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Individualized Proteogenomics Reveals the Mutational Landscape of Melanoma Patients in Response to Immunotherapy.

ABSTRACT: Immune checkpoint inhibitors are used to restore or augment antitumor immune responses and show great promise in the treatment of melanoma and other types of cancers. However, only a small percentage of patients are fully responsive to immune checkpoint inhibition, mostly due to tumor heterogeneity and primary resistance to therapy. Both of these features are largely driven by the accumulation of patient-specific mutations, pointing to the need for personalized approaches in diagnostics and immunotherapy. Proteogenomics integrates patient-specific genomic and proteomic data to study cancer development, tumor heterogeneity and resistance mechanisms. Using this approach, we characterized the mutational landscape of four clinical melanoma patients. This enabled the quantification of hundreds of sample-specific amino acid variants, among them many that were previously not reported in melanoma. Changes in abundance at the protein and phosphorylation site levels revealed patient-specific over-represented pathways, notably linked to melanoma development (MAPK1 activation) or immunotherapy (NLRP1 inflammasome). Personalized data integration resulted in the prediction of protein drug targets, such as the drugs vandetanib and bosutinib, which were experimentally validated and led to a reduction in the viability of tumor cells. Our study emphasizes the potential of proteogenomic approaches to study personalized mutational landscapes, signaling networks and therapy options.

SUBMITTER: Schmitt M

PROVIDER: S-EPMC8582461 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Individualized proteogenomics reveals mutational landscape of melanoma patients in response to immunotherapy

Project description:Immune checkpoint inhibitors are used to restore or augment antitumor immune response and show great promise in treatment of melanoma and other types of cancers. However, only a relatively small percentage of patients are fully responsive to immune checkpoint inhibition, mostly due to tumor heterogeneity and primary resistance to therapy. Both of these features are largely driven by accumulation of patient-specific mutations, pointing to the need for personalized approaches in diagnostics and immunotherapy. Proteogenomics integrates patient-specific genomic and proteomic data to study cancer development and resistance mechanisms, as well as tumor heterogeneity in individual patients. Here, we use a proteogenomic approach to characterize the mutational landscape of samples derived from four clinical melanoma patients at the genomic, proteomic and phosphoproteomic level. Integration of datasets enabled identification and quantification of an extensive number of sample-specific amino acid variants, among them many were not previously reported in melanoma. We detected a disproportional number of alternate peptides between treated and untreated (naïve) samples with a high potential to influence signal transduction. This is one of the first proteogenomic study designed to study the mutational landscape of patient-derived melanoma tissue samples in response to immunotherapy.

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Pre-Treatment Mutational and Transcriptomic Landscape of Responding Metastatic Melanoma Patients to Anti-PD1 Immunotherapy.

Project description:Immunotherapy, such as anti-PD1, has improved the survival of patients with metastatic melanoma. However, predicting which patients will respond to immunotherapy remains a significant knowledge gap. In this study we analyzed pre-immunotherapy treated tumors from 52 patients with metastatic melanoma and monitored their response based on RECIST 1.1 criteria. The responders group contained 21 patients that had a complete or partial response, while the 31 non-responders had stable or progressive disease. Whole exome sequencing (WES) was used to identify biomarkers of anti-PD1 response from somatic mutations between the two groups. Variants in codons G34 and G41 in NFKBIE, a negative regulator of NFkB, were found exclusively in the responders. Mutations in NKBIE-related genes were also enriched in the responder group compared to the non-responders. Patients that harbored NFKBIE-related gene mutations also had a higher mutational burden, decreased tumor volume with treatment, and increased progression-free survival. RNA sequencing on a subset of tumor samples identified that CD83 was highly expressed in our responder group. Additionally, Gene Set Enrichment Analysis showed that the TNFalpha signaling via NFkB pathway was one of the top pathways with differential expression in responders vs. non-responders. In vitro NFkB activity assays indicated that the G34E variant caused loss-of-function of NFKBIE, and resulted in activation of NFkB signaling. Flow cytometry assays indicated that G34E variant was associated with upregulation of CD83 in human melanoma cell lines. These results suggest that NFkB activation and signaling in tumor cells contributes to a favorable anti-PD1 treatment response, and clinical screening to include aberrations in NFkB-related genes should be considered.

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Pre- Treatment Mutational and Transcriptomic Landscape of Responding Metastatic Melanoma Patients to Anti-PD1 Immunotherapy

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Proteomics of Melanoma Response to Immunotherapy Reveals Mitochondrial Dependence.

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Proteogenomics and Differential Ion Mobility Enable the Exploration of the Mutational Landscape in Colon Cancer Cells.

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