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Individualized Proteogenomics Reveals the Mutational Landscape of Melanoma Patients in Response to Immunotherapy.
Schmitt, Marisa; Sinnberg, Tobias; Niessner, Heike; Forschner, Andrea; Garbe, Claus; Macek, Boris; Nalpas, Nicolas C.
Affiliation
  • Schmitt M; Quantitative Proteomics, University of Tübingen, 72074 Tübingen, Germany.
  • Sinnberg T; Division of Dermatooncology, University of Tübingen, 72074 Tübingen, Germany.
  • Niessner H; Cluster of Excellence iFIT (EXC 2180) "Image-Guided and Functionally Instructed Tumor Therapies", University of Tuebingen, 72074 Tübingen, Germany.
  • Forschner A; Division of Dermatooncology, University of Tübingen, 72074 Tübingen, Germany.
  • Garbe C; Division of Dermatooncology, University of Tübingen, 72074 Tübingen, Germany.
  • Macek B; Division of Dermatooncology, University of Tübingen, 72074 Tübingen, Germany.
  • Nalpas NC; Cluster of Excellence iFIT (EXC 2180) "Image-Guided and Functionally Instructed Tumor Therapies", University of Tuebingen, 72074 Tübingen, Germany.
Cancers (Basel) ; 13(21)2021 Oct 28.
Article in En | MEDLINE | ID: mdl-34771574
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.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Cancers (Basel) Year: 2021 Document type: Article Affiliation country:

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Cancers (Basel) Year: 2021 Document type: Article Affiliation country:
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