Journal of Shandong University (Health Sciences) ›› 2020, Vol. 58 ›› Issue (6): 8-13.doi: 10.6040/j.issn.1671-7554.0.2019.1449

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Prediction of the association between genes and glioblastoma based on databases

TIAN Baorui1, ZHANG Yongchao2, HAN Xiaoyang1, TIAN Yingying1, WANG Chuanxi1   

  1. 1. Department of Oncology;
    2. Department of Neurosurgery, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan 250021, Shandong, China
  • Published:2022-09-27

Abstract: Objective To explore the key genes related to prognosis of glioblastoma(GBM)and to investigate their potential as regulatory genes of GBM. Methods Based on the cancer genome atlas(TCGA)database, GBM prognosis related genes and their expression-related genes were screened with GEPIA. The gene expression patterns in GBM patients and healthy controls were analyzed. The correlation between clinical parameters and target genes in GBM patients was analyzed with LinkedOmics. Results The expressions of SAMD13, FAM20C, FUCA1 and RARRES1 were related to both disease-free survival(DFS)and overall survival(OS)in GBM patients. The four genes expressed differently in GBM patients and healthy controls. Kyoto encyclopedia of genes and genomes( KEGG )and gene ontology(GO)analyses showed these genes were closely involved in the oncogenesis and progression of GBM. Conclusion SAMD13, FAM20C, FUCA1 and RARRES1 have the potential to serve as regulatory genes and diagnostic markers of GBM, and they are closely involved in GBM-related regulatory mechanism.

Key words: Glioblastoma, Regulatory genes, Diagnostic markers, Bioinformatics analysis

CLC Number: 

  • R739.4
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