دلائل التمييز للحامض الرايبوزي المايكروي 590 وبروتين FOXA2 في تحديد مرحلة سرطان المبيض

MicroRNA-590 and Forkhead Box A2 Signatures Differentiate Staging of Ovarian Cancer

Abstract

Ovarian cancer remains a leading cause of gynecological cancer-related mortality, with accurate histopathological staging by the International Federation of Gynecology and Obstetrics (FIGO) system being crucial for prognosis and treatment stratification. However, current grading approaches may benefit from complementary molecular biomarkers for improved precision. MicroRNAs (miRNAs) and their gene targets play pivotal roles in cancer progression, including ovarian malignancies.
This study aimed to investigate the potential of MicroRNA-590 (miR-590) and Forkhead box protein A2 (FOXA2) expression signatures to differentiate between various FIGO staging of ovarian cancer.
The present work included case-control study for a group of (105) samples: (70) patient samples, (35) healthy control samples. Patients with ovarian cancer were collected from oncology unite in Imam Al-Hussein Center for Cancer and Hematology and Imam Al-Hassan Al-Mujtaba Hospital in Karbala. The sociodemographic aspects of the patients were collected through the self-reported technique (student questionnaire). All patients were subjected to the full clinical history, clinical examination, and relevant laboratory investigations. Patients were classified according to FIGO stage, tumor grade, Enzyme-Linked Immunosorbent Assay system (ELISA) was performed using Sandwich-ELISA method to measure the concentrations of serum FOXA2.

microRNA590 signatures in all cancer samples and control were analyzed using TransScript Green One-step RT/Rl Enzyme Mix was used for total RNA mesearment according to the manufacturer’s instructions. Total RNA was purified using an RNAClean XP Kit and RNase-Free DNase Set. Statistical analysis was performed and the efficiency of the predicting value was assessed using the receiver operating characteristic (ROC) curve.
Analysis of key biomarkers revealed statistically significant differences between ovarian cancer patients and controls. FOXA2 was significantly lower in patients (mean 3.09) compared to controls (mean 3.72, p=0.025). MicroRNA-590 levels (Ct value) highly significantly increased in patients (mean 19.21) compared to controls (mean 5.25, p<0.001), indicating downregulation in cancer. Correspondingly. The Fold change of MicroRNA-590 was significantly lower in patients (mean 2606.50) versus controls (mean 4788.31, p=0.009).
Further analysis by disease stage showed a dramatic reduction in MicroRNA-590 Fold change in early-stage (Stage 1 and 2: 104) compared to late-stage (Stage 3 and 4: 3148) and healthy controls (10085), suggesting a more pronounced reduction in early stages. FOXA2 levels were generally lower in patients across all stages (Stage 1 and 2: 3.1, Stage 3 and 4: 2.9) compared to controls (5.2). When stratified by grade, FOXA2 levels were lowest in high Grade (2.7) compared to low Grade (3.3) and controls (5.2, p=0.003). Similarly, MicroRNA-590 Fold change was significantly lower in ovarian cancer grades compared to controls, with low Grade (1340) being lower than high Grade (3451) and healthy controls (10085, p=0.05).
Binary logistic regression showed that FOXA2 (OR=1.113, p<0.001), MicroRNA-590 (OR=1.243, p<0.001), and Fold change (OR=1.002, p<0.001) were all significantly associated with the presence of ovarian cancer.
ROC curve analysis for diagnostic utility revealed that Ct. MicroRNA-590 was the most promising biomarker, with a very good AUC of 84.5% (94.1% sensitivity, 72.2% specificity at cut-off 8.97, Youden index 0.663). Fold change showed fair to good diagnostic ability with an AUC of 72.2% (90% sensitivity, 66.7% specificity at cut-off 7.929). In contrast, FOXA2 had poor discriminatory power with an AUC of 51.9%.
The unique expression patterns of miR-590 and FOXA2 serve as promising molecular signatures that can effectively identify FIGO staging of ovarian cancer. These findings suggest that miR-590 and FOXA2 hold potential as a good prognostic biomarker, offering valuable insights.