Identification of early stage recurrence endometrial cancer biomarkers using bioinformatics tools

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),...

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Autores: Besso, María josé, Montivero, Luciana, Lacunza, Ezequiel, Argibay, María cecilia, Abba, Martín, Furlong, Laura I, Colás Ortega, Eva|||0000-0003-0302-4828, Gil-Moreno, Antonio|||0000-0003-1106-5590, Reventos, Jaume, Bello, Ricardo, Vazquez-Levin, Mónica Hebe
Tipo de recurso: artículo
Fecha de publicación:2020
País:España
Institución:Universitat Autònoma de Barcelona
Repositorio:Dipòsit Digital de Documents de la UAB
Idioma:inglés
OAI Identifier:oai:ddd.uab.cat:238790
Acceso en línea:https://ddd.uab.cat/record/238790
https://dx.doi.org/urn:doi:10.3892/or.2020.7648
Access Level:acceso abierto
Palabra clave:Endometrial cancer
Bioinformatics
Biomarkers
Recurrence
TPX2
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spelling Identification of early stage recurrence endometrial cancer biomarkers using bioinformatics toolsBesso, María joséMontivero, LucianaLacunza, EzequielArgibay, María ceciliaAbba, MartínFurlong, Laura IColás Ortega, Eva|||0000-0003-0302-4828Gil-Moreno, Antonio|||0000-0003-1106-5590Reventos, JaumeBello, RicardoVazquez-Levin, Mónica HebeEndometrial cancerBioinformaticsBiomarkersRecurrenceTPX2Endometrial 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.Universitat Autònoma de Barcelona 22020-01-0120202020-01-01Articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://ddd.uab.cat/record/238790https://dx.doi.org/urn:doi:10.3892/or.2020.7648reponame:Dipòsit Digital de Documents de la UABinstname:Universitat Autònoma de BarcelonaInglésengopen accesshttp://purl.org/coar/access_right/c_abf2Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades.https://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:ddd.uab.cat:2387902026-06-06T12:50:31Z
dc.title.none.fl_str_mv Identification of early stage recurrence endometrial cancer biomarkers using bioinformatics tools
title Identification of early stage recurrence endometrial cancer biomarkers using bioinformatics tools
spellingShingle Identification of early stage recurrence endometrial cancer biomarkers using bioinformatics tools
Besso, María josé
Endometrial cancer
Bioinformatics
Biomarkers
Recurrence
TPX2
title_short Identification of early stage recurrence endometrial cancer biomarkers using bioinformatics tools
title_full Identification of early stage recurrence endometrial cancer biomarkers using bioinformatics tools
title_fullStr Identification of early stage recurrence endometrial cancer biomarkers using bioinformatics tools
title_full_unstemmed Identification of early stage recurrence endometrial cancer biomarkers using bioinformatics tools
title_sort Identification of early stage recurrence endometrial cancer biomarkers using bioinformatics tools
dc.creator.none.fl_str_mv Besso, María josé
Montivero, Luciana
Lacunza, Ezequiel
Argibay, María cecilia
Abba, Martín
Furlong, Laura I
Colás Ortega, Eva|||0000-0003-0302-4828
Gil-Moreno, Antonio|||0000-0003-1106-5590
Reventos, Jaume
Bello, Ricardo
Vazquez-Levin, Mónica Hebe
author Besso, María josé
author_facet Besso, María josé
Montivero, Luciana
Lacunza, Ezequiel
Argibay, María cecilia
Abba, Martín
Furlong, Laura I
Colás Ortega, Eva|||0000-0003-0302-4828
Gil-Moreno, Antonio|||0000-0003-1106-5590
Reventos, Jaume
Bello, Ricardo
Vazquez-Levin, Mónica Hebe
author_role author
author2 Montivero, Luciana
Lacunza, Ezequiel
Argibay, María cecilia
Abba, Martín
Furlong, Laura I
Colás Ortega, Eva|||0000-0003-0302-4828
Gil-Moreno, Antonio|||0000-0003-1106-5590
Reventos, Jaume
Bello, Ricardo
Vazquez-Levin, Mónica Hebe
author2_role author
author
author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv Universitat Autònoma de Barcelona
dc.subject.none.fl_str_mv Endometrial cancer
Bioinformatics
Biomarkers
Recurrence
TPX2
topic Endometrial cancer
Bioinformatics
Biomarkers
Recurrence
TPX2
description 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.
publishDate 2020
dc.date.none.fl_str_mv 2
2020-01-01
2020
2020-01-01
dc.type.none.fl_str_mv Article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://ddd.uab.cat/record/238790
https://dx.doi.org/urn:doi:10.3892/or.2020.7648
url https://ddd.uab.cat/record/238790
https://dx.doi.org/urn:doi:10.3892/or.2020.7648
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
https://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Dipòsit Digital de Documents de la UAB
instname:Universitat Autònoma de Barcelona
instname_str Universitat Autònoma de Barcelona
reponame_str Dipòsit Digital de Documents de la UAB
collection Dipòsit Digital de Documents de la UAB
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.300719

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