Data from screening trials indicate that a significant percent of asymptomatic women older than 50 years of age will develop ovarian abnormalities that are detectable by ultrasonography. Most of these abnormalities are benign, and many will resolve spontaneously. However, the risk of ovarian cancer, particularly in postmenopausal women, is of concern. The goal is to use a diagnostic and treatment algorithm that will reliably detect ovarian cancer at the earliest possible stage while limiting the number of women undergoing surgery for benign disease. The combination of morphology indexing and serum biomarker analysis can accurately predict the risk of malignancy in most ovarian tumors. Ovarian tumors with cystic or septate morphology are at minimal risk of malignancy and can be followed with serial ultrasonography evaluations, thereby avoiding the morbidity and cost of surgery. Complex or solid ovarian tumors with a high morphology index score, or those with increasing biomarker production, are at a high risk of malignancy, and patients with these tumors should be referred to a gynecologic oncologist for further evaluation and treatment.

Patients diagnosed with epithelial ovarian cancer (OC) have a 5-year survival rate of 49%. For early-stage disease, the 5-year survival rate is above 90%. However, advanced-stage disease accounts for most cases as patients with early stages often are asymptomatic or present with unspecific symptoms, highlighting the need for diagnostic tools for early diagnosis. Liquid biopsy is a minimal invasive blood-based approach that utilizes circulating tumor DNA (ctDNA) shed from tumor cells for real-time detection of tumor genetics and epigenetics. Increased DNA methylation of promoter regions is an early event during tumorigenesis, and the methylation can be detected in ctDNA, accentuating the promise of methylated ctDNA as a biomarker for OC diagnosis. Many studies have investigated multiple methylation biomarkers in ctDNA from plasma or serum for discriminating OC patients from patients with benign diseases of the ovaries and/or healthy females. This systematic review summarizes and evaluates the performance of the currently investigated DNA methylation biomarkers in blood-derived ctDNA for early diagnosis of OC. PubMed's MEDLINE and Elsevier's Embase were systematically searched, and essential results such as methylation frequency of OC cases and controls, performance measures, as well as preanalytical factors were extracted. Overall, 29 studies met the inclusion criteria for this systematic review. The most common method used for methylation analysis was methylation-specific PCR, with half of the studies using plasma and the other half using serum. RASSF1A, BRCA1, and OPCML were the most investigated gene-specific methylation biomarkers, with OPCML having the best performance measures. Generally, methylation panels performed better than single gene-specific methylation biomarkers, with one methylation panel of 103,456 distinct regions and 1,116,720 CpGs having better performance in both training and validation cohorts. However, the evidence is still limited, and the promising methylation panels, as well as gene-specific methylation biomarkers highlighted in this review, need validation in large, prospective cohorts with early-stage asymptomatic OC patients to assess the true diagnostic value in a clinical setting.© 2023. The Author(s).

Background: Despite a myriad of attempts in the last three decades to diagnose ovarian cancer (OC) earlier, this clinical aim still remains a significant challenge. Aberrant methylation patterns of linked CpGs analyzed in DNA fragments shed by cancers into the bloodstream (i.e. cell-free DNA) can provide highly specific signals indicating cancer presence.Methods: We analyzed 699 cancerous and non-cancerous tissues using a methylation array or reduced representation bisulfite sequencing to discover the most specific OC methylation patterns. A three-DNA-methylation-serum-marker panel was developed using targeted ultra-high coverage bisulfite sequencing in 151 women and validated in 250 women with various conditions, particularly in those associated with high CA125 levels (endometriosis and other benign pelvic masses), serial samples from 25 patients undergoing neoadjuvant chemotherapy, and a nested case control study of 172 UKCTOCS control arm participants which included serum samples up to two years before OC diagnosis.Results: The cell-free DNA amount and average fragment size in the serum samples was up to ten times higher than average published values (based on samples that were immediately processed) due to leakage of DNA from white blood cells owing to delayed time to serum separation. Despite this, the marker panel discriminated high grade serous OC patients from healthy women or patients with a benign pelvic mass with specificity/sensitivity of 90.7% (95% confidence interval [CI] = 84.3-94.8%) and 41.4% (95% CI = 24.1-60.9%), respectively. Levels of all three markers plummeted after exposure to chemotherapy and correctly identified 78% and 86% responders and non-responders (Fisher's exact test, p = 0.04), respectively, which was superior to a CA125 cut-off of 35 IU/mL (20% and 75%). 57.9% (95% CI 34.0-78.9%) of women who developed OC within two years of sample collection were identified with a specificity of 88.1% (95% CI = 77.3-94.3%). Sensitivity and specificity improved further when specifically analyzing CA125 negative samples only (63.6% and 87.5%, respectively).Conclusions: Our data suggest that DNA methylation patterns in cell-free DNA have the potential to detect a proportion of OCs up to two years in advance of diagnosis and may potentially guide personalized treatment. The prospective use of novel collection vials, which stabilize blood cells and reduce background DNA contamination in serum/plasma samples, will facilitate clinical implementation of liquid biopsy analyses.

Variation in intercellular methylation patterns can complicate the use of methylation biomarkers for clinical diagnostic applications such as blood-based cancer testing. Here, we describe development and validation of a methylation density binary classification method called EpiClass (available for download at https://github.com/Elnitskilab/EpiClass ) that can be used to predict and optimize the performance of methylation biomarkers, particularly in challenging, heterogeneous samples such as liquid biopsies. This approach is based upon leveraging statistical differences in single-molecule sample methylation density distributions to identify ideal thresholds for sample classification.We developed and tested the classifier using reduced representation bisulfite sequencing (RRBS) data derived from ovarian carcinoma tissue DNA and controls. We used these data to perform in silico simulations using methylation density profiles from individual epiallelic copies of ZNF154, a genomic locus known to be recurrently methylated in numerous cancer types. From these profiles, we predicted the performance of the classifier in liquid biopsies for the detection of epithelial ovarian carcinomas (EOC). In silico analysis indicated that EpiClass could be leveraged to better identify cancer-positive liquid biopsy samples by implementing precise thresholds with respect to methylation density profiles derived from circulating cell-free DNA (cfDNA) analysis. These predictions were confirmed experimentally using DREAMing to perform digital methylation density analysis on a cohort of low volume (1-ml) plasma samples obtained from 26 EOC-positive and 41 cancer-free women. EpiClass performance was then validated in an independent cohort of 24 plasma specimens, derived from a longitudinal study of 8 EOC-positive women, and 12 plasma specimens derived from 12 healthy women, respectively, attaining a sensitivity/specificity of 91.7%/100.0%. Direct comparison of CA-125 measurements with EpiClass demonstrated that EpiClass was able to better identify EOC-positive women than standard CA-125 assessment. Finally, we used independent whole genome bisulfite sequencing (WGBS) datasets to demonstrate that EpiClass can also identify other cancer types as well or better than alternative methylation-based classifiers.Our results indicate that assessment of intramolecular methylation density distributions calculated from cfDNA facilitates the use of methylation biomarkers for diagnostic applications. Furthermore, we demonstrated that EpiClass analysis of ZNF154 methylation was able to outperform CA-125 in the detection of etiologically diverse ovarian carcinomas, indicating broad utility of ZNF154 for use as a biomarker of ovarian cancer.

DNA damage repair can lead to epigenetic changes. DNA mismatch repair proteins bind to platinum DNA adducts and at sites of DNA damage can recruit the DNA methylating enzyme DNMT1, resulting in aberrant methylation. We hypothesised that DNA damage repair during platinum-based chemotherapy may cause aberrant DNA methylation in normal tissues of patients such as blood. We used Illumina 450k methylation arrays and bisulphite pyrosequencing to investigate methylation at presentation and relapse in blood DNA from patients with ovarian cancer enrolled in the SCOTROC1 trial ( = 247) and in a cohort of ovarian tumor DNA samples collected at first relapse ( = 46). We used an ovarian cancer cell line model to investigate the role of the DNA mismatch repair gene in platinum-induced methylation changes. Specific CpG methylation changes in blood at relapse are observed following platinum-based chemotherapy and are associated with patient survival, independent of other clinical factors [hazard ratio, 3.7; 95% confidence interval, 1.8-7.6, = 2.8 × 10]. Similar changes occur in ovarian tumors at relapse, also associated with patient survival (hazard ratio, 2.6; 95% confidence interval, 1.0-6.8, = 0.048). Using an ovarian cancer cell line model, we demonstrate that functional mismatch repair increases the frequency of platinum-induced methylation. DNA methylation in blood at relapse following chemotherapy, and not at presentation, is informative regarding survival of patients with ovarian cancer. Functional DNA mismatch repair increases the frequency of DNA methylation changes induced by platinum. DNA methylation in blood following chemotherapy could provide a noninvasive means of monitoring patients' epigenetic responses to treatment without requiring a tumor biopsy..©2016 American Association for Cancer Research.

DNA methylation aberrations have been implicated in acquired resistance to platinum drugs in ovarian cancer. In this study, we elucidated an epigenetic signature associated with platinum drug resensitization that may offer utility in predicting the outcomes of patients who are coadministered a DNA methyltransferase inhibitor. The ovarian cancer specimens we analyzed were derived from a recent clinical trial that compared the responses of patients with recurrent platinum-resistant ovarian cancer who received carboplatin plus the DNA methyltransferase inhibitor guadecitabine or a standard-of-care chemotherapy regimen selected by the treating physician. Tumor biopsies or malignant ascites were collected from patients before treatment (day 1, cycle 1) or after treatment (after 2 cycles) for epigenomic and transcriptomic profiling using the Infinium HumanMethylation450 BeadChip (HM450). We defined 94 gene promoters that were hypomethylated significantly by guadecitabine, with 1,659 genes differentially expressed in pretreatment versus posttreatment tumors. Pathway analysis revealed that the experimental regimen significantly altered immune reactivation and DNA repair pathways. Progression-free survival correlated with baseline expression levels of 1,155 genes involved in 25 networks. In functional investigations in ovarian cancer cells, engineered upregulation of certain signature genes silenced by promoter methylation (,, and others) restored platinum drug sensitivity. Overall, our findings illuminate how inhibiting DNA methylation can sensitize ovarian cancer cells to platinum drugs, in large part by altering gene expression patterns related to DNA repair and immune activation, with implications for improving the personalized care and survival outcomes of ovarian cancer patients. Epigenomic targeting may improve therapeutic outcomes in platinum-resistant and recurrent ovarian cancer in part by effects on DNA repair and antitumor immune responses..©2017 American Association for Cancer Research.

Epigenetic alterations play a major role in cancer. Recently we reported that stem cell Polycomb group targets (PcGTs) are up to 12-fold more likely to have cancer-specific promoter DNA hypermethylation than nontargets. To identify potential, prognostic DNA methylation markers in ovarian cancer we analyzed the DNA methylation at 71 different loci in 22 ovarian cancers and 18 non-neoplastic ovarian specimens by means of a quantitative, real-time PCR-based technique (MethyLight). We identified DNA methylation of HOXA10 and HOXA11, both of them PcGTs, to be the best discriminators between cancer and non-neoplastic tissue. In an independent set consisting of 92 ovarian cancer specimens further analysis demonstrated that HOXA11 DNA methylation is (i) strongly associated with the residual tumor after cytoreductive surgery and (ii) is a marker indicating poor prognosis. HOXA11 DNA methylation was independently associated with poor outcome [relative risk for death 3.4 (95% CI 1.2-9.9; p = 0.03)]. These findings support the view that the technical inability to optimally cytoreduce ovarian cancer is associated with particular molecular alterations in the tumor which per se define a subgroup of patients with poor outcome.

Homologous recombination deficiency (HRD) testing has been approved by FDA for selecting epithelial ovarian cancer (EOC) patients who may benefit from the first-line poly (ADP-ribose) polymerase inhibitor (PARPi) maintenance therapy. However, the effects of HRD on the clinical outcomes of first-line chemotherapy and first-line PARPi maintenance therapy have not been rigorously evaluated in Chinese EOC patients. Here, we developed an HRD assay and applied it to two large retrospectively collected Chinese EOC patient cohorts. In the first-line adjuvant chemotherapy cohort (FACT, N = 380), HRD status significantly improved PFS (median, 15.6 months vs. 9.4 months; HR, 0.688; 95% CI, 0.526-0.899; P = 0.003) and OS (median, 89.5 months vs. 60.9 months; HR, 0.636; 95% CI, 0.423-0.955; P = 0.008). In the first-line PARPi maintenance therapy cohort (FPMT, N = 83), HRD status significantly improved PFS (median, NA vs. 12 months; HR, 0.438; 95% CI, 0.201-0.957; P = 0.033) and OS (median, NA vs. NA months; HR, 0.12; 95% CI, 0.029-0.505; P = 0.001). Our results demonstrate that HRD status is a significant predictor for PFS and OS in both first-line chemotherapy and first-line PARPi maintenance therapy, providing strong real-world evidence for conducting genetic testing and improving clinical recommendations for Chinese EOC patients.© 2023. The Author(s).

Poly (ADP-ribose) polymerase (PARP) inhibitors have emerged as a novel treatment option in BRCA-mutated ovarian cancer (OC); however, responses are variable and there is a lack of prognostic and predictive biomarkers. We therefore investigated whether homeobox A9 (HOXA9) promoter methylation in circulating tumour DNA (meth-ctDNA) can serve as a biomarker in patients with platinum-resistant BRCA-mutated OC, undergoing treatment with a PARP inhibitor.Patients (n = 32) were enrolled as part of a phase II trial testing veliparib in platinum-resistant BRCA-mutated OC. HOXA9 meth-ctDNA was determined at baseline and just before each treatment cycle using digital droplet polymerase chain reaction. Methylation status and change in methylation compared with baseline were correlated with overall survival (OS) and progression-free survival (PFS).Detection of HOXA9 meth-ctDNA during treatment with a PARP inhibitor was associated with worse clinical outcomes. This association was apparent after the first cycle of treatment and maintained throughout treatment. After three treatment cycles, patients with detectable HOXA9 meth-ctDNA had a median PFS of 5.1 months compared with 8.3 months for patients without, and a median OS of 9.5 months compared with 19.4 months (p < 0.0001 and p = 0.002, respectively). Patients with detectable HOXA9 meth-ctDNA at baseline, but subsequent undetectable levels, had the most favourable clinical outcome, followed by patients with undetectable levels throughout. These associations were maintained in multivariate analysis.Longitudinal monitoring of HOXA9 meth-ctDNA is clinically feasible and is strongly correlated to clinical outcomes (PFS, OS), suggesting that it may serve as a valuable predictive biomarker to inform clinical decision-making in the setting of platinum-resistant BRCA-mutated OC treated with a PARP inhibitor.Copyright © 2019 Elsevier Ltd. All rights reserved.

There is an immunoreactive subtype of ovarian cancer with a favorable prognosis, but the majority of ovarian cancers have limited immune reactivity. The reason for this is poorly understood. This study aimed to approach this question by identifying prognostically relevant genes whose prognostic mRNA expression levels correlated with a genomic event.Expression microarray and 5-year survival data on 170 ovarian tumors and aCGH data on 45 ovarian cancer cell lines were used to identify amplified/deleted genes associated with prognosis. Three immune-response genes were identified mapping to epigenetically modified chromosome 6p21.3. Genes were searched for roles in epigenetic modification, identifying KANSL1. Genome-wide association studies were searched to identify genetic variants in KANSL1 associated with altered immune profile. Sensitivity to HDAC inhibition in cell lines with KANSL1 amplification/rearrangement was studied.Expression of 196 genes was statistically significantly associated with survival, and expression levels correlated with copy number variations for 82 of them. Among these, 3 immune-response genes (HCP5, PSMB8, PSMB9) clustered together at epigenetically modified chromosome 6p21.3 and their expression was inversely correlated to epigenetic modification gene KANSL1. KANSL1 is amplified/rearranged in ovarian cancer, associated with lymphocyte profile, a biomarker for response to HDAC inhibition, and may drive expression of immune-response genes.This study identifies 82 genes with prognostic relevance and genomic alteration in ovarian cancer. Among these, immune-response genes have correlated expression which is associated with 5-year survival. KANSL1 may be a master gene altering immune-response gene expression at 6p21.3 and drive response to HDAC inhibitors. Future research should investigate KANSL1 and determine whether targeting it alters the immune profile of ovarian cancer and improves survival, HDAC inhibition, and/or immunotherapy response.Copyright © 2020 Elsevier Inc. All rights reserved.

We have addressed whether inter-individual methylation variation in somatic (white blood cells, WBCs) DNA of ovarian cancer patients provides potential for prognostic and/or pharmacoepigenetic stratification.WBC DNA methylation was analysed by bisulphite pyrosequencing at ataxia telangiectasia mutated (ATM), estrogen receptor 1 (ESR1), progesterone receptor (PGR), mutL homologue 1 (MLH1), breast cancer susceptibility gene (BRCA1), secreted frizzled-related protein 1 (SFRP1), stratifin (SFN), retinoic acid receptor beta (RARB) loci and the repetitive element LINE1 in 880 SCOTROC1 trial patients [paclitaxel (Taxol)-carboplatin versus docetaxel (Taxotere)-carboplatin as primary chemotherapy for stage Ic-IV epithelial ovarian cancer].We observed no significant associations (P < 0.005, after correction for multiple testing) for progression-free survival (PFS) using test and validation sets. However, we did identify mean SFN methylation associated with PFS (hazard ratio, HR = 1.01 per 1% increase in methylation, q = 0.028); particularly in the paclitaxel (HR = 1.01, q = 0.006), but not in the docetaxel arm in stratified analyses. Furthermore, higher methylation within the ESR1 gene was associated with CA125 response (odds ratio, OR = 1.06, q = 0.04) and with neuropathy (HR = 0.95, q = 0.002), but only in the paclitaxel arm of the trial.This is the first study linking DNA methylation variability in WBC to clinical outcomes for any tumour type; the data generated on novel prognostic and pharmacoepigenetic DNA methylation biomarkers in the circulation now need independent further evaluation.

Ovarian cancer (OC) is the most lethal gynecologic cancer due primarily to its asymptomatic nature and late stage at diagnosis. The development of non-invasive markers is an urgent priority. We report the accurate detection of epithelial OC using Artificial Intelligence (AI) and genome-wide epigenetic analysis of circulating cell free tumor DNA (cfTDNA). In a prospective study, we performed genome-wide DNA methylation profiling of cytosine (CpG) markers. Both conventional logistic regression and six AI platforms were used for OC detection. Further, we performed Gene Set Enrichment Analysis (GSEA) analysis to elucidate the molecular pathogenesis of OC. A total of 179,238 CpGs were significantly differentially methylated (FDR p-value < 0.05) genome-wide in OC. High OC diagnostic accuracies were achieved. Conventional logistic regression achieved an area under the ROC curve (AUC) [95% CI] 0.99 [± 0.1] with 95% sensitivity and 100% specificity. Multiple AI platforms each achieved high diagnostic accuracies (AUC = 0.99-1.00). For example, for Deep Learning (DL)/AI AUC = 1.00, sensitivity = 100% and 88% specificity. In terms of OC pathogenesis: GSEA analysis identified 'Adipogenesis' and 'retinoblastoma gene in cancer' as the top perturbed molecular pathway in OC. This finding of epigenomic dysregulation of molecular pathways that have been previously linked to cancer adds biological plausibility to our results.© 2022. The Author(s).

High-grade serous ovarian cancer (HGSOC) is a major unmet need in oncology. The remaining uncertainty on its originating tissue has hampered the discovery of molecular oncogenic pathways and the development of effective therapies.We used an approach based on the retention in tumors of a DNA methylation trace (OriPrint) that distinguishes the two putative tissues of origin of HGSOC, the fimbrial (FI) and ovarian surface epithelia (OSE), to stratify HGSOC by several clustering methods, both linear and non-linear. The identified tumor subtypes (FI-like and OSE-like HGSOC) were investigated at the RNAseq level to stratify an in-house cohort of macrodissected HGSOC FFPE samples to derive overall and disease-free survival and identify specific transcriptional alterations of the two tumor subtypes, both by classical differential expression and weighted correlation network analysis. We translated our strategy to published datasets and verified the co-occurrence of previously described molecular classification of HGSOC. We performed cytokine analysis coupled to immune phenotyping to verify alterations in the immune compartment associated with HGSOC. We identified genes that are both differentially expressed and methylated in the two tumor subtypes, concentrating on PAX8 as a bona fide marker of FI-like HGSOC.We show that: - OriPrint is a robust DNA methylation tracer that exposes the tissue of origin of HGSOC. - The tissue of origin of HGSOC is the main determinant of DNA methylation variance in HGSOC. - The tissue of origin is a prognostic factor for HGSOC patients. - FI-like and OSE-like HGSOC are endowed with specific transcriptional alterations that impact patients' prognosis. - OSE-like tumors present a more invasive and immunomodulatory phenotype, compatible with its worse prognostic impact. - Among genes that are differentially expressed and regulated in FI-like and OSE-like HGSOC, PAX8 is a bona fide marker of FI-like tumors.Through an integrated approach, our work demonstrates that both FI and OSE are possible origins for human HGSOC, whose derived subtypes are both molecularly and clinically distinct. These results will help define a new roadmap towards rational, subtype-specific therapeutic inroads and improved patients' care.

The vast majority of epithelial ovarian cancer arises from tissues that are embryologically derived from the Müllerian Duct. Here, we demonstrate that a DNA methylation signature in easy-to-access Müllerian Duct-derived cervical cells from women with and without ovarian cancer (i.e. referred to as the Women's risk IDentification for Ovarian Cancer index or WID-OC-index) is capable of identifying women with an ovarian cancer in the absence of tumour DNA with an AUC of 0.76 and women with an endometrial cancer with an AUC of 0.81. This and the observation that the cervical cell WID-OC-index mimics the epigenetic program of those cells at risk of becoming cancerous in BRCA1/2 germline mutation carriers (i.e. mammary epithelium, fallopian tube fimbriae, prostate) further suggest that the epigenetic misprogramming of cervical cells is an indicator for cancer predisposition. This concept has the potential to advance the field of risk-stratified cancer screening and prevention.© 2022. The Author(s).

Early diagnosis of ovarian carcinoma is bound to boost the long-term endurance rate of the patients. Most ovarian tumors happen post menopause when the ovaries have no vital operation and therefore irregular ovarian role causes no signs. According to Muinao T. et al. (Heliyon. 5(12):e02826, 2019), if we consider the frequency of ovarian carcinoma to be moderate, a screening technique must accomplish a base specificity of 99.6% and sensitivity of over 75%. The classification and approval of early diagnostic biomarkers explicit to ovarian carcinoma are essentially required. Prevailing methods for early diagnosis of ovarian carcinoma incorporate TVS, biological marker examination, or a blend of the two or other. In recent years, it has been revealed that a combination of at least two biomarkers has beaten single biomarkers in measures for early diagnosis of the illness. In the present document, we survey the ongoing exploration of innovative characteristic methodologies and possible panels of carcinoma biological markers for the early diagnosis of ovarian carcinoma and discuss biomarkers as the plausible apparatus for model improvement and other progressed approaches as an effective alternative to the prevailing methods for early diagnosis of this dreadful disease to evade bogus analysis and inordinate expense.