Understanding the cellular and functional changes in the immune tumor microenvironment of glioblastoma during progression and treatments.

Project Summary Glioblastoma (GBM) is an incurable primary malignant brain cancer characterized by a high degree of interpatient and intratumoral genomic and cellular heterogeneity, a brief median survival (~15 months), and absence of an effective treatment. Even the successes of checkpoint blockade immunotherapies observed in many cancers have not translated to GBM. The GBM tumor immune microenvironment (TIME) is highly immunosuppressive and is dominated by resident and infiltrating myeloid cells (30-40% of the tumor mass) compared to rare T cells (<5%). Although recent single-cell RNA-sequencing (scRNAseq) studies have provided broad characterization of the cellular makeup and evolution of GBM tumor cells, dissecting the diversity, function and regional localization of the immune composition of GBM remains incomplete. There is also a widespread lack of knowledge on the evolution of intratumoral immune cells during GBM progression, and throughout treatment with standard of care (SOC) therapies (ionizing radiation/ temozolomide/dexamethasone IR/TMZ/DEX). Major challenges to achieving scientific and clinical impact in GBM remain, including an in-depth understanding of the interactions between cancer cells and the immune microenvironment in the context of SOC and immunotherapy treatments. Such knowledge is difficult to obtain using freshly excised patient samples. The main hypothesis of the proposal is that critical and clinically relevant changes in GBM neoplastic and immune cells brought about by treatment modalities can be revealed using genetically accurate mouse models to parse and redirect analyses of human patient datasets. A mechanistic understanding of the effects of therapies on immune and tumorigenic cell population dynamics in pre-clinical mouse models in combination with analysis of human patient datasets will yield transformative advancements in the field. We will leverage archival patient samples, mouse models of GBM and GLASS consortium datasets to uncover SOC-related cellular and molecular evolutionary changes using scRNA seq and spatial transcriptomics. We will also unveil factors determining sensitivity and resistance to checkpoint blockade therapy. By integrating detailed mouse and human data, we will identify areas of unrecognized therapeutic vulnerabilities and pave the way for the development of new treatment approaches.