Association between RAD51, XRCC2 and XRCC3 gene polymorphisms and risk of ovarian cancer: a case control and an in silico study

A signature of circulating miRNAs predicts the prognosis and therapeutic outcome of taxane/platinum regimen in advanced ovarian carcinoma patients

PURPOSE

Ovarian carcinoma (OC) is ranked as the eighth most lethal gynecological cancer due to late diagnosis and high recurrence. Existing biomarkers are lacking to predict the recurrence and stratify patients who are likely to benefit from chemotherapy. MicroRNAs (miRNAs/miRs) are persistently present in humans and are capable of predicting treatment outcomes. Thus, the purpose of the study was to assess the potential of circulatory miRNAs to predict the efficacy of OC.

METHODS

Newly diagnosed n = 208 OC patients were administrated neoadjuvant/adjuvant chemotherapy (taxane + platinum) after surgery. Their demographic, gynecologic, clinical parameters, response, and survival were recorded. MiR-27a, miR-182, miR-199a, miR-214, and miR-591 were taken and the expression were analyzed using real-time PCR at different treatment intervals. Further, its prognostic value (Kaplan-Meier, and Cox regression analysis) and diagnostic importance (receiver operating characteristic curve) were validated.

RESULT

The mean age of patients with poorly differentiated (45.2%) serous OC was 48.69 ± 10.38. The majority experienced menarche at ≥ 12 (62.2%) with poor menstrual hygiene (81.8%) and were post-menopausal (69.4%), some were associated with high risk of survival (HR =  > 1). MiRNA signature showed three over-expression and two under-expression (miR-27a, miR-182, and miR-214; miR-199a and miR-591) in advanced OC compared to the control (P=  < 0.05). Also, a significant difference was detected at each time interval of treatment with the response (P =  ≤ 0.001) associated with resistance and overall survival (P =  ≤ 0.001) with risk (HR =  > 1). ROC analysis showed enhanced the diagnostics accuracy (< 0.001).

CONCLUSION

Our findings indicate that circulating miRNAs might be a potential minimally invasive diagnostic marker for treatment outcome and recurrence in ovarian carcinoma.

Association of RAD51, XRCC1, XRCC2, and XRCC3 Polymorphisms with Risk of Breast Cancer

Background: DNA repair genes are among the low-penetrance genes implicated in breast cancer. However variants of DNA repair genes may alter their protein function thus leading to carcinogenesis. Breast cancer is the most common cancer among women in India. The aim of the present study was to identify association, if any, of single nucleotide polymorphisms (SNP's) in four genes involved in DNA repair pathways including, RAD51 rs1801320, XRCC1 rs25487, XRCC2 rs3218536, and XRCC3 rs861539 with the risk of breast cancer. Materials and Methods: In this case-control study 611 female subjects (311 breast cancer patients and 300 healthy controls) were screened for four SNPs using polymerase chain reaction-restriction fragment length polymorphism analyses. Multifactor dimensionality reduction (MDR) analysis was performed to estimate the gene-gene interaction. Protein-protein interaction network analysis were studied using the STRING database. Results: The GC genotype (p = 0.018) and the combined GC+CC (p = 0.03) genotypes of RAD51 rs1801320 were significantly associated with reduced risk of breast cancer. The CT genotype (p = 0.0001), the combined CT+TT genotypes (p = 0.0002), and the T allele (p = 0.0019) of XRCC3 rs861539 polymorphism were associated with reduced risk of the breast cancer. No association of XRCC1 rs25487 and XRCC2 rs3218536 polymorphisms with breast cancer was observed. MDR analysis indicated a positive interaction between XRCC3 and XRCC2. String network analysis showed that the RAD51, XRCC1, XRCC2, and XRCC3 proteins are in strong interaction with each other and other breast cancer-related proteins such as BRCA2. Conclusion: RAD51 rs1801320 and XRCC3 rs861539 polymorphisms were associated with reduced risk of breast cancer. There is evidence of positive interactions among XRCC1, XRCC2, XRCC3, and RAD51.

Pathogenicity of PKCγ Genetic Variants-Possible Function as a Non-Invasive Diagnostic Biomarker in Ovarian Cancer

Ovarian cancer has the highest mortality rate among gynecologic malignancies, owing to its misdiagnosis or late diagnosis. Identification of its genetic determinants could improve disease outcomes. Conventional Protein Kinase C-γ (PKCγ) dysregulation is reported in several cancers. Similarly, its variant rs1331262028 is also reported to have an association with hepatocellular carcinoma. Therefore, the aim of the present study was to analyze the variant rs1331262028 association with ovarian cancer and to determine its impact on PKCγ's protein interactions. Association of variation was determined through genotyping PCR (cohort size:100). Protein-protein docking and molecular dynamic simulation were carried out to study the variant impact of PKCγ interactions. The study outcome indicated the positive association of variant rs1331262028 with ovarian cancer and its clinicopathological features. Molecular dynamics simulation depicted the potential influence of variation on PKCγ molecular signaling. Hence, this study provided the foundations for assessing variant rs1331262028 as a potential prognostic marker for ovarian cancer. Through further validation, it can be applied at the clinical level.

Association between XRCC3 rs861539 Polymorphism and the Risk of Ovarian Cancer: Meta-Analysis and Trial Sequential Analysis

Background

Current studies on the relationship between XRCC3 rs861539 polymorphism and ovarian cancer risk have been inconsistent. Therefore, we performed a meta-analysis to explore their association.

Methods

Six electronic databases (PubMed, Embase, Web of Science, Cochrane Library, China National Knowledge Infrastructure, and China Wanfang Database) were searched for relevant studies published before December 2021. Meta-analysis, subgroup analysis, sensitivity analysis, and publication bias analysis were performed using Stata software 16.0. Trial sequential analysis (TSA) was performed using TSA 0.9.5.10 Beta software.

Results

A total of 12 studies were included in 9 literatures, comprising 4,634 cases of ovarian cancer and 7,381 controls. After Bonferroni correction, the meta-analysis showed an association between XRCC3 rs861539 polymorphism and ovarian cancer risk in the heterozygote model and the dominant model (GA vs. GG: OR = 0.88, 95%CI = 0.81-0.96, P = 0.003; GG vs. GA+AA: OR = 0.89, 95%CI = 0.82-0.96, P = 0.004). In an ethnically stratified subgroup analysis, XRCC3 rs861539 was shown to reduce the risk of ovarian cancer in Caucasian in the heterozygote model and the dominant model (GA vs. GG: OR = 0.88, 95%CI = 0.81-0.96, P = 0.004; GG vs. GA+AA: OR = 0.88, 95%CI = 0.81-0.96, P = 0.004). In the control source and detection method stratified subgroup analysis, hospital-based studies and PCR-RFLP-based studies were found to increase ovarian cancer risk (GG vs. AA: OR = 1.30, 95%CI = 1.05-1.62, P = 0.016; GG vs. AA: OR = 1.31, 95%CI = 1.06-1.62, P = 0.013).

Conclusion

This meta-analysis showed a significant association between XRCC3 rs861539 polymorphism and ovarian cancer risk, especially in Caucasians. Large-scale multicenter case-control studies in more different regions will be needed in the future.