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Updated: Jan 17, 2026

Integration of Bioinformatics Approaches and Experimental Validations to Understand the Role of Notch Signaling in Ovarian Cancer
Published on: January 12, 2020
Prognostic model of ubiquitination-related genes in ovarian cancer based on transcriptomic analysis and experimental
Xiaojing Lin1,2,3,4, Shu Zhao1,3,5, Licheng Li6
1Department of Obstetrics and Gynecology, Institute of Precision Medicine of Guizhou Province, Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou, China.
Objective:
Ubiquitination plays a crucial role in the malignant progression of ovarian cancer. With the advent of proteolysis-targeting chimeras (PROTACs) targeting ubiquitin enzymes, precision therapies are now possible. Therefore, it is imperative to ascertain the prognostic significance of ubiquitination-related genes in ovarian cancer.
Methods:
A prognostic model based on ubiquitination-related genes was developed using data from TCGA and GTEx databases. Performance was assessed via Kaplan-Meier, ROC curves, and Cox regression; a nomogram was created. The model's stability was checked using training and test sets. FBXO45 was also experimentally validated in ovarian cancer.
Results:
The model, based on 17 genes related to ubiquitination, showed high performance (1-year AUC = 0.703, 3-year AUC = 0.704, 5-year AUC = 0.705). The high-risk group had significantly lower overall survival (P < 0.05). Immune analysis showed higher levels of CD8+ T (P < 0.05), M1 (P < 0.01) and follicular (P < 0.05) cells in the low-risk group. High-risk patients had more mutations in MUC17 and LRRK2, while low-risk patients had more RYR2 mutations. FBXO45 is a key E3 ubiquitin ligase in ovarian cancer, promoting growth, spread and migration via the Wnt/β-catenin pathway.
Conclusion:
Ubiquitination-related markers provide reliable prognostic insights and reflect the immune microenvironment in ovarian cancer, offering a basis for clinical targeting strategies.
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