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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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