Objective: In this study, we used the Weighted gene co-expression network analysis (WGCNA) analysis to find the gene module that are specifically expressed in Medulloblastoma and screened the marker genes that may diagnose and treat Medulloblastoma. Methods: WGCNA was used to identify the gene modules that are specifically associated with suvival in Medulloblastoma. Cytoscape software was used to construct Co-expression Network. Survival analysis of hub genes using Kaplan Meier (KM) analysis method. Results: Based on the predicted co-expression network, we found that green module significantly associated with survival traits. Green module genes were analyzed and we identified the hub gene UBE2G1 by cytoscape software which have the most correlation with survival trait. Conclusions: Our results indicate that UBE2G1 may be served as a candidate diagnostic biomarker and a promising therapeutic target for Medulloblastoma.