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Abstract Immune dysfunction in cancer is enacted by multiple programs, including tumor cell-intrinsic responses to distinct immune subpopulations. A subset of these immune evasion programs can be systematically recapitulated through direct tumor-immune interactionsin vitro. Here, we present an integrated, high-throughput single-cell CRISPR screening framework focused on the protein kinome for mapping the tumor-intrinsic regulation of T cell-driven immune pressure in glioblastoma (GBM). We combine pooled CRISPR interference and activation (CRISPRi/a) with immune-matched NY-ESO-1 antigen-specific allogeneic GBM-T cell co-culture and massively multiplexed single-cell transcriptomics to systematically quantify how genetic perturbation reshapes baseline tumor state and adaptive responses across graded effector-to-target ratios. We further leverage deep generative models for analyzing pooled CRISPR screens to decipher the effects of genetic perturbations on the mechanisms of tumor resistance. This framework resolves distinct modules of immune evasion and survival, including the regulation of the antigen-presentation machinery, interferon/NF-κB signaling, oxidative stress resilience, and checkpoint/cytokine programs, while identifying perturbations that reroute the continuous tumor transcriptional trajectory induced by T cell engagement. A secondary chemical screen in patient-derived GBM cultures identified putative kinase targets of immune evasion phenotypes (e.g., EPHA2 and PDGFRA), whose inhibition leads to the blockade of evasive programs and enhances T cell-mediated GBM killing. Together, this workflow provides a scalable blueprint for comprehensive charting of the genetic control of tumor-immune interactions. 

Abstract Over-activation of the epidermal growth factor receptor (EGFR) is a hallmark of glioblastoma. However, EGFR-targeted therapies have led to minimal clinical response. While delivery of EGFR inhibitors (EGFRis) to the brain constitutes a major challenge, how additional drug-specific features alter efficacy remains poorly understood. We apply highly multiplex single-cell chemical genomics to define the molecular response of glioblastoma to EGFRis. Using a deep generative framework, we identify shared and drug-specific transcriptional programs that group EGFRis into distinct molecular classes. We identify programs that differ by the chemical properties of EGFRis, including induction of adaptive transcription and modulation of immunogenic gene expression. Finally, we demonstrate that pro-immunogenic expression changes associated with a subset of tyrphostin family EGFRis increase the ability of cytotoxic T-cells to eradicate tumor cells. Our study provides a framework that considers each agent’s unique and often unknown poly-pharmacology to prioritize compounds that induce clinically favorable molecular responses.