Distinct transcriptional and functional modules mediate resistance to targeted therapy in glioblastoma

Glioblastomas (GBM) harbor recurrent mutations in receptor tyrosine kinase (RTK) signaling, yet targeted therapy has shown limited efficacy. To dissect mechanisms underlying drug resistance, we combined single cell RNA-sequencing (scRNA-seq) and functional genomic screens following MEK or SHP2 inhibition in preclinical GBM models. ScRNA-seq of mouse intracranial xenografts revealed that although mesenchymal-like GBM subpopulation exhibits heightened sensitivity to both MEK or SHP2 inhibition, each targeted therapy induces distinct transcriptional signatures. Genome-wide CRISPR interference (CRISPRi) screens identified shared mediators of MEK or SHP2 inhibitor sensitivity enriched for the conserved downstream effector Ras/RAF/MEK pathway. However, genes uniquely mediating SHP2 inhibitor response were enriched for Ras/RAF/MEK-independent signaling modules such as SRC family kinases, GSK3B, and SMAD proteins regulating cell adhesion and differentiation. Perturb-seq of 39 target genes following MEK or SHP2 inhibition identified 10 discrete clusters with distinct effects on Ras signaling and cellular phenotypes. Proliferation and differentiation gene expression signatures clustered genetic perturbations into 4 broad classes: cell cycle regulators, positive effectors of Ras/RAF/MEK signaling, negative regulators of Ras/RAF/MEK signaling, or parallel regulators of Ras/RAF/MEK independent pathways. Combinatorial linear modeling from transcriptional signatures identified multiple gene-drug relationships including expected synergistic and potentiation combinations between MEK, SHP2, and CDKN2A/B and unexpected antagonistic and neomorphic interactions with indirect effectors such as LZTR1 and RAC1. Finally, preclinical testing of predicted synergistic inhibitor combinations with MEK, SHP2, and CDK4/6 inhibition demonstrated improved efficacy compared to molecular monotherapy in multiple GBM preclinical models. Taken together, our approach provides a systems-level framework for understanding RTK-Ras signaling network principles and targeted therapy resistance in glioblastoma.