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Identification of molecular subtypes and gene expression patterns of breast cancer analysing RNA-seq data

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dc.contributor Universitat de Vic. Escola Politècnica Superior
dc.contributor Universitat de Vic. Màster Universitari en Anàlisi de Dades Òmiques
dc.contributor.author Piqué Borràs, Maria Riera
dc.date.accessioned 2015-01-12T08:35:51Z
dc.date.available 2015-01-12T08:35:51Z
dc.date.created 2014-09
dc.date.issued 2014-09
dc.identifier.uri http://hdl.handle.net/10854/3802
dc.description Curs 2013-2014 ca_ES
dc.description.abstract Breast cancer is the most common diagnosed cancer and the leading cause of cancer death among females worldwide. It is considered a highly heterogeneous disease and it must be classified into more homogeneous groups. Hence, the purpose of this study was to classify breast tumors based on variations in gene expression patterns derived from RNA sequencing by using different class discovery methods. 42 breast tumors paired-samples were sequenced by Illumine Genome Analyzer and the data was analyzed and prepared by TopHat2 and htseq-count. As reported previously, breast cancer could be grouped into five main groups known as basal epithelial-like group, HER2 group, normal breast-like group and two Luminal groups with a distinctive expression profile. Classifying breast tumor samples by using PAM50 method, the most common subtype was Luminal B and was significantly associated with ESR1 and ERBB2 high expression. Luminal A subtype had ESR1 and SLC39A6 significant high expression, whereas HER2 subtype had a high expression of ERBB2 and CNNE1 genes and low luminal epithelial gene expression. Basal-like and normal-like subtypes were associated with low expression of ESR1, PgR and HER2, and had significant high expression of cytokeratins 5 and 17. Our results were similar compared with TGCA breast cancer data results and with known studies related with breast cancer classification. Classifying breast tumors could add significant prognostic and predictive information to standard parameters, and moreover, identify marker genes for each subtype to find a better therapy for patients with breast cancer. ca_ES
dc.format application/pdf
dc.format.extent 50 p. ca_ES
dc.language.iso eng ca_ES
dc.rights Aquest document està subjecte a aquesta llicència Creative Commons ca_ES
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/ ca_ES
dc.subject.other Mama -- Càncer ca_ES
dc.subject.other Gens del càncer ca_ES
dc.title Identification of molecular subtypes and gene expression patterns of breast cancer analysing RNA-seq data ca_ES
dc.type info:eu-repo/semantics/masterThesis ca_ES
dc.description.version Director/a: Victor Moreno, M. Luz Calle
dc.rights.accesRights info:eu-repo/semantics/openAccess ca_ES

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