Show simple item record

dc.contributor.authorCabrera-Andrade, Alejandro
dc.contributor.authorLópez-Cortés, Andrés
dc.contributor.authorJaramillo-Koupermann, Gabriela
dc.contributor.authorPaz-y-Miño, César
dc.contributor.authorPérez-Castillo, Yunierkis
dc.contributor.authorMunteanu, Cristian-Robert
dc.contributor.authorGonzález-Díaz, Humberto
dc.contributor.authorPazos, A.
dc.contributor.authorTejera, Eduardo
dc.date.accessioned2020-03-04T15:20:17Z
dc.date.available2020-03-04T15:20:17Z
dc.date.issued2020-02-05
dc.identifier.citationCabrera-Andrade A, López-Cortés A, Jaramillo-Koupermann G, Paz-y-Miño C, Pérez-Castillo Y, Munteanu CR, et al. Gene Prioritization through Consensus Strategy, Enrichment Methodologies Analysis, and Networking for Osteosarcoma Pathogenesis. Int. J. Mol. Sci. 2020; 21:1053.es_ES
dc.identifier.issn1422-0067
dc.identifier.issn1661-6596
dc.identifier.issn1424-6783
dc.identifier.urihttp://hdl.handle.net/2183/25108
dc.description.abstract[Abstract] Osteosarcoma is the most common subtype of primary bone cancer, affecting mostly adolescents. In recent years, several studies have focused on elucidating the molecular mechanisms of this sarcoma; however, its molecular etiology has still not been determined with precision. Therefore, we applied a consensus strategy with the use of several bioinformatics tools to prioritize genes involved in its pathogenesis. Subsequently, we assessed the physical interactions of the previously selected genes and applied a communality analysis to this protein–protein interaction network. The consensus strategy prioritized a total list of 553 genes. Our enrichment analysis validates several studies that describe the signaling pathways PI3K/AKT and MAPK/ERK as pathogenic. The gene ontology described TP53 as a principal signal transducer that chiefly mediates processes associated with cell cycle and DNA damage response It is interesting to note that the communality analysis clusters several members involved in metastasis events, such as MMP2 and MMP9, and genes associated with DNA repair complexes, like ATM, ATR, CHEK1, and RAD51. In this study, we have identified well-known pathogenic genes for osteosarcoma and prioritized genes that need to be further explored.es_ES
dc.description.sponsorshipInstituto Carlos III; PI17/01826es_ES
dc.description.sponsorshipXunta de Galicia; ED431C 2018/49es_ES
dc.description.sponsorshipXunta de Galicia; ED431G/01es_ES
dc.language.isoenges_ES
dc.publisherM D P I AGes_ES
dc.relation.urihttps://doi.org/10.3390/ijms21031053es_ES
dc.rightsAtribución 3.0 Españaes_ES
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subjectGene prioritizationes_ES
dc.subjectOsteosarcomaes_ES
dc.subjectCommunality analysises_ES
dc.subjectPathogenesises_ES
dc.subjectEarly recognitiones_ES
dc.titleGene Prioritization through Consensus Strategy, Enrichment Methodologies Analysis, and Networking for Osteosarcoma Pathogenesises_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessinfo:eu-repo/semantics/openAccesses_ES
UDC.journalTitleInternational Journal of Molecular Scienceses_ES
UDC.volume21es_ES
UDC.issue3es_ES
UDC.startPage1053es_ES
dc.identifier.doi10.3390/ijms21031053


Files in this item

Thumbnail
Thumbnail

This item appears in the following Collection(s)

Show simple item record