Clinical value of prognosis gene expression signatures in colorectal cancer: a systematic review

dc.contributor.authorSanz Pamplona, Rebeca
dc.contributor.authorBerenguer, Antoni
dc.contributor.authorCordero Romera, David
dc.contributor.authorRiccadonna, Samantha
dc.contributor.authorSolé Acha, Xavier
dc.contributor.authorCrous Bou, Marta
dc.contributor.authorGuinó, Elisabet
dc.contributor.authorSanjuan, Xavier
dc.contributor.authorBiondo, Sebastián
dc.contributor.authorSoriano Izquierdo, Antonio
dc.contributor.authorJurman, Giuseppe
dc.contributor.authorCapellá, G. (Gabriel)
dc.contributor.authorFurlanello, Cesare
dc.contributor.authorMoreno Aguado, Víctor
dc.date.accessioned2018-01-30T12:38:01Z
dc.date.available2018-01-30T12:38:01Z
dc.date.issued2012-11-07
dc.date.updated2018-01-30T12:38:01Z
dc.description.abstractIntroduction: the traditional staging system is inadequate to identify those patients with stage II colorectal cancer (CRC) at high risk of recurrence or with stage III CRC at low risk. A number of gene expression signatures to predict CRC prognosis have been proposed, but none is routinely used in the clinic. The aim of this work was to assess the prediction ability and potential clinical usefulness of these signatures in a series of independent datasets. Methods: a literature review identified 31 gene expression signatures that used gene expression data to predict prognosis in CRC tissue. The search was based on the PubMed database and was restricted to papers published from January 2004 to December 2011. Eleven CRC gene expression datasets with outcome information were identified and downloaded from public repositories. Random Forest classifier was used to build predictors from the gene lists. Matthews correlation coefficient was chosen as a measure of classification accuracy and its associated p-value was used to assess association with prognosis. For clinical usefulness evaluation, positive and negative post-tests probabilities were computed in stage II and III samples. Results: five gene signatures showed significant association with prognosis and provided reasonable prediction accuracy in their own training datasets. Nevertheless, all signatures showed low reproducibility in independent data. Stratified analyses by stage or microsatellite instability status showed significant association but limited discrimination ability, especially in stage II tumors. From a clinical perspective, the most predictive signatures showed a minor but significant improvement over the classical staging system. Conclusions: the published signatures show low prediction accuracy but moderate clinical usefulness. Although gene expression data may inform prognosis, better strategies for signature validation are needed to encourage their widespread use in the clinic.
dc.format.extent14 p.
dc.format.mimetypeapplication/pdf
dc.identifier.idgrec621560
dc.identifier.issn1932-6203
dc.identifier.pmid23145004
dc.identifier.urihttps://hdl.handle.net/2445/119413
dc.language.isoeng
dc.publisherPublic Library of Science (PLoS)
dc.relation.isformatofReproducció del document publicat a: https://doi.org/10.1371/journal.pone.0048877
dc.relation.ispartofPLoS One, 2012, vol. 7, num. 11, p. e48877
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/FP7/223378/EU//HIPERDART
dc.relation.urihttps://doi.org/10.1371/journal.pone.0048877
dc.rightscc-by (c) Sanz Pamplona, Rebeca et al., 2012
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es
dc.sourceArticles publicats en revistes (Ciències Clíniques)
dc.subject.classificationPronòstic mèdic
dc.subject.classificationExpressió gènica
dc.subject.classificationCàncer colorectal
dc.subject.classificationRessenyes sistemàtiques (Investigació mèdica)
dc.subject.otherPrognosis
dc.subject.otherGene expression
dc.subject.otherColorectal cancer
dc.subject.otherSystematic reviews (Medical research)
dc.titleClinical value of prognosis gene expression signatures in colorectal cancer: a systematic review
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion

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