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Title: Identificación de genes con papel driver en cáncer de mama y su red génica
Author: Asensio Calavia, Patricia
Director: Morán Moreno, José Antonio
Tutor: Bassaganyas Bars, Laia
Keywords: bioinformatics tools
breast cancer
driver genes
Issue Date: 5-Jun-2018
Publisher: Universitat Oberta de Catalunya (UOC)
Abstract: Breast cancer research is important nowadays because it is the most common cancer in women, and it is estimated that 12% of women will be affected along their lives. The aim of this study is to identify possible driver genes, the interaction between them and their functions, in order to understand how they can influence the disease, help in the diagnosis and design of new drugs. 239 putative driver genes are identified with the DriverDBv2 tool, from the initial 990 mutagenic data from patients with invasive breast cancer. An interaction network is created with the FunRich software from identified genes, 9 of them appear as nodes with a greater number of interactions: EGFR, TP53, BRCA1, FLNA, EP300, ERBB3, AKT1, ERBB2 and PIK3R1. A functional analysis is then performed with PANTHER, presenting a higher percentage of genes with binding and catalytic molecular function. The pathways with the greatest number of possible driver genes involve are: Wnt signalling pathway (6.7%), EGF receptor signalling pathway (6.7%) and Gonadotropin-releasing hormone receptor pathway (6.7%). There are several studies on breast cancer driver genes but no method of identification has been reached agreement yet. The results show some possible new driver genes identified, in addition, receptor function classification genes. Finally, these results could serve as a basis for future research of pharmacological targets, to improve diagnosis and personalized medicine.
Language: Spanish
Appears in Collections:Bachelor thesis, research projects, etc.

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