Abstract
The MM500 meta‐study aims to establish a knowledge basis of the tumor proteome to serve as a complement to genome and transcriptome studies. Somatic mutations and their effect on the transcriptome have been extensively characterized in melanoma. However, the effects of these genetic changes on the proteomic landscape and the impact on cellular processes in melanoma remain poorly understood. In this study, the quantitative mass‐spectrometry‐based proteomic analysis is interfaced with pathological tumor characterization, and associated with clinical data. The melanoma proteome landscape, obtained by the analysis of 505 well‐annotated melanoma tumor samples, is defined based on almost 16 000 proteins, including mutated proteoforms of driver genes. More than 50 million MS/MS spectra were analyzed, resulting in approximately 13,6 million peptide spectrum matches (PSMs). Altogether 13 176 protein‐coding genes, represented by 366 172 peptides, in addition to 52 000 phosphorylation sites, and 4 400 acetylation sites were successfully annotated. This data covers 65% and 74% of the predicted and identified human proteome, respectively. A high degree of correlation (Pearson, up to 0.54) with the melanoma transcriptome of the TCGA repository, with an overlap of 12 751 gene products, was found.Mapping of the expressed proteins with quantitation, spatiotemporal localization, mutations, splice isoforms, and PTM variants was proven not to be predicted by genome sequencing alone. The melanoma tumor molecular map was complemented by analysis of blood protein expression, including data on proteins regulated after immunotherapy. By adding these key proteomic pillars, the MM500 study expands the knowledge on melanoma disease.
Highlights
Malignant melanoma is the deadliest of skin cancers[1]
It was found that 2608 proteins included in the full human proteome were not identified in the present melanoma data, nor were any corresponding transcripts detected in the The Cancer Genome Atlas (TCGA) data
We explored our ability to identify melanoma key mutations by including amino acid sequences containing known driver mutations of the disease in the database used for protein identification
Summary
∙ A melanoma proteome landscape, complementing genome and transcriptome studies. ∙ Mass-spectrometry-based analysis of almost 16 000 tumor proteins, PTM variants, driver mutations, and missing proteins, reaches 65% and 74% of the predicted and identified human proteome, respectively. ∙ A melanoma proteome landscape, complementing genome and transcriptome studies. ∙ Mass-spectrometry-based analysis of almost 16 000 tumor proteins, PTM variants, driver mutations, and missing proteins, reaches 65% and 74% of the predicted and identified human proteome, respectively. The MM500 meta-study aims to establish a knowledge basis of the tumor proteome to serve as a complement to genome and transcriptome studies. The melanoma proteome landscape, obtained by the analysis of 505 well-annotated melanoma tumor samples, is defined based on almost 16 000 proteins, including mutated proteoforms of driver genes. This data covers 65% and 74% of the predicted and identified human proteome, respectively. Funding information Conselho Nacional de Desenvolvimento Científico e Tecnológico, Grant/Award Numbers: 440613/2016-7, 308341-2019-8; Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro, Grant/Award Number: E-26/210.173/2018; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Grant/Award Number: 88887.130697; Országos Tudományos Kutatási Alapprogramok, Grant/Award Numbers: OTKA-NKFI, K-125509; Fru Berta Kamprads Stiftelse; Mats and Stefan Paulsson Trust; National Research Foundation of Korea, Grant/Award Numbers: MSIP, 2015K1A1A2028365
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