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MAPK-related gene signature predicting MAPKi sensitivity in pLGG - McGill cohort

ABSTRACT: MAPK inhibitor sensitivity scores (MSS) were developed to predict sensitivity to MAPK inhibitors in pediatric low-grade gliomas (pLGG). The scores were validated in pLGG cell lines in vitro and in the publicly available Open Pediatric Brain Tumor Atlas dataset. Validation in independent datasets is warranted.

ORGANISM(S): Homo sapiens

PROVIDER: GSE222405 | GEO | 2023/06/28

REPOSITORIES: GEO

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Project description:MAPK inhibitor sensitivity scores (MSS) were developed to predict sensitivity to MAPK inhibitors in pediatric low-grade gliomas (pLGG). The scores were validated in pLGG cell lines in vitro and in the publicly available Open Pediatric Brain Tumor Atlas dataset. Validation in independent datasets is warranted.

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Drug-class specific gene-based MAPK sensitivity scores predict sensitivity to MAPK inhibitors in pediatric low-grade gliomas

Project description:Pediatric low-grade gliomas (pLGG) have shown heterogeneous responses to MAPK inhibitors (MAPKi) in clinical trials. A predictive feature for stratification is needed to identify patients likely to benefit from MAPKi therapy. MAPK-related genes differentially regulated between MAPKi sensitive and non-sensitive cell lines from the Genomics of Drug Sensitivity in Cancer dataset identified class-specific MAPKi sensitivity gene signatures used to calculate the MAPKi sensitivity score (MSS) via single sample gene set enrichment analysis. The MSS discerned gliomas with varying MAPK alterations from those without, and was higher in pLGG compared to other pediatric CNS tumors. As in clinical trials, the MSS was heterogeneous within pLGGs with a common MAPK alteration. A positive correlation between the MSS and the predicted immune infiltration determined by the ESTIMATE signature was observed. The MSS therefore represents a potential tool for the stratification of pLGG patients, worth of further investigation in upcoming clinical trials. Our data could support a role of microglia in the response to MAPKi, warranting further validation.

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Project description:Melanoma resistance to MAPK- or T cell checkpoint-targeted therapies represents a major clinical challenge, and treatment failures of MAPK-targeted therapies due to acquired resistance often require salvage immunotherapies. We show that genomic analysis of acquired resistance to MAPK inhibitors revealed key driver genes but failedto adequately account for clinical resistance. From a large-scale comparative analysis of temporal transcriptomes from patient-matched tumor biopsies, we discovered highly recurrent differential expression and signature outputs of c-MET, LEF1 and YAP1 as drivers of acquired MAPK inhibitor resistance. Moreover, integration of gene- and signature-based transcriptomic analysis revealed profound CD8 T cell deficiency detected in half of resistant melanomas in association with downregulation of dendritic cells and antigen presentation. We also propose a major methylomic basis to transcriptomic evolution under MAPK inhibitor selection. Thus, this database provides a rich informational resource, and the current landscape represents a benchmark to understanding melanoma therapeutic resistance. Melanoma biopsies pre and post MAPKi treatment were sent for RNAseq analysis

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