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In vitro modeling of the tumor-immune microenvironment

Current Team Members: Kristen Shema, Emily Liu, Lorenzo Netti, Vibha Sheshadri

Former Team Members: Ruolan Zhou, Rachel Weathered

Dozens of tumor-immune microenvironment (TIME) targets are being explored to improve immunotherapy responses, as current immunotherapies only benefit a minority of patients. However, because different tumors exploit different mechanisms of immune evasion, there is a need for a predictive high-throughput in vitro model to determine how tumor-specific features of the TIME affect immunotherapy responses. Because current organoid tumor models have prioritized survival of the tumor parenchyma rather than the immune and stromal cells, they are suited for screening tumor-intrinsic therapies, such as tumor-targeting drugs and chemotherapies. To address this, we developed an in vitro culture platform that preserves immune and stromal features of the TIME and therefore we can screen tumor-extrinsic immunotherapies that rely on the endogenous immune response.

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In this platform, in vitro "avatars" of the tumor-immune circuit (TIvatar) are created from reconstituted tumors excised mice or humans with a connected upstream well containing immune cells from tumor-draining lymph nodes or blood; thus, most key cell types that shape immunotherapy response are present. This model preserves ex vivo immune, stromal and tumor cells in a 3D tumor-mimetic extracellular matrix seeded in series within a paper channel. TIvatar supports tumor viability and replicates features of immune activity in response to immunotherapy more effectively than state-of-the-art 3D organoid cultures (Figure 1).

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Because TIvatar maintains tumor, stromal cells, and immune cells in long-term culture, TIvatar enables users to conduct screening on therapies that rely on the endogenous immune repertoire in a manner that more closely resembles in vivo therapy outcome than current technologies. We validated that TIvatar recapitulates in vivo vulnerabilities across tumor models (Figure 2).

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Our team is currently utilizing the TIvatar platform to address various biological and therapy-driven questions in cancer immunology.

  • Kristen is using TIvatar to understand how different cell populations of the TIME contribute to immunotherapy response or nonresponse in various tumor models. In collaboration with UChicago Medicine, Kristen has also optimized TIvatar to screen immunotherapy response of freshly resected ovarian tumors. She will use this in vitroimmunotherapy response data to interrogate paired whole exome sequencing (WES) and single cell RNAseq (scRNAseq) datasets to identify tumor-intrinsic features that contribute to immunotherapy responsiveness in ovarian cancer patients.

  • Emily is interested in improving the therapeutic efficacy of immunotherapies in refractory or relapsed diffuse large b cell lymphoma (R/R DLBCL) patients. Inspired by previous immunogenomics research, Emily will use TIvatar to investigate the role of lymphangiogenesis in DLBCL models, focusing on the impact of lymphatic proliferation on the TIME and its subsequent influence on the responsiveness to chimeric antigen receptor T-cell (CAR-T) therapy.

  • Lorenzo is working on optimizing the platform for tumor compartment infiltration studies to assess CD8+ T cell fitness. The lab has previously shown how lymphatic endothelial cells prime naïve CD8+ T cells into a memory like state. We are extensively probing the phenotypic results of this education method. Simultaneously, using the TIvatar platform, we aim to tease out functional differences in the T cells when compared to the classical DC or antibody-based activation methods.

  • Vibha plans on using TIvatar to investigate how myeloid cell populations influence a tumor’s response to different therapies. She also plans on exploring changes in innate and adaptive immune cell interactions in different TIMEs.

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