Identifying the miRNA signature associated with survival time in patients with lung adenocarcinoma using miRNA expression profiles

Abstract Lung adenocarcinoma is a multifactorial disease. MicroRNA (miRNA) expression profiles are extensively used for discovering potential theranostic biomarkers of lung cancer. This work proposes an optimized support vector regression (SVR) method called SVR-LUAD to simultaneously identify a set...

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Autores principales:	Srinivasulu Yerukala Sathipati, Shinn-Ying Ho
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/071f0e818b704eceb31f311cc2d18612
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spelling	oai:doaj.org-article:071f0e818b704eceb31f311cc2d186122021-12-02T11:41:20ZIdentifying the miRNA signature associated with survival time in patients with lung adenocarcinoma using miRNA expression profiles10.1038/s41598-017-07739-y2045-2322https://doaj.org/article/071f0e818b704eceb31f311cc2d186122017-08-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-07739-yhttps://doaj.org/toc/2045-2322Abstract Lung adenocarcinoma is a multifactorial disease. MicroRNA (miRNA) expression profiles are extensively used for discovering potential theranostic biomarkers of lung cancer. This work proposes an optimized support vector regression (SVR) method called SVR-LUAD to simultaneously identify a set of miRNAs referred to the miRNA signature for estimating the survival time of lung adenocarcinoma patients using their miRNA expression profiles. SVR-LUAD uses an inheritable bi-objective combinatorial genetic algorithm to identify a small set of informative miRNAs cooperating with SVR by maximizing estimation accuracy. SVR-LUAD identified 18 out of 332 miRNAs using 10-fold cross-validation and achieved a correlation coefficient of 0.88 ± 0.01 and mean absolute error of 0.56 ± 0.03 year between real and estimated survival time. SVR-LUAD performs well compared to some well-recognized regression methods. The miRNA signature consists of the 18 miRNAs which strongly correlates with lung adenocarcinoma: hsa-let-7f-1, hsa-miR-16-1, hsa-miR-152, hsa-miR-217, hsa-miR-18a, hsa-miR-193b, hsa-miR-3136, hsa-let-7g, hsa-miR-155, hsa-miR-3199-1, hsa-miR-219-2, hsa-miR-1254, hsa-miR-1291, hsa-miR-192, hsa-miR-3653, hsa-miR-3934, hsa-miR-342, and hsa-miR-141. Gene ontology annotation and pathway analysis of the miRNA signature revealed its biological significance in cancer and cellular pathways. This miRNA signature could aid in the development of novel therapeutic approaches to the treatment of lung adenocarcinoma.Srinivasulu Yerukala SathipatiShinn-Ying HoNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-15 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Srinivasulu Yerukala Sathipati Shinn-Ying Ho Identifying the miRNA signature associated with survival time in patients with lung adenocarcinoma using miRNA expression profiles
description	Abstract Lung adenocarcinoma is a multifactorial disease. MicroRNA (miRNA) expression profiles are extensively used for discovering potential theranostic biomarkers of lung cancer. This work proposes an optimized support vector regression (SVR) method called SVR-LUAD to simultaneously identify a set of miRNAs referred to the miRNA signature for estimating the survival time of lung adenocarcinoma patients using their miRNA expression profiles. SVR-LUAD uses an inheritable bi-objective combinatorial genetic algorithm to identify a small set of informative miRNAs cooperating with SVR by maximizing estimation accuracy. SVR-LUAD identified 18 out of 332 miRNAs using 10-fold cross-validation and achieved a correlation coefficient of 0.88 ± 0.01 and mean absolute error of 0.56 ± 0.03 year between real and estimated survival time. SVR-LUAD performs well compared to some well-recognized regression methods. The miRNA signature consists of the 18 miRNAs which strongly correlates with lung adenocarcinoma: hsa-let-7f-1, hsa-miR-16-1, hsa-miR-152, hsa-miR-217, hsa-miR-18a, hsa-miR-193b, hsa-miR-3136, hsa-let-7g, hsa-miR-155, hsa-miR-3199-1, hsa-miR-219-2, hsa-miR-1254, hsa-miR-1291, hsa-miR-192, hsa-miR-3653, hsa-miR-3934, hsa-miR-342, and hsa-miR-141. Gene ontology annotation and pathway analysis of the miRNA signature revealed its biological significance in cancer and cellular pathways. This miRNA signature could aid in the development of novel therapeutic approaches to the treatment of lung adenocarcinoma.
format	article
author	Srinivasulu Yerukala Sathipati Shinn-Ying Ho
author_facet	Srinivasulu Yerukala Sathipati Shinn-Ying Ho
author_sort	Srinivasulu Yerukala Sathipati
title	Identifying the miRNA signature associated with survival time in patients with lung adenocarcinoma using miRNA expression profiles
title_short	Identifying the miRNA signature associated with survival time in patients with lung adenocarcinoma using miRNA expression profiles
title_full	Identifying the miRNA signature associated with survival time in patients with lung adenocarcinoma using miRNA expression profiles
title_fullStr	Identifying the miRNA signature associated with survival time in patients with lung adenocarcinoma using miRNA expression profiles
title_full_unstemmed	Identifying the miRNA signature associated with survival time in patients with lung adenocarcinoma using miRNA expression profiles
title_sort	identifying the mirna signature associated with survival time in patients with lung adenocarcinoma using mirna expression profiles
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/071f0e818b704eceb31f311cc2d18612
work_keys_str_mv	AT srinivasuluyerukalasathipati identifyingthemirnasignatureassociatedwithsurvivaltimeinpatientswithlungadenocarcinomausingmirnaexpressionprofiles AT shinnyingho identifyingthemirnasignatureassociatedwithsurvivaltimeinpatientswithlungadenocarcinomausingmirnaexpressionprofiles
_version_	1718395382526902272

Identifying the miRNA signature associated with survival time in patients with lung adenocarcinoma using miRNA expression profiles

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