Research Paper Volume 11, Issue 2 pp 467—479
Combined eight-long noncoding RNA signature: a new risk score predicting prognosis in elderly non-small cell lung cancer patients
- 1 Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi 710061, China
- 2 Department of Respiratory Medicine, Liaocheng People’s Hospital, Taishan Medical College, Liaocheng 252000, Shandong Province, China
- 3 Department of General Surgery, Shaanxi Provincial People's Hospital, The Third Affiliated Hospital, Medical College, Xi'an Jiao Tong University, Xi'an 710068, China
- 4 Department of Thoracic Surgery, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi 710061, China
received: October 17, 2018 ; accepted: December 27, 2018 ; published: January 19, 2019 ;https://doi.org/10.18632/aging.101752
How to Cite
Copyright: Miao et al. This is an open‐access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
The elderly are the majority of patients with non-small cell lung cancer (NSCLC). Compared to the overall population's predictive guidance, an effective predictive guidance for elderly patients can better guide patients' postoperative treatment and improve overall survival (OS) and disease-free survival (DFS). Recently, the long non-coding RNAs (lncRNAs) have been found to play an important role in predicting tumor prognosis. To identify potential lncRNAs to predict survival in elderly patients with NSCLC, in the present study, we chose 456 elderly patients with NSCLC and analyzed differentially expressed lncRNAs from four Gene Expression Omnibus (GEO) datasets (GSE30219, GSE31546, GSE37745 and GSE50081). We then constructed an eight-lncRNA formula to predict elderly patients’ prognosis in NSCLC. Furthermore, we validated the prognostic values of the new risk model in two independent datasets, TCGA (n=670) and GSE31210 (n=130). Our data suggested a significant association between risk model and patients’ prognosis. Finally, stratification analysis further revealed the eight-lncRNA signature was an independent factor to predict OS and DFS in stage I elderly patients from both the discovery and validation groups. Functional prediction revealed that 8 lncRNAs have potential effects on tumor immune processes such as lymphocyte activation and TNF production in NSCLC. In summary, our data provides evidence that the eight-lncRNA signature could serve as an independent biomarker to predict prognosis in elderly patients with NSCLC especially in elderly stage I patients.