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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.
Global proteome and phosphoproteome data have been acquired for 105 TCGA breast cancer samples using iTRAQ (isobaric Tags for Relative and Absolute Quantification) protein quantification methods. Samples were selected from each of the 4 breast tumor subtypes (Luminal A, Luminal B, Basal-like, HER2-enriched) described in the publication, Comprehensive molecular portraits of human breast tumors (Cancer Genome Atlas Network, Nature 2012).
Three TCGA samples and 1 common internal reference control sample are included in each iTRAQ experiment, consisting of 25 proteome and 13 phosphoproteome files. The internal reference is comprised of a mixture of 40 TCGA samples (of the 105 breast cancer samples) with equal representation of the 4 breast subtypes. Three of the TCGA samples have been assayed in duplicate for quality control purposes.
05TCGA_AO-A12D-01A_AN-A04A-01A_BH-A0AV-01A_Proteome_BI iTRAQ proteome data were acquired twice, before (20130310) and after (20130416) maintenance of the Q Exactive MS system. The "20130416" dataset was used in the final publication. The replicate dataset 05TCGA_AO-A12D-01A_AN-A04A-01A_BH-A0AV-01A_Proteome_BI_20130310_Replicate can be obtained here.
Global proteome and phosphoproteome data were acquired for three normal breast samples in Experiment 37. Samples "263d3f-I", "blcdb9-I", and "c4155b-C" are normal breast tissue samples that were measured in the iTRAQ-114, -115, and -116 channels, respectively. All normal samples were compared to the internal reference sample in the iTRAQ-117 channel (see CPTAC, TCGA Breast Cancer iTRAQ Sample Mapping file below).
Additional supplementary datasets are provided below that were too large to store at Nature Journal:
Information on the complete TCGA Breast invasive carcinoma cohort (BRCA) can be found here.
Genomic data for the 105 TCGA samples used in the CPTAC Proteome study can be downloaded from here.
Principal Investigators: (in alphabetical order) |
Steven A. Carr, Broad Institute of MIT and Harvard, United States |
Submitting User: | cptac |
Mertins P, Mani DR, Ruggles KV, Gillette MA,, Clauser KR, Wang P, Wang X, Qiao JW, Cao S, Petralia F, Kawaler E, Mundt F,, Krug K, Tu Z, Lei JT, Gatza ML, Wilkerson M, Perou CM, Yellapantula V, Huang KL, Lin C, McLellan MD, Yan P, Davies SR, Townsend RR, Skates SJ, Wang J, Zhang B, Kinsinger CR, Mesri M, Rodriguez H, Ding L, Paulovich AG, Fenyƶ D, Ellis MJ, Carr SA; NCI CPTAC.
Proteogenomics connects somatic mutations to signalling in breast cancer.
Nature. 2016 Jun 2;534(7605):55-62. doi: 10.1038/nature18003. Epub 2016 May 25.
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