How is transgelin involved in the mechanism of breast cancer metastasis?
| Autoři | |
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| Rok publikování | 2011 |
| Druh | Konferenční abstrakty |
| Fakulta / Pracoviště MU | |
| Citace | |
| Popis | The main challenge in breast cancer treatment is a metastatic disease. For estimation of the risk of metastatic disease, traditional prognostic factors like tumor size, tumor grade or lymph node status are currently used. However, the predictive value of these factors is not sufficient and there is an urgent need for new more reliable molecular markers with higher sensitivity and selectivity. Using a comparative proteomic approach, we identified transgelin as protein with increased expression in lymph-node positive low grade breast tumors compared to non-metastatic ones. This altered expression was further confirmed on transcriptional level using quantitative real-time PCR with absolute quantitation. Transgelin has been largely studied as an abundant protein of smooth muscle cells. With further development of proteomics and progress in the field of biomarker discovery, there is increasing number of studies in which altered expression of transgelin in tumor samples is described. Transgelin is thus, in all probability, involved in the process of tumor development. However, the results from the studies are often contradictory, even in the same tumor type and there are missing studies describing its function in these processes. With the aim to clarify the role of transgelin in breast cancer metastasis, we used a panel of breast cancer tissues with different characteristics and metastatic potential. Using siRNA silencing of transgelin expression, we characterized its effect on migration features of tumor cells. We also focused on the identification of protein-protein interactions of this protein using combination of pull-down approach with a quantitative proteomics based on stable isotope labeling with amino acids in cell cultures (SILAC). The samples were measured on a high-resolution mass spectrometry instrument (Orbitrap Velos) and the data were evaluated using MaxQuant software. Our results contribute to understanding the complex field of breast cancer metastasis and indicate new directions of our further experiments. |
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