Kuan-lin Huang, Mehdi Mesri, Sherri R. Davies, Filip Mundt, Li Ding, Matthew J. Ellis, R. Reid Townsend, Kelly V. Ruggles, Francesca Petralia, Mani, Philipp Mertins, David Fenyö, Karl R. Clauser, Jing Wang, Michael A. Gillette, Pei Wang, Bing Zhang, Matthew D. Wilkerson, Song Cao, Michael D. McLellan, Chenwei Lin, Michael L. Gatza, Xianlong Wang, Charles M. Perou, Amanda G. Paulovich, Nci Cptac, Venkata Yellapantula, Zhidong Tu, Steven J. Skates, Ping Yan, Jana Qiao, Jonathan T. Lei, Christopher R. Kinsinger, Steven A. Carr, and Henry Rodriguez
The genetic landscape of human breast cancer has been well defined in The Cancer Genome Atlas (TCGA) project. Mass spectrometry (MS)-based global proteome and phosphoproteome analyses provide a complementary, orthogonal approach to genomic studies to further improve the molecular taxonomy and biological understanding of breast cancer. We analyzed human breast cancer samples that had previously undergone comprehensive genomic and reversed phase protein array (RPPA) characterization by TCGA. Tumor samples were analyzed by global shotgun proteomics and phosphoproteomics at an unprecedented coverage of >11,000 quantified proteins and >27,000 phosphorylation sites for each tumor. We verified the translation of hundreds of genomically characterized single nucleotide and splice junction variants at the protein level. The correlation of mRNA to protein abundance was significant for 6,135 out of 9,302 protein/mRNA pairs, but differed amongst protein classes. Genes that did not correlate on the protein/mRNA level included components of basic cellular machineries such as the ribosome, RNA polymerase and spliceosome, as well as those involved in processes regulated by proteolysis. Hierarchical clustering yielded three major clusters in both the proteome and the phosphoproteome data: basal-enriched, luminal-enriched and stroma-enriched groups, the last also enriched for what have been previously designated “reactive-type” tumors by RPPA. Our deep proteome analysis promoted new insights including the consequences of chromosomal loss, such as the 5q deletion characteristic of basal-like breast cancer. The 5q trans effects were interrogated using the Library of Integrated Network-based Cellular Signatures. Theses analyses connected the 5q genes CETN3 and SKP1 to elevated expression of EGFR, and SKP1 also to SRC. Differential phosphopeptide analyses, integrated with activity maps derived from knock-in mutated cell lines, identified multiple novel downstream effects of PIK3CA and TP53 mutation. Besides ERBB2, other amplicon-associated, highly phosphorylated kinases were identified, including CDK12, PAK1, PTK2, RIPK2 and TLK2. These and other examples 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 potential therapeutic targets. Citation Format: Philipp Mertins, DR Mani, Kelly Ruggles, Michael Gillette, Karl Clauser, Pei Wang, Xianlong Wang, Jana Qiao, Song Cao, Francesca Petralia, Filip Mundt, Zhidong Tu, Jonathan Lei, Michael Gatza, Matthew Wilkerson, Charles Perou, Venkata Yellapantula, Kuan-lin Huang, Chenwei Lin, Michael McLellan, Ping Yan, Sherri Davies, Reid Townsend, Steven Skates, Jing Wang, Bing Zhang, Christopher Kinsinger, Mehdi Mesri, Henry Rodriguez, Li Ding, Amanda Paulovich, David Fenyo, Matthew Ellis, Steven Carr, NCI CPTAC. Proteogenomic and phosphoproteomic analysis of breast cancer. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Breast Cancer Research; Oct 17-20, 2015; Bellevue, WA. Philadelphia (PA): AACR; Mol Cancer Res 2016;14(2_Suppl):Abstract nr IA29.