A seven-gene prognostic signature predicts overall survival of patients with lung adenocarcinoma (LUAD)

Abstract Background Lung adenocarcinoma (LUAD) is one of the most common types in the world with a high mortality rate. Despite advances in treatment strategies, the overall survival (OS) remains short. Our study aims to establish a reliable prognostic signature closely related to the survival of LU...

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Main Authors: Aisha Al-Dherasi, Qi-Tian Huang, Yuwei Liao, Sultan Al-Mosaib, Rulin Hua, Yichen Wang, Ying Yu, Yu Zhang, Xuehong Zhang, Chao Huang, Haithm Mousa, Dongcen Ge, Sufiyan Sufiyan, Wanting Bai, Ruimei Liu, Yanyan Shao, Yulong Li, Jingkai Zhang, Leming Shi, Dekang Lv, Zhiguang Li, Quentin Liu
Format: Article
Language:English
Published: BMC 2021-06-01
Series:Cancer Cell International
Subjects:
Online Access:https://doi.org/10.1186/s12935-021-01975-z
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language English
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author Aisha Al-Dherasi
Qi-Tian Huang
Yuwei Liao
Sultan Al-Mosaib
Rulin Hua
Yichen Wang
Ying Yu
Yu Zhang
Xuehong Zhang
Chao Huang
Haithm Mousa
Dongcen Ge
Sufiyan Sufiyan
Wanting Bai
Ruimei Liu
Yanyan Shao
Yulong Li
Jingkai Zhang
Leming Shi
Dekang Lv
Zhiguang Li
Quentin Liu
spellingShingle Aisha Al-Dherasi
Qi-Tian Huang
Yuwei Liao
Sultan Al-Mosaib
Rulin Hua
Yichen Wang
Ying Yu
Yu Zhang
Xuehong Zhang
Chao Huang
Haithm Mousa
Dongcen Ge
Sufiyan Sufiyan
Wanting Bai
Ruimei Liu
Yanyan Shao
Yulong Li
Jingkai Zhang
Leming Shi
Dekang Lv
Zhiguang Li
Quentin Liu
A seven-gene prognostic signature predicts overall survival of patients with lung adenocarcinoma (LUAD)
Cancer Cell International
Lung adenocarcinoma (LUAD)
Overall survival
Risk score
Prognostic signature
author_facet Aisha Al-Dherasi
Qi-Tian Huang
Yuwei Liao
Sultan Al-Mosaib
Rulin Hua
Yichen Wang
Ying Yu
Yu Zhang
Xuehong Zhang
Chao Huang
Haithm Mousa
Dongcen Ge
Sufiyan Sufiyan
Wanting Bai
Ruimei Liu
Yanyan Shao
Yulong Li
Jingkai Zhang
Leming Shi
Dekang Lv
Zhiguang Li
Quentin Liu
author_sort Aisha Al-Dherasi
title A seven-gene prognostic signature predicts overall survival of patients with lung adenocarcinoma (LUAD)
title_short A seven-gene prognostic signature predicts overall survival of patients with lung adenocarcinoma (LUAD)
title_full A seven-gene prognostic signature predicts overall survival of patients with lung adenocarcinoma (LUAD)
title_fullStr A seven-gene prognostic signature predicts overall survival of patients with lung adenocarcinoma (LUAD)
title_full_unstemmed A seven-gene prognostic signature predicts overall survival of patients with lung adenocarcinoma (LUAD)
title_sort seven-gene prognostic signature predicts overall survival of patients with lung adenocarcinoma (luad)
publisher BMC
series Cancer Cell International
issn 1475-2867
publishDate 2021-06-01
description Abstract Background Lung adenocarcinoma (LUAD) is one of the most common types in the world with a high mortality rate. Despite advances in treatment strategies, the overall survival (OS) remains short. Our study aims to establish a reliable prognostic signature closely related to the survival of LUAD patients that can better predict prognosis and possibly help with individual monitoring of LUAD patients. Methods Raw RNA-sequencing data were obtained from Fudan University and used as a training group. Differentially expressed genes (DEGs) for the training group were screened. The univariate, least absolute shrinkage and selection operator (LASSO), and multivariate cox regression analysis were conducted to identify the candidate prognostic genes and construct the risk score model. Kaplan–Meier analysis, time-dependent receiver operating characteristic (ROC) curve were used to evaluate the prognostic power and performance of the signature. Moreover, The Cancer Genome Atlas (TCGA-LUAD) dataset was further used to validate the predictive ability of prognostic signature. Results A prognostic signature consisting of seven prognostic-related genes was constructed using the training group. The 7-gene prognostic signature significantly grouped patients in high and low-risk groups in terms of overall survival in the training cohort [hazard ratio, HR = 8.94, 95% confidence interval (95% CI)] [2.041–39.2]; P = 0.0004), and in the validation cohort (HR = 2.41, 95% CI [1.779–3.276]; P < 0.0001). Cox regression analysis (univariate and multivariate) demonstrated that the seven-gene signature is an independent prognostic biomarker for predicting the survival of LUAD patients. ROC curves revealed that the 7-gene prognostic signature achieved a good performance in training and validation groups (AUC = 0.91, AUC = 0.7 respectively) in predicting OS for LUAD patients. Furthermore, the stratified analysis of the signature showed another classification to predict the prognosis. Conclusion Our study suggested a new and reliable prognostic signature that has a significant implication in predicting overall survival for LUAD patients and may help with early diagnosis and making effective clinical decisions regarding potential individual treatment.
topic Lung adenocarcinoma (LUAD)
Overall survival
Risk score
Prognostic signature
url https://doi.org/10.1186/s12935-021-01975-z
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spelling doaj-95567e414ef6441d91d3d0df21487eec2021-06-13T11:26:55ZengBMCCancer Cell International1475-28672021-06-0121111610.1186/s12935-021-01975-zA seven-gene prognostic signature predicts overall survival of patients with lung adenocarcinoma (LUAD)Aisha Al-Dherasi0Qi-Tian Huang1Yuwei Liao2Sultan Al-Mosaib3Rulin Hua4Yichen Wang5Ying Yu6Yu Zhang7Xuehong Zhang8Chao Huang9Haithm Mousa10Dongcen Ge11Sufiyan Sufiyan12Wanting Bai13Ruimei Liu14Yanyan Shao15Yulong Li16Jingkai Zhang17Leming Shi18Dekang Lv19Zhiguang Li20Quentin Liu21Center of Genome and Personalized Medicine, Institute of Cancer Stem Cell, Dalian Medical UniversityCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell, Dalian Medical UniversityYangjiang Key Laboratory of Respiratory Diseases, Yangjiang People’s HospitalDepartment of Computer Science and Technology, Sahyadri Science College, Kuvempu UniversityCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell, Dalian Medical UniversityCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell, Dalian Medical UniversityState Key Laboratory of Genetic Engineering, School of Life Sciences and Human Phenome Institute, Fudan UniversityCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell, Dalian Medical UniversityCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell, Dalian Medical UniversityCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell, Dalian Medical UniversityDepartment of Clinical Biochemistry, College of Laboratory Diagnostic Medicine, Dalian Medical UniversityCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell, Dalian Medical UniversityCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell, Dalian Medical UniversityCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell, Dalian Medical UniversityCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell, Dalian Medical UniversityCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell, Dalian Medical UniversityCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell, Dalian Medical UniversityCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell, Dalian Medical UniversityState Key Laboratory of Genetic Engineering, School of Life Sciences and Human Phenome Institute, Fudan UniversityCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell, Dalian Medical UniversityCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell, Dalian Medical UniversityCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell, Dalian Medical UniversityAbstract Background Lung adenocarcinoma (LUAD) is one of the most common types in the world with a high mortality rate. Despite advances in treatment strategies, the overall survival (OS) remains short. Our study aims to establish a reliable prognostic signature closely related to the survival of LUAD patients that can better predict prognosis and possibly help with individual monitoring of LUAD patients. Methods Raw RNA-sequencing data were obtained from Fudan University and used as a training group. Differentially expressed genes (DEGs) for the training group were screened. The univariate, least absolute shrinkage and selection operator (LASSO), and multivariate cox regression analysis were conducted to identify the candidate prognostic genes and construct the risk score model. Kaplan–Meier analysis, time-dependent receiver operating characteristic (ROC) curve were used to evaluate the prognostic power and performance of the signature. Moreover, The Cancer Genome Atlas (TCGA-LUAD) dataset was further used to validate the predictive ability of prognostic signature. Results A prognostic signature consisting of seven prognostic-related genes was constructed using the training group. The 7-gene prognostic signature significantly grouped patients in high and low-risk groups in terms of overall survival in the training cohort [hazard ratio, HR = 8.94, 95% confidence interval (95% CI)] [2.041–39.2]; P = 0.0004), and in the validation cohort (HR = 2.41, 95% CI [1.779–3.276]; P < 0.0001). Cox regression analysis (univariate and multivariate) demonstrated that the seven-gene signature is an independent prognostic biomarker for predicting the survival of LUAD patients. ROC curves revealed that the 7-gene prognostic signature achieved a good performance in training and validation groups (AUC = 0.91, AUC = 0.7 respectively) in predicting OS for LUAD patients. Furthermore, the stratified analysis of the signature showed another classification to predict the prognosis. Conclusion Our study suggested a new and reliable prognostic signature that has a significant implication in predicting overall survival for LUAD patients and may help with early diagnosis and making effective clinical decisions regarding potential individual treatment.https://doi.org/10.1186/s12935-021-01975-zLung adenocarcinoma (LUAD)Overall survivalRisk scorePrognostic signature