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Clinical Value of Prognosis Gene Expression Signatures in Colorectal Cancer: A Systematic Review
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...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3492249/ https://www.ncbi.nlm.nih.gov/pubmed/23145004 http://dx.doi.org/10.1371/journal.pone.0048877 |
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author | Sanz-Pamplona, Rebeca Berenguer, Antoni Cordero, David Riccadonna, Samantha Solé, Xavier Crous-Bou, Marta Guinó, Elisabet Sanjuan, Xavier Biondo, Sebastiano Soriano, Antonio Jurman, Giuseppe Capella, Gabriel Furlanello, Cesare Moreno, Victor |
author_facet | Sanz-Pamplona, Rebeca Berenguer, Antoni Cordero, David Riccadonna, Samantha Solé, Xavier Crous-Bou, Marta Guinó, Elisabet Sanjuan, Xavier Biondo, Sebastiano Soriano, Antonio Jurman, Giuseppe Capella, Gabriel Furlanello, Cesare Moreno, Victor |
author_sort | Sanz-Pamplona, Rebeca |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-3492249 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-34922492012-11-09 Clinical Value of Prognosis Gene Expression Signatures in Colorectal Cancer: A Systematic Review Sanz-Pamplona, Rebeca Berenguer, Antoni Cordero, David Riccadonna, Samantha Solé, Xavier Crous-Bou, Marta Guinó, Elisabet Sanjuan, Xavier Biondo, Sebastiano Soriano, Antonio Jurman, Giuseppe Capella, Gabriel Furlanello, Cesare Moreno, Victor PLoS One Research Article 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. Public Library of Science 2012-11-07 /pmc/articles/PMC3492249/ /pubmed/23145004 http://dx.doi.org/10.1371/journal.pone.0048877 Text en © 2012 Sanz-Pamplona et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Sanz-Pamplona, Rebeca Berenguer, Antoni Cordero, David Riccadonna, Samantha Solé, Xavier Crous-Bou, Marta Guinó, Elisabet Sanjuan, Xavier Biondo, Sebastiano Soriano, Antonio Jurman, Giuseppe Capella, Gabriel Furlanello, Cesare Moreno, Victor Clinical Value of Prognosis Gene Expression Signatures in Colorectal Cancer: A Systematic Review |
title | 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_short | 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 |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3492249/ https://www.ncbi.nlm.nih.gov/pubmed/23145004 http://dx.doi.org/10.1371/journal.pone.0048877 |
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