Objective: To identify candidate urinary protein biomarkers to distinguish medulloblastoma (MB) patients from healthy patients or benign brain disease control patients. Methods: The tandem mass tag (TMT)-labeled quantitative proteomics approach was used to identify differential proteins in the urinary proteome of 9 pre- and postsurgery MB patients and 9 healthy control patients, respectively. Ingenuity pathway analysis was used for functional annotation of differential proteins. The biomarker candidates were validated by the parallel reaction monitoring (PRM) method in 112 samples (29 pre- and postsurgery MB patients, 26 healthy control patients, and 28 benign brain disease control patients). Receiver operating characteristic (ROC) curves were developed to evaluate candidate biomarkers. Results: A total of 114 differential proteins were found. Bioinformatic analysis revealed that the urinary proteome could reflect changes in MB. Seventeen candidate biomarkers were validated by PRM. The combination of CADH1, FGFR4, FIBB, and A1BG could be used to discriminate MB patients from healthy control patients with an area under the curve (AUC) of 0.974, and the combination of CADH1 and FIBB showed good discriminative power for differentiating MB from benign brain disease with an AUC of 0.884. Conclusion: This report describes the first application of a TMT-PRM workflow to identify and validate MB-specific biomarkers in urine. These findings might contribute to the application of urinary proteomics for detecting and monitoring MB. Funding Statement: Dr. Tian was supported by Beijing Natural Science Foundation (7172041). Prof. Sun was supported by National Key Research and Development Program of China (No. 2016YFC1306300, 2018YFC0910202,), National Natural Science Foundation of China (No. 30970650, 31200614, 31400669, 81371515, 81170665, 81560121), Beijing Natural Science Foundation (No. 7173264, 7172076), Beijing cooperative construction project (No.110651103), Beijing Science Program for the Top Young (No.2015000021223TD04 ), Beijing Normal University (No.11100704), Peking Union Medical College Hospital (No.2016-2.27), CAMS Innovation Fund for Medical Sciences (2017-I2M-1-009) and Biologic Medicine Information Center of China, National Scientific Data Sharing Platform for Population and Health. Declaration of Interests: The authors declare no conflicts of interests. Ethics Approval Statement: This study was approved by the Institutional Review Board of the Institute of Basic Medical Sciences.