The BRCA Gene in Epithelial Ovarian Cancer

Advances in artificial intelligence for the diagnosis and treatment of ovarian cancer (Review)

Artificial intelligence (AI) has emerged as a crucial technique for extracting high‑throughput information from various sources, including medical images, pathological images, and genomics, transcriptomics, proteomics and metabolomics data. AI has been widely used in the field of diagnosis, for the differentiation of benign and malignant ovarian cancer (OC), and for prognostic assessment, with favorable results. Notably, AI‑based radiomics has proven to be a non‑invasive, convenient and economical approach, making it an essential asset in a gynecological setting. The present study reviews the application of AI in the diagnosis, differentiation and prognostic assessment of OC. It is suggested that AI‑based multi‑omics studies have the potential to improve the diagnostic and prognostic predictive ability in patients with OC, thereby facilitating the realization of precision medicine.

Ovarian Cancer Diagnosis and Prognosis Based on Cell-Free DNA Methylation

Background: Ovarian cancer stands as the deadliest malignant tumor within the female reproductive tract. As a result of the absence of effective diagnostic and monitoring markers, 75% of ovarian cancer cases are diagnosed at a late stage, leading to a mere 50% survival rate within five years. The advancement of molecular biology is essential for accurate diagnosis and treatment of ovarian cancer. Methods: A review of several randomized clinical trials, focusing on the ovarian cancer, was undertaken. The advancement of molecular biology and diagnostic methods related to accurate diagnosis and treatment of ovarian cancer were examined. Results: Liquid biopsy is an innovative method of detecting malignant tumors that has gained increasing attention over the past few years. Cell-free DNA assay-based liquid biopsies show potential in delineating tumor status heterogeneity and tracking tumor recurrence. DNA methylation influences a multitude of biological functions and diseases, especially during the initial phases of cancer. The cell-free DNA methylation profiling system has emerged as a sensitive and non-invasive technique for identifying and detecting the biological origins of cancer. It holds promise as a biomarker, enabling early screening, recurrence monitoring, and prognostic evaluation of cancer. Conclusions: This review evaluates recent advancements and challenges associated with cell-free DNA methylation analysis for the diagnosis, prognosis monitoring, and assessment of therapeutic responses in the management of ovarian cancers, aiming to offer guidance for precise diagnosis and treatment of this disease.

The role of circRNAs in regulation of drug resistance in ovarian cancer

Ovarian cancer is one of the female reproductive system tumors. Chemotherapy is used for advanced ovarian cancer patients; however, drug resistance is a pivotal cause of chemotherapeutic failure. Hence, it is critical to explore the molecular mechanisms of drug resistance of ovarian cancer cells and to ameliorate chemoresistance. Noncoding RNAs (ncRNAs) have been identified to critically participate in drug sensitivity in a variety of human cancers, including ovarian cancer. Among ncRNAs, circRNAs sponge miRNAs and prevent miRNAs from regulation of their target mRNAs. CircRNAs can interact with DNA or proteins to modulate gene expression. In this review, we briefly describe the biological functions of circRNAs in the development and progression of ovarian cancer. Moreover, we discuss the underneath regulatory molecular mechanisms of circRNAs on governing drug resistance in ovarian cancer. Furthermore, we mention the novel strategies to overcome drug resistance via targeting circRNAs in ovarian cancer. Due to that circRNAs play a key role in modulation of drug resistance in ovarian cancer, targeting circRNAs could be a novel approach for attenuation of chemoresistance in ovarian cancer.

Risk factors for the failure of first-line PARP inhibitor maintenance therapy in patients with advanced ovarian cancer: Gynecologic Oncology Research Investigators Collaboration Study (GORILLA-3004)

OBJECTIVE

To identify the risk factors for failure of first-line poly (ADP-ribose) polymerase inhibitor (PARPi) maintenance therapy in patients with advanced ovarian cancer.

METHOD

Patients with stage III-IV epithelial ovarian cancer who received first-line PARPi maintenance therapy were retrospectively reviewed. Clinicopathologic factors were compared between two groups-recur/progression of disease (PD) and non-recur/PD.

RESULTS

In total, 191 patients were included. Median follow-up was 9.9 months, and recurrence rate was 20.9%. BRCA mutations were found in 63.4% patients. Postoperative residual tumor (60.5% vs. 37.8%), non-high grade serous carcinoma (HGSC) (15.0% vs. 6.0%), neoadjuvant chemotherapy (NAC) (55.0% vs. 35.8%), and pre-PARPi serum CA-125 levels ≥23.5 U/mL (35.9% vs. 15.2%) were more frequently observed in the recur/PD group. Multivariate Cox-regression analysis revealed pre-PARPi serum CA-125 levels ≥23.5 U/mL (HR, 2.17; 95%CI, 1.03-4.57; p = 0.042), non-HGSC (3.28; 1.20-8.97; p = 0.021), NAC (2.11; 1.04-4.26; p = 0.037), and no BRCA mutation (2.23; 1.12-4.44; p = 0.023) as independent risk factors associated with poor progression-free survival (PFS). A subgroup analysis according to BRCA mutation status showed that pre-PARPi serum CA-125 levels ≥26.4 U/mL were the only independent risk factor for poor PFS in women with BRCA mutations (2.75; 1.03-7.39; p = 0.044). Non-HGSC (5.05; 1.80-14.18; p = 0.002) and NAC (3.36; 1.25-9.04; p = 0.016) were independent risk factors in women without BRCA mutations.

CONCLUSION

High pre-PARPi serum CA-125 levels, non-HGSC histology, NAC, and no BRCA mutation might be risk factors for early failure of first-line PARPi maintenance therapy. In women with BRCA mutations, high pre-PARPi serum CA-125 levels, which represent a large tumor burden before PARPi, were the only independent risk factor for poor PFS.

Prognostic factors and clinic-pathologic characteristics of ovarian tumor with different histologic subtypes-a SEER database population study of 41,376 cases

Background

Ovarian cancer is considered the leading cause of cancer-related deaths among all gynecological malignancies and a significant reason for mortality in women. This cohort study aimed to explore the survival trends of malignant ovarian tumors (MOT), cancer antigen 125 (CA125) level, and clinicopathological prognostic factors of MOT by histological subtype.

Methods

Using the Surveillance, Epidemiology, and End Results (SEER) database, a total of 41,411 MOT cases diagnosed between January 2005 and December 2014 were extracted. According to the histological classification of MOT, four categories were included: epithelial ovarian carcinoma (EOC), malignant ovarian germ cell tumors (MOGCTs), malignant ovarian sex cord-stromal tumors (MOSCSTs) and ovarian neuroendocrine tumors (ONTs). We analyzed disease-specific survival (DS) and overall survival (OS) among the four categories, and their histological subtypes. Kaplan-Meier method was used to estimate survival curves, and log-rank test was used to evaluate differences between curves. Univariate and multivariate Cox proportional hazards models were applied to evaluate the prognostic impact of MOT.

Results

Significant predictors related to improved OS were younger age, low grade, early FIGO stage and localized SEER stage, while positive/elevated CA125 level was a risk factor. For MOGCT and MOSCST, 3-, 5- and 10-year DS rate estimates were all >80%, followed by ONT around 70%. Malignant epithelial cancer showed low DS rate at 3-year (70.7%), 5-year (58.7%), and 10-year (47.3%).

Conclusions

EOC patients had the worst outcome, whereas MOGCT cases had the most favorable survival. Positive/elevated CA125 level led to poor prognosis. Furthermore, younger age, low grade, early FIGO stage and localized SEER stage were significant predictors for improved OS.

MicroRNAs as Potential Biomarkers in Gynecological Cancers

MicroRNAs are non-coding transcripts that, thanks to the ability to regulate the mRNA of target genes, can affect the expression of genes encoding tumor suppressors and oncogenes. They can control many important cellular processes, including apoptosis, differentiation, growth, division, and metabolism. Therefore, miRNAs play an important role in the development of many cancers, including gynecological cancers. Ovarian cancer, endometrial cancer, cervical cancer, and vulvar cancer are the most common cancers in women and are a frequent cause of death. The heterogeneity of the pathogenesis of these gynecological diseases makes the diagnostic process a significant obstacle for modern medicine. To date, many studies have been carried out, in which particular attention has been paid to the molecular pathomechanism of these diseases, with particular emphasis on miRNAs. To date, the changed profile of many miRNAs, which influenced the promotion of proliferation, migration, invasion processes and the simultaneous inhibition of programmed cell death, has been proven many times. Detailed understanding of the molecular effects of miRNAs in the above-mentioned gynecological cancers will enable the development of potential predictive and prognostic biomarkers, as well as the optimization of the diagnostic process.

Laboratory Cross-Comparison and Ring Test Trial for Tumor BRCA Testing in a Multicenter Epithelial Ovarian Cancer Series: The BORNEO GEICO 60-0 Study

Germline and tumor BRCA testing constitutes a valuable tool for clinical decision-making in the management of epithelial ovarian cancer (EOC) patients. Tissue testing is able to identify both germline (g) and somatic (s) BRCA variants, but tissue preservation methods and the widespread implementation of NGS represent pre-analytical and analytical challenges that need to be managed. This study was carried out on a multicenter prospective GEICO cohort of EOC patients with known gBRCA status in order to determine the inter-laboratory reproducibility of tissue sBRCA testing. The study consisted of two independent experimental approaches, a bilateral comparison between two reference laboratories (RLs) testing 82 formalin-paraffin-embedded (FFPE) EOC samples each, and a Ring Test Trial (RTT) with five participating clinical laboratories (CLs) evaluating the performance of tissue BRCA testing in a total of nine samples. Importantly, labs employed their own locally adopted next-generation sequencing (NGS) analytical approach. BRCA mutation frequency in the RL sub-study cohort was 23.17%: 12 (63.1%) germline and 6 (31.6%) somatic. Concordance between the two RLs with respect to BRCA status was 84.2% (gBRCA 100%). The RTT study distributed a total of nine samples (three commercial synthetic human FFPE references, three FFPE, and three OC DNA) among five CLs. The median concordance detection rate among them was 64.7% (range: 35.3-70.6%). Analytical discrepancies were mainly due to the minimum variant allele frequency thresholds, bioinformatic pipeline filters, and downstream variant interpretation, some of them with consequences of clinical relevance. Our study demonstrates a wide range of concordance in the identification and interpretation of BRCA sequencing data, highlighting the relevance of establishing standard criteria for detecting, interpreting, and reporting BRCA variants.

Next-generation sequencing based detection of BRCA1 and BRCA2 large genomic rearrangements in Chinese cancer patients

BRCA1/2 mutation is a biomarker for guiding multiple solid tumor treatment. However, the prevalence of BRCA1/2 large genomic rearrangements (LGRs) in Chinese cancer patients has not been well revealed partially due to technical difficulties in LGR detection. This study utilized next-generation sequencing (NGS) to analyze the BRCA1/2 mutation profile, including LGR, in 56126 Chinese cancer patients. We also reported that two ovarian and breast cancer patients with NGS-determined BRCA1/2 LGR benefited from PARP inhibitors (PARPi). DNA sequencing identified BRCA1/2 variants (including LGR, pathogenic and likely-pathogenic variants) in 2108 individuals. Seventy patients were discovered to harbor germline LGRs in BRCA1 and 14 had germline LGRs in BRCA2. Among the LGRs detected, exon 1-2 deletion was the predominant LGR (14/70) in BRCA1, and exon 22-24 deletion was the most frequent LGR (3/14) in BRCA2. Notably, the BRCA1 exon 7 deletion was a novel LGR and was identified in six patients, suggesting a specific LGR in Chinese cancer patients. The prevalence analysis of BRCA1 and BRCA2 LGRs across multiple cancers revealed that BRCA1 LGR more frequently occurred in ovarian cancer (1.31%, 33/2526), and BRCA2 LGR was more commonly seen in cholangiocarcinoma (0.47%, 2/425). Two ovarian and breast cancer patients with BRCA1/2 LGR benefited from PARPi therapy. This is the first study to reveal the BRCA1/2 LGR profile of a Chinese pan-cancer cohort by using an NGS-based assay. Two breast and ovarian cancer patients harboring NGS-determined BRCA1/2 LGR benefited from PARPi, indicating that NGS-based detection of BRCA1/2 LGR has the potential to guide PARPi treatment.

Hexokinase 2 promoted cell motility and proliferation by activating Akt1/p-Akt1 in human ovarian cancer cells

Background

Recently, increasing evidence has indicated that elevation of Hexokinase 2 (HK2) plays an important role in several cancers on regulating cell motility and growth. However, its role on regulating cell EMT in human ovarian cancer still less to known.

Methods

The transwell and wound-healing assay were used to detect the effective of HK2 on regulating motility of ovarian cancer cells. Real Time PCR and Western Blotting were used to explore the changing of EMT-related proteins in HK2-modified cells. The clonogenic formation, cell growth curves and MTT assays were used to evaluate the effective of HK2 on regulating cell proliferation in HK2-modified cells. The flow cytometry was used to detect the differences in the distribution of cells in the cell cycle between the HK2-modified cells and their control cells. The correlation of HK2 and Akt1/p-Akt1 was explored by using Western Blotting, Akt1 inhibitor (MK2206) and transient transfection of an Akt1 recombinant plasmid. The potential correlation between HK2 and EMT-related proteins in human ovarian cancer tissues and OV (ovarian serous cystadenocarcinoma) was confirmed by using Pearson correlation analysis and TIMER 2.0.

Results

In ovarian cancer cells, overexpressing of HK2 enhanced cell motility by inducing of EMT-related proteins, such as CDH2, fibronectin, MMP9, ZEB1, ZEB2 and vimentin. Moreover, overexpressing of HK2 promoted cell growth by reducing p21 and p27 expression in ovarian cancer cells. Further studies demonstrated that this promotion of cell motility and growth by HK2 was probably a result of it activating of Akt1 (p-Akt1) in ovarian cancer cells. Additionally, the positive correlation between HK2 and p-Akt1, fibronectin, MMP9 expression in human ovarian cancer samples was verified by using Pearson correlation analysis. The positive correlation between HK2 and CDH2, fibronectin, MMP9, ZEB1, ZEB2 and vimentin in OV (ovarian serous cystadenocarcinoma) was confirmed by using TIMER 2.0.

Conclusion

This study demonstrated that HK2 could induce EMT-related proteins and reduce cell cycle inhibitor by activating Akt1 in human ovarian cancer cells, subsequently enhancing cell motility and growth, suggesting that HK2 participate in the malignant process of ovarian cancer by interacting with Akt1.