Meta-data analysis as a strategy to evaluate individual and common features of proteomic changes in breast cancer

• BACKGROUND: Individual differences among breast tumours in patients is a significant challenge for the treatment of breast cancer. This study reports a strategy to assess these individual differences and the common regulatory mechanisms that may underlie breast tumourigenesis. MATERIALS AND METHODS: The two-step strategy was based firstly on a full-scale proteomics analysis of individual cases, and secondly on the analysis of common features of the individual proteome-centred networks (meta-data). RESULTS: Proteomic profiling of human invasive ductal carcinoma tumours was performed and each case was analysed individually. Analysis of primary datasets for common cancer-related proteins identified keratins. Analysis of individual networks built with identified proteins predicted features and regulatory mechanisms involved in each individual case. Validation of these findings by immunohistochemistry confirmed the predicted deregulation of expression of CK2α, PDGFRα, PYK and p53 proteins. CONCLUSION: Meta-data analysis allowed efficient evaluation of both individual and common features of the breast cancer proteome.

Nyckelord

Proteomics

breast cancer

signalling

meta-data analysis

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