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Identification of a 6-gene signature predicting prognosis for colorectal cancer

BACKGROUND: An accurate and robust gene signature is of the utmost importance in assisting oncologists to make a more accurate evaluation in clinical practice. In our study, we extracted key mRNAs significantly related to colorectal cancer (CRC) prognosis and we constructed an expression-based gene...

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Autores principales: Zuo, Shuguang, Dai, Gongpeng, Ren, Xuequn
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6321660/
https://www.ncbi.nlm.nih.gov/pubmed/30627052
http://dx.doi.org/10.1186/s12935-018-0724-7
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author Zuo, Shuguang
Dai, Gongpeng
Ren, Xuequn
author_facet Zuo, Shuguang
Dai, Gongpeng
Ren, Xuequn
author_sort Zuo, Shuguang
collection PubMed
description BACKGROUND: An accurate and robust gene signature is of the utmost importance in assisting oncologists to make a more accurate evaluation in clinical practice. In our study, we extracted key mRNAs significantly related to colorectal cancer (CRC) prognosis and we constructed an expression-based gene signature to predict CRC patients’ survival. METHODS: mRNA expression profiles and clinicopathological data of colon adenocarcinoma (COAD) cases and rectum adenocarcinoma (READ) were collected from The Cancer Genome Atlas database to investigate gene expression alteration associated to the prognosis of CRC. Differentially expressed mRNAs (DEMs) were detected between COAD/READ and normal tissue samples. Relying on a univariate and multivariate Cox regression analyses, a mRNA panel signature was established and used for predicting the overall survival (OS) in CRC patients. Receiver operating characteristic curve was used to evaluate the prognosis performance of our model through calculating the AUC values corresponding to the 3-year and 5-year survival. To assess the performance of gene signature in the given cancer subgroups (CRC entire cohort, COAD cohort, and READ cohort), a stratified analysis was carried out according to clinical factors. RESULTS: A total of 5341 and 5594 DEMs were collected from COAD vs. normal tissue samples, and READ vs. normal samples respectively. A univariate regression analysis for the common DEMs between COAD and READ cohorts resulted in 14 common mRNAs related to OS. The multivariate Cox regression analysis revealed that 6 of these mRNAs (EPHA6, TIMP1, IRX6, ART5, HIST3H2BB, and FOXD1) had significant prognostic value allowing the discrimination between high- and low-risk patients, implying poor and good outcomes, respectively. The stratified analysis identified 6-gene signature as an independent prognostic signature in predicting CRC patients’ survival. CONCLUSIONS: The 6-gene signature could act as an independent biomarker for survival prediction of CRC patients. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12935-018-0724-7) contains supplementary material, which is available to authorized users.
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spelling pubmed-63216602019-01-09 Identification of a 6-gene signature predicting prognosis for colorectal cancer Zuo, Shuguang Dai, Gongpeng Ren, Xuequn Cancer Cell Int Primary Research BACKGROUND: An accurate and robust gene signature is of the utmost importance in assisting oncologists to make a more accurate evaluation in clinical practice. In our study, we extracted key mRNAs significantly related to colorectal cancer (CRC) prognosis and we constructed an expression-based gene signature to predict CRC patients’ survival. METHODS: mRNA expression profiles and clinicopathological data of colon adenocarcinoma (COAD) cases and rectum adenocarcinoma (READ) were collected from The Cancer Genome Atlas database to investigate gene expression alteration associated to the prognosis of CRC. Differentially expressed mRNAs (DEMs) were detected between COAD/READ and normal tissue samples. Relying on a univariate and multivariate Cox regression analyses, a mRNA panel signature was established and used for predicting the overall survival (OS) in CRC patients. Receiver operating characteristic curve was used to evaluate the prognosis performance of our model through calculating the AUC values corresponding to the 3-year and 5-year survival. To assess the performance of gene signature in the given cancer subgroups (CRC entire cohort, COAD cohort, and READ cohort), a stratified analysis was carried out according to clinical factors. RESULTS: A total of 5341 and 5594 DEMs were collected from COAD vs. normal tissue samples, and READ vs. normal samples respectively. A univariate regression analysis for the common DEMs between COAD and READ cohorts resulted in 14 common mRNAs related to OS. The multivariate Cox regression analysis revealed that 6 of these mRNAs (EPHA6, TIMP1, IRX6, ART5, HIST3H2BB, and FOXD1) had significant prognostic value allowing the discrimination between high- and low-risk patients, implying poor and good outcomes, respectively. The stratified analysis identified 6-gene signature as an independent prognostic signature in predicting CRC patients’ survival. CONCLUSIONS: The 6-gene signature could act as an independent biomarker for survival prediction of CRC patients. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12935-018-0724-7) contains supplementary material, which is available to authorized users. BioMed Central 2019-01-05 /pmc/articles/PMC6321660/ /pubmed/30627052 http://dx.doi.org/10.1186/s12935-018-0724-7 Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Primary Research
Zuo, Shuguang
Dai, Gongpeng
Ren, Xuequn
Identification of a 6-gene signature predicting prognosis for colorectal cancer
title Identification of a 6-gene signature predicting prognosis for colorectal cancer
title_full Identification of a 6-gene signature predicting prognosis for colorectal cancer
title_fullStr Identification of a 6-gene signature predicting prognosis for colorectal cancer
title_full_unstemmed Identification of a 6-gene signature predicting prognosis for colorectal cancer
title_short Identification of a 6-gene signature predicting prognosis for colorectal cancer
title_sort identification of a 6-gene signature predicting prognosis for colorectal cancer
topic Primary Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6321660/
https://www.ncbi.nlm.nih.gov/pubmed/30627052
http://dx.doi.org/10.1186/s12935-018-0724-7
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