Construction of a SUMOylation regulator-based prognostic model in low-grade glioma.
作者： Yutong Meng , Xiaozhi Li
DOI: 10.1111/JCMM.16553
关键词:
摘要: Low-grade glioma (LGG) is an intracranial malignant tumour that mainly originates from astrocytes and oligodendrocytes. SUMOylation one of the post-translational modifications but studies in LGG quite limited. Transcriptome data, single nucleotide variant (SNV) data clinical were derived public databases. The differences between expression regulators normal brain tissue analysed. Cox regression was used to construct a prognostic model training cohort. Kaplan-Meier survival curves ROC plotted validation cohort evaluate effectiveness model. GO KEGG analyses applied preliminarily analyse biological functions. Compared with tissue, SENP1 SENP7 up-regulated SENP5 down-regulated LGG. may be involved functions such as mRNA splicing, DNA replication, ATPase activity spliceosome. One established based on 4 regulator-related signatures (RFWD3, MPHOSPH9, WRN NUP155), which had good predictive ability for overall survival. This study expected provide targets diagnosis treatment low-grade glioma.
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