Zhenyu Zhao, Cheng Zhang, Mi Li*, Xinguang Yu, Hailong Liu, Jian Wang, Qi Chen, Shaopin Shen and Jingjing Jiang Pages 1 - 12 ( 12 )
Background: Competing endogenous RNA (ceRNA) networks play a pivotal role in tumor diagnosis and progression. Numerous studies have explored the functional landscape and prognostic significance of ceRNA interaction within differentiated tumor cells.
Objective: We propose a new perspective by exploring ceRNA networks in the process of glioblastoma stem cell (GSC) differentiation.
Method: In this study, expression profiles of lncRNAs and mRNAs were compared between GSCs and differentiated glioblastoma cells. Using a comprehensive computational method, miRNAmediated and GSC differentiation-associated ceRNA crosstalk between lncRNAs and mRNAs was identified. A ceRNA network was then established to select potential candidates that regulate GSC differentiation.
Results: Based on the specific ceRNA network related to GSC differentiation, we identified lnc MYOSLID: 11 as a ceRNA that regulated the expression of the downstream gene PXN by competitively binding with hsa-miR-149-3p. After Kaplan-Meier (KM) survival analysis, the expression of PXN gene (PPXN = 0.0015) and lnc MYOSLID: 11 (PMYOSLID: 11=0.041) showed significant correlation with glioblastoma in 160 patients from TCGA.
Conclusion: This result sheds light on a potential way of studying the ceRNA network, which can provide clues for developing new diagnostic methods and finding therapeutic targets for clinical treatment of glioblastoma.
glioblastoma stem cell (GSC), glioblastoma, ceRNA network, Bioinformatics
Department of Neurosurgery, Chinese PLA General Hospital, Beijing, Department of Medical Genetics and Molecular Diagnostic Laboratory, Shanghai Children's Medical Center, Shanghai Jiao tong University School of Medicine, Shanghai, Department of Mathematics & Statistics, Boston University, Boston, MA, Department of Neurosurgery, Chinese PLA General Hospital, Beijing, Department of Neurosurgery, Chinese PLA General Hospital, Beijing, Department of Neurosurgery, Chinese PLA General Hospital, Beijing, National Engineering Laboratory for Medical Big Data Application Technology, Chinese PLA General Hospital, Beijing, Department of Neurosurgery, Chinese PLA General Hospital, Beijing, Clinical Data and Specimen Repositories, Chinese PLA General Hospital, Beijing