167 Comprehensive profiling of cancer-associated fibroblasts in CD8+T cell-exclusive non-small cell lung cancer tumor microenvironments using the Nanostring GeoMX® digital spatial profiler (2022)

<h3>Background</h3> Cancer-associated fibroblasts (CAFs) are a major component of the non-small cell lung cancer (NSCLC) tumor microenvironment (TME).<sup>1–4</sup> Recent studies indicate that CAFs play a role in generating a CD8+T cell (CTL)-exclusive TME.<sup>5–9</sup> Given that immune-checkpoint inhibitors (ICIs) rely on CTLs, an abundance of CAFs in the TME may result in reduced ICI efficacy. Although CAFs are considered potential targets for therapy, attempts to deplete CAFs have largely failed.<sup>10</sup> This is due to the fact that CAFs are a heterogenous population of cells and depletion of the wrong subpopulation could worsen disease.<sup>1</sup> Thus, to enhance ICI efficacy and improve patient outcome, we must identify and target CAF subtypes that promote CTL exclusion. Single-cell RNA sequencing (scRNAseq) has improved our understanding of CAF heterogeneity<sup>11–13</sup>; yet this technology cannot provide a comprehensive profile of CAF subtypes within the TME. For scRNAseq, tumor tissues are digested, causing cell death, and the resultant transcriptomic profile is incomplete. To generate a holistic profile of CAF subtypes within NSCLC, and identify the subpopulation that promotes CTL exclusion, we have utilized the GeoMX® Digital Spatial Profiler (DSP)<sup>14–17</sup>, a state-of-the-art platform that allows for spatially resolved, high-plexed molecular profiling of intact tumor tissues. <h3>Methods</h3> We performed digital spatial profiling on a tissue microarray (TMA) slide containing fifty-five cores of human lung tumors. We performed in-situ hybridization (ISH) on the slide with the GeoMx Whole Transcriptome Atlas (WTA), a mixture of photocleavable oligo-linked RNA probes that covers 18,000+ protein-coding human genes. Next, we stained the slide with fluorescent antibodies against Vimentin (VIM, a CAF marker), CD8, and SYTO (nuclear dye). Each core was a region of interest (ROI), and UV-light was masked to focus on CD8+ and VIM+ areas within each ROI to generate distinct areas of illumination (AOI) that were read out separately. NSG data was analyzed with DESeq2 to identify genes that were differentially expressed in CAFs living in CTL-exclusive tumors. <h3>Results</h3> We identified 441 genes that were differentially expressed in CAFs residing in CTL-exclusive tumors compared to CAFs in CTL-inclusive tumors. Ingenuity Pathway Analysis (IPA) of those genes revealed several pathways which were inactivated in CTL-exclusive CAFs, including Leukocyte Extravasation Signaling and Ephrin Receptor Signaling, both of which could contribute to reduced CTL migration and infiltration. <h3>Conclusions</h3> The GeoMX DSP can be used to identify CAF subpopulations that contribute to the formation of immune-exclusive TMEs and reveal novel molecular targets for immunotherapy. <h3>References</h3> Sahai E, Astsaturov I, Cukierman E, <i>et al</i> (2020) A framework for advancing our understanding of cancer-associated fibroblasts. <i>Nat Rev Cancer</i><b> 20</b>:174–186. Kilvaer TK, Khanehkenari MR, Hellevik T, Al-Saad S, Paulsen E-E, Bremnes RM, Busund L-T, Donnem T, Martinez IZ (2015) Cancer Associated Fibroblasts in Stage I-IIIA NSCLC: Prognostic Impact and Their Correlations with Tumor Molecular Markers. <i>PLoS One</i><b> 10</b>:e0134965. Schulze AB, Schmidt LH, Heitkötter B, <i>et al</i> (2020) Prognostic impact of CD34 and SMA in cancer-associated fibroblasts in stage I–III NSCLC. <i>Thorac Cancer</i><b> 11</b>:120–129. Li L, Lu G, Liu Y, Gong L, Zheng X, Zheng H, Gu W, Yang L (2021) Low Infiltration of CD8+ PD-L1+ T Cells and M2 Macrophages Predicts Improved Clinical Outcomes After Immune Checkpoint Inhibitor Therapy in Non-Small Cell Lung Carcinoma. <i>Front Oncol</i><b> 11</b>:1513. Puré E, Lo A (2016) Can targeting stroma pave the way to enhanced antitumor immunity and immunotherapy of solid tumors? <i>Cancer Immunol Res</i><b> 4</b>:269–278. Kilvaer TK, Rakaee M, Hellevik T, Østman A, Strell C, Bremnes RM, Busund LT, DØnnem T, Martinez-Zubiaurre I (2018) Tissue analyses reveal a potential immune-adjuvant function of FAP-1 positive fibroblasts in non-small cell lung cancer. <i>PLoS One</i><b> 13</b>:e0192157. Barrett RL, Pure E (2020) Cancer-associated fibroblasts and their influence on tumor immunity and immunotherapy. <i>Elife</i><b> 9</b>:1–20. Monteran L, Erez N (2019) The dark side of fibroblasts: Cancer-associated fibroblasts as mediators of immunosuppression in the tumor microenvironment. <i>Front Immunol</i>. https://doi.org/10.3389/fimmu.2019.01835. De Jaeghere EA, Denys HG, De Wever O (2019) Fibroblasts Fuel Immune Escape in the Tumor Microenvironment. <i>Trends in Cancer</i><b> 5</b>:704–723. Shah K, Mallik SB, Gupta P, Iyer A (2022) Targeting Tumour-Associated Fibroblasts in Cancers. <i>Front Oncol</i><b> 12</b>:908156. Lambrechts D, Wauters E, Boeckx B, <i>et al</i> (2018) Phenotype molding of stromal cells in the lung tumor microenvironment. <i>Nat Med</i><b> 24</b>:1277–1289. D Ö, A H-S, G B, et al (2017) Distinct populations of inflammatory fibroblasts and myofibroblasts in pancreatic cancer. <i>J Exp Med</i> 214:579–596. Elyada E, Bolisetty M, Laise P, et al (2019) Cross-species single-cell analysis of pancreatic ductal adenocarcinoma reveals antigen-presenting cancer-associated fibroblasts. <i>Cancer Discov</i><b> 9</b>:1102–1123. Zollinger DR, Lingle SE, Sorg K, Beechem JM, Merritt CR (2020) GeoMxTM RNA Assay: High Multiplex, Digital, Spatial Analysis of RNA in FFPE Tissue. In: <i>Methods Mol. Biol</i>. Springer US, pp 331–345. Wang N, Li X, Wang R, Ding Z (2021) Spatial transcriptomics and proteomics technologies for deconvoluting the tumor microenvironment. <i>Biotechnol J</i>. https://doi.org/10.1002/biot.202100041. Bergholtz H, Carter JM, Cesano A, <i>et al</i> (2021) Best Practices for Spatial Profiling for Breast Cancer Research with the GeoMx ® Digital Spatial Profiler. <i>Cancers (Basel)</i>. https://doi.org/10.3390/CANCERS13174456. Monkman J, Taheri T, Warkiani ME, O’leary C, Ladwa R, Richard D, O’ Byrne K, Kulasinghe A (2020) High-Plex and High-Throughput Digital Spatial Profiling of Non-Small-Cell Lung Cancer (NSCLC). <i>Cancers (Basel)</i><b> 12</b>:1–14