Proteome-wide analysis of protein abundance and turnover remodelling during oncogenic transformation of human breast epithelial cells [version 1; referees: 2 approved, 1 approved with reservations]

Background: Viral oncogenes and mutated proto-oncogenes are potent drivers of cancer malignancy. Downstream of the oncogenic trigger are alterations in protein properties that give rise to cellular transformation and the acquisition of malignant cellular phenotypes. Developments in mass spectrometry enable large-scale, multidimensional characterisation of proteomes. Such techniques could provide an unprecedented, unbiased view of how oncogene activation remodels a human cell proteome. Methods: Using quantitative MS-based proteomics and cellular assays, we analysed how transformation induced by activating v-Src kinase remodels the proteome and cellular phenotypes of breast epithelial (MCF10A) cells. SILAC MS was used to comprehensively characterise the MCF10A proteome and to measure v-Src-induced changes in protein abundance across seven time-points (1-72 hrs). We used pulse-SILAC MS (Boisvert et al., 2012), to compare protein synthesis and turnover in control and transformed cells. Follow-on experiments employed a combination of cellular and functional assays to characterise the roles of selected Src-responsive proteins. Results: Src-induced transformation changed the expression and/or turnover levels of ~3% of proteins, affecting ~1.5% of the total protein molecules in the cell. Transformation increased the average rate of proteome turnover and disrupted protein homeostasis. We identify distinct classes of protein kinetics in response to Src activation. We demonstrate that members of the polycomb repressive complex 1 (PRC1) are important regulators of invasion and migration in MCF10A cells. Many Src-regulated proteins are present in low abundance and some are regulated post-transcriptionally. The signature of Src-responsive proteins is highly predictive of poor patient survival across multiple cancer types. Open access to search and interactively explore all these proteomic data is provided via the EPD database (www.peptracker.com/epd). Conclusions: We present the first comprehensive analysis measuring how protein expression and protein turnover is affected by cell transformation, providing a detailed picture at the protein level of the consequences of activation of an oncogene.