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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.

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 may provide an orthogonal approach to genomic studies to further improve the molecular taxonomy and our understanding of breast cancer. Central questions in breast cancer biology that will be addressed in this study are: (1) Which genomic characteristics are executed at the protein level? (2) How is the molecular taxonomy of breast cancer reinforced and revised by protein and phosphorylation data? and (3) What phosphorylation-driven signaling networks emerge from genetic alterations? We analyzed human breast cancer samples that have been previously genetically characterized by the TCGA project. Tumor samples were analyzed by global shotgun-proteomics and phosphoproteomics using iTRAQ4-plex peptide labeling. All mass spectrometry data was acquired using nearly 5,000 h of measurement time on a Q Exactive instrument and the data was analyzed in Spectrum Mill using patient-specific RNA-sequencing derived protein databases. In total we quantified >16,000 proteins and >70,000 phosphorylation sites, with an average of >12,000 quantified proteins and >20,000 phosphorylation-sites for each tumor. Only 1-2% of all 9,600 genetically encoded somatic single amino acid variants and 1-2% of 36,000 alternative splice junctions were detected at the protein level despite the very comprehensive proteome coverage obtained. While the global mRNA protein abundance correlation was rather low (Spearman's correlation of 0.4), we found very good correlation for most protein kinase gene amplifications for mRNA, protein and phosphoprotein abundance. Hierarchical clustering analysis of both the proteome and the phosphoproteome data yielded an overlapping set of three major clusters: a basal-enriched, a luminal-enriched and a normal-inclusive group. The two most recurrently mutated genes in human breast cancer are PIK3CA and TP53 at frequencies of 30-40%. Comparison of PIK3CA or TP53 mutated vs non-mutated tumors highlights specific phosphorylation signaling events downstream of mutated PI3-kinase and increased phosphorylation of cell cycle check point kinases in p53-mutated tumors. Network and pathway analysis is being performed to comprehensively integrate genetic and phospho-/proteomic alterations in one model. The effects observed in human tumors will be compared to a set of 24 patient-derived xenograft tumors that will allow drug efficacy studies in fully genetically characterized tumors in the future. Citation Format: Philipp Mertins, DR Mani, Karl Clauser, Michael Gillette, Pei Wang, Jana Qiao, David Fenyo, Kelly Ruggles, Sherri Davies, Bing Zhang, Michael Gatza, Sean Wang, Ping Yan, Chenwei Lin, Michael McLellan, Reid Townsend, Li Ding, Song Cao, Henry Rodriguez, Amanda Paulovich, Matthew Ellis, Steven A. Carr, Clinical Proteomics Tumor Analysis Consortium: CPTAC. Proteogenomic and phosphoproteomic analysis of breast cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr SY44-02. doi:10.1158/1538-7445.AM2015-SY44-02

High-risk medulloblastoma is one of the most recalcitrant pediatric cancers, and children with MYC-amplified disease frequently succumb to relapsed disease. Extensive analyses of the coding genome in this disease have characterized additional somatic events in some subsets of patients, though most tumors lack targetable mutations and do not yield insights regarding their aggressive behavior. At the same time, medulloblastoma is known to exhibit extensive rewiring of translational control in MYC-driven tumors, consistent with recent genetic evidence that the impact of this transcription factor on control of mRNA translation may be the most critical aspect of its function during tumorigenesis. Therefore, to propose previously unknown mechanisms for this disease, we have investigated the functional impact of translation of non-canonical open reading frames (ORFs) across medulloblastoma model systems. We demonstrate that these ORFs are commonly translated in medulloblastoma model systems and patient tumors, correlating with disease subtype. Using genome-wide CRISPR/Cas9 screens, we found that ORFs are frequently essential for cell survival in medulloblastoma and describe widespread reliance on upstream open reading frames (uORFs) in particular. From these, we identify a uORF in the ASNSD1 gene that is selectively upregulated and required for maintenance of cell survival by coordinating the function of the prefoldin-like complex, a poorly understood complex implicated in post-translational control. Together, our findings provide a blueprint for oncogenic uORFs as critical disease mediators both in medulloblastoma and, by extension, human cancers more broadly.

Tyrosine kinases (TKs) are frequently, aberrantly activated in human cancers. Moreover, they could be easily inhibited by small molecules and thereby represent excellent therapeutic targets. Here, our project aims to systematically identify activated, essential TKs in human cancers. In our previously published study, we have developed a high-throughput, multiplex antibody-based assay capable of identifying activated tyrosine kinases regardless of their mode of activation. Using this approach, we profiled 130 established cancer cell lines and 31 primary patient samples. In particular, we found frequent SRC activation in glioblastomas in the absent of genomic alterations. Moreover, we determined SRC essentiality and demonstrated SRC being a relevant target of a FDA-approved drug, dasatinib, in this deadly disease. Since then, we have expanded the Luminex assay to include additional TKs, adaptors and other important signaling molecules. Specifically, the version 2 of this assay is capable of simultaneously analyzing the tyrosine phosphorylation levels on 71 out of the 90 TKs, 9 adaptor proteins, ERK1/2, PLCG1 in the human genome. In addition, we have established separate assays to measure activities of AKT1, GSK3B, p70S6K and RSK1/2. Besides expanding the panel of analytes, we have made significant improvement on assay setup and data analysis. In particular, we have fully automated assay setup in 96-well format. In addition, we have generated negative and positive control samples to enable more accurate background signal estimation and plate-to-plate comparison, respectively. Using the improved version o f the assay, we have profiled 200 additional cancer cell lines and 100 primary tumor specimens. We found that some TKs are frequently activated across multiple malignancies while other are restricted to a particular tumor type. Interestingly, majority of the TKs are activated at very low frequency. Together, these results stress the importance of personalized treatment (i.e. choosing kinase inhibitors based on kinase activation profile of a tumor). In parallel to our effort on identifying activated TKs, we are systematically assessing TK essentiality using the pharmacological approach. Specifically, we have collected 25 small molecules targeting all known oncogenic TKs and are in the process of measuring sensitivities towards these inhibitors in various cancer cell lines. By comparing TK activation status and sensitivity to inhibitors, we have identified potential targets and corresponding drug candidates for treating subsets of cancer patients. Together, we have gained a comprehensive view on aberrant TK activations and downstream signaling in human cancers. Beyond the mechanistic understanding of tyrosine kinase signaling, our study has identified potential targets for devising effective therapeutic strategies for treating cancer patients. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 5559.