Research Paper Volume 13, Issue 13 pp 17864—17879
A innovative prognostic symbol based on neutrophil extracellular traps (NETs)-related lncRNA signature in non-small-cell lung cancer
- 1 Department of Medical Oncology, The First Affiliated Hospital of Nanchang University, Nanchang 330000, China
- 2 Critical Care Medicine, The First Affiliated Hospital of Nanchang University, Nanchang 330000, China
- 3 Department of Rheumatology, The First Affiliated Hospital of Nanchang University, Nanchang 330000, China
Received: February 25, 2021 Accepted: May 18, 2021 Published: July 13, 2021
https://doi.org/10.18632/aging.203289How to Cite
Copyright: © 2021 Fang 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.
Abstract
Neutrophil extracellular traps (NETs) are closely related to cancer progression. NETs-related lncRNAs play crucial roles in non-small-cell lung cancer (NSCLC) but there have been no systematic studies regarding NETs-related long noncoding RNA (lncRNA) signatures to forecast the prognosis of NSCLC patients. It’s essential to build commensurate NETs-related lncRNA signatures. The expression profiles of prognostic mRNAs and lncRNAs and relevant clinical data of NSCLC patients were downloaded from The Cancer Genome Atlas (TCGA) database. The NETs-related genes came from the results of our transcriptome RNA microarray data. The co-expression network of lncRNAs and NETs-related genes was structured to confirm NETs-related lncRNAs. The 19 lncRNAs correlated with overall survival (OS) were selected by exploiting univariate Cox regression (P < 0.05). Lasso regression and multivariate Cox regression (P < 0.05) were utilized to develop a 12-NETs-related lncRNA signature. We established a risk score based on the signature, which suggested that patients in the high-risk group displayed significantly shorter OS than patients in the low-risk group (P < 0.0001, P = 0.0023 respectively in the two cohorts). The risk score worked as an independent predictive factor for OS in both univariate and multivariate Cox regression analyses (HR> 1, P< 0.001). Additionally, by RT-qPCR, we confirmed that NSCLC cell lines have higher levels of the three adverse prognostic NETs-related lncRNAs than normal lung cells. The expression of lncRNAs significantly increases after NETs stimulation. In short, the 12 NETs-related lncRNAs and their model could play effective roles as molecular markers in predicting survival for NSCLC patients.