患者来源的肿瘤-免疫类器官捕捉功能与机制界面，用于预测结直肠癌患者对标准疗法和免疫疗法的应答

Background: Colorectal cancer (CRC) is an emerging challenge, with rising early onset incidence and high mortality among younger individuals. Curative outcomes remain difficult due to its complexity. While chemotherapy and targeted drugs remain standard, immune checkpoint inhibitors (ICI) and engineered CAR-T are advancing as promising therapy options. Objectives: Here we report the development of Aryastha BioSolution®, an integrated patient-derived tumor-immune organoid platform designed to predict therapeutic responses in CRC. The mechanistic interface of this platform enables parallel assessment of agents, ICI, and adoptive cell therapies, while capturing patient specific tumor-immune interaction dynamics that underlie treatment sensitivity and resistance. Experimental procedure: Patient Derived Tumor Organoids (PDTOs) were established from surgically resected colorectal tumors and maintained in 3D milieu. PDTOs were treated with human equivalent doses of Oxaliplatin and Capecitabine and tumor killing was measured by live/dead staining. PDTOs were also co-cultured with human immune cells (PBMCs or engineered CAR-Ts) for 72 hours. Dynamics of tumor-immune engagement and therapy-induced organoid killing was tracked using time-lapse live imaging. Modulatory effects of ICI and CAR-T and their inflammatory responses were determined 72 hours post-culture by IFN-gamma and chemokines levels. Results: Early passage PDTOs retained the core genomic and phenotypic landscape of parent tumors, including point mutations, copy-number alterations, microsatellite (MSI) profile, as well as viability (Ki67) and histopathology signatures. Evaluation of SOC regimens showed that PDTO sensitivity markedly correlated with clinical treatment outcomes as measured by PET-CT. Co-culture assays showed distinct infiltration and killing trajectories of ICI treated PBMCs and CAR-T, characterized by robust cytolytic activity and close to 50% tumor volume reduction. We identified augmented IFN-gamma and proinflammatory chemokines in responder PDTOs. Genomic profile (MSI-H/MMRd, tumor mutational burden, transcriptomic profile) and reactivity of tumor using these functional readouts underscore the mechanism of response and non-response which align with their known clinical trends. Conclusions: The PDTO platform effectively bridges the translational gap that conventional models fail to overcome. Aryastha BioSolutions® provides a clinically aligned drug-response system that captures the phenotypic diversity of CRC and delineates the biology distinguishing responders from non-responders, enabling rational therapeutic combinations. The platform's high translatability positions it to strengthen clinical trial design and personalize both standard and emerging immunotherapy approaches.