ArticleCancer science2026
Genotype-Informed Whole-Animal Kinome Screening Reveals Shared Kinase Vulnerabilities Across Driver Contexts in PDAC.
Article in Cancer science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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11 authors.
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Abstract
Pancreatic ductal adenocarcinoma (PDAC) frequently harbors co-occurring alterations in KRAS, TP53, CDKN2A, and SMAD4, yet how clinically prevalent driver combinations shape kinase dependencies remains incompletely understood. To systematically interrogate genotype-dependent and shared vulnerabilities, we generated Drosophila models representing dominant PDAC driver contexts, including 2-hit (KRAS-TP53) and 3-hit (KRAS-TP53-CDKN2A or KRAS-TP53-SMAD4) genotypes, and conducted comparative whole-animal genetic screening using organismal viability as a phenotypic readout. This approach identified both genotype-specific modifiers and a subset of kinases whose suppression consistently improved viability across distinct genetic contexts, enabling prioritization of conserved candidates for cross-species validation. Among these, the Drosophila kinase Drak, orthologous to human STK17A/STK17B, emerged as a recurrent shared vulnerability. Functional validation in three-dimensional spheroid cultures of human PDAC cell lines representing distinct driver genotypes demonstrated that STK17B perturbation impairs spheroid growth across models. Transcriptomic profiling further revealed coordinated downregulation of gene sets linked to DNA replication and E2F-driven cell-cycle programs upon STK17B knockdown. Together, these findings establish a genotype-informed screening framework for systematic discovery of shared and context-dependent kinase dependencies in PDAC, and nominate STK17B as a conserved genetic vulnerability across dominant driver contexts.
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