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Proteogenomics analysis to identify acquired resistance-specific alterations in melanoma PDXs on MAPKi therapy [RNA-seq]

GSE266762 Homo sapiens Expression profiling by high throughput sequencing 5 samples Submitted 2024/05/10 Platform GPL24676
Summary
Therapeutic approaches to treat melanoma include small molecule drugs that target activating protein mutations in pro-growth signaling pathways like the MAPK pathway. While beneficial to the approximately 50% of patients with activating BRAFV600 mutation, mono- and combination therapy with MAPK inhibitors is ultimately associated with acquired resistance. To better characterize the mechanisms of MAPK inhibitor resistance in melanoma, we utilize patient-derived xenografts and apply proteogenomic approaches leveraging genomic, transcriptomic, and proteomic technologies that permit the identification of resistance-specific alterations and therapeutic vulnerabilities. A specific challenge for proteogenomic applications comes at the level of data curation to enable multi-omics data integration. Here, we present a proteogenomic approach that uses custom curated databases to identify unique resistance-specific alternations in melanoma PDX models of acquired MAPK inhibitor resistance. We demonstrate this approach with a NRASQ61L melanoma PDX model from which resistant tumors were developed following treatment with a MEK inhibitor. Our multi-omics strategy addresses current challenges in bioinformatics by leveraging development of custom curated proteogenomics databases derived from individual resistant melanoma that evolves following MEK inhibitor treatment and is scalable to comprehensively characterize acquired MAPK inhibitor resistance across patient-specific models and genomic subtypes of melanoma.
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Direct links to NCBI, no account and no request form: the whole study as GSE266762_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 5 samples. Raw sequencing reads are also available from ENA.

Also filed as BioProject PRJNA1108320 and SRA study SRP506001. Searching any of these in the dataset finder brings you back here.

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