Open AccessA innovative prognostic symbol based on neutrophil extracellular traps (NETs)-related lncRNA signature in non-small-cell lung cancer
Author(s) -
Fang Chen,
Fen Liu,
Yong Wang,
Shangkun Yuan,
Renfang Chen,
Xiaotong Qiu,
Xiaoying Qian,
Xinwei Zhang,
Zhehao Xiao,
Qian Wang,
Biqi Fu,
Yong Li
Publication year - 2021
Publication title -
aging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 90
ISSN - 1945-4589
DOI - 10.18632/aging.203289
Subject(s) - neutrophil extracellular traps , signature (topology) , symbol (formal) , lung , cancer , medicine , lung infection , cell , oncology , computer science , biology , inflammation , mathematics , genetics , geometry , programming language
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.