An integrated model of CDCA5 and FOXM1 expression combined with a residual disease that predicts prognosis in ovarian cancer patients.

Ovarian cancer (OC) is the most prevalent type of gynecologic cancer, leading to global death. Unfortunately, less than half of patients diagnosed with this cancer survive for up to five years. The factor forkhead box M1 (FOXM1) is a crucial oncoprotein in ovarian cancer and is currently recognized as a potential therapeutic target. The role of the Cell division cycle-associated 5 (CDCA5) is critical for advancing different types of cancers. However, the significance of CDCA5 in OC from a clinical perspective is not well comprehended. This study aimed to build a risk prognosis model and assess the data supporting the prognostic usefulness of CDCA5 and FOXM1 expression in patients with OC. In OC, we found that CDCA5 and FOXM1 were expressed. To establish the existence of variables that were independently related to PFS and OS, Cox regression, data from clinics, and Kaplan-Meier analysis were used. A risk score model and nomogram were created using the independent prognostic parameters. The accuracy of the model's predictions was then evaluated using decision curve analysis (DCA), calibration curve, and receiver operating characteristic(ROC) analysis. Finally, the patients were separated into groups based on their cut-off value, and then the differences in survival were investigated. Significant correlations were found between OC and CDCA5, and FOXM1 expression levels (P <0.0001). Serous ovarian tumors (P=0.025) and even specific subgroups of high-grade serous ovarian tumors were shown to have elevated CDCA5 expression levels. In our database, FOXM1 expression levels were discovered to be related to intestinal metastases (P=0.014). In OC, the expression of FOXM1 was positively correlated with the overexpression of CDCA5 (rs=0.46, P<0.0001). The results of the multivariate analysis indicated that residual disease (RD) (P=0.005), CDCA5 expression level (P=0.028), and FOXM1 expression level (P<0.0001) were identified as independent prognostic factors for PFS. Additionally, RD (P=0.023) and FOXM1 expression level (P<0.0001) were identified as independent prognostic factors for OS. While the prediction model's performance with RD was poor (AUC=0.645 for PFS, AUC=0.650 for OS), the model's performance with tissue biomarkers was enhanced (AUC=0.797 for PFS, AUC=0.741 for OS). The nomogram and risk score method showed a benefit for prognosis prediction. In summary, poor outcomes are predicted by CDCA5, which is overexpressed in OC patients and has a positive correlation with the level of FOXM1 expression. An aid to prognosis prediction in patients with OC and a resource for therapy planning is a risk prognosis model based on CDCA5 and FOXM1 expression with RD.