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Proteogenomics connects somatic mutations to signalling in breast cancer

Authors :
Yan, Ping
Petralia, Francesca
Wang, Pei
Huang, Kuan-Lin
Davies, Sherri R.
Carr, Steven A.
Mesri, Mehdi
Wang, Xianlong
Mani
Krug, Karsten
Wilkerson, Matthew
Paulovich, Amanda G.
Fenyƶ, David
Ruggles, Kelly V.
Lei, Jonathan T.
Mertins, Philipp
Kawaler, Emily
Qiao, Jana W.
Tu, Zhidong
Wang, Jing
Clauser, Karl R.
Ellis, Matthew J.
Kinsinger, Christopher R.
Gatza, Michael L.
Lin, Chenwei
Cao, Song
Mundt, Filip
Yellapantula, Venkata
Townsend, R. Reid
Gillette, Michael A.
Zhang, Bing
Ding, Li
Skates, Steven J.
Rodriguez, Henry
Perou, Charles M.
McLellan, Michael D.
Publication Year :
2016
Publisher :
The University of North Carolina at Chapel Hill University Libraries, 2016.

Abstract

Somatic mutations have been extensively characterized in breast cancer, but the effects of these genetic alterations on the proteomic landscape remain poorly understood. 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 allowed insights into the somatic cancer genome including the consequences of chromosomal loss, such as the 5q deletion characteristic of basal-like breast cancer. The 5q trans effects were interrogated against the Library of Integrated Network-based Cellular Signatures, thereby connecting CETN3 and SKP1 loss to elevated expression of EGFR, and SKP1 loss also to increased SRC. Global proteomic data confirmed a stromal-enriched group 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. Besides 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 functional consequences of somatic mutations, narrows candidate nominations for driver genes within large deletions and amplified regions, and identifies therapeutic targets.

Details

Language :
English
Database :
OpenAIRE
Accession number :
edsair.doi...........a3ab96e6d732b893aae84289820a3eb4
Full Text :
https://doi.org/10.17615/mepw-5x28