Microbiome-Mediated Tumor Immunomodulation in a Pathomimetic Colorectal Cancer Chip - ABSTRACT Immune checkpoint inhibitors (ICI) have demonstrated notable efficacy in various cancers, yet the majority of colorectal cancer (CRC) patients with mismatch repair-proficient (MMR-p) and microsatellite-stable (MSS) tumors do not respond to ICI-based immunotherapy. Recent research suggests that the gut microbiome may influence the outcome of ICI-mediated cancer immunotherapy in certain cancers. However, the precise molecular mechanisms underlying the immunomodulatory tumor-microbiome crosstalk and its impact on tumor immune checkpoint molecules (ICM) and immunotherapy outcomes in unresponsive tumors remain poorly understood. In this proposal, we aim to profile patient-specific tumor-microbiome interactions and conduct quantitative molecular analyses to elucidate microbiome-mediated modulation of ICMs in MMR-p MSS colorectal tumors. We will utilize patient-derived tumors or normal organoids in a pathomimetic CRC Chip model. Our overarching goal is to provide a strategic roadmap and personalized workflow to enhance immunotherapeutic effects on non-responsive colorectal tumors by quantitatively assessing and robustly validating various tumor- microbiome interactions. Preliminary studies from our NCI IMAT R21 program (R21CA236690, completed) have demonstrated that patient-derived tumor or tumor-adjacent normal organoids can verify a patient's pathological characteristics. We have also established 3D tumor microenvironment and tumor-microbiome co-cultures in a Gut-on-a-chip platform, showing that co-culture with Bifidobacterium adolescentis substantially reduces PD-L1 expression on MMR-p MSS colorectal tumors, followed by CTL-mediated tumor eradication in a CRC Chip. In this project, we will conduct cellular and molecular phenotyping of tumor ICMs under tumor-microbiome interactions (Aim 1), examine microbial immunomodulation on normal epithelium adjacent to tumors (Aim 2), and validate microbiome-mediated ICM perturbations in the presence of paired fecal microbiota (Aim 3). We envision that our personalized pre-clinical CRC Chip model will have translational and transformative impacts, as the expected outcomes can generate implementable databases reflecting patient genetics, demographic impact, quantitative molecular phenotyping, and improved responsiveness to immunotherapy.