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The integration of single-cell genomics into the chemical genetics paradigm is reshaping how researchers profile drug activity, prioritize lead candidates, and uncover new therapeutic opportunities. Traditional chemical genetic approaches, though instrumental in linking compounds to cellular phenotypes, often rely on bulk measurements that obscure important cellular heterogeneity and limit insight into mechanisms of action. By contrast, single-cell technologies offer a transformative view of how compounds influence diverse cell types and states, capturing nuanced molecular responses that further our understanding of efficacy, resistance, and polypharmacology. From cancer to neurodegenerative disorders and other disease contexts, single-cell chemical profiling enables a more precise annotation of drug-induced effects, revealing differential responses across cellular subpopulations. These methods help identify both beneficial and adverse outcomes that may not be readily predicted by a compound’s structure or known targets, enhancing preclinical prioritization and supporting rational drug repurposing strategies. As these technologies mature, advances in multiplexing, multimodal profiling, and computational analysis are expanding their scalability and applicability to increasingly complex models. The resulting data-rich assays are poised to bridge critical gaps between compound screening and clinical relevance. This review highlights the evolution of chemical genomics toward single-cell resolution and outlines emerging opportunities to leverage these methods throughout the drug discovery pipeline, from early preclinical prioritization to late-stage repurposing, ultimately accelerating the development of safer, more effective therapies. 

Abstract The protein tyrosine phosphatase SHP2, encoded byPTPN11, is an important regulator of Ras/MAPK signaling that acts downstream of receptor tyrosine kinases and other transmembrane receptors. GermlinePTPN11mutations cause developmental disorders such as Noonan Syndrome, whereas somatic mutations drive various cancers. While many pathogenic mutations enhance SHP2 catalytic activity, others are inactivating or affect protein interactions, confounding our understanding of SHP2-driven disease. Here, we combine single-cell transcriptional profiling of cells expressing clinically diverse SHP2 variants with protein biochemistry, structural analysis, and cell biology to explain how pathogenic mutations dysregulate signaling. Our analyses reveal that loss of catalytic activity does not phenocopy SHP2 knock-out at the gene expression level, that some mechanistically distinct mutations have convergent phenotypic effects, and that different mutations at the same hotspot residue can yield divergent cell states. These findings provide a framework for understanding the connection between SHP2 structural perturbations, cellular outcomes, and human diseases. 

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. 

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.