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- Zakharchenko, Olena, et al.
(författare)
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Meta-data analysis as a strategy to evaluate individual and common features of proteomic changes in breast cancer
- 2011
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Ingår i: Cancer Genomics & Proteomics. - 1109-6535 .- 1790-6245. ; 8:1, s. 1-14
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 2. |
- Zakharchenko, Olena
(författare)
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Proteome profiling of human breast cancer
- 2011
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Breast cancer (BC) takes thousands of woman’s lives yearly. Several factors have been found to influence initiation and development of breast cancer, and to affect prognosis and treatment of this disease. This thesis is focuses on opening-out this complexity and search for approaches that may lead to individualized treatment of breast cancer patients. We studied clinical samples of breast tumors and adjacent normal tissues using protein-based proteomics. By studying each patient individually, we identified proteins that changed expression during carcinogenesis (p53, Smad2, etc). We observed significant differences in the lists of cancer-related proteins between individual patients. We demonstrated that meta-data analysis of the identified proteins is the most efficient way to describe common and individual features of tumors from different patients. Our validation study by immunohistochemistry analysis of identified molecules (PYK, Smad2, CK2α) confirmed the changed expressions between tumor and normal tissue, and thereby confirmed the conclusions obtained with proteomics analysis. Thus, we found that meta-data analysis approach is suitable for improved and individualized diagnostics and selection of treatment. Transforming growth factor-β (TGFβ) is a potent regulator of tumorigenesis. In our study of the clinical cases, we demonstrated that TGFβ signaling might be influenced in breast tumorigenesis. Phosphoproteomics analysis of TGFβ action on MCF10A human breast epithelial cells showed a complex regulation of cell signaling, with strong representation of functional domains such as metabolism. One of the targets of TGFβ is 14-3-3σ protein, and we found that 14-3-3σ was of a crucial importance for the cross-talk between TGFβ and p53 signaling. We reported also proteins identified by expression proteomics, which are regulated by TGFβ in human breast epithelial cells that have phenotype similar to normal breast epithelial cells. We found more than 100 proteins that were regulated by TGFβ. Among them, Casein Kinase 2α (CK2α), Structure-Specific Recognition Protein-1 (SSRP1) and protein convertase-4 (PC4) may be involved in TGFβ-dependent inhibition of cell proliferation by modulating p53 phosphorylation. Therefore, presented here study describes development of tools for individualized treatment of patients, and provides insights in the complexity of cancer related signaling in breast epithelial cells.
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