Cargando…

Identification of a Five-Gene Signature for Predicting Survival in Malignant Pleural Mesothelioma Patients

Malignant pleural mesothelioma (MPM), predominantly caused by asbestos exposure, is a highly aggressive cancer with poor prognosis. The staging systems currently used in clinics is inadequate in evaluating the prognosis of MPM. In this study, a five-gene signature was developed and enrolled into a p...

Descripción completa

Detalles Bibliográficos
Autores principales: Bai, Yiyang, Wang, Xiao, Hou, Jia, Geng, Luying, Liang, Xuan, Ruan, Zhiping, Guo, Hui, Nan, Kejun, Jiang, Lili
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7427512/
https://www.ncbi.nlm.nih.gov/pubmed/32849853
http://dx.doi.org/10.3389/fgene.2020.00899
_version_ 1783570890296918016
author Bai, Yiyang
Wang, Xiao
Hou, Jia
Geng, Luying
Liang, Xuan
Ruan, Zhiping
Guo, Hui
Nan, Kejun
Jiang, Lili
author_facet Bai, Yiyang
Wang, Xiao
Hou, Jia
Geng, Luying
Liang, Xuan
Ruan, Zhiping
Guo, Hui
Nan, Kejun
Jiang, Lili
author_sort Bai, Yiyang
collection PubMed
description Malignant pleural mesothelioma (MPM), predominantly caused by asbestos exposure, is a highly aggressive cancer with poor prognosis. The staging systems currently used in clinics is inadequate in evaluating the prognosis of MPM. In this study, a five-gene signature was developed and enrolled into a prognostic risk score model by LASSO Cox regression analysis based on two expression profiling datasets (GSE2549 and GSE51024) from Gene Expression Omnibus (GEO). The five-gene signature was further validated using the Cancer Genome Atlas (TCGA) MPM dataset. Univariate and multivariate Cox analyses proved that the five-gene signature was an independent prognostic factor for MPM. The signature remained statistically significant upon stratification by Brigham stage, AJCC stage, gender, tumor size, and lymph node status. Time-dependent receiver operating characteristic (ROC) curve indicated good performance of our model in predicting 1- and 2-years overall survival in MPM patients. The C-index was 0.784 for GSE2549 and 0.753 for the TCGA dataset showing moderate predictive accuracy of our model. Furthermore, Gene Set Enrichment Analysis suggested that the five-gene signature was related to pathways resulting in MPM tumor progression. Together, we have established a five-gene signature significantly associated with prognosis in MPM patients. Hence, the five-genes signature may serve as a potentially useful prognostic tool for MPM patients.
format Online
Article
Text
id pubmed-7427512
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-74275122020-08-25 Identification of a Five-Gene Signature for Predicting Survival in Malignant Pleural Mesothelioma Patients Bai, Yiyang Wang, Xiao Hou, Jia Geng, Luying Liang, Xuan Ruan, Zhiping Guo, Hui Nan, Kejun Jiang, Lili Front Genet Genetics Malignant pleural mesothelioma (MPM), predominantly caused by asbestos exposure, is a highly aggressive cancer with poor prognosis. The staging systems currently used in clinics is inadequate in evaluating the prognosis of MPM. In this study, a five-gene signature was developed and enrolled into a prognostic risk score model by LASSO Cox regression analysis based on two expression profiling datasets (GSE2549 and GSE51024) from Gene Expression Omnibus (GEO). The five-gene signature was further validated using the Cancer Genome Atlas (TCGA) MPM dataset. Univariate and multivariate Cox analyses proved that the five-gene signature was an independent prognostic factor for MPM. The signature remained statistically significant upon stratification by Brigham stage, AJCC stage, gender, tumor size, and lymph node status. Time-dependent receiver operating characteristic (ROC) curve indicated good performance of our model in predicting 1- and 2-years overall survival in MPM patients. The C-index was 0.784 for GSE2549 and 0.753 for the TCGA dataset showing moderate predictive accuracy of our model. Furthermore, Gene Set Enrichment Analysis suggested that the five-gene signature was related to pathways resulting in MPM tumor progression. Together, we have established a five-gene signature significantly associated with prognosis in MPM patients. Hence, the five-genes signature may serve as a potentially useful prognostic tool for MPM patients. Frontiers Media S.A. 2020-08-07 /pmc/articles/PMC7427512/ /pubmed/32849853 http://dx.doi.org/10.3389/fgene.2020.00899 Text en Copyright © 2020 Bai, Wang, Hou, Geng, Liang, Ruan, Guo, Nan and Jiang. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Bai, Yiyang
Wang, Xiao
Hou, Jia
Geng, Luying
Liang, Xuan
Ruan, Zhiping
Guo, Hui
Nan, Kejun
Jiang, Lili
Identification of a Five-Gene Signature for Predicting Survival in Malignant Pleural Mesothelioma Patients
title Identification of a Five-Gene Signature for Predicting Survival in Malignant Pleural Mesothelioma Patients
title_full Identification of a Five-Gene Signature for Predicting Survival in Malignant Pleural Mesothelioma Patients
title_fullStr Identification of a Five-Gene Signature for Predicting Survival in Malignant Pleural Mesothelioma Patients
title_full_unstemmed Identification of a Five-Gene Signature for Predicting Survival in Malignant Pleural Mesothelioma Patients
title_short Identification of a Five-Gene Signature for Predicting Survival in Malignant Pleural Mesothelioma Patients
title_sort identification of a five-gene signature for predicting survival in malignant pleural mesothelioma patients
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7427512/
https://www.ncbi.nlm.nih.gov/pubmed/32849853
http://dx.doi.org/10.3389/fgene.2020.00899
work_keys_str_mv AT baiyiyang identificationofafivegenesignatureforpredictingsurvivalinmalignantpleuralmesotheliomapatients
AT wangxiao identificationofafivegenesignatureforpredictingsurvivalinmalignantpleuralmesotheliomapatients
AT houjia identificationofafivegenesignatureforpredictingsurvivalinmalignantpleuralmesotheliomapatients
AT gengluying identificationofafivegenesignatureforpredictingsurvivalinmalignantpleuralmesotheliomapatients
AT liangxuan identificationofafivegenesignatureforpredictingsurvivalinmalignantpleuralmesotheliomapatients
AT ruanzhiping identificationofafivegenesignatureforpredictingsurvivalinmalignantpleuralmesotheliomapatients
AT guohui identificationofafivegenesignatureforpredictingsurvivalinmalignantpleuralmesotheliomapatients
AT nankejun identificationofafivegenesignatureforpredictingsurvivalinmalignantpleuralmesotheliomapatients
AT jianglili identificationofafivegenesignatureforpredictingsurvivalinmalignantpleuralmesotheliomapatients