Mapping kinase-dependent tumor immune adaptation with multiplexed single-cell CRISPR screens

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 interactions in 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. Competing Interest Statement K.L.L. reports research support to DFCI from Bristol Meyers Squibb (BMS). R.R. is a founder of Genotwin and a member of the Scientific Advisory Board of DiaTech and Flahy. The other authors declare no competing interests. Footnotes We obtained additional hashing reads for the CRISPRa library and updated the analysis accordingly. Supplementary files updated.