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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.

105 breast tumours previously characterized by the TCGA were selected for proteomic analysis after histopathological documentation (Supplementary Tables 1 and 2). The cohort included a balanced representation of PAM50-defined intrinsic subtypes⁹ including 25 basal-like, 29 luminal A, 33 luminal B, and 18 HER2 (ERBB2)-enriched tumours, along with 3 normal breast tissue samples. Samples were analysed by high-resolution accurate-mass tandem mass spectrometry (MS/MS) that included extensive peptide fractionation and phosphopeptide enrichment (Extended Data Fig. 1a). An isobaric peptide labelling approach (iTRAQ) was employed to quantify protein and phosphosite levels across samples, with 37 iTRAQ 4-plexes analysed in total. A total of 15,369 proteins (12,405 genes) and 62,679 phosphosites were confidently identified with 11,632 proteins per tumour and 26,310 phosphosites per tumour on average (Supplementary Tables 3, 4 and Supplementary Methods). After filtering for observation in at least a quarter of the samples (Supplementary Methods, Extended Data Fig. 1b), 12,553 proteins (10,062 genes) and 33,239 phosphosites, with their relative abundances quantified across tumours, were used in subsequent analyses in this study. Stable longitudinal performance and low technical noise were demonstrated by repeated interspersed analyses of a single batch of patient-derived luminal and basal breast cancer xenograft samples¹⁰ (Extended Data Fig. 1d, e). Owing to the heterogeneous nature of breast tumours^11,12,13, and because proteomic analyses were performed on tumour fragments that were different from those used in the genomic analyses, rigorous pre-specified sample and data quality control metrics were implemented^14,15 (Supplementary Discussion and Extended Data Figs 2, 3). Extensive analyses concluded that 28 of the 105 samples were compromised by protein degradation. These samples were excluded from further analysis with subsequent informatics focused on the 77 tumour samples and three biological replicates.