu\u003eEthics approval and consent to participate\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003ePatient samples were obtained from ongoing clinical trials assigned to NCT04511078 and NCT02415881. Trials were approved by IRB committees at Stanford University and Vanderbilt University Medical Center (respectively) and their respective institutional Scientific Review Committees.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll animal studies were approved by Vanderbilt University/ VUMC IACUC and were conducted in accordance with American Association for Laboratory Animal Science (AALAS).\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eConsent for publication\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eAvailability of data and materials\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eCompeting interests\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interest.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eFunding\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by Barry Baker Biorepository Fund and two institutional training grants (T32GM007347 and T32GM152284).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eAuthors' contributions\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eCG, EL conceived and designed the study; HT, AM, NM, MH, SG, BB engaged in sample collection and \u0026nbsp;processing of human samples; CG, AN completed spatial transcriptomics and analysis; CG, HT, AM, GV, SMAZ assisted with mouse husbandry and tissue processing; CG, HT, GV, SMAZ, CO, SG engaged in protein immunofluorescent and IHC staining and analysis; GV. developed tumor nest analysis algorithm; HT, GV, MH, VW, JC, YM, MR assisted with methodology, data analysis, and critically evaluating the study. All authors reviewed the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eAcknowledgements\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank all of the patients who have offered their support and participation in our clinical trials. We hope this work will continue to benefit these patients and many others in the future.\u0026nbsp;\u003cbr\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGellerman MAFANDG. Targeted drug delivery for cancer therapy: the other side of antibodies. BioMed Cent. 2012;5(1). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/1756-8722-5-70\u003c/span\u003e\u003cspan address=\"10.1186/1756-8722-5-70\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eProvenzano KYEGANDMCANDJZANDPP. 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Oncogene. 2018;37(32):4343\u0026ndash;57. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/S41388-018-0275-3\u003c/span\u003e\u003cspan address=\"10.1038/S41388-018-0275-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Head and neck squamous cell carcinoma, immunotherapy, drug delivery","lastPublishedDoi":"10.21203/rs.3.rs-6228925/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6228925/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eAntibody-based therapies (such as anti-EGFR and anti-PD1/L1 agents) have altered the landscape of cancer treatment to improve patient outcomes in formerly unresponsive tumor types. However, this robust response is not ubiquitous for all patients or cancer subtypes. Head and neck squamous cell carcinoma continues to have reduced response in many patient populations regardless of target expression (e.g. EGFR or PDL1). The role of microenvironmental proteins, such as fibroblast activation protein (FAP), may hold the key to improving antibody drug delivery and efficacy. We explore the role of FAP in restricting antibody drug therapies and the subsequent impact of targeting FAP to improve immunotherapy response.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eOur study uses fluorescently- labeled panitumumab (anti-EGFR) to dissect the impact of FAP on drug delivery in HNSCC patients. Through spatial transcriptomic analysis on these patient samples, we explored the effects of FAP expression on another highly relevant subset of antibody-based drugs- immunotherapy. Based on our patient findings, we used a flank syngeneic mouse model to corroborate the role of FAP in responsive (MOC1) and unresponsive (MOC2) tumor types. Our work culminated in a therapeutic proof-of concept using combination anti-FAP therapy with anti-PDL1.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOur patient samples revealed that high FAP areas had significantly reduced panitumumab compared to regions with lower FAP expression. Furthermore, depth of penetration within tumor nest was reduced in high FAP areas. Our spatial transcriptomic analysis segmented by FAP, PanCK (tumor), and CD31 (vasculature) showed reduced immunotherapy responsiveness (via TIDE scores) in FAP segments. We confirmed that high-FAP expression was associated with reduced immunotherapy (anti-PDL1) response in our MOC2 tumor-bearing model. We also saw reduced anti-PDL1 drug delivery within MOC2 tumors. However, concurrent administration of an anti-FAP monoclonal antibody improved anti-PDL1 response and overall survival. The administration of anti-FAP agents simultaneously enhanced CD8 T cell infiltration while inducing collagen reorganization (both mechanisms previously linked to improved cancer therapeutic efficacy).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eOur study used human and \u003cem\u003ein vivo\u003c/em\u003e data to support a clinically implementable approach for improving antibody-based drug efficacy and response. These findings suggest targeting FAP improves drug penetration and alters the microenvironment to result in higher drug efficacy.\u003c/p\u003e","manuscriptTitle":"FAP+ cells restrict antibody drug delivery and promote an immunosuppressive environment in head and neck squamous cell carcinoma.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-25 09:47:05","doi":"10.21203/rs.3.rs-6228925/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b0b2ecfe-fc95-4ccb-8273-5f67396cf072","owner":[],"postedDate":"March 25th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-04-09T06:23:44+00:00","versionOfRecord":[],"versionCreatedAt":"2025-03-25 09:47:05","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6228925","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6228925","identity":"rs-6228925","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}