Gene Prioritization, Communality Analysis, Networking and Metabolic Integrated Pathway to Better Understand Breast Cancer Pathogenesis
dc.contributor.author | López Cortés, Andrés | |
dc.contributor.author | Paz y Miño, César | |
dc.contributor.author | Cabrera Andrade, Alejandro | |
dc.contributor.author | Barigye, Stephen J. | |
dc.contributor.author | Munteanu, Cristian R. | |
dc.contributor.author | González Díaz, Humberto | |
dc.contributor.author | Pazos, Alejandro | |
dc.contributor.author | Pérez Castillo, Yunierkis | |
dc.contributor.author | Tejera, Eduardo | |
dc.date.accessioned | 2019-01-16T09:00:10Z | |
dc.date.available | 2019-01-16T09:00:10Z | |
dc.date.issued | 2018-11-12 | |
dc.identifier.citation | Scientific Reports 8 : (2018) // Article ID 16679 | es_ES |
dc.identifier.issn | 2045-2322 | |
dc.identifier.uri | http://hdl.handle.net/10810/30886 | |
dc.description.abstract | Consensus strategy was proved to be highly efficient in the recognition of gene-disease association. Therefore, the main objective of this study was to apply theoretical approaches to explore genes and communities directly involved in breast cancer (BC) pathogenesis. We evaluated the consensus between 8 prioritization strategies for the early recognition of pathogenic genes. A communality analysis in the protein-protein interaction (PPi) network of previously selected genes was enriched with gene ontology, metabolic pathways, as well as oncogenomics validation with the OncoPPi and DRIVE projects. The consensus genes were rationally filtered to 1842 genes. The communality analysis showed an enrichment of 14 communities specially connected with ERBB, PI3K-AKT, mTOR, FOXO, p53, HIF-1, VEGF, MAPK and prolactin signaling pathways. Genes with highest ranking were TP53, ESR1, BRCA2, BRCA1 and ERBB2. Genes with highest connectivity degree were TP53, AKT1, SRC, CREBBP and EP300. The connectivity degree allowed to establish a significant correlation between the OncoPPi network and our BC integrated network conformed by 51 genes and 62 PPi. In addition, CCND1, RAD51, CDC42, YAP1 and RPA1 were functional genes with significant sensitivity score in BC cell lines. In conclusion, the consensus strategy identifies both well-known pathogenic genes and prioritized genes that need to be further explored. | es_ES |
dc.description.sponsorship | This work was supported by Universidad UTE (Quito, Ecuador), Universidad de las Americas (Quito, Ecuador), University of Coruna (Coruna, Spain), University of the Basque Country (Bilbao, Spain), and McGill University (Montreal, Canada). Additionally, this work was supported by "Collaborative Project in Genomic Data Integration (CICLOGEN)" PI17/01826 funded by the Carlos III Health Institute from the Spanish National plan for Scientific and Technical Research and Innovation 2013-2016 and the European Regional Development Funds (FEDER). | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Nature Publishing Group | es_ES |
dc.rights | info:eu-repo/semantics/openAccess | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/es/ | * |
dc.subject | signaling pathways | es_ES |
dc.subject | phenotypic characterization | es_ES |
dc.subject | large-scale | es_ES |
dc.subject | DNA-damage | es_ES |
dc.subject | map kinase | es_ES |
dc.subject | mutations | es_ES |
dc.subject | expression | es_ES |
dc.subject | risk | es_ES |
dc.subject | targets | es_ES |
dc.subject | identification | es_ES |
dc.title | Gene Prioritization, Communality Analysis, Networking and Metabolic Integrated Pathway to Better Understand Breast Cancer Pathogenesis | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.holder | This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. Attribution 4.0 International (CC BY 4.0) | es_ES |
dc.rights.holder | Atribución 3.0 España | * |
dc.relation.publisherversion | https://www.nature.com/articles/s41598-018-35149-1 | es_ES |
dc.identifier.doi | 10.1038/s41598-018-35149-1 | |
dc.departamentoes | Química orgánica II | es_ES |
dc.departamentoeu | Kimika organikoa II | es_ES |
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