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Two-gene signature improves the discriminatory power of IASLC/ATS/ERS classification to predict the survival of patients with early-stage lung adenocarcinoma

BACKGROUND: In this study, we investigated the contribution of a gene expression–based signature (composed of BAG1, BRCA1, CDC6, CDK2AP1, ERBB3, FUT3, IL11, LCK, RND3, SH3BGR) to survival prediction for early-stage lung adenocarcinoma categorized by the new International Association for the Study of...

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Autores principales: Sun, Yifeng, Hou, Likun, Yang, Yu, Xie, Huikang, Yang, Yang, Li, Zhigang, Zhao, Heng, Gao, Wen, Su, Bo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove Medical Press 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4966694/
https://www.ncbi.nlm.nih.gov/pubmed/27524912
http://dx.doi.org/10.2147/OTT.S107272
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author Sun, Yifeng
Hou, Likun
Yang, Yu
Xie, Huikang
Yang, Yang
Li, Zhigang
Zhao, Heng
Gao, Wen
Su, Bo
author_facet Sun, Yifeng
Hou, Likun
Yang, Yu
Xie, Huikang
Yang, Yang
Li, Zhigang
Zhao, Heng
Gao, Wen
Su, Bo
author_sort Sun, Yifeng
collection PubMed
description BACKGROUND: In this study, we investigated the contribution of a gene expression–based signature (composed of BAG1, BRCA1, CDC6, CDK2AP1, ERBB3, FUT3, IL11, LCK, RND3, SH3BGR) to survival prediction for early-stage lung adenocarcinoma categorized by the new International Association for the Study of Lung Cancer (IASLC)/the American Thoracic Society (ATS)/the European Respiratory Society (ERS) classification. We also aimed to verify whether gene signature improves the risk discrimination of IASLC/ATS/ERS classification in early-stage lung adenocarcinoma. PATIENTS AND METHODS: Total RNA was extracted from 93 patients with pathologically confirmed TNM stage Ia and Ib lung adenocarcinoma. The mRNA expression levels of ten genes in the signature (BAG1, BRCA1, CDC6, CDK2AP1, ERBB3, FUT3, IL11, LCK, RND3, and SH3BGR) were detected using real-time polymerase chain reaction. Each patient was categorized according to the new IASLC/ATS/ERS classification by accessing hematoxylin–eosin-stained slides. The corresponding Kaplan–Meier survival analysis by the log-rank statistic, multivariate Cox proportional hazards modeling, and c-index calculation were conducted using the programming language R (Version 2.15.1) with the “risksetROC” package. RESULTS: The multivariate analysis demonstrated that the risk factor of the ten-gene expression signature can significantly improve the discriminatory value of TNM staging in survival prediction, but not the value of the IASLC/ATS/ERS classification. Further analysis suggested that only BRCA1 and ERBB3 in the signature were independent risk factors after adjusting for the IASLC/ATS/ERS classification by Cox regression. A new algorithm of the two-gene expression signature containing BRCA1 and ERBB3 was generated. Adding the two-gene signature into the IASLC/ATS/ERS classification model further improved the discriminatory c-statistic from 0.728 to 0.756. CONCLUSION: The two-gene signature composed of BRCA1 and ERBB3 was an independent risk factor of the IASLC/ATS/ERS classification, which can be used to improve the discriminatory power of prognosis prediction of the IASLC/ATS/ERS classification in early-stage lung adenocarcinoma. The two-gene signature combination with the IASLC/ATS/ERS classification might contribute to better patient stratification for adjuvant chemoradiotherapy or targeted therapy after the surgery.
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spelling pubmed-49666942016-08-12 Two-gene signature improves the discriminatory power of IASLC/ATS/ERS classification to predict the survival of patients with early-stage lung adenocarcinoma Sun, Yifeng Hou, Likun Yang, Yu Xie, Huikang Yang, Yang Li, Zhigang Zhao, Heng Gao, Wen Su, Bo Onco Targets Ther Original Research BACKGROUND: In this study, we investigated the contribution of a gene expression–based signature (composed of BAG1, BRCA1, CDC6, CDK2AP1, ERBB3, FUT3, IL11, LCK, RND3, SH3BGR) to survival prediction for early-stage lung adenocarcinoma categorized by the new International Association for the Study of Lung Cancer (IASLC)/the American Thoracic Society (ATS)/the European Respiratory Society (ERS) classification. We also aimed to verify whether gene signature improves the risk discrimination of IASLC/ATS/ERS classification in early-stage lung adenocarcinoma. PATIENTS AND METHODS: Total RNA was extracted from 93 patients with pathologically confirmed TNM stage Ia and Ib lung adenocarcinoma. The mRNA expression levels of ten genes in the signature (BAG1, BRCA1, CDC6, CDK2AP1, ERBB3, FUT3, IL11, LCK, RND3, and SH3BGR) were detected using real-time polymerase chain reaction. Each patient was categorized according to the new IASLC/ATS/ERS classification by accessing hematoxylin–eosin-stained slides. The corresponding Kaplan–Meier survival analysis by the log-rank statistic, multivariate Cox proportional hazards modeling, and c-index calculation were conducted using the programming language R (Version 2.15.1) with the “risksetROC” package. RESULTS: The multivariate analysis demonstrated that the risk factor of the ten-gene expression signature can significantly improve the discriminatory value of TNM staging in survival prediction, but not the value of the IASLC/ATS/ERS classification. Further analysis suggested that only BRCA1 and ERBB3 in the signature were independent risk factors after adjusting for the IASLC/ATS/ERS classification by Cox regression. A new algorithm of the two-gene expression signature containing BRCA1 and ERBB3 was generated. Adding the two-gene signature into the IASLC/ATS/ERS classification model further improved the discriminatory c-statistic from 0.728 to 0.756. CONCLUSION: The two-gene signature composed of BRCA1 and ERBB3 was an independent risk factor of the IASLC/ATS/ERS classification, which can be used to improve the discriminatory power of prognosis prediction of the IASLC/ATS/ERS classification in early-stage lung adenocarcinoma. The two-gene signature combination with the IASLC/ATS/ERS classification might contribute to better patient stratification for adjuvant chemoradiotherapy or targeted therapy after the surgery. Dove Medical Press 2016-07-25 /pmc/articles/PMC4966694/ /pubmed/27524912 http://dx.doi.org/10.2147/OTT.S107272 Text en © 2016 Sun et al. This work is published and licensed by Dove Medical Press Limited The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed.
spellingShingle Original Research
Sun, Yifeng
Hou, Likun
Yang, Yu
Xie, Huikang
Yang, Yang
Li, Zhigang
Zhao, Heng
Gao, Wen
Su, Bo
Two-gene signature improves the discriminatory power of IASLC/ATS/ERS classification to predict the survival of patients with early-stage lung adenocarcinoma
title Two-gene signature improves the discriminatory power of IASLC/ATS/ERS classification to predict the survival of patients with early-stage lung adenocarcinoma
title_full Two-gene signature improves the discriminatory power of IASLC/ATS/ERS classification to predict the survival of patients with early-stage lung adenocarcinoma
title_fullStr Two-gene signature improves the discriminatory power of IASLC/ATS/ERS classification to predict the survival of patients with early-stage lung adenocarcinoma
title_full_unstemmed Two-gene signature improves the discriminatory power of IASLC/ATS/ERS classification to predict the survival of patients with early-stage lung adenocarcinoma
title_short Two-gene signature improves the discriminatory power of IASLC/ATS/ERS classification to predict the survival of patients with early-stage lung adenocarcinoma
title_sort two-gene signature improves the discriminatory power of iaslc/ats/ers classification to predict the survival of patients with early-stage lung adenocarcinoma
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4966694/
https://www.ncbi.nlm.nih.gov/pubmed/27524912
http://dx.doi.org/10.2147/OTT.S107272
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