SUMOylation Regulator-Related Molecules Can Be Used as Prognostic Biomarkers for Glioblastoma - Li, Xiaozhi; Meng, Yutong (Frontiers in Cell and Developmental Biology, 2021)
SUMOylation is one of post-translational modifications. The relationship between the expression of SUMOylation regulators and the prognosis of glioblastoma is not quite clear. The single nucleotide variant data, the transcriptome data and survival information were acquired from TCGA, GEO and cBioportal database. Wilcoxon test was used to analyze differentially expressed genes between glioblastoma and normal brain tissues. Gene set enrichment analysis was conducted to find the possible functions. One risk scoring model was built by LASSO Cox regression. Kaplain-Meier survival curves and ROC curves were applied evaluate the effectiveness of the model in predicting the prognosis of glioblastoma. SNV mutations were found in SENP7, SENP3, SENP5, PIAS3, RANBP2, USPL1, SENP1, PIAS2, SENP2, PIAS1. Moreover, UBE2I, UBA2, PIAS3 and SENP1 were highly expressed in glioblastoma, while PIAS1, RANBP2, SENP5, and SENP2 were down-regulated in glioblastoma. GSEA showed that the SUMOylation regulators of glioblastoma might involve in nuclear division, DNA replication, ATPase activity, cell cycle and other functions. A prognostic model of glioblastoma was constructed based on SUMOylation regulator-related molecules (ATF7IP, CCNB1IP1 and LBH). Kaplain-Meier survival curves and ROC curves showed that the model had a strong ability to predict the overall survival of glioblastoma. This study analyzed the expression of 15 SUMOylation regulators in glioblastoma. The risk assessment model was constructed based on the SUMOylation regulator-related genes, which had a strong predictive ability for the overall survival of patients with glioblastoma. It might provide targets for the study of the relationship between SUMOylation and glioblastoma.