Abstract
Abstract Background: Immuno-oncology (IO) therapy with checkpoint inhibitors has demonstrated a higher response rate, duration of response, and overall survival than chemotherapy. However, predicting which FDA approved IO therapies or pharmaceutical agents, as well as best combinations and delivery sequence, will have optimal patient response remains a significant challenge for personalized medicine. Nilogen Oncosystem’s 3D-PREDICT is a novel ex vivo therapeutic investigative platform that provides a functional model of a patient’s tumor to investigate susceptibility to different therapeutic approaches directly. Derived from core biopsies, the 3D-PREDICT model captures the tumor heterogeneity while preserving the tumor microenvironment by retaining stromal components and cell-cell and cell-extracellular matrix interactions. Here, we employed the 3D-PREDICT platform to compare the efficacy of different immunotherapeutic approaches in various solid tumor indications ex vivo. Methods: Tumoroids from 18-gauge core biopsies from solid tumors were generated using Nilogen Oncosystems’s proprietary mechanical process forgoing any enzymatic digestion or propagation while keeping the spatial contexture of stroma intact. Pooled tumoroids were treated ex vivo for 72 hours with various standard-of-care mono or combo therapy (carboplatin, anti-programmed death-ligand 1 (PD-L1) antibody atezolizumab, anti-CD47 antibody magrolimab, anti-programmed cell death receptor-1 (PD-1) antibody nivolumab, or a combination of magrolimab and atezolizumab). Treatment-mediated immune modulation in tumor microenvironment were analyzed to predict patient response to subjected therapies. Results: Treatment-mediated tumor cell killing activity was evaluated using 3D high throughput confocal imaging and Nilogen Oncosystems’s proprietary algorithm for data analysis. The ex vivo response to checkpoint inhibitors was correlated with retrospective patient clinical information. Tumoroid samples treated with atezolizumab and magrolimab demonstrated enhanced tumor cell killing. Approximately 20% of tumors showed increased CD8 T-cell activation upon ex vivo treatment, correlating with proinflammatory cytokine release in conditioned media. Conclusions: The 3D-PREDICT ex vivo tumoroid platform provides a unique resource to predict patients’ response to treatment, potentially serving as a clinical diagnostic to guide clinical care and stratifying patient procurement into clinical trials. This would allow prospective assessment of therapeutic efficacy ex vivo to match each patient to the most effective and least toxic, to improving outcomes, reducing costs, and assigning therapeutics on a more rational basis. Citation Format: Jared Ehrhart, Seth Currlin, Michelle Ataya, Alliyah Humphrey, Rikhia Chakraborty. 3D-PREDICT - An ex vivo precision oncology and clinical trial enrichment platform by Nilogen Oncosystems [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 951.
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