Myranda Maynard

TL;DR: Proteogenomics involves the integrative analysis of genomic, transcriptomic, proteomic and post-translational modification data produced by next-generation sequencing and mass spectrometry-based proteomics, and PANOPLY—a cloud-based platform for automated and reproducible proteogenomic data analysis is developed.

Abstract: We investigate the impact of germline variants on cancer patients' proteomes, encompassing 1,064 individuals across 10 cancer types. We introduced an approach, "precision peptidomics," mapping 337,469 coding germline variants onto peptides from patients' mass spectrometry data, revealing their potential impact on post-translational modifications, protein stability, allele-specific expression, and protein structure by leveraging the relevant protein databases. We identified rare pathogenic and common germline variants in cancer genes potentially affecting proteomic features, including variants altering protein abundance and structure and variants in kinases (ERBB2 and MAP2K2) impacting phosphorylation. Precision peptidome analysis predicted destabilizing events in signal-regulatory protein alpha (SIRPA) and glial fibrillary acid protein (GFAP), relevant to immunomodulation and glioblastoma diagnostics, respectively. Genome-wide association studies identified quantitative trait loci for gene expression and protein levels, spanning millions of SNPs and thousands of proteins. Polygenic risk scores correlated with distal effects from risk variants. Our findings emphasize the contribution of germline genetics to cancer heterogeneity and high-throughput precision peptidomics.

TL;DR: Monte as discussed by the authors is a highly sensitive multi-omic native tissue enrichment workflow that enables serial, deep-scale analysis of HLA-I and HLAII immunopeptidome, ubiquitylome, proteome, phosphoproteome, and acetylome from the same tissue sample.