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

<h4>Introduction</h4>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...

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Autores principales: Rebeca Sanz-Pamplona, Antoni Berenguer, David Cordero, Samantha Riccadonna, Xavier Solé, Marta Crous-Bou, Elisabet Guinó, Xavier Sanjuan, Sebastiano Biondo, Antonio Soriano, Giuseppe Jurman, Gabriel Capella, Cesare Furlanello, Victor Moreno
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Publicado: Public Library of Science (PLoS) 2012
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spelling oai:doaj.org-article:07e22085fbab488d96e4d6101fd408042021-11-18T08:09:38ZClinical value of prognosis gene expression signatures in colorectal cancer: a systematic review.1932-620310.1371/journal.pone.0048877https://doaj.org/article/07e22085fbab488d96e4d6101fd408042012-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23145004/?tool=EBIhttps://doaj.org/toc/1932-6203<h4>Introduction</h4>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.<h4>Methods</h4>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.<h4>Results</h4>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.<h4>Conclusions</h4>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.Rebeca Sanz-PamplonaAntoni BerenguerDavid CorderoSamantha RiccadonnaXavier SoléMarta Crous-BouElisabet GuinóXavier SanjuanSebastiano BiondoAntonio SorianoGiuseppe JurmanGabriel CapellaCesare FurlanelloVictor MorenoPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 7, Iss 11, p e48877 (2012)
institution DOAJ
collection DOAJ
language EN
topic Medicine
R
Science
Q
spellingShingle Medicine
R
Science
Q
Rebeca Sanz-Pamplona
Antoni Berenguer
David Cordero
Samantha Riccadonna
Xavier Solé
Marta Crous-Bou
Elisabet Guinó
Xavier Sanjuan
Sebastiano Biondo
Antonio Soriano
Giuseppe Jurman
Gabriel Capella
Cesare Furlanello
Victor Moreno
Clinical value of prognosis gene expression signatures in colorectal cancer: a systematic review.
description <h4>Introduction</h4>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.<h4>Methods</h4>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.<h4>Results</h4>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.<h4>Conclusions</h4>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.
format article
author Rebeca Sanz-Pamplona
Antoni Berenguer
David Cordero
Samantha Riccadonna
Xavier Solé
Marta Crous-Bou
Elisabet Guinó
Xavier Sanjuan
Sebastiano Biondo
Antonio Soriano
Giuseppe Jurman
Gabriel Capella
Cesare Furlanello
Victor Moreno
author_facet Rebeca Sanz-Pamplona
Antoni Berenguer
David Cordero
Samantha Riccadonna
Xavier Solé
Marta Crous-Bou
Elisabet Guinó
Xavier Sanjuan
Sebastiano Biondo
Antonio Soriano
Giuseppe Jurman
Gabriel Capella
Cesare Furlanello
Victor Moreno
author_sort Rebeca Sanz-Pamplona
title Clinical value of prognosis gene expression signatures in colorectal cancer: a systematic review.
title_short Clinical value of prognosis gene expression signatures in colorectal cancer: a systematic review.
title_full Clinical value of prognosis gene expression signatures in colorectal cancer: a systematic review.
title_fullStr Clinical value of prognosis gene expression signatures in colorectal cancer: a systematic review.
title_full_unstemmed Clinical value of prognosis gene expression signatures in colorectal cancer: a systematic review.
title_sort clinical value of prognosis gene expression signatures in colorectal cancer: a systematic review.
publisher Public Library of Science (PLoS)
publishDate 2012
url https://doaj.org/article/07e22085fbab488d96e4d6101fd40804
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