Construction of glioma prognosis model with n7-methylguanosine related long non-coding RNA based on transcriptome
10.3760/cma.j.cn115455-20230106-00015
- VernacularTitle:基于转录组构建n7-甲基鸟苷相关长链非编码RNA的胶质瘤预后模型
- Author:
Xin FENG
1
;
Shen ZHANG
;
Yuhang ZHAO
;
Yue LIU
Author Information
1. 湖北医药学院附属襄阳市第一人民医院研究生培养基地，襄阳 441000
- Keywords:
Glioma;
Prognosis;
N7-methylguanosine;
Long non-coding RNA
- From:
Chinese Journal of Postgraduates of Medicine
2023;46(7):639-645
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the relationship between n7-methylguanosine (m7G) related long non-coding RNA (lncRNA) expression and glioma prognosis, and to construct a prognosis model with m7G-related lncRNA in patients with glioma.Methods:Data related to the test set and validation set were downloaded from the Cancer and Tumor Genome Atlas (TCGA) database and the China Glioma Genome Atlas (CGGA) database. LASSO regression and random forest algorithm were used to establish the glioma prognosis model with m7G related lncRNA. Individualized risk scores were calculated using the weighted expression levels of the 12 extracted lncRNA coefficients, and test set and validation set glioma patients were categorized into high and low risk groups based on median risk score. Kaplan-Meier survival curve was drawn, the comparison method used log rank test. The efficacy of risk score in predicting the 1-, 2- and 5-year survival rate in patients with glioma was evaluated using the receiver operating characteristics (ROC) curve.Results:A total of 12 lncRNA associated with m7G were obtained, with a risk score = 1.026 × AC002454.1 + 1.086 × AC131097.4 + 1.039 × AC147651.3 + 1.01 × AGAP2-AS1 + 1.036 × CRNDE + 0.733 × GDNF-AS1 + 1.321 × HOXD-AS2 + 0.934 × LINC00641 + 1.183 × PAXIP1-AS2 + 1.258 × PVT1 + 0.909 × SOX21-AS1 + 0.754 × TTC28-AS1, with a median risk score of - 0.45 scores. Kaplan-Meier survival curve analysis result showed that the median survival time in high risk group was significantly shorter than that in low risk group (1.98 years vs. 9.51 years, log-rank χ2 = 131.78, P<0.01). ROC curve analysis result showed that the area under the curve (AUC) of risk score in predicting the 1-, 2- and 5-year survival rate in patients with glioma was 0.891, 0.923 and 0.912. In the validation set of glioma patients, Kaplan-Meier survival curve analysis result showed that the median survival time in high risk group was significantly shorter than that in low risk group (1.29 years vs. 6.88 years, log-rank χ2 = 103.27, P<0.01); ROC curve analysis result showed that the AUC of risk score in predicting the 1-, 2- and 5-year survival rate in patients with glioma was 0.724, 0.795 and 0.762. In the test set and validation set, multivariate Cox regression analysis result showed that the risk score was the independent risk factors of prognosis in patients with glioma ( HR = 1.992 and 1.247, P<0.01 or <0.05). Conclusions:A risk score model with m7G related lncRNA based on transcriptome is a novel approach to predict the prognosis of glioma patients.
