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

ABSTRACT: 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.

ORGANISM(S): Mus musculus Homo sapiens

PROVIDER: GSE319338 | GEO | 2026/07/27

REPOSITORIES: GEO

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Project description:Background: Signaling by receptor tyrosine kinases (RTK) is frequently dysregulated in gliomas. Inter-individual variability in the causes for dysregulated RTK signaling may have hampered the efficacy of targeted therapies. Using gene expression modules around key regulators in the RAS-RAF-MEK-MAPK cascade and in the phosphatidylinositol 3-kinase-AKT pathways, we developed a âRMPAâ clustering scheme to distinguish gliomas with varying extents of RTK signaling. Results: We identified gene modules consistently co-expressed with NF1 (NF1-M), Sprouty (SPRY-M) and PTEN (PTEN-M) in gliomas. Their signatures enabled robust clustering of adult diffuse gliomas of WHO grades II-IV into RMPAhigh and RMPAlow phenotypes in a morphology-independent manner. In five independent data sets from three continents containing more than 1500 adult diffuse gliomas, RMPAhigh gliomas were associated with poor prognosis while RMPAlow gliomas were not. The RMPAhigh and RMPAlow glioma subtypes showed distinct levels of the activities of RAS-RAF-MEK-MAPK cascade and PI3K-AKT pathway and harbored unique sets of genomic alterations in the RTK signaling-related genes. The RMPAhigh gliomas contained large numbers of immature vessel cells and tumor associated macrophages and both cell types expressed high levels of pro-angiogenic RTKs including MET, VEGFR1, KDR, EPHB4 and NRP1. Conclusion: Inter-glioma variability in RTK signaling activities can be defined using the RMPA clustering scheme. The combined signatures of NF1-M, SPRY-M and PTEN-M reflect RTK signaling activity both in the glioma cells and in the glioma microenvironment. Our data show that RTK signaling in the glioma microenvironment may play a pivotal role in glioma progression. Transcriptome data from 22 fresh gliomas (2 astrocytoma II, 1 oligodendrocytoma II, 7 oligoastrocytoma II, 4 anaplastic oligoastrocytoma III and 8 GBM) were obtained using Affymetrix Human Gene 1.0 ST Array. Unsupervised hierarchical clustering of the expression data for the SPRY-M, NF1-M and PTEN-M was performed on these transcriptome data to identify samples with RMPAhigh or RMPAlow signature.

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

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