Identification of early stage recurrence endometrial cancer biomarkers using bioinformatics tools

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• dc.contributor.author Besso, María José
• dc.contributor.author Montivero, Luciana
• dc.contributor.author Lacunza, Ezequiel
• dc.contributor.author Argibay, María Cecilia
• dc.contributor.author Abba, Martín
• dc.contributor.author Furlong, Laura I., 1971-
• dc.contributor.author Colas, Eva
• dc.contributor.author Gil-Moreno, Antonio
• dc.contributor.author Reventós, Jaume
• dc.contributor.author Bello, Ricardo
• dc.contributor.author Vázquez-Levin, Mónica Hebe
• dc.date.accessioned 2020-12-15T08:05:08Z
• dc.date.available 2020-12-15T08:05:08Z
• dc.date.issued 2020
• dc.description.abstract Endometrial cancer (EC) is the sixth most common cancer in women worldwide. Early diagnosis is critical in recurrent EC management. The present study aimed to identify biomarkers of EC early recurrence using a workflow that combined text and data mining databases (DisGeNET, Gene Expression Omnibus), a prioritization algorithm to select a set of putative candidates (ToppGene), protein‑protein interaction network analyses (Search Tool for the Retrieval of Interacting Genes, cytoHubba), association analysis of selected genes with clinicopathological parameters, and survival analysis (Kaplan‑Meier and Cox proportional hazard ratio analyses) using a The Cancer Genome Atlas cohort. A total of 10 genes were identified, among which the targeting protein for Xklp2 (TPX2) was the most promising independent prognostic biomarker in stage I EC. TPX2 expression (mRNA and protein) was higher (P<0.0001 and P<0.001, respectively) in ETS variant transcription factor 5‑overexpressing Hec1a and Ishikawa cells, a previously reported cell model of aggressive stage I EC. In EC biopsies, TPX2 mRNA expression levels were higher (P<0.05) in high grade tumors (grade 3) compared with grade 1‑2 tumors (P<0.05), in tumors with deep myometrial invasion (>50% compared with <50%; P<0.01), and in intermediate‑high recurrence risk tumors compared with low‑risk tumors (P<0.05). Further validation studies in larger and independent EC cohorts will contribute to confirm the prognostic value of TPX2.
• dc.format.mimetype application/pdf
• dc.identifier.citation Besso MJ, Montivero L, Lacunza E, Argibay MC, Abba M, Furlong LI, et al. Identification of early stage recurrence endometrial cancer biomarkers using bioinformatics tools. Oncol Rep. 2020 Sep; 44(3):873-86. DOI: 10.3892/or.2020.7648
• dc.identifier.doi http://dx.doi.org/10.3892/or.2020.7648
• dc.identifier.issn 1021-335X
• dc.identifier.uri http://hdl.handle.net/10230/46036
• dc.language.iso eng
• dc.publisher Spandidos Publications, Ltd.
• dc.relation.ispartof Oncology Reports. 2020 Sep;44(3):873-86
• dc.rights Copyright: © Besso et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, https://creativecommons.org/licenses/by-nc-nd/4.0/, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/4.0/
• dc.subject.other Endometri -- Càncer
• dc.subject.other Bioinformàtica
• dc.title Identification of early stage recurrence endometrial cancer biomarkers using bioinformatics tools
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion