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Development of in vitro 2D and 3D tumor-stroma microenvironment models to assess the impact of metabolic and oxygen gradients on the resistance to drugs and immunotherapies based on checkpoint inhibitors and CAR-T cells

Abstract

Metabolic and oxygen gradients influence the biology and distribution of tumor, stromal, and immune cells within the Tumor MicroEnvironment (TME), as well as in protective niches, such as the Bone Marrow and Lymph Nodes. These gradients orchestrate tumor escape mechanisms, reducing the efficacy of anti-cancer drugs, as well as immunotherapies, such as checkpoint inhibitor and adoptive cell therapies, including those based on CAR-T cells. Effects downstream hypoxia are partially mediated by adenosinergic signaling, trough the induction of adenosine-producing enzymes CD39/CD73 and repression of the nucleoside transporter ENT1, resulting in extracellular accumulation of immunosuppressive adenosine, as well as resistance to chemotherapeutic nucleoside analogs. There is a scarcity of physiologically-relevant straightforward experimental in vitro approaches to systematically explore these specific biological aspects of the TME. To tackle this, we propose to develop advanced in vitro 2D (coverslip hypoxia) and 3D (spheroid) immunocompetent tumor-stroma co-culture TME models, and apply automated quantitative fluorescence microscopy (High-Content Screening) and flow-cytometry. A fluorescent hypoxia probe will be used to identify cells within the normoxic or hypoxic compartments of the TME models, allowing the quantitative assessment of the infiltration, spatial distribution, proliferation, survival, and function of cells labeled with distinct fluorescent dyes. Fluorescent reagents will be used to quantitate apoptotic/dead cells and the expression of CD73, ENT1 and the stem-cell marker ALDH1A1. Tumor-stroma models with distinct cancer cell lines will be used to explore the effects of hypoxia-adenosinergic signaling in the immune-landscape of pancreatic cancer, CAR-T cell function in CD19+ lymphoma, and stemness and drug-resistance in acute myeloid leukemia. Single-cell scRNA-seq public data will also be used to quantify the relative frequencies of distinct cell types within the hypoxic or normoxic compartments of the TME. (AU)

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