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Consensus of gene expression phenotypes and prognostic risk predictors in primary lung adenocarcinoma

Transcriptional profiling of lung adenocarcinomas has identified numerous gene expression phenotype (GEP) and risk prediction (RP) signatures associated with patient outcome. However, classification agreement between signatures, underlying transcriptional programs, and independent signature validati...

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Autores principales: Ringnér, Markus, Staaf, Johan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals LLC 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5288161/
https://www.ncbi.nlm.nih.gov/pubmed/27437773
http://dx.doi.org/10.18632/oncotarget.10641
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author Ringnér, Markus
Staaf, Johan
author_facet Ringnér, Markus
Staaf, Johan
author_sort Ringnér, Markus
collection PubMed
description Transcriptional profiling of lung adenocarcinomas has identified numerous gene expression phenotype (GEP) and risk prediction (RP) signatures associated with patient outcome. However, classification agreement between signatures, underlying transcriptional programs, and independent signature validation are less studied. We classified 2395 transcriptional adenocarcinoma profiles, assembled from 17 public cohorts, using 11 GEP and seven RP signatures, finding that 16 signatures were associated with patient survival in the total cohort and in multiple individual cohorts. For significant signatures, total cohort hazard ratios were ~2 in univariate analyses (mean=1.95, range=1.4-2.6). Strong classification agreement between signatures was observed, especially for predicted low-risk patients by adenocarcinoma-derived signatures. Expression of proliferation-related genes correlated strongly with GEP subtype classifications and RP scores, driving the gene signature association with prognosis. A three-group consensus definition of samples across 10 GEP classifiers demonstrated aggregation of samples with specific smoking patterns, gender, and EGFR/KRAS mutations, while survival differences were only significant when patients were divided into low- or high-risk. In summary, our study demonstrates a consensus between GEPs and RPs in lung adenocarcinoma through a common underlying transcriptional program. This consensus generalizes reported problems with current signatures in a clinical context, stressing development of new adenocarcinoma-specific single sample predictors for clinical use.
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spelling pubmed-52881612017-02-07 Consensus of gene expression phenotypes and prognostic risk predictors in primary lung adenocarcinoma Ringnér, Markus Staaf, Johan Oncotarget Research Paper Transcriptional profiling of lung adenocarcinomas has identified numerous gene expression phenotype (GEP) and risk prediction (RP) signatures associated with patient outcome. However, classification agreement between signatures, underlying transcriptional programs, and independent signature validation are less studied. We classified 2395 transcriptional adenocarcinoma profiles, assembled from 17 public cohorts, using 11 GEP and seven RP signatures, finding that 16 signatures were associated with patient survival in the total cohort and in multiple individual cohorts. For significant signatures, total cohort hazard ratios were ~2 in univariate analyses (mean=1.95, range=1.4-2.6). Strong classification agreement between signatures was observed, especially for predicted low-risk patients by adenocarcinoma-derived signatures. Expression of proliferation-related genes correlated strongly with GEP subtype classifications and RP scores, driving the gene signature association with prognosis. A three-group consensus definition of samples across 10 GEP classifiers demonstrated aggregation of samples with specific smoking patterns, gender, and EGFR/KRAS mutations, while survival differences were only significant when patients were divided into low- or high-risk. In summary, our study demonstrates a consensus between GEPs and RPs in lung adenocarcinoma through a common underlying transcriptional program. This consensus generalizes reported problems with current signatures in a clinical context, stressing development of new adenocarcinoma-specific single sample predictors for clinical use. Impact Journals LLC 2016-07-16 /pmc/articles/PMC5288161/ /pubmed/27437773 http://dx.doi.org/10.18632/oncotarget.10641 Text en Copyright: © 2016 Ringnér and Staaf http://creativecommons.org/licenses/by/2.5/ 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 credited.
spellingShingle Research Paper
Ringnér, Markus
Staaf, Johan
Consensus of gene expression phenotypes and prognostic risk predictors in primary lung adenocarcinoma
title Consensus of gene expression phenotypes and prognostic risk predictors in primary lung adenocarcinoma
title_full Consensus of gene expression phenotypes and prognostic risk predictors in primary lung adenocarcinoma
title_fullStr Consensus of gene expression phenotypes and prognostic risk predictors in primary lung adenocarcinoma
title_full_unstemmed Consensus of gene expression phenotypes and prognostic risk predictors in primary lung adenocarcinoma
title_short Consensus of gene expression phenotypes and prognostic risk predictors in primary lung adenocarcinoma
title_sort consensus of gene expression phenotypes and prognostic risk predictors in primary lung adenocarcinoma
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5288161/
https://www.ncbi.nlm.nih.gov/pubmed/27437773
http://dx.doi.org/10.18632/oncotarget.10641
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