1. Integrative analysis of a Novel six methylated pseudogene Prognostic signature in patients with glioma
- Author
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Zhigang Chen, Jialin Zhou, Bingran Wang, Jiahui Li, Han Xie, JiaJia Zhao, Jun Liu, Dasheng Tian, and Erbao Bian
- Abstract
Background: Gliomas are the most common malignant tumor of the central nervous system(CNS). Dysregulated pseudogene expression was significantly associated with the prognosis of glioma patients. However, the role of abnormal methylation of pseudogenes in glioma prognosis has not yet been studied. This study aimed to develop a novel six-methylated pseudogenes signature to predict the prognosis of glioma patients. Methods: Based on lasso regression analysis, a risk signature for six methylated pseudogenes was constructed. Next, a prognostic nomogram including grade, age, gender, and radiation was constructed. Besides, the immune cell infiltration analyses of patients based on the six-methylated pseudogenes were performed. Meanwhile, consensus cluster analysis of six methylated pseudogenes identified two glioma patient subgroups. Furthermore, GO, KEGG and GSEA were used to analyze related genes. Finally, the ability of glioma to proliferate, migrate and invade was used to verify subsequent functions. Results: In this study, six gene models consisting of methylated pseudogenes were identified and validated, and showed strong prognostic power in the training dataset, validation dataset, and entire dataset. The calibration diagram showed good predictive performance. In addition, the proportion of B cells and CD4+T cells was significantly higher in the high-risk group, while the proportion of mono cells was lower. By silencing the expression of SBF1P1 and SUMO1P1, the ability of glioma to proliferate, migrate, and invade can be inhibited. Conclusions: The six-methylated pseudogene signature may be a novel predictor for prognostic assessment of glioma patients, which could accurately predict patient prognosis.
- Published
- 2023