BACKGROUND: Ovarian cancer (OC) is the most prevalent gynecologic malignancy, with high mortality rates. However, its pathogenesis remains unclear. The current study aimed to explore potential biomarkers and suppressor genes for diagnosing and treating OC. METHODS: Biochemical and bioinformatics approaches were used to detect differentially expressed genes (DEGs) in ovarian tissues integration analysis. Kaplan-Meier plot analysis was performed to assess progression-free survival and overall survival according to DEGs. Then, we constructed a protein-protein interaction (PPI) network based on data from the STRING database to identify the related target genes of DEGs. Finally, DEGs regulating the proliferation, migration, and invasion of SKOV3 cell lines were validated via in vitro experiments. RESULTS: Four DEGs (, and ) with enriched expression in ovarian tissues were explicitly expressed in the ovary based on an analysis of all human proteins. MUM1L1 had high specificity, and its expression was higher in normal ovarian tissues than in OC tissues. Kaplan-Meier plot analysis showed that a high expression was associated with longer progression-free survival and overall survival in OC. Based on the PPI analysis results, , and were associated with . studies revealed that MUM1L1 overexpression decreased the proliferation, migration, and invasion ability of SKOV3 cell lines. Meanwhile, MUM1L1 knockdown had contrasting results. CONCLUSION: is a tumor suppressor gene and is a potential biomarker for diagnosing and treating OC.