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- Title
An Immune-Related lncRNA Expression Profile to Improve Prognosis Prediction for Lung Adenocarcinoma: From Bioinformatics to Clinical Word.
- Authors
Zhang, Boxiang; Wang, Rui; Li, Kai; Peng, Ziyang; Liu, Dapeng; Zhang, Yunfeng; Zhou, Liuzhi
- Abstract
Background: Lung cancer is still the top-ranked cancer-related deaths all over the world. Now immunotherapy has emerged as a promising option for treating lung cancer. Recent evidence indicated that lncRNAs were also key regulators in immune system. We aimed to develop a novel prognostic signature based on the comprehensive analysis of immune-related lncRNAs to predict survival outcome of LUAD patients. Methods: The gene expression profiles of 491 LUAD patients were downloaded from TCGA. 1047 immune-related lncRNAs were obtained through Pearson correlation analysis of immune genes and lncRNAs using statistical software R language. Univariate and multivariate Cox regression analysis were performed to determine the optimal immune-related lncRNAs prognostic signature (ITGCB-DT, ABALON, TMPO-AS1 and VIM-AS1). Finally, we validated the immune-related lncRNAs prognostic signature in The First Affiliated Hospital of Xi'an Jiaotong University cancer center cohort. Results: A four immune-related lncRNAs prognostic signature was constructed to predict the survival outcome of LUAD patients. Statistical significance were found that the LUAD patients in high-risk group suffered shorter overall survival than those in low-risk group (P <0.001). ROC curve analysis shown that the four immune-related lncRNAs prognostic signature had the best predictive effect compared with age, gender, AJCC-stage, T stage, N stage, M stage (AUC = 0.756). More importantly, clinical cohort studies proved that the signature could predict the overall survival of LUAD patients with an AUC = 0.714. Conclusions: In summary, we demonstrated that the novel immune-related lncRNAs signature had the ability to predict the prognosis of LUAD patients, which might serve as potential prognostic biomarkers and guide the individualized treatment strategies for LUAD patients.
- Subjects
GENE expression profiling; BIOINFORMATICS software; LINCRNA; REGRESSION analysis; PROGNOSIS; STATISTICAL correlation
- Publication
Frontiers in Oncology, 2021, Vol 11, pN.PAG
- ISSN
2234-943X
- Publication type
Article
- DOI
10.3389/fonc.2021.671341