Identification of a Glycolysis-Related LncRNA Signature to Predict Survival in Diffuse Glioma Patients

Frontiers in Oncology

Shunchang Ma¹  Wang Jia²  Peiliang Li³  Dainan Zhang³  Beibei Mao³  Wenjianlong Zhou³  Deling Li³  Xi Wang³  Xiudong Guan³  Peng Kang³  Yangyang Wang³  Linhao Yuan³  Chuanbao Zhang³  Jiayi Peng³ 

[1] Beijing Neurosurgery Research Institute, Capital Medical University, Beijing, China;China National Clinical Research Center for Neurological Diseases (NCRC-ND), Beijing, China;Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China;

关键词: glioma;    glycolysis;    long non-coding RNAs (LncRNA);    prognosis;    risk model;   

DOI  :  10.3389/fonc.2020.597877

来源: DOAJ

【 摘 要 】

Glycolysis refers to one of the critical phenotypes of tumor cells, regulating tumor cell phenotypes and generating sufficient energy for glioma cells. A range of noticeable genes [such as isocitrate dehydrogenase (IDH), phosphatase, and tensin homolog (PTEN), or Ras] overall impact cell proliferation, invasion, cell cycle, and metastasis through glycolysis. Moreover, long non-coding RNAs (LncRNAs) are increasingly critical to disease progression. Accordingly, this study aimed to identify whether glycolysis-related LncRNAs have potential prognostic value for glioma patients. First, co-expression network between glycolysis-related protein-coding RNAs and LncRNAs was established according to Pearson correlation (Filter: |r| > 0.5 & P < 0.001). Furthermore, based on univariate Cox regression, the Least Absolute Shrinkage and Selection Operator (LASSO) analysis and multivariate Cox regression, a predictive model were built; vital glycolysis-related LncRNAs were identified; the risk score of every single patient was calculated. Moreover, receiver operating characteristic (ROC) curve analysis, gene set enrichment analysis (GSEA), GO and KEGG enrichment analysis were performed to assess the effect of risk score among glioma patients. 685 cases (including RNA sequences and clinical information) from two different cohorts of the Chinese Glioma Genome Atlas (CGGA) database were acquired. Based on the mentioned methods, the risk score calculation formula was yielded as follows: Risk score = (0.19 × EXPFOXD2-AS1) + (−0.27 × EXPAC062021.1) + (−0.16 × EXPAF131216.5) + (−0.05 × EXPLINC00844) + (0.11 × EXPCRNDE) + (0.35 × EXPLINC00665). The risk score was independently related to prognosis, and every single mentioned LncRNAs was significantly related to the overall survival of patients. Moreover, functional enrichment analysis indicated that the biologic process of the high-risk score was mainly involved in the cell cycle and DNA replication signaling pathway. This study confirmed that glycolysis-related LncRNAs significantly impact poor prognosis and short overall survival and may act as therapeutic targets in the future.

【 授权许可】

Unknown