Proteogenomics Connects Somatic Mutations to Signalling in Breast Cancer

Mertins P, Mani DR, Ruggles KV, Gillette MA, Clauser KR, Wang P et al., Nature (2016) doi:10.1038/nature18003 Published online 25 May 2016

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:

  • Gene-by-Gene CNA-RNA and CNA-Protein Pearson correlations with p-values and Benjamini-Hochberg adjusted p-values
  • Phosphoproteome dataset "Phosphoproteome-P3": This table contains phosphosite iTRAQ log2 ratios for the 83 QC-passed samples (77 tumors + 3 tumor replicates + 3 normal breast samples). Phosphosite abundances are normalized (see Supplementary Methods, "Normalization").
  • Phosphoproteome raw files and datasets for PIK3CA- and TP53-mutant isogenic cell lines (TMT10-plex quantification; see Supplementary Methods)
  • Proteome Peptide Spectrum Match reports exported from Spectrum Mill for each of the 37 iTRAQ4 experiments, including the RefSeq FASTA file used for searches, and a Spectrum Mill quality metrics report

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.

Please include this attribution in publications:
“Data used in this publication were generated by the Clinical Proteomic Tumor Analysis Consortium (NCI/NIH).”

Biospecimens and Metadata Files

Clinical Data for Proteogenomics Connects Somatic Mutations to Signalling in Breast Cancer
CPTAC, TCGA Breast Cancer iTRAQ Sample Mapping
Folder, File, and Sample Naming

Data Types Available for Download

(ALL): Selection of this box downloads all data in the row
(raw): The original mass spectrometry(MS) instrument files
(mzML): HUPO-PSI standard raw data files generated from the original MS instrument files
(PSM): Peptide-Spectrum Match data
(prot): Protein assembly data and protein relative abundance
(meta): Clinical data files, mapping of biospecimens to iTRAQ labels or TMT10 labels (where applicable), folder and file naming conventions
Checksum files are included in all downloads for verification.

Peptide-Spectrum-Matches and Protein Summary Reports from the CPTAC Common Data Analysis Pipeline (CDAP) can be downloaded from here.

Data Sets


Data set name

BI The Broad Institute Steven A. Carr, Ph.D.