Proteogenomics connects somatic mutations to signaling in breast cancer

By Philipp Mertins, D. Mani, K. Ruggles, Michael A. Gillette, Karl R. Clauser, Pei Wang, Xianlong Wang, Jana W. Qiao, Song Cao, F. Petralia and 26 more. Nature, 2016

1,509 citations recorded by the source corpus.

Somatic mutations have been extensively characterized in breast cancer, but the effects of these genetic alterations on the proteomic landscape remain poorly understood. Here we describe quantitative mass-spectrometry-based proteomic and phosphoproteomic analyses of 105 genomically annotated breast cancers, of which 77 provided high-quality data. Integrated analyses provided insights into the somatic cancer genome including the consequences of chromosomal loss, such as the 5q deletion characteristic of basal-like breast cancer. Interrogation of the 5q trans-effects against the Library of Integrated Network-based Cellular Signatures, connected loss of CETN3 and SKP1 to elevated expression of epidermal growth factor receptor (EGFR), and SKP1 loss also to increased SRC tyrosine kinase. Global proteomic data confirmed a stromal-enriched group of proteins in addition to basal and luminal clusters, and pathway analysis of the phosphoproteome identified a G-protein-coupled receptor cluster that was not readily identified at the mRNA level. In addition to ERBB2, other amplicon-associated highly phosphorylated kinases were identified, including CDK12, PAK1, PTK2, RIPK2 and TLK2. We demonstrate that proteogenomic analysis of breast cancer elucidates the functional consequences of somatic mutations, narrows candidate nominations for driver genes within large deletions and amplified regions, and identifies therapeutic targets. Quantitative mass-spectrometry-based proteomic and phosphoproteomic analyses of genomically annotated human breast cancer samples elucidates functional consequences of somatic mutations, narrows candidate nominations for driver genes within large deletions and amplified regions, and identifies potential therapeutic targets. This large-scale collaborative study describes quantitative-mass spectrometry-based proteomic and phosphoproteomic analyses of 105 breast cancer samples from The Cancer Genome Atlas (TCGA), representing the four principal mRNA-defined breast cancer intrinsic subtypes. The result is a high-quality proteomic resource for human breast cancer investigation, achieved using technologies and analytical approaches that illuminate the connections between genome and proteome. The data narrow candidate nominations for driver genes within large deletions and amplified regions, and identify potential therapeutic targets.

Subfields: Cancer Research, Oncology

View Paper: https://www.semanticscholar.org/paper/c9e3f9e9828c7a078e1d3f8652f12027e988e306

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Citations in the corpus

Comprehensive Analysis of Alternative Splicing Across Tumors from 8,705 Patients (2018, methodology): “…a list of candidate ASNs based on a pipeline of Clinical Proteomic Tumor Analysis Consortium (CPTAC) mass spectrometry (MS) data confirmation (Mertins et al., 2016; Zhang et al., 2016) andMHC-I binding affinity prediction (Andreatta and Nielsen, 2016) incorporating information on the human…”
The target landscape of clinical kinase drugs (2017, background): “For example, RIPK2 has recently been implicated as a target in breast cancer (42).”
Quantitative Proteomics of the Cancer Cell Line Encyclopedia (2020, positive): “Recently, proteomic studies of several cancers have rediscovered many of the same subtypes found by gene expression, as well as new disease categorizations, highlighting the gains from studying the proteome (Mertins et al., 2016; Pozniak et al., 2016; Zhang et al., 2014, 2016; Vasaikar et al., 2019)”
The functional landscape of the human phosphoproteome (2019, methodology): “The changes in phosphorylation for TF sites quantified across the 77 samples passing the CPTAC quality control criteria were correlated with their corresponding TF activities.”
A deep proteome and transcriptome abundance atlas of 29 healthy human tissues (2018, background): “Broader scale analyses have more recently become possible owing to advances in proteome and transcriptome profiling technologies, but these have mostly focussed on a single (disease) tissue or the cell-type resolved analysis of protein expression in single tissues (Zhang et al. 2014; Mertins et al. ”
Systems Biology and Multi-Omics Integration: Viewpoints from the Metabolomics Research Community (2019, background): “However, until such time that specialized high‐end instrumentation is more broadly available, FFPE analysis remains an issue for many researchers looking to perform multi‐omics experiments [30,31].”