Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/119413
Title: Clinical value of prognosis gene expression signatures in colorectal cancer: a systematic review
Author: Sanz Pamplona, Rebeca
Berenguer, Antoni
Cordero Romera, David
Riccadonna, Samantha
Solé Acha, Xavier
Crous Bou, Marta
Guinó, Elisabet
Sanjuan, Xavier
Biondo, Sebastián
Soriano Izquierdo, Antonio
Jurman, Giuseppe
Capellá, G. (Gabriel)
Furlanello, Cesare
Moreno Aguado, Víctor
Keywords: Pronòstic mèdic
Expressió gènica
Càncer colorectal
Ressenyes sistemàtiques (Investigació mèdica)
Prognosis
Gene expression
Colorectal cancer
Systematic reviews (Medical research)
Issue Date: 7-Nov-2012
Publisher: Public Library of Science (PLoS)
Abstract: Introduction: 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.
Note: Reproducció del document publicat a: https://doi.org/10.1371/journal.pone.0048877
It is part of: PLoS One, 2012, vol. 7, num. 11, p. e48877
URI: http://hdl.handle.net/2445/119413
Related resource: https://doi.org/10.1371/journal.pone.0048877
ISSN: 1932-6203
Appears in Collections:Articles publicats en revistes (Ciències Clíniques)
Articles publicats en revistes (Institut d'lnvestigació Biomèdica de Bellvitge (IDIBELL))

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