Tumor-microenvironment Interactions Research Articles

BET inhibition reforms the immune microenvironment and alleviates T cell dysfunction in chronic lymphocytic leukemia.

Redundant tumor microenvironment (TME) immunosuppressive mechanisms and epigenetic maintenance of terminal T cell exhaustion greatly hinder functional antitumor immune responses in chronic lymphocytic leukemia (CLL). Bromodomain and extraterminal (BET) proteins regulate key pathways contributing to CLL pathogenesis and TME interactions, including T cell function and differentiation. Herein, we report that blocking BET protein function alleviates immunosuppressive networks in the CLL TME and repairs inherent CLL T cell defects. The pan-BET inhibitor OPN-51107 reduced exhaustion-associated cell signatures resulting in improved T cell proliferation and effector function in the Eμ-TCL1 splenic TME. Following BET inhibition (BET-i), TME T cells coexpressed significantly fewer inhibitory receptors (IRs) (e.g., PD-1, CD160, CD244, LAG3, VISTA). Complementary results were witnessed in primary CLL cultures, wherein OPN-51107 exerted proinflammatory effects on T cells, regardless of leukemic cell burden. BET-i additionally promotes a progenitor T cell phenotype through reduced expression of transcription factors that maintain terminal differentiation and increased expression of TCF-1, at least in part through altered chromatin accessibility. Moreover, direct T cell effects of BET-i were unmatched by common targeted therapies in CLL. This study demonstrates the immunomodulatory action of BET-i on CLL T cells and supports the inclusion of BET inhibitors in the management of CLL to alleviate terminal T cell dysfunction and potentially enhance tumoricidal T cell activity.

The Tumor Stroma of Squamous Cell Carcinoma: A Complex Environment That Fuels Cancer Progression.

The tumor microenvironment (TME), a complex assembly of cellular and extracellular matrix (ECM) components, plays a crucial role in driving tumor progression, shaping treatment responses, and influencing metastasis. This narrative review focuses on the cutaneous squamous cell carcinoma (cSCC) tumor stroma, highlighting its key constituents and their dynamic contributions. We examine how significant changes within the cSCC ECM-specifically, alterations in fibronectin, hyaluronic acid, laminins, proteoglycans, and collagens-promote cancer progression, metastasis, and drug resistance. The cellular composition of the cSCC TME is also explored, detailing the intricate interplay of cancer-associated fibroblasts (CAFs), mesenchymal stem cells (MSCs), endothelial cells, pericytes, adipocytes, and various immune cell populations. These diverse players modulate tumor development, angiogenesis, and immune responses. Finally, we emphasize the TME's potential as a therapeutic target. Emerging strategies discussed in this review include harnessing the immune system (adoptive cell transfer, checkpoint blockade), hindering tumor angiogenesis, disrupting CAF activity, and manipulating ECM components. These approaches underscore the vital role that deciphering TME interactions plays in advancing cSCC therapy. Further research illuminating these complex relationships will uncover new avenues for developing more effective treatments for cSCC.

A zebrafish xenotransplant model of anaplastic thyroid cancer to study tumor microenvironment and innate immune cell interactions in vivo.

Anaplastic thyroid cancer (ATC) is of the most aggressive thyroid cancer. While ATC is rare, it accounts for a disproportionately high number of thyroid cancer-related deaths. Here, we developed an ATC xenotransplant model in zebrafish larvae, where we can study tumorigenesis and therapeutic response in vivo. Using both mouse (T4888M) and human (C643)-derived fluorescently labeled ATC cell lines, we show these cell lines display different engraftment rates, mass volume, proliferation, cell death, angiogenic potential, and neutrophil and macrophage recruitment and infiltration. Next, using a PIP-FUCCI reporter to track proliferation in vivo, we observed cells in each phase of the cell cycle. Additionally, we performed long-term non-invasive intravital microscopy over 48 h to understand cellular dynamics in the tumor microenvironment at the single-cell level. Lastly, we tested two drug treatments, AZD2014 and a combination therapy of dabrafenib and trametinib, to show our model could be used as an effective screening platform for new therapeutic compounds for ATC. Altogether, we show that zebrafish xenotransplants make a great model to study thyroid carcinogenesis and the tumor microenvironment, while also being a suitable model to test new therapeutics in vivo.

Integrative single-cell analysis of LUAD: elucidating immune cell dynamics and prognostic modeling based on exhausted CD8+ T cells.

The tumor microenvironment (TME) plays a pivotal role in the progression and metastasis of lung adenocarcinoma (LUAD). However, the detailed characteristics of LUAD and its associated microenvironment are yet to be extensively explored. This study aims to delineate a comprehensive profile of the immune cells within the LUAD microenvironment, including CD8+ T cells, CD4+ T cells, and myeloid cells. Subsequently, based on marker genes of exhausted CD8+ T cells, we aim to establish a prognostic model for LUAD. Utilizing the Seurat and Scanpy packages, we successfully constructed an immune microenvironment atlas for LUAD. The Monocle3 and PAGA algorithms were employed for pseudotime analysis, pySCENIC for transcription factor analysis, and CellChat for analyzing intercellular communication. Following this, a prognostic model for LUAD was developed, based on the marker genes of exhausted CD8+ T cells, enabling effective risk stratification in LUAD patients. Our study included a thorough analysis to identify differences in TME, mutation landscape, and enrichment across varying risk groups. Moreover, by integrating risk scores with clinical features, we developed a new nomogram. The expression of model genes was validated via RT-PCR, and a series of cellular experiments were conducted, elucidating the potential oncogenic mechanisms of GALNT2. Our study developed a single-cell atlas for LUAD from scRNA-seq data of 19 patients, examining crucial immune cells in LUAD's microenvironment. We underscored pDCs' role in antigen processing and established a Cox regression model based on CD8_Tex-LAYN genes for risk assessment. Additionally, we contrasted prognosis and tumor environments across risk groups, constructed a new nomogram integrating clinical features, validated the expression of model genes via RT-PCR, and confirmed GALNT2's function in LUAD through cellular experiments, thereby enhancing our understanding and approach to LUAD treatment. The creation of a LUAD single-cell atlas in our study offered new insights into its tumor microenvironment and immune cell interactions, highlighting the importance of key genes associated with exhausted CD8+ T cells. These discoveries have enabled the development of an effective prognostic model for LUAD and identified GALNT2 as a potential therapeutic target, significantly contributing to the improvement of LUAD diagnosis and treatment strategies.

Abstract 4223: The dual immunestimulatory and immunesuppressive role of MRC5 fibroblast cells in 3D coculture with T cells and tumor cells

Abstract Introduction: Cancer-associated fibroblasts (CAFs) alter anti-tumor immune responses and modulate resistance to immune checkpoint inhibitors. The mechanisms of crosstalk between tumor cells, CAFs, and T cells remain not fully understood, and studying these multicellular interactions requires adoption of novel tools in preclinical research. Here, we established a spheroid co-culture model comprising of tumor cell lines, a fibroblast cell line, and primary human T cells, for studying the immunomodulatory effects of fibroblasts on T cell responses in vitro, in the context of immunotherapies. Methods: For setting up the 3D co-culture, A375 or OV-90 tumor cells were seeded alone or with MRC-5 fibroblasts in 96-well ultra-low attachment round bottom plates in complete growth medium supplemented with 1% Geltrex matrix. The cells were centrifuged, and spheroids were allowed to form for 24 hours. After spheroid initiation, activated T cells and treatments with anti-PD1 antibody or an immune stimulatory drug were added. Spheroid co-cultures were live imaged by Incucyte SX5 for 72 hours taking images every 4 hours, after which treatment responses were evaluated by flow cytometry and measuring IFN-γ accumulation with ELISA. Results: To mimic fibroblast and T cell interactions in tumor microenvironment we built and optimized an in vitro 3D co-culture assay using various tumor cell lines. With this assay we found that depending on the tumor cell interaction, fibroblasts MRC-5 cell line have either immune-suppressive or immune-promoting properties. IFN-γ secretion of T cells in the assay indicated that MRC-5 cells suppressed T cells when co-cultured with A375 cells, while with OV-90 cells T cells activation was enhanced. In addition to the IFN- γ secretion, T cells in MRC-5 OV-90 interaction significantly upregulated 4-1BB expression on both CD4 & CD8 T cells. Interestingly we noticed that MRC-5 fibroblasts could modulate T cell responses to anti-PD-1 treatment in the co-culture depending on the tumor cell used. Conclusion: Here, we established a spheroid co-culture model, which will allow studies of the immunomodulatory crosstalk occurring in tumor microenvironment. Our model revealed a bifunctional role of MRC-5 fibroblasts in altering T cell phenotype. This finding is in line with literature highlighting the ability of fibroblasts to act as either tumor promoters or tumor suppressors depending on tumor microenvironment. We believe that this model, would aid in elucidating mechanisms of interaction between CAFs and T cells, potentially leading to discoveries of novel targets for immuno-oncology drug development. Additional studies, such as gene expression analysis using single cell RNA sequencing, are warranted to further validated the model and to better understand the kinetics of these interaction occurring in the co-culture with various tumor cell lines. Citation Format: Ilona Arnkil, Can Hekim, Elli Narvi, Emmi-Leena Ihantola, Endrit Elbasani, Anil Thotakura. The dual immunestimulatory and immunesuppressive role of MRC5 fibroblast cells in 3D coculture with T cells and tumor cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4223.

Abstract 4241: Development of stroma cells-rich oral cancer organoid for functional analysis of tumor microenvironment

Abstract Background: Tumor microenvironment (TME), composed of cancer cells, endothelial cells, fibroblast, immune cells, and etc, plays crucial roles in tumor progression and treatment resistance. Thus, it is extremely important to find its role involved in the interaction of TME. However, it is more difficult to examine the biological activities of those cells in vitro assay. The purpose of this study is to develop stroma cells-incorporating preclinical model, termed stroma cells-rich oral cancer organoid, for functional analysis of TME. Materials and Methods: We have first developed the stroma cells-rich oral cancer organoid by selecting the types of stroma cells such as endothelial cells, fibroblast, ratio of those cells, culture method, 3-D methods, culture media, and supplement of growth factors. Then, growth rate, morphology, radiosensitivity, and drug response were analyzed to investigate the effect of TME. Finally, the function of tumor-associated macrophage was determined using this organoid model. The growth rate of cancer cells and drug response were investigated using the organoid treated with supernatant of M1 and M2 macrophages polarized from THP-1 monocyte. Results: Oral cancer cells were co-cultured with endothelial cells (ECs) and mesenchymal stem cells (MSCs) in a particular ratio in 3D-culture, and the formed organoid became sphere. The vascular formation in the organoid was confirmed by immunofluorescent analysis. The organoid also showed higher tumorigenicity in nude mice when inoculated, compared to cancer cells alone or mixed cells with ECs and MSCs. Cell viability of luciferase-expressing tongue cancer cells (OSC-19-luc) in the organoid was assessed after treatment with cisplatin using the IVIS system showing that OSC-19-luc organoid was resistance to cisplatin compared to 3D-cultured OSC-19-luc alone or OSC-19-luc co-cultured with ECs/MSCs. The supernatant of M1 or M2 macrophage had no effect on cancer cell growth in the organoid. However, when the organoid was treated with cisplatin in the presence of M2 macrophage supernatant, the drug sensitivity was low compared to those of M1 suggesting that secretory factor from M2 macrophage may lead to drug resistance of oral cancer cells in the presence of TME. Conclusions: We have successfully established stroma cells-incorporating preclinical model that recreates the tumor microenvironment by co-culturing stromal cells. This will serve as a platform that can recapitulate the tumor biology and drug response profiles of cancer cells derived from individual oral cancer patients. This will also enable us to elucidate the role of other factors in TME and to identify novel targets for the treatment of chemo-resistant oral cancer. Citation Format: Ami Shimoda, Shizuka Shiiya, Haruka Yoshii, Kenji Mitsudo, Mitomu Kioi. Development of stroma cells-rich oral cancer organoid for functional analysis of tumor microenvironment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4241.

Abstract 2341: Morph: A feature extraction toolset for spatial transcriptomics

Abstract Accurately defining spatial characteristics of tumors has been a challenge in cancer research. Specifically, there is still a lack of spatial transcriptomic (ST) bioinformatic methods that infer tumor boundaries, a necessity for tumor microenvironment (TME) analyses, that are fully automated and handle non-rectangular grids (like the one found in Visium). Here we introduce Morph, a toolset that not only addresses these limitations, but also accurately extracts tumor regions, layers surrounding them, and distances related to such regions. Morph was tested on a dataset composed of 117 ST slides across 6 different cancer types, including primary and metastatic tumors. More broadly, Morph is a computationally efficient tool based on mathematical morphology that is designed to work without any approximations on ST slides (that can be composed of spots in a hexagonal lattice) of any resolution. The toolset accepts a variety of input types, such as tumor purity and manual annotation, and can perform a diverse set of morphological operations, such as erosion, dilation, opening and closing, using a number of structuring elements with different shapes and sizes, such as a hexagon of side 1. Moreover, Morph runs quickly (seconds per sample). Its main focus is to unveil the aforementioned features of any spatially distinct tumor region (here defined as microregion) for various downstream analyses, such as spatially-varying copy number variations, cell-type distribution, and tumor-microenvironment interaction. Overall, we developed a spatial transcriptomics toolset that is not limited to any specific technology platform, and that can accurately extract ST features facilitating the discovery of spatial transcriptomic and interaction patterns. Citation Format: André Luiz N. Targino da Costa, Jingxian Liu, Chia-Kuei Mo, Erik Storrs, Austin N. Southard-Smith, Reyka G. Jayasinghe, Julia T. Wang, Michael D. Iglesia, Michael Wendl, Siqi Chen, Andrew Houston, Alla Karpova, Yize Li, Li Ding. Morph: A feature extraction toolset for spatial transcriptomics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2341.

Abstract 5028: Detection of non-small cell lung and bladder cancer signatures in peripheral blood using a novel antibody-free chromatin capture assay

Abstract Immune checkpoint inhibition (ICI) via anti-PD-1/PD-L1 has improved clinical outcomes for multiple cancers, including bladder and non-small cell lung cancer (NSCLC). Yet, the response rates remain low highlighting a significant knowledge gap in the mechanisms driving response and resistance. While the expression of PD-L1 has been established as a predictive biomarker of ICI response, other features, including molecular tumor burden, tumor microenvironment (TME), and the host’s immune mechanisms may contribute to overall response. The complex interactions between a tumor and the immune system underscore the need for a more comprehensive approach to explore novel biological and immunological insights of cancer progression. Circulating tumor DNA assays, while integral to contemporary decision-making in oncology, fall short in delineating the transcriptional programs that dictate cancer phenotypes and their evolution over the disease trajectory. To bridge this gap, we have developed a plasma-based active chromatin capture method that enables the comprehensive epigenetic and transcriptomic interrogation of both tumor and immune components. In this study, we quantified epigenetic profiles from plasma samples (n=100) of patients with bladder cancer (n=20) and NSCLC (n=24) undergoing ICI therapy, along with samples (n=70) from healthy individuals (n=5). As expected, the total cfDNA yield (ng) of lung (1.7x, p=2.3e-08) and bladder (1.98x, p=1.6e-11) cancer samples were higher than those of healthy individuals. More Interestingly, the longer cfDNA fragments derived from regulatory-active chromatin, also showed a significantly higher abundance in plasma samples from both lung (2.0x, p=2.5e-09) and bladder (3.2x, p=3.2e-14) cancer patients. Furthermore, the patterns of epigenetic regulations across cancer and healthy conditions showed distinct and stable clusters, consistent between gene bodies and transcription start sites, highlighting the epigenetic changes that may be driving cancer progression. We also observed a common enrichment of immune epigenetic signatures in both lung and bladder cancer samples, likely attributed to shared mechanisms associated with the modulation of the tumor microenvironment and immune interactions. Understanding these changes at an epigenetic level could provide insights into novel therapeutic approaches that target the tumor microenvironment and the immune interactions. Citation Format: Kevin Lai, Katharine Dilger, Rachael Cunningham, Timothy Barnes, Khiet Truong, Kathy Lam, Rhea Boquiren, Maggie C. Louie, Diana Abdueva. Detection of non-small cell lung and bladder cancer signatures in peripheral blood using a novel antibody-free chromatin capture assay [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5028.

Abstract 6245: Missed opportunity at the subcellular level: Enhancing the utility of cellular imaging modality in spatial transcriptomic profiling of tumor tissues

Abstract Mini-bulk or single-spot spatial transcriptomic technologies, such as GeoMX Digital Spatial Profiler (DSP), have revolutionized our ability to probe spatial heterogeneity and examine transcripts at a subcellular level. In cancer research, this level of granularity is crucial for uncovering the distinct gene expression signatures within specific compartments or structures of interest such as tumor, immune, stroma, and tertiary lymphoid structures. However, in most GeoMX DSP studies, the spatial information obtained from multiplex immunofluorescence imaging has been primarily used for identifying the regions of interest (ROI), rather than as an integral part of the downstream transcriptomic data interpretation. To fix this missed opportunity, we developed a machine learning based analytical framework to fully leverage the rich spatial context provided by the in situ imaging modality. The framework has two main functionalities. (1) ROI cropping and cell segmentation: our framework enables the automated cropping of ROI images, followed by a cell segmentation process utilizing a multi-color-optimized deep learning model pre-trained based on the TissueNet. (2) Cell typing and integrative spatial analysis: the pipeline extracts cell-level morphological features (e.g. cell size and circularity), and AI-driven characteristics. These features are subsequently employed for cell typing and the quantification of cell mixture. The framework is equipped to perform a series of advanced spatial analyses, such as spatial metrics calculation and consensus clustering analysis with the matched gene expression data. To validate the framework, we conducted GeoMX DSP analyses on samples obtained from bladder cancer and upper tract urothelial carcinoma, encompassing 56 ROIs annotated by pathologists. Our results demonstrated high accuracy, with the calculated tumor-immune proportions aligning precisely with the original annotations. We further compared the cell deconvolution results of our framework with those obtained using SpatialDecon. Consistency was noted across both methods, with a high correlation reaching 0.90. However, we observed that SpatialDecon tends to underestimate tumor purity in tumor core regions, with discrepancies as large as 0.30, and overestimating tumor purity in stromal regions. Additionally, analysis of ROIs in tumor margins revealed that SpatialDecon consistently overestimates the overall proportions of immune cells. In conclusion, our results underscore the importance of integrating in situ imaging with subcellular-level spatial transcriptomics for a more accurate and reliable analysis of tumor tissues. Our approach provides critical insights into the tumor microenvironment and cellular interactions, with significant implications for both research and clinical applications in oncology. Citation Format: Xiaofei Song, Xiaoqing Yu, Carlos M. Moran-Segura, G Daniel Grass, Roger Li, Xuefeng Wang. Missed opportunity at the subcellular level: Enhancing the utility of cellular imaging modality in spatial transcriptomic profiling of tumor tissues [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6245.

Abstract 5552: Uncovering clinically significant tumor microenvironment interaction programs across diverse cancers

Abstract Background: Cell-cell interactions (CCI) within the tumor microenvironment (TME) play pivotal roles in various tumor behaviors, including cancer growth, metastasis, immune evasion, and resistance to therapy. Compared to front-line treatments, targeting specific CCIs marks a paradigm shift in cancer therapy, aiming for enhanced response rates with reduced side effects. Although current approaches targeting immune regulation pathways exhibit effective anti-tumor responses, substantial variability in response rates across patients and cancer types persists. Consequently, a critical imperative emerges to discover novel interaction programs (IPs) across diverse TMEs, demonstrating clear clinical impact across a broad spectrum of patients. Methods: Characterization of pan cancer IPs. We compiled a pan cancer single-cell RNA-seq (scRNA-seq) atlas, including 4 million cells from 890 tumors across 14 cancer types. In each sample, CCIs were inferred using a ligand-receptor (LR) analysis framework, generating ranked CCI scores based on consensus from various LR inference methods. To find IPs enriched across TMEs, we applied an unsupervised factorization approach. The outcome represents CCIs as factors, where sample loading indicates factors’ strength, and feature loading highlights the cells and LR pairs constituting each IP. Evaluating IPs in clinical RNA-seq cohorts. Given the more immediate translational potential of bulk cancer sequencing for patient stratification, we devised an approach to predict IPs' strengths in bulk RNA-seq. Random Forest regression models using pseudo-bulk expression of cancer genes were trained to predict the loading (strength) of factors (IPs) in each sample in the scRNA-seq pan-cancer atlas. These models were subsequently applied to cancer samples in The Cancer Genome Atlas (TCGA) cohort to assess the clinical impact of various IPs on patient mortality. Results: We assessed the impact of IPs on 5-year overall survival using Cox proportional hazard models. We identified multiple factors significantly associated with survival in at least 4 cancer types. Notably, a robust prognostic factor linked to the inclusion of anti-tumor natural killer cell interactions and exclusion of pro-tumor macrophage interactions was found in MESO, LGG, ACC, and UVM (HR 1.6-6.6, p < 0.05). The validation of IPs using spatial transcriptomics and evaluation of IP prediction's utility in targeted treatment cohorts are currently underway. Conclusion: We highlight a potent method for detecting clinically significant IPs involving cells in TME communicating through LR pairs. The ability to assess these scRNA-seq-derived IPs in clinical bulk RNA-seq cohorts signifies a valuable advancement. Our approach holds promise for expanding the repertoire of cell therapies, identifying new treatment targets, and improving our predictive capabilities for responses to existing therapies. Citation Format: Ido Nofech-Mozes, Vivian Wang, Philip Awadalla, Sagi Abelson. Uncovering clinically significant tumor microenvironment interaction programs across diverse cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5552.

Abstract 7378: Using game theory to investigate the therapeutic potential of disrupting tumor-microenvironment interactions

Abstract Cancer is a complex disease involving the interplay of several types of malignant and nonmalignant cells. The growth of tumors and surrounding stromal cells can be modeled as an ecosystem, where populations of cancerous and healthy cells interact and compete for resources. In this work, we have explored the application of game theoretic models of cancer to the design of novel anticancer therapies. Notably, a game theoretic-model of tumor-stromal interactions can capture the impact of interactions between cell types and can be used to investigate frequency-dependent parameters describing the impact of drug action during the initiation and growth of metastatic cancers. Previous studies using game theoretic models to describe cancer have focused on explaining progression patterns of specific tumors with known tumor-stromal interactions. This study takes a more general approach to cancer growth dynamics, modeling cancer as a simple game between healthy and cancer cells. This simplified model is used to make general predictions about cancer progression and the efficacy of treatment strategies. Our work suggests that disruption of beneficial interactions between healthy and cancer cells may be a viable treatment strategy for small tumors and preventing metastasis by ensuring that the healthy cell strategy is evolutionarily stable. The efficacy of treatment strategies that disrupt cancer cell cooperation or tumor-stromal dynamics changes as the cancer cell frequency changes. Our work suggests that drugs that target tumor-stromal cell interactions would need to be combined with other types of treatments to be effective against large tumors. Although based on a simplistic model of cancer initiation and progression, the framework derived here can be extended to the real-world design of experimental anticancer therapeutics, and fundamental analyses of this nature can be of practical utility in setting strategy for Target Product Profile design. Citation Format: Debra Van Egeren, Andrew Chen, Madison Stoddard, Lin Yuan, Arijit Chakravarty. Using game theory to investigate the therapeutic potential of disrupting tumor-microenvironment interactions [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7378.

247 (PB-063) Poster - SARS-CoV-2 M-protein promotes malignancy of breast cancer cells and alters interaction in breast tumor microenvironment

247 (PB-063) Poster - SARS-CoV-2 M-protein promotes malignancy of breast cancer cells and alters interaction in breast tumor microenvironment

The secretome from human-derived mesenchymal stem cells augments the activity of antitumor plant extracts in vitro

Cancer is understood as a multifactorial disease that involve multiple cell types and phenotypes in the tumor microenvironment (TME). The components of the TME can interact directly or via soluble factors (cytokines, chemokines, growth factors, extracellular vesicles, etc.). Among the cells composing the TME, mesenchymal stem cells (MSCs) appear as a population with debated properties since it has been seen that they can both promote or attenuate tumor progression. For various authors, the main mechanism of interaction of MSCs is through their secretome, the set of molecules secreted into the extracellular milieu, recruiting, and influencing the behavior of other cells in inflammatory environments where they normally reside, such as wounds and tumors. Natural products have been studied as possible cancer treatments, appealing to synergisms between the molecules in their composition; thus, extracts obtained from Petiveria alliacea (Anamu-SC) and Caesalpinia spinosa (P2Et) have been produced and studied previously on different models, showing promising results. The effect of plant extracts on the MSC secretome has been poorly studied, especially in the context of the TME. Here, we studied the effect of Anamu-SC and P2Et extracts in the human adipose-derived MSC (hAMSC)–tumor cell interaction as a TME model. We also investigated the influence of the hAMSC secretome, in combination with these natural products, on tumor cell hallmarks such as viability, clonogenicity, and migration. In addition, hAMSC gene expression and protein synthesis were evaluated for some key factors in tumor progression in the presence of the extracts by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and Multiplex, respectively. It was found that the presence of the hAMSC secretome did not affect the cytotoxic or clonogenicity-reducing activities of the natural extracts on cancer cells, and even this secretome can inhibit the migration of these tumor cells, in addition to the fact that the profile of molecules can be modified by natural products. Overall, our findings demonstrate that hAMSC secretome participation in TME interactions can favor the antitumor activities of natural products.

Abstract B002: Profiling intra-tumor heterogeneity and chromosomal instability in malignant peripheral nerve sheath tumors

Abstract Malignant peripheral nerve sheath tumors (MPNSTs) are rare soft-tissue sarcomas that manifest on peripheral nerves, constituting 2% of all sarcomas. They arise both sporadically and in 8% to 13% of individuals with neurofibromatosis type 1 (NF1), where they represent the major cause of morbidity and mortality. While previous genomic analyses of MPNSTs have been conducted on small cohorts, often limited to single samples per patient and lacking comprehensive resolution, the extent of intra-tumor heterogeneity and the contribution of chromosomal instability to MPNST development remain unclear. To address these limitations, we developed a multi-omics integration pipeline and applied it to integrate bulk Next Generation Sequencing (NGS), single-cell RNA sequencing, single-cell DNA sequencing, spatial transcriptomics (ST), and Laser Capture Microsection (LCM) information. 35 tumor samples were collected from 10 patients with MPNST, and for each sample, data were generated using the above five techniques. Overall, we detected copy-number aberrations recurrently found in MPNSTs, including events such as loss of heterozygosity (LOH), whole genome doubling (WGD) and chromosome 7 and 8 amplifications. Subclonal copy number alterations were called by the Battenberg algorithm, followed by SNV clustering using Dirichlet Process-based methods. Applying the pigeonhole principle, we constructed tumor phylogenetic trees. Intriguingly, our findings indicate that for patient 2.3, primary tumor samples PT_1 and PT_2 displayed a close phylogenetic relationship, while local recurrences LR_2 and LR_3 represent a different branch of the phylogenetic tree. Following stringent quality control and cell type annotation, we leveraged normal cells identified within the snRNA data as controls to infer copy number changes in tumor cells through inferCNV. Notably, in patient 2.16, we identified significant copy number gains on chromosomes 5, 7, 8, and 15. Comparing the inferred copy number changes derived from snRNA with those obtained through Battenberg copy number profiles showed a remarkable congruence, thereby reinforcing the robustness of our results. To reveal communication networks among tumor microenvironment (TME) cells, we used iTalk to visualize ligand-receptor interactions between distinct cell types. For Patient 2.3, macrophages emerged as key players, releasing cytokines such as IL-16 and IL-18, which exerted their influence on receptors in tumor cells. Additionally, T cells engaged in checkpoint factors, including TNFSF4 and CD28, interacting with receptors on tumor cells, such as TRAF2 and LGALS9. Our research revealed that MPNSTs are primarily driven by chromosomal instability and intra-tumor heterogeneity is shaped by TME interactions. We enhanced our understanding of the tumors' evolutionary histories and intra-tumor heterogeneity down to single-cell resolution. By shedding light on the genomic landscape of MPNSTs, we aspire to make profound contributions to the field of sarcoma research, ultimately improving patient outcomes. Citation Format: Yixiao Cheng, Haixi Yan, Maxime Tarabichi, Zhihui Zhang, Chunxu Gao, Tom Lesluyes, Adrienne Flanagan, Peter Van Loo. Profiling intra-tumor heterogeneity and chromosomal instability in malignant peripheral nerve sheath tumors [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr B002.

Gut microbiota and its therapeutic implications in tumor microenvironment interactions.

The development of cancer is not just the growth and proliferation of a single transformed cell, but its tumor microenvironment (TME) also coevolves with it, which is primarily involved in tumor initiation, development, metastasis, and therapeutic responses. Recent years, TME has been emerged as a potential target for cancer diagnosis and treatment. However, the clinical efficacy of treatments targeting the TME, especially its specific components, remains insufficient. In parallel, the gut microbiome is an essential TME component that is crucial in cancer immunotherapy. Thus, assessing and constructing frameworks between the gut microbiota and the TME can significantly enhance the exploration of effective treatment strategies for various tumors. In this review the role of the gut microbiota in human cancers, including its function and relationship with various tumors was summarized. In addition, the interaction between the gut microbiota and the TME as well as its potential applications in cancer therapeutics was described. Furthermore, it was summarized that fecal microbiota transplantation, dietary adjustments, and synthetic biology to introduce gut microbiota-based medical technologies for cancer treatment. This review provides a comprehensive summary for uncovering the mechanism underlying the effects of the gut microbiota on the TME and lays a foundation for the development of personalized medicine in further studies.

Therapeutic importance and diagnostic function of circRNAs in urological cancers: from metastasis to drug resistance.

Circular RNAs (circRNAs) are a member of non-coding RNAs with no ability in encoding proteins and their aberrant dysregulation is observed in cancers. Their closed-loop structure has increased their stability, and they are reliable biomarkers for cancer diagnosis. Urological cancers have been responsible for high mortality and morbidity worldwide, and developing new strategies in their treatment, especially based on gene therapy, is of importance since these malignant diseases do not respond to conventional therapies. In the current review, three important aims are followed. At the first step, the role of circRNAs in increasing or decreasing the progression of urological cancers is discussed, and the double-edged sword function of them is also highlighted. At the second step, the interaction of circRNAs with molecular targets responsible for urological cancer progression is discussed, and their impact on molecular processes such as apoptosis, autophagy, EMT, and MMPs is highlighted. Finally, the use of circRNAs as biomarkers in the diagnosis and prognosis of urological cancer patients is discussed to translate current findings in the clinic for better treatment of patients. Furthermore, since circRNAs can be transferred to tumor via exosomes and the interactions in tumor microenvironment provided by exosomes such as between macrophages and cancer cells is of importance in cancer progression, a separate section has been devoted to the role of exosomal circRNAs in urological tumors.

Biophysical Control of the Glioblastoma Immunosuppressive Microenvironment: Opportunities for Immunotherapy.

GBM is the most aggressive and common form of primary brain cancer with a dismal prognosis. Current GBM treatments have not improved patient survival, due to the propensity for tumor cell adaptation and immune evasion, leading to a persistent progression of the disease. In recent years, the tumor microenvironment (TME) has been identified as a critical regulator of these pro-tumorigenic changes, providing a complex array of biomolecular and biophysical signals that facilitate evasion strategies by modulating tumor cells, stromal cells, and immune populations. Efforts to unravel these complex TME interactions are necessary to improve GBM therapy. Immunotherapy is a promising treatment strategy that utilizes a patient's own immune system for tumor eradication and has exhibited exciting results in many cancer types; however, the highly immunosuppressive interactions between the immune cell populations and the GBM TME continue to present challenges. In order to elucidate these interactions, novel bioengineering models are being employed to decipher the mechanisms of immunologically "cold" GBMs. Additionally, these data are being leveraged to develop cell engineering strategies to bolster immunotherapy efficacy. This review presents an in-depth analysis of the biophysical interactions of the GBM TME and immune cell populations as well as the systems used to elucidate the underlying immunosuppressive mechanisms for improving current therapies.

Abstract B017: NINJA PDAC: A robust murine pancreatic cancer organoid transplant model with inducible neoantigens for studying tumor microenvironment interactions with anti-tumor T-cell immunity

Abstract Pancreatic ductal adenocarcinoma (PDAC) is highly lethal due to early metastasis and poor therapeutic response including to anti-PD1/CTLA4-based immunotherapy, characteristics attributed to a desmoplastic tumor microenvironment (TME) and low immunogenicity. However, long-term human PDAC survivors exhibit higher neoantigen expression with active T-cell immunogenicity, and most human PDAC express predicted neoepitopes, arguing that T-cell mediated anti-tumor immunity shapes PDAC progression. By contrast, tumors in classical pre-clinical (KRASLSL-G12D; TRP53F/F; pancreas-specific Cre, or KPC) murine models exhibit low neoantigen burden, are non-immunogenic, with growth kinetics independent of T cells, making them poorly suited to study T-cell immunity. Combined chemoimmunotherapy regimens for human PDAC might be developed more efficiently via preclinical studies in murine models with physiologic stroma, defined neoantigens that can be induced in established tumors, and measurable neoantigen-specific T-cell responses. We developed NINJA PDAC, a novel, robust transplantable murine pancreatic cancer organoid model, to study neoantigen-specific anti-tumor T-cell responses and how they are influenced by the TME. The NINJA (Damo et al., 2021) system allows for spatially (Cre) and temporally (doxycycline+tamoxifen) controlled inducible expression of LCMV-derived neoantigens with low-to-moderate MHCI/II-binding affinity (GP33 and GP66, respectively) comparable to human PDAC, in Kras-mutated, p53-deficient PDAC organoids. Transplanted NINJA PDAC organoids engraft robustly both subcutaneously and orthotopically in syngeneic mice, with reproducible kinetics. Unlike 2D cell line transplants, these organoid-derived tumors have a complex ductal architecture, immune islands, and fibrotic stroma more representative of human PDAC. T-cell depletion studies demonstrated that full rejection of tumors with constitutive neoantigen expression (NINJA ‘ON’) requires both CD4+ and CD8+ neoantigen-specific T-cells, allowing the study of the roles of both helper and cytotoxic T-cells in anti-PDAC immunity. ‘Poised’ NINJA PDAC organoids do not express neoantigen until induction, and we confirmed high tumor neoantigen expression can be induced with doxycycline/tamoxifen in vivo (38%±18% neoantigen-expressing tumor cells). Early induction in vivo leads to intratumoral CD3+ T-cell infiltration, with increased neoantigen-specific (H2Db/gp33-41-tetramer positive) T-cells in tumors and tumor-draining lymph nodes. Late induction in vivo leads to neoantigen induction, but more muted T-cell infiltration and minimally attenuated tumor growth, suggesting a role of an established TME in suppressing T-cell responses. NINJA PDAC is a promising model that affords a high-fidelity toolset to study how murine neoantigen-specific anti-tumor T-cell responses are perturbed by the TME and further altered by host variables (such as obesity) that modulate the TME with the potential to expedite the development of new combination immunotherapies. Citation Format: Jeremy B. Jacox, Gena G. Foster, Dhruvi Shah, Nikhil S. Joshi, Mandar D. Muzumdar. NINJA PDAC: A robust murine pancreatic cancer organoid transplant model with inducible neoantigens for studying tumor microenvironment interactions with anti-tumor T-cell immunity [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr B017.

Abstract B090: Targeting the unfolded protein response enhances sensitivity to chemotherapy

Abstract Introduction: Pancreatic ductal adenocarcinoma (PDAC) is currently the 3rd leading cause of cancer-related deaths in North American with ~10% survival 5 years after diagnosis. A contributing factor to this low survival rate is chemotherapy resistance. Major risk factors for PDAC, including smoking and chronic pancreatitis, promote activation of the unfolded protein response (UPR). The UPR reduces protein load to alleviate stress, and cancer cells can utilize the UPR to promote cell survival. We previously showed loss of Activating Transcription Factor 3 (ATF3), a mediator of the UPR, restricted early events in PDAC progression. The goal of this study was to determine if ATF3 and the UPR promote resistance to chemotherapy in PDAC. We hypothesized that cancer cells activate the UPR and ATF3 to reduce cell stress and promote chemotherapeutic resistance. Methods: Murine-derived organoids (MDOs) were developed from pancreatic tissue expressing KRASG12D with (Ptf1acreERT/+KRASG12D/+) or without Atf3 (Atf3-/-Ptf1acreERT/+KRASG12D; referred to as APK) expression, and patient-derived organoids (PDOs) were examined for mediators of the UPR. Transcriptomic changes related to ATF3 loss was determined by RNA-sequencing of Ptf1acreERT/+KRASG12D/+ and APK organoids. UPR activation was examined by qRT-PRC in MDOs and PDOs with and without gemcitabine treatment, and related to organoid viability and phenotype. PDOs viability was examined following treatment with gemcitabine +/- UPR inhibitors. Results: RNA-seq analysis of Ptf1acreERT/+KRASG12D/+ and APK MDOs identified drug metabolism cytochrome P450, metabolism of xenobiotics by cytochrome P450, and platinum drug resistance as key pathways affected by the loss of ATF3 suggesting reduced UPR activation impacts drug metabolism in KRASG12D expressing cells. Ptf1acreERT/+KRASG12D/+ and APK MDOs showed a differential response in cell viability and UPR activation to gemcitabine treatment suggesting an importance of ATF3 in gemcitabine resistance. Consistent with this role, treatment of PDOs with gemcitabine resulted in UPR activation in a patient-specific fashion, particularly regarding increased expression of ATF3 and spliced XBP1. In lines showing enhanced UPR activation to gemcitabine, combinatorial treatment with UPR inhibitors showed increased cell death compared to gemcitabine alone. Conclusions: This study shows the UPR and ATF3 are rapidly activated in response to gemcitabine, but in a patient-specific fashion. These results suggest cancer cells activate the UPR to increase resistance to chemotherapies, and a subset of patients may benefit from combined gemcitabine treatment with UPR inhibitors. Since the tumor microenvironment is believed to be a major contributing factor to chemotherapy resistance, future experiments will include the tumor microenvironment interactions and UPR inhibition. Citation Format: Mickenzie B. Martin, Teresa Borello, Fatemeh Mousavi, Nelson Dusetti, Christopher L. Pin. Targeting the unfolded protein response enhances sensitivity to chemotherapy [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr B090.

Cellular interactions in tumor microenvironment during breast cancer progression: new frontiers and implications for novel therapeutics.

The breast cancer tumor microenvironment (TME) is dynamic, with various immune and non-immune cells interacting to regulate tumor progression and anti-tumor immunity. It is now evident that the cells within the TME significantly contribute to breast cancer progression and resistance to various conventional and newly developed anti-tumor therapies. Both immune and non-immune cells in the TME play critical roles in tumor onset, uncontrolled proliferation, metastasis, immune evasion, and resistance to anti-tumor therapies. Consequently, molecular and cellular components of breast TME have emerged as promising therapeutic targets for developing novel treatments. The breast TME primarily comprises cancer cells, stromal cells, vasculature, and infiltrating immune cells. Currently, numerous clinical trials targeting specific TME components of breast cancer are underway. However, the complexity of the TME and its impact on the evasion of anti-tumor immunity necessitate further research to develop novel and improved breast cancer therapies. The multifaceted nature of breast TME cells arises from their phenotypic and functional plasticity, which endows them with both pro and anti-tumor roles during tumor progression. In this review, we discuss current understanding and recent advances in the pro and anti-tumoral functions of TME cells and their implications for developing safe and effective therapies to control breast cancer progress.