Proteogenomics analysis to identify acquired resistance-specific alterations in melanoma PDXs on MAPKi therapy [WES]
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ABSTRACT:
PROVIDER: PRJNA1108300 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR28919635_1.fastq.gz | Fastqsanger.gz | |||
| SRR28919635_2.fastq.gz | Fastqsanger.gz | |||
| SRR28919636_1.fastq.gz | Fastqsanger.gz | |||
| SRR28919636_2.fastq.gz | Fastqsanger.gz | |||
| SRR28919637_1.fastq.gz | Fastqsanger.gz |
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Project description: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.
2024-05-10 | GSE266735 | GEO
Project description:Proteogenomics analysis to identify acquired resistance-specific alterations in melanoma PDXs on MAPKi therapy [RNA-seq]
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Project description: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.
2024-05-10 | GSE266762 | GEO
Project description: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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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
2015-09-15 | E-GEOD-65185 | biostudies-arrayexpress
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 transcriptomic analysis using Affymetrix HuGene 2.1 microarray
2015-09-15 | E-GEOD-65184 | biostudies-arrayexpress
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 DNA methylation analysis using Illumina Human Methylation 450K bead chips
2015-09-15 | E-GEOD-65183 | biostudies-arrayexpress
Project description:Non-genomic and Immune Evolution in Melanoma with Acquired MAPKi Resistance
| PRJNA273358 | ENA
Project description:MAPK inhibitor (MAPKi) therapy in melanoma leads to accumulation of tumor-surface PD-L1/2, which may evade antitumor immunity and accelerate acquired resistance. Here, we discover that the E3 ligase ITCH binds, ubiquitinates, and down-regulates tumor-surface PD-L1/L2 in MAPKi-treated human melanoma cells, thereby modulating activation of co-cultured T cells. During MAPKi therapy in vivo, tumor cell-intrinsic ITCH knockdown in murine melanoma induced tumor-surface PD-L1, reduced intratumoral cytolytic CD8+ T cells, and accelerated acquired resistance only in immune-proficient mice. Conversely, tumor cell-intrinsic ITCH over-expression reduced MAPKi-elicited PD-L1 accumulation, augmented cytolytic CD8+ T-cell infiltration, and suppressed acquired resistance in BrafMUT, NrasMUT, and Nf1MUT murine melanoma and KrasMUT pancreatic cancer models. CD8+ T-cell depletion and tumor cell-intrinsic PD-L1 over-expression nullified the ability of ITCH over-expression to suppress MAPKi-resistance, supporting in vivo the ITCH–PD-L1–T-cell regulatory axis demonstrated in human cancer cell lines. Moreover, we identified a small-molecular ITCH activator which suppressed acquired MAPKi-resistance in vivo. Thus, MAPKi-elicited tumor-surface PD-L1 accelerates acquired-resistance, and degrading PD-L1 by activating ITCH may be a combinatorial approach to promote antitumor T-cell immunity and durable responses.
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