Assessment of gynecological and lifestyle-related risk factors of ovarian cancer

The Associations and Causal Relationships of Ovarian Cancer - Construction of a Prediction Model

Purpose

To explore the risk and protective factors for developing ovarian cancer and construct a risk prediction model.

Methods

Information related to patients diagnosed with ovarian cancer on the electronic medical record data platform of three tertiary hospitals in Guangdong Province from May 2018 to September 2023 was collected as the case group. Patients with non-ovarian cancer who attended the clinic during the same period were included in the control group. Logistic regression analysis was used to screen the independent variables and explore the factors associated with the development of ovarian cancer. An ovarian cancer risk prediction model was constructed using a decision tree C4.5 algorithm. The ROC and calibration curves were plotted, and the model was validated.

Results

Logistic regression analysis identified independent risk and protective factors for ovarian cancer. The sample size was divided into training and test sets in a ratio of 7:3 for model construction and validation. The AUC of the training and test sets of the decision tree model were 0.961 (95% CI:0.944-0.978) and 0.902 (95% CI:0.840-0.964), respectively, and the optimal cut-off values and their coordinates were 0.532 (0.091, 0.957), and 0.474 (0.159, 0.842) respectively. The accuracies of the training and test sets were 93.3% and 84.2%, respectively, and their sensitivities were 95.7% and 84.2%, respectively.

Conclusion

The constructed ovarian cancer risk prediction model has good predictive ability, which is conducive to improving the efficiency of early warning of ovarian cancer in high-risk groups.

Moderate-Risk Genes for Hereditary Ovarian Cancers Involved in the Homologous Recombination Repair Pathway

Approximately 20% of cases of epithelial ovarian cancer (EOC) are hereditary, sharing many causative genes with breast cancer. The lower frequency of EOC compared to breast cancer makes it challenging to estimate absolute or relative risk and verify the efficacy of risk-reducing surgery in individuals harboring germline pathogenic variants (GPV) in EOC predisposition genes, particularly those with relatively low penetrance. Here, we review the molecular features and hereditary tumor risk associated with several moderate-penetrance genes in EOC that are involved in the homologous recombination repair pathway, i.e., ATM, BRIP1, NBN, PALB2, and RAD51C/D. Understanding the molecular mechanisms underlying the expression and function of these genes may elucidate trends in the development and progression of hereditary tumors, including EOC. A fundamental understanding of the genes driving EOC can help us accurately estimate the genetic risk of developing EOC and select appropriate prevention and treatment strategies for hereditary EOC. Therefore, we summarize the functions of the candidate predisposition genes for EOC and discuss the clinical management of individuals carrying GPV in these genes.

Clinical and molecular evaluation of patients with ovarian cancer in the context of drug resistance to chemotherapy

The present study aimed to evaluate changes in the expression patterns at the gene and protein levels associated with drug resistance. The study group included 48 women who had a histopathologically confirmed diagnosis of stage I-IV ovarian cancer, they were divided into two subgroups (groups A and B). In group A, there were 36 patients in whom surgical treatment was supplemented with first-line chemotherapy according to current standards. Within this patient group, 5 had stage I (14%), 5 had stage II (14%), 25 had stage III (69%), and 1 had stage IV ovarian cancer (3%). Drug resistance was found after the third cycle of chemotherapy in 17 patients (71%) and after the sixth cycle in 7 patients (29%). Group B included 12 women with type I ovarian cancer, including 11 with stage I and 1 patient with stage IV ovarian cancer. The oncological treatment required only surgery. The control group (C) included 50 women in whom the uterus and adnexa were surgically removed for non-oncological reasons. Significantly higher levels of carcinoma antigen 125 CA-125 and human epididymis protein 4 HE4 were observed in group A and in menopausal women. Moreover, drug resistance was associated with significantly higher levels of CA-125 (p < 0.05). The genes UBA2, GLO1, STATH, and TUFT1 were differentiated in test samples from control samples. Moreover, drug resistance was associated with significantly higher expression of GLO1. The results of these assessments indicated the strong link between UBA2 and hsa-miR-133a-3p and hsa-miR-133b; GLO1 and hsa-miR-561-5p; STATH and hsa-miR-137-3p and hsa-miR-580-3p; and TUFT1 and hsa-miR-1233-3p and hsa-miR-2052. Correlation analysis showed a significant correlation between CA-125 and HE4 levels. Moreover, a significant correlation between TUFT1 mRNA and UBA2, GLO1, STATH (negative correlation), and TUFT1 in relation to CA-125 and HE4 (p < 0.05) was noted in all patients. In view of the lack of screening tests for ovarian cancer, the occurrence of the described correlation may be inscribed as an attempt to establish an assay that meets the criteria of a screening test and thus increase the early diagnosis of ovarian cancer.