Prognostic significance of a long non-coding RNA signature in patients with diffuse large B-cell lymphoma
10.16462/j.cnki.zhjbkz.2019.08.022
- Author:
Hui-fang ZHANG
1
;
Qian GAO
;
Tong WANG
Author Information
1. Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan 030001, China
- Publication Type:Research Article
- Keywords:
Diffuse large B-cell lymphoma;
Long non-coding RNA;
Prognosis
- From:
Chinese Journal of Disease Control & Prevention
2019;23(8):998-1002
- CountryChina
- Language:Chinese
-
Abstract:
Objective To identify the relationship between a set of long non-coding RNA (lncRNA) signature and the prognosis of diffuse large B-cell lymphoma (DLBCL) patients,so as to evaluate their prognostic significance.Methods LncRNA expression profiles and clinical data of DLBCL patients were extracted from the gene expression omnibus (GEO) database: GSE31312 (n=424, training set) and GSE10846 (n=295, validation set). In the training set,a set of 8-lncRNA signature associated with the overall survival (OS) of DLBCL patients was established through least absolute shrinkage and selection operator (LASSO) combined with stability selection method and multivariate Cox regression analysis.Based on this 8-lncRNA signature, the patients in each data set could be classified into high-risk group and low-risk group. The survival curves of patients in both groups were compared by log-rank test. Then three Cox proportional hazard models, namely, international prognostic index (IPI), lncRNA signature and IPI+lncRNA signature model were constructed. The incident/dynamic receiver operating characteristic (ROC) curves method was applied to evaluate and compare their predict accuracy.Results A total of 8 lncRNAs related to the prognosis of DLBCL were found.In the training and validation sets,the difference of survival curves between high-risk group and low-risk group was statistically significant respectively (training set: 2=73.1, P<0.001, validation set: 2=13.4, P<0.001), the difference of C-index between IPI+lncRNA signature model and either of the other two models were also statistically significant (training set: IPI+lncRNA vs. IPI: Z=76.536, P<0.001; IPI+lncRNA vs. lncRNA: Z=17.714, P<0.001;validation set: IPI+lncRNA vs. IPI: Z=42.427, P<0.001; IPI+lncRNA vs. lncRNA: Z=30.587, P<0.001).Conclusions The 8-lncRNA signature can be used as a composite prognostic biomarker of DLBCL. Besides, lncRNA combined with IPI has better prognostic predict ability than IPI alone.
