Identification of early stage recurrence endometrial cancer biomarkers using bioinformatics tools

Autores
Besso, María José; Montivero, Luciana; Lacunza, Ezequiel; Argibay, María Cecilia; Abba, Martín Carlos; Furlong, Laura Ines; Colas, Eva; Gil Moreno, Antonio; Reventos, Jaume; Bello, Ricarlo; Vazquez, Monica Hebe
Año de publicación
2020
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
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.
Fil: Besso, María José. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; Argentina
Fil: Montivero, Luciana. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; Argentina
Fil: Lacunza, Ezequiel. Universidad Nacional de La Plata. Facultad de Ciencias Médicas. Centro de Investigaciones Inmunológicas Básicas y Aplicadas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; Argentina
Fil: Argibay, María Cecilia. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; Argentina
Fil: Abba, Martín Carlos. Universidad Nacional de La Plata. Facultad de Ciencias Médicas. Centro de Investigaciones Inmunológicas Básicas y Aplicadas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; Argentina
Fil: Furlong, Laura Ines. Universitat Pompeu Fabra; España
Fil: Colas, Eva. Universitat Autònoma de Barcelona; España
Fil: Gil Moreno, Antonio. Universitat Autònoma de Barcelona; España
Fil: Reventos, Jaume. Universitat Autònoma de Barcelona; España
Fil: Bello, Ricarlo. Universidad Nacional de Tres de Febrero. Departamento de Metodología, Estadística y Matemáticas; Argentina
Fil: Vazquez, Monica Hebe. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; Argentina
Materia
Molecular Oncology
Endometrial Cancer
Bioinformatics
Biomarkers
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/112581
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/112581
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Identification of early stage recurrence endometrial cancer biomarkers using bioinformatics toolsBesso, María JoséMontivero, LucianaLacunza, EzequielArgibay, María CeciliaAbba, Martín CarlosFurlong, Laura InesColas, EvaGil Moreno, AntonioReventos, JaumeBello, RicarloVazquez, Monica HebeMolecular OncologyEndometrial CancerBioinformaticsBiomarkershttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1Endometrial 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.Fil: Besso, María José. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; ArgentinaFil: Montivero, Luciana. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; ArgentinaFil: Lacunza, Ezequiel. Universidad Nacional de La Plata. Facultad de Ciencias Médicas. Centro de Investigaciones Inmunológicas Básicas y Aplicadas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; ArgentinaFil: Argibay, María Cecilia. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; ArgentinaFil: Abba, Martín Carlos. Universidad Nacional de La Plata. Facultad de Ciencias Médicas. Centro de Investigaciones Inmunológicas Básicas y Aplicadas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; ArgentinaFil: Furlong, Laura Ines. Universitat Pompeu Fabra; EspañaFil: Colas, Eva. Universitat Autònoma de Barcelona; EspañaFil: Gil Moreno, Antonio. Universitat Autònoma de Barcelona; EspañaFil: Reventos, Jaume. Universitat Autònoma de Barcelona; EspañaFil: Bello, Ricarlo. Universidad Nacional de Tres de Febrero. Departamento de Metodología, Estadística y Matemáticas; ArgentinaFil: Vazquez, Monica Hebe. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; ArgentinaBoletim do Instituto de Pesca2020-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/112581Besso, María José; Montivero, Luciana; Lacunza, Ezequiel; Argibay, María Cecilia; Abba, Martín Carlos; et al.; Identification of early stage recurrence endometrial cancer biomarkers using bioinformatics tools; Boletim do Instituto de Pesca; Oncology Reports; 44; 3; 6-2020; 873-8861021-335X1791-2431CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.spandidos-publications.com/10.3892/or.2020.7648info:eu-repo/semantics/altIdentifier/doi/10.3892/or.2020.7648info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T10:07:02Zoai:ri.conicet.gov.ar:11336/112581instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 10:07:02.613CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
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
Molecular Oncology
Endometrial Cancer
Bioinformatics
Biomarkers
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 Carlos
Furlong, Laura Ines
Colas, Eva
Gil Moreno, Antonio
Reventos, Jaume
Bello, Ricarlo
Vazquez, Monica Hebe
author Besso, María José
author_facet Besso, María José
Montivero, Luciana
Lacunza, Ezequiel
Argibay, María Cecilia
Abba, Martín Carlos
Furlong, Laura Ines
Colas, Eva
Gil Moreno, Antonio
Reventos, Jaume
Bello, Ricarlo
Vazquez, Monica Hebe
author_role author
author2 Montivero, Luciana
Lacunza, Ezequiel
Argibay, María Cecilia
Abba, Martín Carlos
Furlong, Laura Ines
Colas, Eva
Gil Moreno, Antonio
Reventos, Jaume
Bello, Ricarlo
Vazquez, Monica Hebe
author2_role author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Molecular Oncology
Endometrial Cancer
Bioinformatics
Biomarkers
topic Molecular Oncology
Endometrial Cancer
Bioinformatics
Biomarkers
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv 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.
Fil: Besso, María José. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; Argentina
Fil: Montivero, Luciana. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; Argentina
Fil: Lacunza, Ezequiel. Universidad Nacional de La Plata. Facultad de Ciencias Médicas. Centro de Investigaciones Inmunológicas Básicas y Aplicadas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; Argentina
Fil: Argibay, María Cecilia. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; Argentina
Fil: Abba, Martín Carlos. Universidad Nacional de La Plata. Facultad de Ciencias Médicas. Centro de Investigaciones Inmunológicas Básicas y Aplicadas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; Argentina
Fil: Furlong, Laura Ines. Universitat Pompeu Fabra; España
Fil: Colas, Eva. Universitat Autònoma de Barcelona; España
Fil: Gil Moreno, Antonio. Universitat Autònoma de Barcelona; España
Fil: Reventos, Jaume. Universitat Autònoma de Barcelona; España
Fil: Bello, Ricarlo. Universidad Nacional de Tres de Febrero. Departamento de Metodología, Estadística y Matemáticas; Argentina
Fil: Vazquez, Monica Hebe. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; Argentina
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 2020-06
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/112581
Besso, María José; Montivero, Luciana; Lacunza, Ezequiel; Argibay, María Cecilia; Abba, Martín Carlos; et al.; Identification of early stage recurrence endometrial cancer biomarkers using bioinformatics tools; Boletim do Instituto de Pesca; Oncology Reports; 44; 3; 6-2020; 873-886
1021-335X
1791-2431
CONICET Digital
CONICET
url http://hdl.handle.net/11336/112581
identifier_str_mv Besso, María José; Montivero, Luciana; Lacunza, Ezequiel; Argibay, María Cecilia; Abba, Martín Carlos; et al.; Identification of early stage recurrence endometrial cancer biomarkers using bioinformatics tools; Boletim do Instituto de Pesca; Oncology Reports; 44; 3; 6-2020; 873-886
1021-335X
1791-2431
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.spandidos-publications.com/10.3892/or.2020.7648
info:eu-repo/semantics/altIdentifier/doi/10.3892/or.2020.7648
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Boletim do Instituto de Pesca
publisher.none.fl_str_mv Boletim do Instituto de Pesca
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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