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...
Main Authors: | , , , , , , , , , , , , , , , , , , , , , |
---|---|
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 |
id |
doaj-95567e414ef6441d91d3d0df21487eec |
---|---|
record_format |
Article |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
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 |
work_keys_str_mv |
AT aishaaldherasi asevengeneprognosticsignaturepredictsoverallsurvivalofpatientswithlungadenocarcinomaluad AT qitianhuang asevengeneprognosticsignaturepredictsoverallsurvivalofpatientswithlungadenocarcinomaluad AT yuweiliao asevengeneprognosticsignaturepredictsoverallsurvivalofpatientswithlungadenocarcinomaluad AT sultanalmosaib asevengeneprognosticsignaturepredictsoverallsurvivalofpatientswithlungadenocarcinomaluad AT rulinhua asevengeneprognosticsignaturepredictsoverallsurvivalofpatientswithlungadenocarcinomaluad AT yichenwang asevengeneprognosticsignaturepredictsoverallsurvivalofpatientswithlungadenocarcinomaluad AT yingyu asevengeneprognosticsignaturepredictsoverallsurvivalofpatientswithlungadenocarcinomaluad AT yuzhang asevengeneprognosticsignaturepredictsoverallsurvivalofpatientswithlungadenocarcinomaluad AT xuehongzhang asevengeneprognosticsignaturepredictsoverallsurvivalofpatientswithlungadenocarcinomaluad AT chaohuang asevengeneprognosticsignaturepredictsoverallsurvivalofpatientswithlungadenocarcinomaluad AT haithmmousa asevengeneprognosticsignaturepredictsoverallsurvivalofpatientswithlungadenocarcinomaluad AT dongcenge asevengeneprognosticsignaturepredictsoverallsurvivalofpatientswithlungadenocarcinomaluad AT sufiyansufiyan asevengeneprognosticsignaturepredictsoverallsurvivalofpatientswithlungadenocarcinomaluad AT wantingbai asevengeneprognosticsignaturepredictsoverallsurvivalofpatientswithlungadenocarcinomaluad AT ruimeiliu asevengeneprognosticsignaturepredictsoverallsurvivalofpatientswithlungadenocarcinomaluad AT yanyanshao asevengeneprognosticsignaturepredictsoverallsurvivalofpatientswithlungadenocarcinomaluad AT yulongli asevengeneprognosticsignaturepredictsoverallsurvivalofpatientswithlungadenocarcinomaluad AT jingkaizhang asevengeneprognosticsignaturepredictsoverallsurvivalofpatientswithlungadenocarcinomaluad AT lemingshi asevengeneprognosticsignaturepredictsoverallsurvivalofpatientswithlungadenocarcinomaluad AT dekanglv asevengeneprognosticsignaturepredictsoverallsurvivalofpatientswithlungadenocarcinomaluad AT zhiguangli asevengeneprognosticsignaturepredictsoverallsurvivalofpatientswithlungadenocarcinomaluad AT quentinliu asevengeneprognosticsignaturepredictsoverallsurvivalofpatientswithlungadenocarcinomaluad AT aishaaldherasi sevengeneprognosticsignaturepredictsoverallsurvivalofpatientswithlungadenocarcinomaluad AT qitianhuang sevengeneprognosticsignaturepredictsoverallsurvivalofpatientswithlungadenocarcinomaluad AT yuweiliao sevengeneprognosticsignaturepredictsoverallsurvivalofpatientswithlungadenocarcinomaluad AT sultanalmosaib sevengeneprognosticsignaturepredictsoverallsurvivalofpatientswithlungadenocarcinomaluad AT rulinhua sevengeneprognosticsignaturepredictsoverallsurvivalofpatientswithlungadenocarcinomaluad AT yichenwang sevengeneprognosticsignaturepredictsoverallsurvivalofpatientswithlungadenocarcinomaluad AT yingyu sevengeneprognosticsignaturepredictsoverallsurvivalofpatientswithlungadenocarcinomaluad AT yuzhang sevengeneprognosticsignaturepredictsoverallsurvivalofpatientswithlungadenocarcinomaluad AT xuehongzhang sevengeneprognosticsignaturepredictsoverallsurvivalofpatientswithlungadenocarcinomaluad AT chaohuang sevengeneprognosticsignaturepredictsoverallsurvivalofpatientswithlungadenocarcinomaluad AT haithmmousa sevengeneprognosticsignaturepredictsoverallsurvivalofpatientswithlungadenocarcinomaluad AT dongcenge sevengeneprognosticsignaturepredictsoverallsurvivalofpatientswithlungadenocarcinomaluad AT sufiyansufiyan sevengeneprognosticsignaturepredictsoverallsurvivalofpatientswithlungadenocarcinomaluad AT wantingbai sevengeneprognosticsignaturepredictsoverallsurvivalofpatientswithlungadenocarcinomaluad AT ruimeiliu sevengeneprognosticsignaturepredictsoverallsurvivalofpatientswithlungadenocarcinomaluad AT yanyanshao sevengeneprognosticsignaturepredictsoverallsurvivalofpatientswithlungadenocarcinomaluad AT yulongli sevengeneprognosticsignaturepredictsoverallsurvivalofpatientswithlungadenocarcinomaluad AT jingkaizhang sevengeneprognosticsignaturepredictsoverallsurvivalofpatientswithlungadenocarcinomaluad AT lemingshi sevengeneprognosticsignaturepredictsoverallsurvivalofpatientswithlungadenocarcinomaluad AT dekanglv sevengeneprognosticsignaturepredictsoverallsurvivalofpatientswithlungadenocarcinomaluad AT zhiguangli sevengeneprognosticsignaturepredictsoverallsurvivalofpatientswithlungadenocarcinomaluad AT quentinliu sevengeneprognosticsignaturepredictsoverallsurvivalofpatientswithlungadenocarcinomaluad |
_version_ |
1721379832504254464 |
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 |