Breast cancer biomarker discovery in the functional genomic age: A systematic review of 42 gene expression signatures

Autores
Abba, Martín Carlos; Lacunza, Ezequiel; Butti, Matías A.; Aldaz, C. Marcelo
Año de publicación
2010
Idioma
inglés
Tipo de recurso
reseña artículo
Estado
versión publicada
Descripción
In this review we provide a systematic analysis of transcriptomic signatures derived from 42 breast cancer gene expression studies, in an effort to identify the most relevant breast cancer biomarkers using a meta-analysis method. Meta-data revealed a set of 117 genes that were the most commonly affected ranging from 12% to 36% of overlap among breast cancer gene expression studies. Data mining analysis of transcripts and protein-protein interactions of these commonly modulated genes indicate three functional modules signifcantly affected among signatures, one module related with the response to steroid hormone stimulus, and two modules related to the cell cycle. Analysis of a publicly available gene expression data showed that the obtained meta-signature is capable of predicting overall survival (P < 0.0001) and relapse-free survival (P < 0.0001) in patients with early-stage breast carcinomas. In addition, the identifed meta-signature improves breast cancer patient stratifcation independently of traditional prognostic factors in a multivariate Cox proportional-hazards analysis.
Facultad de Ciencias Médicas
Materia
Ciencias Médicas
biomarkers
APC protein
aurora A kinase
breast cancer
Bub1 related protein
gene expression signatures
cyclin
estrogen receptor alpha
forkhead transcription factor
hepatocyte nuclear factor 3alpha
manganese superoxide dismutase
TTK protein kinase
ubiquitin conjugating enzyme
microarray analysis
mitosis spindle
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by/3.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/34620
Acceder
id SEDICI_172d79f8232d5d4820ae249f0afcbcbe
oai_identifier_str oai:sedici.unlp.edu.ar:10915/34620
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Breast cancer biomarker discovery in the functional genomic age: A systematic review of 42 gene expression signaturesAbba, Martín CarlosLacunza, EzequielButti, Matías A.Aldaz, C. MarceloCiencias MédicasbiomarkersAPC proteinaurora A kinasebreast cancerBub1 related proteingene expression signaturescyclinestrogen receptor alphaforkhead transcription factorhepatocyte nuclear factor 3alphamanganese superoxide dismutaseTTK protein kinaseubiquitin conjugating enzymemicroarray analysismitosis spindleIn this review we provide a systematic analysis of transcriptomic signatures derived from 42 breast cancer gene expression studies, in an effort to identify the most relevant breast cancer biomarkers using a meta-analysis method. Meta-data revealed a set of 117 genes that were the most commonly affected ranging from 12% to 36% of overlap among breast cancer gene expression studies. Data mining analysis of transcripts and protein-protein interactions of these commonly modulated genes indicate three functional modules signifcantly affected among signatures, one module related with the response to steroid hormone stimulus, and two modules related to the cell cycle. Analysis of a publicly available gene expression data showed that the obtained meta-signature is capable of predicting overall survival (P < 0.0001) and relapse-free survival (P < 0.0001) in patients with early-stage breast carcinomas. In addition, the identifed meta-signature improves breast cancer patient stratifcation independently of traditional prognostic factors in a multivariate Cox proportional-hazards analysis.Facultad de Ciencias Médicas2010-10-27info:eu-repo/semantics/reviewinfo:eu-repo/semantics/publishedVersionRevisionhttp://purl.org/coar/resource_type/c_dcae04bcinfo:ar-repo/semantics/resenaArticuloapplication/pdf103-118http://sedici.unlp.edu.ar/handle/10915/34620enginfo:eu-repo/semantics/altIdentifier/url/http://www.la-press.com/breast-cancer-biomarker-discovery-in-the-functional-genomic-age-a-syst-article-a2325info:eu-repo/semantics/altIdentifier/issn/1177-2719info:eu-repo/semantics/altIdentifier/doi/10.4137/BMI.S5740info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/3.0/Creative Commons Attribution 3.0 Unported (CC BY 3.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-03T10:29:49Zoai:sedici.unlp.edu.ar:10915/34620Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-03 10:29:49.555SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Breast cancer biomarker discovery in the functional genomic age: A systematic review of 42 gene expression signatures
title Breast cancer biomarker discovery in the functional genomic age: A systematic review of 42 gene expression signatures
spellingShingle Breast cancer biomarker discovery in the functional genomic age: A systematic review of 42 gene expression signatures
Abba, Martín Carlos
Ciencias Médicas
biomarkers
APC protein
aurora A kinase
breast cancer
Bub1 related protein
gene expression signatures
cyclin
estrogen receptor alpha
forkhead transcription factor
hepatocyte nuclear factor 3alpha
manganese superoxide dismutase
TTK protein kinase
ubiquitin conjugating enzyme
microarray analysis
mitosis spindle
title_short Breast cancer biomarker discovery in the functional genomic age: A systematic review of 42 gene expression signatures
title_full Breast cancer biomarker discovery in the functional genomic age: A systematic review of 42 gene expression signatures
title_fullStr Breast cancer biomarker discovery in the functional genomic age: A systematic review of 42 gene expression signatures
title_full_unstemmed Breast cancer biomarker discovery in the functional genomic age: A systematic review of 42 gene expression signatures
title_sort Breast cancer biomarker discovery in the functional genomic age: A systematic review of 42 gene expression signatures
dc.creator.none.fl_str_mv Abba, Martín Carlos
Lacunza, Ezequiel
Butti, Matías A.
Aldaz, C. Marcelo
author Abba, Martín Carlos
author_facet Abba, Martín Carlos
Lacunza, Ezequiel
Butti, Matías A.
Aldaz, C. Marcelo
author_role author
author2 Lacunza, Ezequiel
Butti, Matías A.
Aldaz, C. Marcelo
author2_role author
author
author
dc.subject.none.fl_str_mv Ciencias Médicas
biomarkers
APC protein
aurora A kinase
breast cancer
Bub1 related protein
gene expression signatures
cyclin
estrogen receptor alpha
forkhead transcription factor
hepatocyte nuclear factor 3alpha
manganese superoxide dismutase
TTK protein kinase
ubiquitin conjugating enzyme
microarray analysis
mitosis spindle
topic Ciencias Médicas
biomarkers
APC protein
aurora A kinase
breast cancer
Bub1 related protein
gene expression signatures
cyclin
estrogen receptor alpha
forkhead transcription factor
hepatocyte nuclear factor 3alpha
manganese superoxide dismutase
TTK protein kinase
ubiquitin conjugating enzyme
microarray analysis
mitosis spindle
dc.description.none.fl_txt_mv In this review we provide a systematic analysis of transcriptomic signatures derived from 42 breast cancer gene expression studies, in an effort to identify the most relevant breast cancer biomarkers using a meta-analysis method. Meta-data revealed a set of 117 genes that were the most commonly affected ranging from 12% to 36% of overlap among breast cancer gene expression studies. Data mining analysis of transcripts and protein-protein interactions of these commonly modulated genes indicate three functional modules signifcantly affected among signatures, one module related with the response to steroid hormone stimulus, and two modules related to the cell cycle. Analysis of a publicly available gene expression data showed that the obtained meta-signature is capable of predicting overall survival (P < 0.0001) and relapse-free survival (P < 0.0001) in patients with early-stage breast carcinomas. In addition, the identifed meta-signature improves breast cancer patient stratifcation independently of traditional prognostic factors in a multivariate Cox proportional-hazards analysis.
Facultad de Ciencias Médicas
description In this review we provide a systematic analysis of transcriptomic signatures derived from 42 breast cancer gene expression studies, in an effort to identify the most relevant breast cancer biomarkers using a meta-analysis method. Meta-data revealed a set of 117 genes that were the most commonly affected ranging from 12% to 36% of overlap among breast cancer gene expression studies. Data mining analysis of transcripts and protein-protein interactions of these commonly modulated genes indicate three functional modules signifcantly affected among signatures, one module related with the response to steroid hormone stimulus, and two modules related to the cell cycle. Analysis of a publicly available gene expression data showed that the obtained meta-signature is capable of predicting overall survival (P < 0.0001) and relapse-free survival (P < 0.0001) in patients with early-stage breast carcinomas. In addition, the identifed meta-signature improves breast cancer patient stratifcation independently of traditional prognostic factors in a multivariate Cox proportional-hazards analysis.
publishDate 2010
dc.date.none.fl_str_mv 2010-10-27
dc.type.none.fl_str_mv info:eu-repo/semantics/review
info:eu-repo/semantics/publishedVersion
Revision
http://purl.org/coar/resource_type/c_dcae04bc
info:ar-repo/semantics/resenaArticulo
format review
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/34620
url http://sedici.unlp.edu.ar/handle/10915/34620
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.la-press.com/breast-cancer-biomarker-discovery-in-the-functional-genomic-age-a-syst-article-a2325
info:eu-repo/semantics/altIdentifier/issn/1177-2719
info:eu-repo/semantics/altIdentifier/doi/10.4137/BMI.S5740
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/3.0/
Creative Commons Attribution 3.0 Unported (CC BY 3.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/3.0/
Creative Commons Attribution 3.0 Unported (CC BY 3.0)
dc.format.none.fl_str_mv application/pdf
103-118
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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score 13.13397

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