A highly expressed mRNA signature for predicting survival in patients with stage I/II non-small-cell lung cancer after operation

Abstract There is an urgent need to identify novel biomarkers that predict the prognosis of patients with NSCLC. In this study,we aim to find out mRNA signature closely related to the prognosis of NSCLC by new algorithm of bioinformatics. Identification of highly expressed mRNA in stage I/II patient...

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Autores principales:	Nan Ma, Lu Si, Meiling Yang, Meihua Li, Zhiyi He
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/f95fe2809a7c431fa7116023bf8a6285
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spelling	oai:doaj.org-article:f95fe2809a7c431fa7116023bf8a62852021-12-02T11:36:21ZA highly expressed mRNA signature for predicting survival in patients with stage I/II non-small-cell lung cancer after operation10.1038/s41598-021-85246-x2045-2322https://doaj.org/article/f95fe2809a7c431fa7116023bf8a62852021-03-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-85246-xhttps://doaj.org/toc/2045-2322Abstract There is an urgent need to identify novel biomarkers that predict the prognosis of patients with NSCLC. In this study,we aim to find out mRNA signature closely related to the prognosis of NSCLC by new algorithm of bioinformatics. Identification of highly expressed mRNA in stage I/II patients with NSCLC was performed with the “Limma” package of R software. Survival analysis of patients with different mRNA expression levels was subsequently calculated by Cox regression analysis, and a multi-RNA signature was obtained by using the training set. Kaplan–Meier estimator, log-rank test and receiver operating characteristic (ROC) curves were used to analyse the predictive ability of the multi-RNA signature. RT-PCR used to verify the expression of the multi-RNA signature, and Westernblot used to verify the expression of proteins related to the multi-RNA signature. We identified fifteen survival-related mRNAs in the training set and classified the patients as high risk or low risk. NSCLC patients with low risk scores had longer disease-free survival than patients with high risk scores. The fifteen-mRNA signature was an independent prognostic factor, as shown by the ROC curve. ROC curve also showed that the combined model of the fifteen-mRNA signature and tumour stage had higher precision than stage alone. The expression of fifteen mRNAs and related proteins were higher in stage II NSCLC than in stage I NSCLC. Multi-gene expression profiles provide a moderate prognostic tool for NSCLC patients with stage I/II disease.Nan MaLu SiMeiling YangMeihua LiZhiyi HeNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-18 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Nan Ma Lu Si Meiling Yang Meihua Li Zhiyi He A highly expressed mRNA signature for predicting survival in patients with stage I/II non-small-cell lung cancer after operation
description	Abstract There is an urgent need to identify novel biomarkers that predict the prognosis of patients with NSCLC. In this study,we aim to find out mRNA signature closely related to the prognosis of NSCLC by new algorithm of bioinformatics. Identification of highly expressed mRNA in stage I/II patients with NSCLC was performed with the “Limma” package of R software. Survival analysis of patients with different mRNA expression levels was subsequently calculated by Cox regression analysis, and a multi-RNA signature was obtained by using the training set. Kaplan–Meier estimator, log-rank test and receiver operating characteristic (ROC) curves were used to analyse the predictive ability of the multi-RNA signature. RT-PCR used to verify the expression of the multi-RNA signature, and Westernblot used to verify the expression of proteins related to the multi-RNA signature. We identified fifteen survival-related mRNAs in the training set and classified the patients as high risk or low risk. NSCLC patients with low risk scores had longer disease-free survival than patients with high risk scores. The fifteen-mRNA signature was an independent prognostic factor, as shown by the ROC curve. ROC curve also showed that the combined model of the fifteen-mRNA signature and tumour stage had higher precision than stage alone. The expression of fifteen mRNAs and related proteins were higher in stage II NSCLC than in stage I NSCLC. Multi-gene expression profiles provide a moderate prognostic tool for NSCLC patients with stage I/II disease.
format	article
author	Nan Ma Lu Si Meiling Yang Meihua Li Zhiyi He
author_facet	Nan Ma Lu Si Meiling Yang Meihua Li Zhiyi He
author_sort	Nan Ma
title	A highly expressed mRNA signature for predicting survival in patients with stage I/II non-small-cell lung cancer after operation
title_short	A highly expressed mRNA signature for predicting survival in patients with stage I/II non-small-cell lung cancer after operation
title_full	A highly expressed mRNA signature for predicting survival in patients with stage I/II non-small-cell lung cancer after operation
title_fullStr	A highly expressed mRNA signature for predicting survival in patients with stage I/II non-small-cell lung cancer after operation
title_full_unstemmed	A highly expressed mRNA signature for predicting survival in patients with stage I/II non-small-cell lung cancer after operation
title_sort	highly expressed mrna signature for predicting survival in patients with stage i/ii non-small-cell lung cancer after operation
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/f95fe2809a7c431fa7116023bf8a6285
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A highly expressed mRNA signature for predicting survival in patients with stage I/II non-small-cell lung cancer after operation

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