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Radek Fedr, Ján Remšík, Jiří Navrátil, Lucia Binó, Eva Slabáková, Pavel Fabian, Marek Svoboda, and Karel Souček (1-Institute of Biophysics of the Czech Academy of Sciences, CZ; 2-Center of Biomolecular and Cellular Engineering, International Clinical Research Center, St. Anne's University Hospital Brno, CZ)
Breast cancer is the most common cancer in women which includes remarkably heterogeneous subtypes, with the relatively poor outcome due to aggressive clinical behaviour and lack of characterized molecular targets for therapy. Intratumoral heterogeneity characterized by the presence of multiple distinct clones of cancer cells within one tumour is one of the main obstacles in effective cancer treatment. Therefore, we established a 12-colour flow cytometric panel for the multiparametric description of breast cancer heterogeneity and plasticity in patient samples. Analysis and visualization of the multidimensional flow cytometric data are challenging, and traditional methods of sequential gating are no more possible to employ for analysis. In this study, we aimed to apply automated clustering methods implemented in the R scripting language. Four luminal type A patient samples of breast cancer were analysed with the specific aim to compare results of algorithms and more importantly to describe inter and intra tumour variability.