• Yuan Zheng, Wenliang Lu, Bo Chen, and Kankan Zhao.
• Department of Thyroid and Breast Surgery, Maternal and Child Health Hospital of Hubei Province, Tongji Medical College, Huazhong University of Science and Technology, Wuhan City, P.R. China.
• Medicine (Baltimore). 2022 Sep 16; 101 (37): e30598.

AbstractUbiquitination related genes (URGs) are important biomarkers and therapeutic targets in cancer. However, URG prognostic prediction models have not been established in breast cancer (BC) before. Our study aimed to identify URGs to serve as potential prognostic indicators in patients with BC.The URGs were downloaded from the ubiquitin and ubiquitin-like conjugation database. GSE42568 and The Cancer Genome Atlas were exploited to screen differentially expressed URGs in BC. The univariate Cox proportional hazards regression analysis, least absolute shrinkage and selection operator analysis, and multivariate Cox proportional hazards regression analysis were employed to construct multi-URG signature in the training set (GSE42568). Kaplan-Meier curve and log-rank method analysis, and ROC curve were applied to validate the predictive ability of the multi-URG signature in BC. Next, we validated the signature in test set (GSE20685). Finally, we performed GSEA analysis to explore the mechanism.We developed a 4-URG (CDC20, PCGF2, UBE2S, and SOCS2) signature with good performance for patients with BC. According to this signature, BC patients can be classified into a high-risk and a low-risk group with significantly different overall survival. The predictive ability of this signature was favorable in the test set. Univariate and multivariate Cox regression analysis showed that the 4-URG signature was independent risk factor for BC patients. GSEA analysis showed that the 4-URG signature may related to the function of DNA replication, DNA repair, and cell cycle.Our study developed a novel 4-URG signature as a potential indicator for BC.Copyright © 2022 the Author(s). Published by Wolters Kluwer Health, Inc.

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