Despite progress in recent years, epithelial ovarian cancer remains a pathology with a poor prognosis, primarily because of late and invasive diagnosis. Conventional follow-up relies on imaging, CA125, and predictive tools such as KELIM-CA125 and the chemotherapy response score. However, these methods are non-specific and result in delays before obtaining results. Recently, many research teams have focused on liquid biopsies, which provide direct access to tumor material in biological fluids. This review examines the clinical potential of circulating tumor DNA (ctDNA) in epithelial ovarian cancer. A systematic search of the PubMed database was conducted. Inclusion criteria were studies published in English, original research articles, reviews, or meta-analyses focused on ctDNA and ovarian cancer. Exclusion criteria included non-peer-reviewed sources, articles with insufficient data, and studies not directly related to the topic. In epithelial ovarian cancer, ctDNA allows quantitative evaluation of tumor burden and qualitative analysis by detecting specific tumor DNA variations, such as epigenetic modifications or genetic mutations. Furthermore, its half-life is less than 2 hours, enabling dynamic monitoring of tumor evolution. This capability could facilitate earlier diagnosis, better screening, and more effective therapeutic follow-up. The qualitative approach also has the potential to predict chemoresistance. Technologies used to detect ctDNA in blood include quantitative polymerase chain reaction, digital polymerase chain reaction, and next-generation sequencing, which allow quantification and identification of DNA molecule modifications. CtDNA is a promising biomarker for epithelial ovarian cancer and could address several challenges in its management. However, further research is needed to establish its role in routine clinical practice, particularly, to identify a detection method that is highly sensitive, specific, and generalizable to a wide patient population.

Ovarian and tubal cancers are lethal gynaecological cancers, with over 50% of the patients diagnosed at advanced stage.

Randomised controlled trial involving 27 primary care trusts adjacent to 13 trial centres based at NHS Trusts in England, Wales and Northern Ireland.

Postmenopausal average-risk women, aged 50-74, with intact ovaries and no previous ovarian or current non-ovarian cancer.

One of two annual screening strategies: (1) multimodal screening (MMS) using a longitudinal CA125 algorithm with repeat CA125 testing and transvaginal scan (TVS) as second line test (2) ultrasound screening (USS) using TVS alone with repeat scan to confirm any abnormality. The control (C) group had no screening. Follow-up was through linkage to national registries, postal follow-up questionnaires and direct communication with trial centres and participants.

To assess comprehensively risks and benefits of ovarian cancer screening in the general population.

Primary outcome was death due to ovarian or tubal cancer as assigned by an independent outcomes review committee. Secondary outcomes included incidence and stage at diagnosis of ovarian and tubal cancer, compliance, performance characteristics, harms and cost-effectiveness of the two screening strategies and a bioresource for future research.

The trial management system confirmed eligibility and randomly allocated participants using computer-generated random numbers to MMS, USS and C groups in a 1:1:2 ratio.

Investigators and participants were unblinded and outcomes review committee was masked to randomisation group.

Primary analyses were by intention to screen, comparing separately MMS and USS with C using the Versatile test.

1,243,282 women were invited and 205,090 attended for recruitment between April 2001 and September 2005.

202,638 women: 50,640 MMS, 50,639 USS and 101,359 C group.

202,562 (>99.9%): 50,625 (>99.9%) MMS, 50,623 (>99.9%) USS, and 101,314 (>99.9%) C group.

Women in MMS and USS groups underwent 345,570 and 327,775 annual screens between randomisation and 31 December 2011. At median follow-up of 16.3 (IQR 15.1-17.3) years, 2055 women developed ovarian or tubal cancer: 522 (1.0% of 50,625) MMS, 517 (1.0% of 50,623) USS, and 1016 (1.0% of 101314) in C group. Compared to the C group, in the MMS group, the incidence of Stage I/II disease was 39.2% (95% CI 16.1 to 66.9) higher and stage III/IV 10.2% (95% CI -21.3 to 2.4) lower. There was no difference in stage in the USS group. 1206 women died of the disease: 296 (0.6%) MMS, 291 (0.6%) USS, and 619 (0.6%) C group. There was no significant reduction in ovarian and tubal cancer deaths in either MMS (p = 0.580) or USS (p = 0.360) groups compared to the C group. Overall compliance with annual screening episode was 80.8% (345,570/420,047) in the MMS and 78.0% (327,775/420,047) in the USS group. For ovarian and tubal cancers diagnosed within one year of the last test in a screening episode, in the MMS group, the sensitivity, specificity and positive predictive values were 83.8% (95% CI 78.7 to 88.1), 99.8% (95% CI 99.8 to 99.9), and 28.8% (95% CI 25.5 to 32.2) and in the USS group, 72.2% (95% CI 65.9 to 78.0), 99.5% (95% CI 99.5 to 99.5), and 9.1% (95% CI 7.8 to 10.5) respectively. The final within-trial cost-effectiveness analysis was not undertaken as there was no mortality reduction. A bioresource (UKCTOCS Longitudinal Women's Cohort) of longitudinal outcome data and over 0.5 million serum samples including serial annual samples in women in the MMS group was established and to date has been used in many new studies, mainly focused on early detection of cancer.

Both screening tests (venepuncture and TVS) were associated with minor complications with low (8.6/100,000 screens MMS; 18.6/100,000 screens USS) complication rates. Screening itself did not cause anxiety unless more intense repeat testing was required following abnormal screens. In the MMS group, for each screen-detected ovarian or tubal cancer, an additional 2.3 (489 false positives; 212 cancers) women in the MMS group had unnecessary false-positive (benign adnexal pathology or normal adnexa) surgery. Overall, 14 (489/345,572 annual screens) underwent unnecessary surgery per 10,000 screens. In the USS group, for each screen-detected ovarian or tubal cancer, an additional 10 (1630 false positives; 164 cancers) underwent unnecessary false-positive surgery. Overall, 50 (1630/327,775 annual screens) women underwent unnecessary surgery per 10,000 screens.

Population screening for ovarian and tubal cancer for average-risk women using these strategies should not be undertaken. Decreased incidence of Stage III/IV cancers during multimodal screening did not translate to mortality reduction. Researchers should be cautious about using early stage as a surrogate outcome in screening trials. Meanwhile the bioresource provides a unique opportunity to evaluate early cancer detection tests.

Long-term follow-up UKCTOCS (2015-2020) - National Institute for Health and Care Research (NIHR HTA grant 16/46/01), Cancer Research UK, and The Eve Appeal. UKCTOCS (2001-2014) - Medical Research Council (MRC) (G9901012/G0801228), Cancer Research UK (C1479/A2884), and the UK Department of Health, with additional support from The Eve Appeal. Researchers at UCL were supported by the NIHR UCL Hospitals Biomedical Research Centre and by MRC Clinical Trials Unit at UCL core funding (MR_UU_12023).

DNA methylation is a crucial epigenetic modification used as a biomarker for early cancer progression. However, existing methods for DNA methylation analysis are complex, time-consuming, and prone to DNA degradation. This work demonstrates selective capture of unmethylated DNAs using ZnO nanowires without chemical or biological modifications, thereby concentrating methylated DNA, particularly those with high methylation levels that can predict cancer risk. We observe varying affinities between methylated and unmethylated DNA on ZnO nanowires, which may be influenced by differences in hydrogen bonding strength, potentially related to the effects of methylation on DNA strand behavior, including self-aggregation and stretching inhibition. As a result, the nanowire-based microfluidic device effectively collects unmethylated DNA, leading to a significantly increased ratio of methylated to unmethylated DNA, particularly for collecting low-concentration methylated DNA. This simplified microfluidic device, composed of ZnO nanowires, enables direct separation of specific methylated DNA, offering a potential approach for DNA methylation mapping in clinical disease diagnostics.

The aim of this study was to identify differentially methylated regions in cell-free DNA (cfDNA) between healthy persons and patients with advanced stage ovarian cancer (ASOC) and to identify differences in cfDNA methylation before and after cytoreductive surgery. Plasma-derived cfDNA was analyzed by a high-throughput genome wide DNA methylation sequencing technique: MeD-seq. A training set of therapy naïve cfDNA samples of patients with ASOC (≥FIGO stage IIIB, n=10) was compared with cfDNA of healthy controls (n=10) to define a ASOC specific cfDNA methylation signature. A cumulative hypermethylation score was constructed and a validation set of pre- and postoperative samples of 39 patients were compared using this score. MeD-seq results of tumor tissue samples were correlated with cfDNA results. Patients with ASOC showed a clear distinct cfDNA methylation signature from healthy controls (p<0.0001). This cfDNA-methylation signature resulted in preoperative hypermethylation scores (135; interquartile range 110-163) that were significantly higher than postoperative hypermethylation scores (91; interquartile range 76-101) (p<0.001). The cfDNA methylation signature at baseline differed from tumor tissue and was more closely related to DNA methylation of immune-related cells (T-lymphocytes, neutrophil granulocytes, monocytes, and B-lymphocytes) than to ASOC tissue. MeD-seq provides a promising method for genome wide methylation profiling of cfDNA. Patients with ASOC could clearly be distinguished from healthy controls and differed pre- and postoperatively.

The surgeon's subjective intraoperative evaluation is the standard of care to assess postoperative residual disease (RD) in advanced epithelial ovarian cancer (EOC). We investigated the feasibility of ctDNA as an objective marker for postoperative RD.

This prospective study included 27 patients with advanced ovarian cancer (FIGO IIIA1-IVB) who underwent primary surgery between July 2021 and July 2022. Blood samples were analyzed preoperatively and on days 2 (d2) and 10 (d10) postoperatively. Low-coverage whole genome sequencing (WGS) was used to identify structural variants (SVs) at single-base pair resolution, single nucleotide variants (SNVs), and indels in tumor tissue to develop personalized, tumor-informed digital polymerase chain reaction (dPCR) fingerprint assays for each patient.

dPCR fingerprint assays were successfully developed for all patients by identifying one to eight SVs/SNVs per patient. ctDNA was detected in 96% (n = 26/27) of patients preoperatively and in 81% (n = 22/27) of patients at d10. Median ctDNA levels at d10 were significantly higher in patients with postoperative RD (median 367.38 copies (cps)/mL, 2.84% variant allele frequency; VAF) than in patients without postoperative RD (median 0.92 cps/mL, 0.017% VAF, p < 0.001). In patients with postoperative RD, ctDNA levels increased from the preoperative stage to d10 in seven out of eight patients (p = 0.016). In patients with complete tumor resection, ctDNA levels decreased from the preoperative stage to d10 in 17/19 patients (p < 0.001).

A tumor-informed personalized ctDNA approach demonstrated feasibility, providing extremely high detection rates pre- and postoperatively. These results indicate that this approach could potentially be used for postoperative RD assessment in patients with primary advanced EOC.

Characterization of tumor epigenetic aberrations is integral to understanding the mechanisms of tumorigenesis and provide diagnostic, prognostic, and predictive information of high clinical relevance. Among the different tumor-associated epigenetic signatures, 5 methyl-cytosine (5mC) and 5-hydroxymethylcytosine (5hmC) are the two most well-characterized DNA methylation alterations linked to cancer pathogenesis. 5hmC has a tissue-specific distribution and its abundance is subjected to changes in tumor DNA, making it a promising biomarker. Detecting tumor-related DNA methylation alterations in tissues is highly invasive, while the analysis of the cell-free DNA (cfDNA) is poised to supplement, if not replace, surgical biopsies. Despite many studies attempted to identify new epigenetic targets for liquid biopsy assays, little is known about the regulatory roles of 5hmC, its impacts on the molecular phenotypes in tumors. Most importantly, whether the oncogenic-associated 5hmC signatures found in tumor tissues can be recapitulated in patients' cfDNA. In this study, we performed the unbiased and simultaneous detection of 5mC and 5hmC whole-genome DNA modifications at base-resolution from two distinct cancer cohorts, from patients with bladder cancer or B-Cell lymphoma, their corresponding normal tissues, and cfDNAs from plasma. We analyzed tissue-specific methylation patters and searched for signatures in gene coding and regulatory regions linked to cancerous states. We then looked for methylation signatures in patients' cfDNA to determine if they were consistent with the tumor-specific patterns. We determined the functional significance of 5hmC in tissue specific transcription and uncovered hundreds of tumor-associated 5hmC signatures. These tumor-associated 5hmC changes, particularly in genes and enhancers, were functionally significant in tumorigenesis pathways and correlated with tumor specific gene expression. To investigate if cfDNA is a faithful surrogate for tumor-associated 5hmC, we devised a targeted capture strategy to examine the alterations of 5hmC in cfDNA from patients with bladder cancer and lymphoma with sufficient sensitivity and specificity and confirmed that they recapitulated the patterns we observed in tumor tissues. Our results provide analytic validation of 5hmC as a cancer-specific biomarker. The methods described here for systematic characterization of 5hmC at functional elements open new avenues to discover epigenetic markers for non-invasive diagnosis, monitoring, and stratifying cancer.

Cirrhosis is the precursor to most cases of hepatocellular carcinoma (HCC). Understanding the mechanisms leading to the transition from cirrhosis to HCC and identifying key biomarkers is crucial to developing effective screening strategies and reducing HCC-related mortality. DNA methylation is associated with gene inactivation and plays an important role in physiological and pathological processes; however, its role in cirrhosis progression to HCC is unknown.

We performed genome-wide DNA methylation profiling using Illumina Infinium MethylationEPI BeadChip in pre-diagnostic samples from 22 cirrhosis patients who subsequently developed HCC and 22 cirrhosis patients who remained HCC-free during an average 4-year follow-up. In a secondary analysis, we examined a subset of patients without hepatitis C virus (HCV) infection.

We identified three differentially methylated positions (DMPs) located in ADAM12 (cg13674437) and PSD3 (cg06758847 and cg24595678) that show a strong association with HCC risk (lower median vs. higher median hazards ratio (HR): HR cg13674437 = 0.34, 95% CI = 0.14-0.83; HR cg06758847 = 4.89, 95% CI = 1.79-13.33; HR cg24595678 = 11.19, 95% CI = 3.27-38.35). After excluding all HCV-active patients from our analysis, the HR for the DMPs remained significant.

In conclusion, the findings in this study support the theory that buffy coat-derived DNA methylation markers could be used to identify biomarkers among cirrhosis patients at high risk for HCC before clinical symptoms appear. A further study with a large prospective cohort is required to validate these findings.

To evaluate the prognostic impact of circulating tumor DNA (ctDNA) detection at diagnosis (T0) and its early decrease after one cycle (T1) of neoadjuvant chemotherapy (NACT) in patients with advanced epithelial ovarian cancer (EOC) included in the CHIVA trial (NCT01583322).

Blood samples were collected at T0 and before each administration of NACT. Circulating tumor DNA detection was performed by next-generation sequencing. Multivariate analysis was performed. A p-value of 0.05 was considered significant. Progression-free survival (PFS) and overall survival (OS) were compared between groups defined by ctDNA kinetic profile. Cox survival model was used to search variables associated with PFS and OS. Kaplan-Mayer curve was used to graphically express the differences in PFS and OS. A log-rank test compared the two curves.

188 patients were included. Blood samples were available for 168 patients at T0 and for 160 patients at T0 and T1 to assess ctDNA ratio kinetics. At T0, 107 patients (63.7 %) had detectable ctDNA. At T1, 137 (85.6 %) patients had negative ctDNA or a decrease of more than 80 %. There was a significant benefit in either PFS (p = 0.0017) or OS (p = 0.0036) in favor of early decrease of ctDNA ratio. A favorable decrease was associated with a greater likelihood of being able to perform CRS (OR: 3.94 (CI95 % 1.45-10.70), p = 0.0074).

Early decrease of ctDNA ratio can provide prognostic information early in the management of patients, allowing a more accurate information to patients and an early preparation for CRS (prehabilitation).

Aim: Cancers lacking standard screening (LSS) options account for approximately 70% of cancer-related deaths due to late-stage diagnosis. Circulating tumor DNA (ctDNA) is a promising biomarker for multi-cancer early detection. We previously developed SPOT-MAS, a multimodal ctDNA-based assay analyzing methylation and fragmentomic profiles, effective in detecting common cancers (breast, colorectal, liver, lung and gastric). This study extends the analysis to five LSS cancers: endometrial, esophageal, head and neck, ovarian and pancreatic.Methods: SPOT-MAS was applied to profile cfDNA methylation and fragmentomic patterns in 739 healthy individuals and 135 LSS cancer patients.Results: We identified 347 differentially methylated regions and observed genome-wide hypomethylation across all five LSS cancers. Esophageal and head and neck cancers showed an enrichment of short cfDNA fragments (<150 bp). Eleven 4-mer end motifs were consistently altered in cfDNA fragments across all LSS cancers. Many significant signatures were consistent with previous observations in common cancers. Notably, SPOT-MAS achieved 96.2% specificity and 74.8% overall sensitivity, with a lower sensitivity of 60.7% in early-stage cancers.Conclusion: This proof-of-concept study demonstrates that SPOT-MAS a non-invasive test trained on five common cancer types, could detect a number of LSS cancer cases, potentially complementing existing screening programs.

Ovarian cancer is the deadliest of all gynecological diseases because its diagnosis and treatment still pose many problems. Surgical excision, hormone therapy, radiation, chemotherapy, or targeted therapy for eradicating the main tumor and halting the spread of metastases are among the treatment options available to individuals with ovarian cancer, depending on the disease's stage. Tumor DNA that circulates in a patient's bodily fluids has been studied recently as a possible novel biomarker for a number of cancers, as well as a means of quantifying tumor size and evaluating the efficacy of cancer therapy. The most significant alterations that we could find in the ctDNA of ovarian cancer patients-such as chromosomal instability, somatic mutations, and methylation-are discussed in this review. Additionally, we talk about the utility of ctDNA in diagnosis, prognosis, and therapy response prediction for these patients.

The primary reason for high mortality rates among cancer patients is metastasis, where tumor cells migrate through the bloodstream from the original site to other parts of the body. Recent advancements in technology have significantly enhanced our comprehension of the mechanisms behind the bloodborne spread of circulating tumor cells (CTCs). One critical process, DNA methylation, regulates gene expression and chromosome stability, thus maintaining dynamic equilibrium in the body. Global hypomethylation and locus-specific hypermethylation are examples of changes in DNA methylation patterns that are pivotal to carcinogenesis. This comprehensive review first provides an overview of the various processes that contribute to the formation of CTCs, including epithelial-mesenchymal transition (EMT), immune surveillance, and colonization. We then conduct an in-depth analysis of how modifications in DNA methylation within CTCs impact each of these critical stages during CTC dissemination. Furthermore, we explored potential clinical implications of changes in DNA methylation in CTCs for patients with cancer. By understanding these epigenetic modifications, we can gain insights into the metastatic process and identify new biomarkers for early detection, prognosis, and targeted therapies. This review aims to bridge the gap between basic research and clinical application, highlighting the significance of DNA methylation in the context of cancer metastasis and offering new avenues for improving patient outcomes.

Epithelial ovarian cancer (EOC) is the deadliest women's cancer and has a poor prognosis. Early detection is the key for improving survival (a 5-year survival rate in stage I/II is over 70% compared to that of 25% in stage III/IV) and can be achieved through methylation markers from circulating cell-free DNA (cfDNA) using a liquid biopsy. In this study, we first identify top 500 EOC markers differentiating EOC from healthy female controls from 3.3 million methylome-wide CpG sites and validated them in 1,800 independent cfDNA samples. We then utilize a pretrained AI transformer system called MethylBERT to develop an EOC diagnostic model which achieves 80% sensitivity and 95% specificity in early-stage EOC diagnosis. We next develop a simple digital droplet PCR (ddPCR) assay which archives good performance, facilitating early EOC detection.

Ovarian cancer (OC) is the most lethal gynecologic malignancy worldwide. Due to the lack of effective screening and early detection strategies, many patients with OC are diagnosed with advanced disease, where treatment is rarely curative. Moreover, OC is characterized by high intratumor heterogeneity, which represents a major barrier to the development of effective treatments. Conventional tumor biopsy and blood-based biomarkers, such as cancer antigen 125 (CA125), have different limitations. Liquid biopsy has recently emerged as an attractive and promising area of investigation in oncology, due to its minimally invasive, safe, comprehensive, and real-time dynamic nature. Preliminary evidence suggests a potential role of liquid biopsy to refine OC management, by improving screening, early diagnosis, assessment of response to treatment, detection, and profiling of drug resistance. The current knowledge and the potential clinical value of liquid biopsy in OC is discussed in this review to provide an overview of the clinical settings in which its use might support and improve diagnosis and treatment.

High ovarian cancer mortality rates motivate the development of effective and patient-friendly diagnostics. Here, we explored the potential of molecular testing in patient-friendly samples for ovarian cancer detection.

Home-collected urine, cervicovaginal self-samples, and clinician-taken cervical scrapes were prospectively collected from 54 patients diagnosed with a highly suspicious ovarian mass (benign n = 25, malignant n = 29). All samples were tested for nine methylation markers, using quantitative methylation-specific PCRs that were verified on ovarian tissue samples, and compared to non-paired patient-friendly samples of 110 age-matched healthy controls. Copy number analysis was performed on a subset of urine samples of ovarian cancer patients by shallow whole-genome sequencing.

Three methylation markers are significantly elevated in full void urine of ovarian cancer patients as compared to healthy controls (C2CD4D, P = 0.008; CDO1, P = 0.022; MAL, P = 0.008), of which two are also discriminatory in cervical scrapes (C2CD4D, P = 0.001; CDO1, P = 0.004). When comparing benign and malignant ovarian masses, GHSR shows significantly elevated methylation levels in the urine sediment of ovarian cancer patients (P = 0.024). Other methylation markers demonstrate comparably high methylation levels in benign and malignant ovarian masses. Cervicovaginal self-samples show no elevated methylation levels in patients with ovarian masses as compared to healthy controls. Copy number changes are identified in 4 out of 23 urine samples of ovarian cancer patients.

Our study reveals increased methylation levels of ovarian cancer-associated genes and copy number aberrations in the urine of ovarian cancer patients. Our findings support continued research into urine biomarkers for ovarian cancer detection and highlight the importance of including benign ovarian masses in future studies to develop a clinically useful test.

The high mortality rate of epithelial ovarian cancer (EOC) is often attributed to the frequent development of chemoresistance. DNA methylation is a predictive biomarker for chemoresistance.

This study utilized DNA methylation profiles and relevant information from GEO and TCGA to identify different methylated CpG sites (DMCs) between chemoresistant and chemosensitive patients. Subsequently, we constructed chemoresistance risk models with DMCs. The genes corresponding to candidate DMCs in chemoresistance risk models were further analyzed to identify different methylated gene symbols (DMGs) associated with chemoresistance. The DMGs that showed a strong correlation with the corresponding DMCs were analyzed through immunohistochemistry.

Compared to chemosensitive EOC patients, chemoresistant patients showed 423 hypermethylated CpGs and 1445 hypomethylated CpGs. The chemoresistance risk models based on DMCs have shown the improved predictive ability for chemoresistance in EOC (AUC = 65.0-76.2%). The methylations of cg25510164, cg13154880, cg15362155 and cg08665359 were strongly associated with decreased risk of chemoresistance. Conversely, the methylation of cg08872590 and cg14739437 significantly increased the risk. We identified 13 DMGs, from 47 DMCs corresponding genes, between chemosensitive and chemoresistant samples. Among the DMGs, the expression levels of DDR2 and OPCML exhibited strong correlations with the corresponding DMCs. DDR2 and OPCML both showed enhanced expression in chemoresistant ovarian microarray tissue.

Hypomethylated CpGs may play a significant role in DNA methylation associated with chemoresistance in EOC. The epigenetic modification of DDR2 could have important implications for the development of chemoresistance. Our study provides valuable insights for future research on DNA methylation in the chemoresistance of EOC.

Analysis of cell-free DNA methylation (cfDNAme), alone or combined with CA125, could help to detect ovarian cancers earlier and may reduce mortality. We assessed cfDNAme in regions of ZNF154, C2CD4D and WNT6 via targeted bisulfite sequencing in diagnostic and early detection (preceding diagnosis) settings. Diagnostic samples were obtained via prospective blood collection in cell-free DNA tubes in a convenience series of patients with a pelvic mass. Early detection samples were matched case-control samples derived from the UK Familial Ovarian Cancer Screening Study (UKFOCSS). In the diagnostic set (ncases  = 27, ncontrols  = 41), the specificity of cfDNAme was 97.6% (95% CI: 87.1%-99.9%). High-risk cancers were detected with a sensitivity of 80% (56.3%-94.3%). Combination of cfDNAme and CA125 resulted in a sensitivity of 94.4% (72.7%-99.9%) for high-risk cancers. Despite technical issues in the early detection set (ncases  = 29, ncontrols  = 29), the specificity of cfDNAme was 100% (88.1%-100.0%). We detected 27.3% (6.0%-61.0%) of high-risk cases with relatively lower genomic DNA (gDNA) contamination. The sensitivity rose to 33.3% (7.5%-70.1%) in samples taken <1 year before diagnosis. We detected ovarian cancer in several patients up to 1 year before diagnosis despite technical limitations associated with archival samples (UKFOCSS). Combined cfDNAme and CA125 assessment may improve ovarian cancer screening in high-risk populations, but future large-scale prospective studies will be required to validate current findings.

Circulating tumour DNA (ctDNA) facilitates longitudinal study of the tumour genome, which, unlike tumour tissue biopsies, globally reflects intratumor and intermetastatis heterogeneity. Despite its costs, next-generation sequencing (NGS) has revolutionised the study of ctDNA, ensuring a more comprehensive and multimodal approach, increasing data collection, and introducing new variables that can be correlated with clinical outcomes. Current NGS strategies can comprise a tumour-informed set of genes or the entire genome and detect a tumour fraction as low as 10-5. Despite some conflicting studies, there is evidence that ctDNA levels can predict the worse outcomes of ovarian cancer (OC) in both early and advanced disease. Changes in those levels can also be informative regarding treatment efficacy and tumour recurrence, capable of outperforming CA-125, currently the only universally utilised plasma biomarker in high-grade serous OC (HGSOC). Qualitative evaluation of sequencing shows that increasing copy number alterations and gene variants during treatment may correlate with a worse prognosis in HGSOC. However, following tumour clonality and emerging variants during treatment poses a more unique opportunity to define treatment response, select patients based on their emerging resistance mechanisms, like BRCA secondary mutations, and discover potential targetable variants. Sequencing of tumour biopsies and ctDNA is not always concordant, likely as a result of clonal heterogeneity, which is better captured in the plasma samples than it is in a large number of biopsies. These incoherences may reflect tumour clonality and reveal the acquired alterations that cause treatment resistance. Cell-free DNA methylation profiles can be used to distinguish OC from healthy individuals, and NGS methylation panels have been shown to have excellent diagnostic capabilities. Also, methylation signatures showed promise in explaining treatment responses, including BRCA dysfunction. ctDNA is evolving as a promising new biomarker to track tumour evolution and clonality through the treatment of early and advanced ovarian cancer, with potential applicability in prognostic prediction and treatment selection. While its role in HGSOC paves the way to clinical applicability, its potential interest in other histological subtypes of OC remains unknown.

High-grade serous ovarian cancer (HGSOC) is the most lethal tumor of the female genital tract. Despite extensive studies and the identification of some precursor lesions like serous tubal intraepithelial cancer (STIC) or the deviated mutational status of the patients (BRCA germinal mutation), the pathophysiology of HGSOC and the existence of particular risk factors is still a puzzle. Moreover, a lack of screening programs results in delayed diagnosis, which is accompanied by a secondary chemo-resistance of the tumor and usually results in a high recurrence rate after the primary therapy. Therefore, there is an urgent need to identify the substantial risk factors for both predisposed and low-risk populations of women, as well as to create an economically and clinically justified screening program. This paper reviews the classic and novel risk factors for HGSOC and methods of diagnosis and prediction, including serum biomarkers, the liquid biopsy of circulating tumor cells or circulating tumor DNA, epigenetic markers, exosomes, and genomic and proteomic biomarkers. The novel future complex approach to ovarian cancer diagnosis should be devised based on these findings, and the general outcome of such an approach is proposed and discussed in the paper.

Globally, liver cancers are the second most lethal malignancy after lung cancer (0.83 million deaths in 2020). Hepatocellular carcinoma (HCC) is the predominant type of primary liver cancer and is typically associated with liver fibrosis or cirrhosis. HCC diagnosis relies on histologic examination of surgical specimens or conventional tissue biopsy material. However, standard tissue biopsies are invasive and often do not accurately reflect the tumor heterogeneity. On the other hand, the use of liquid biopsies, represented mainly by circulating tumor DNA (ctDNA) and circulating tumor cells (CTCs), has greatly increased in the past 2 decades. Indeed, liquid biopsies are a noninvasive, repeatable, and sensitive approach to studying tumor biology.

This review describes current clinical applications of ctDNA analysis in the management of patients with chronic liver disease, cirrhosis, and HCC. There is a substantial clinical potential of ctDNA, but interventional studies are still lacking for the moment.

Detection of ctDNA in both asymptomatic individuals and high-risk patients (with chronic liver disease or cirrhosis) contributes to the early diagnosis of HCC. ctDNA analysis also offer tremendous information on the tumor burden and on the risk of early recurrence. The implementation of ctDNA analysis, in association with classical tumor markers (e.g., alpha-fetoprotein), may improve (a) HCC screening in high-risk patients, (b) stratification of the recurrence risk after surgery, and (c) prognosis evaluation of patients with HCC.

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.

Ovarian cancer (OC) is the eighth most common cancer in women, but the mild, non-specific clinical presentation in early stages often prevents diagnosis until progression to advanced-stage disease, contributing to the high mortality associated with OC. While serum cancer antigen 125 (CA-125) has been successfully used as a blood-borne marker and is routinely monitored in patients with OC, CA-125 testing has limitations in sensitivity and specificity and does not provide direct information on important molecular characteristics that can guide treatment decisions, such as homologous recombination repair deficiency. We comprehensively review the literature surrounding methods based on liquid biopsies, which may provide improvements in sensitivity, specificity, and provide valuable additional information to enable early diagnosis, monitoring of recurrence/progression/therapeutic response, and accurate prognostication for patients with OC, highlighting applications of this research in China.

The risk of death from ovarian cancer is highly associated with the clinical stage at diagnosis. Efforts to implement screening for ovarian cancer have been largely unsuccessful, due to the low prevalence of the disease in the general population and the heterogeneity of the various cancer types that fall under the ovarian cancer designation. A practical test for early detection will require both high sensitivity and high specificity to balance reducing the number of cancer deaths with minimizing surgical interventions for false positive screens. The technology must be cost-effective to deliver at scale, widely accessible, and relatively noninvasive. Most importantly, a successful early detection test must be effective not only at diagnosing ovarian cancer but also in reducing ovarian cancer deaths. Stepwise or multimodal approaches among the various areas under investigation will likely be required to make early detection a reality.

Tubo-ovarian cancer is the most lethal gynaecological cancer. More than 75% of patients are diagnosed at an advanced stage, which is associated with poorer overall survival. Symptoms at presentation are vague and non-specific, contributing to late diagnosis. Multimodal risk models have improved the diagnostic accuracy of adnexal mass assessment based on patient risk factors, coupled with findings on imaging and serum-based biomarker tests. Newly developed ultrasonographic assessment algorithms have standardised documentation and enable stratification of care between local hospitals and cancer centres. So far, no screening test has proven to reduce ovarian cancer mortality in the general population. This review is an update on the evidence behind ovarian cancer diagnostic strategies.

Ovarian cancer has a poor prognosis and is difficult to detect in early stages. Therefore, developing new diagnostic markers for early-stage ovarian cancer is critical. Here, we developed a diagnostic marker for early-stage ovarian cancer on the basis of fatty acid metabolism characteristics of cancer cells. The expression of various fatty acid metabolizing enzymes such as stearoyl-CoA desaturase 1 (SCD1) was altered in early-stage ovarian cancer tissue compared with that in normal ovarian tissue. Changes in the expression of fatty acid metabolizing enzymes, particularly SCD1, in cancer tissues were found to alter concentrations of multiple free fatty acids (FFA) in serum. We were the first to show that fatty acid metabolic characteristics in tissues are related to the FFA composition of serum. Surprisingly, patients with stage I/II ovarian cancer also showed significant changes in serum levels of eight FFAs, which can be early diagnostic markers. Finally, using statistical analysis, an optimal early diagnostic model combining oleic and arachidic acid levels, fatty acids associated with SCD1, was established and confirmed to have higher diagnostic power than CA125, regardless of histology. Thus, our newly developed diagnostic model using serum FFAs may be a powerful tool for the noninvasive early detection of ovarian cancer.

Measurement of serum FFA levels by changes in the expression of fatty acid metabolizing enzymes in tumor tissue would allow early detection of ovarian cancer. In particular, the SCD1-associated FFAs, oleic and arachidic acid, would be powerful new screening tools for early-stage ovarian cancer.

Grade 4 glioma is the most aggressive and currently incurable brain tumor with a median survival of one year in adult patients. Elucidating novel transcriptomic and epigenetic contributors to the molecular heterogeneity underlying its aggressiveness may lead to improved clinical outcomes.

To identify grade 4 glioma -associated 5-hydroxymethylcytosine (5hmC) and transcriptomic features as well as their cross-talks, genome-wide 5hmC and transcriptomic profiles of tissue samples from 61 patients with grade 4 gliomas and 9 normal controls were obtained for differential and co-regulation/co-modification analyses. Prognostic models on overall survival based on transcriptomic features and the 5hmC modifications summarized over genic regions (promoters, gene bodies) and brain-derived histone marks were developed using machine learning algorithms.

Despite global reduction, the majority of differential 5hmC features showed higher modification levels in grade 4 gliomas as compared to normal controls. In addition, the bi-directional correlations between 5hmC modifications over promoter regions or gene bodies and gene expression were greatly disturbed in grade 4 gliomas regardless of IDH1 mutation status. Phenotype-associated co-regulated 5hmC-5hmC modules and 5hmC-mRNA modules not only are enriched with different molecular pathways that are indicative of the pathogenesis of grade 4 gliomas, but also are of prognostic significance comparable to IDH1 mutation status. Lastly, the best-performing 5hmC model can predict patient survival at a much higher accuracy (c-index = 74%) when compared to conventional prognostic factor IDH1 (c-index = 57%), capturing the molecular characteristics of tumors that are independent of IDH1 mutation status and gene expression-based molecular subtypes.

The 5hmC-based prognostic model could offer a robust tool to predict survival in patients with grade 4 gliomas, potentially outperforming existing prognostic factors such as IDH1 mutations. The crosstalk between 5hmC and gene expression revealed another layer of complexity underlying the molecular heterogeneity in grade 4 gliomas, offering opportunities for identifying novel therapeutic targets.

Ovarian cancer (OC) is characterized by silent progression and late-stage diagnosis. It is critical to detect and accurately diagnose the disease early to improve survival rates. Tumor markers have emerged as valuable tools in the diagnosis and management of OC, offering non-invasive and cost-effective options for screening, monitoring, and prognosis.

This paper explores the diagnostic importance of various tumor markers including CA-125, CA15-3, CA 19-9, HE4,hCG, inhibin, AFP, and LDH, and their impact on disease monitoring and treatment response assessment.

Article searches were performed on PubMed, Scopus, and Google Scholar. Keywords used for the searching process were "Ovarian cancer", "Cancer biomarkers", "Early detection", "Cancer diagnosis", "CA-125","CA 15-3","CA 19-9", "HE4","hCG", "inhibin", "AFP", "LDH", and others.

HE4, when combined with CA-125, shows improved sensitivity and specificity, particularly in early-stage detection. Additionally, hCG holds promise as a prognostic marker, aiding treatment response prediction and outcome assessment. Novel markers like microRNAs, DNA methylation patterns, and circulating tumor cells offer potential for enhanced diagnostic accuracy and personalized management. Integrating these markers into a comprehensive panel may improve sensitivity and specificity in ovarian cancer diagnosis. However, careful interpretation of tumor marker results is necessary, considering factors such as age, menopausal status, and comorbidities. Further research is needed to validate and refine diagnostic algorithms, optimizing the clinical significance of tumor markers in ovarian cancer management. In conclusion, tumor markers such as CA-125, CA15-3, CA 19-9, HE4, and hCG provide valuable insights into ovarian cancer diagnosis, monitoring, and prognosis, with the potential to enhance early detection.

Ovarian cancer is the third most common gynecologic cancer worldwide and has the highest mortality rate among gynecologic cancers. Identifying timely and effective biomarkers at different stages of the disease is the key to improve the prognosis of ovarian cancer patients. Circulating tumor DNA (ctDNA) is a fragment of free DNA produced by tumor cells in the blood. Current techniques for detecting ctDNA mainly include quantitative polymerase chain reaction (PCR), targeted next-generation sequencing (NGS), and non-targeted NGS (such as whole exon or whole genome sequencing). As a non-invasive liquid biopsy technique, ctDNA has a good application prospect in the ovarian cancer diagnosis, monitoring of treatment response and efficacy evaluation, detection of reverse mutation and related medication guidance, and prognosis evaluation. This article reviews the advances in application of ctDNA in ovarian cancer.

Epigenetic alterations are a near-universal feature of human malignancy and have been detected in malignant cells as well as in easily accessible specimens such as blood and urine. These findings offer promising applications in cancer detection, subtyping, and treatment monitoring. However, much of the current evidence is based on findings in retrospective studies and may reflect epigenetic patterns that have already been influenced by the onset of the disease.

Studying breast cancer, we established genome-scale DNA methylation profiles of prospectively collected buffy coat samples (n = 702) from a case-control study nested within the EPIC-Heidelberg cohort using reduced representation bisulphite sequencing (RRBS).

We observed cancer-specific DNA methylation events in buffy coat samples. Increased DNA methylation in genomic regions associated with SURF6 and REXO1/CTB31O20.3 was linked to the length of time to diagnosis in the prospectively collected buffy coat DNA from individuals who subsequently developed breast cancer. Using machine learning methods, we piloted a DNA methylation-based classifier that predicted case-control status in a held-out validation set with 76.5% accuracy, in some cases up to 15 years before clinical diagnosis of the disease.

Taken together, our findings suggest a model of gradual accumulation of cancer-associated DNA methylation patterns in peripheral blood, which may be detected long before clinical manifestation of cancer. Such changes may provide useful markers for risk stratification and, ultimately, personalized cancer prevention.

Ovarian cancer (OC) is an aggressive disease, primarily diagnosed in late stages with only 20% of patients surviving more than 5 years. Liquid biopsy markers have great potential to improve current diagnostic and prognostic methods. Here, we compared miRNAs and DNA methylation in matched plasma, whole blood and tissues as a surrogate marker for OC. We found that while both cfDNA and cf-miRNAs levels were upregulated in OC compared to patients with benign lesions or healthy controls, only cf-miRNA levels were an independent prognosticator of survival. Following on our previous work, we found members of the miR-200 family, miR-200c and miR-141 to be upregulated in both plasma and matched tissues of OC patients which correlated with adverse clinical features. We could also show that the upregulation of miR-200c and -141 correlated with promoter DNA hypomethylation in tissues, but not in plasma or matched whole blood samples. As cf-miRNAs are more easily obtained and very stable in blood, we conclude that they might serve as a more appropriate surrogate liquid biopsy marker than cfDNA for OC.

Terahertz (THz) radiation can affect the degree of DNA methylation, the spectral characteristics of which exist in the terahertz region. DNA methylation is an epigenetic modification in which a methyl (CH₃) group is attached to cytosine, a nucleobase in human DNA. Appropriately controlled DNA methylation leads to proper regulation of gene expression. However, abnormal gene expression that departs from controlled genetic transcription through aberrant DNA methylation may occur in cancer or other diseases. In this study, we demonstrate the modification of gene expression in cells by THz demethylation using resonant THz radiation. Using an enzyme-linked immunosorbent assay, we observed changes in the degree of global DNA methylation in the SK-MEL-3 melanoma cell line under irradiation with 1.6-THz radiation with limited spectral bandwidth. Resonant THz radiation demethylated living melanoma cells by 19%, with no significant occurrence of apurinic/apyrimidinic sites, and the demethylation ratio was linearly proportional to the power of THz radiation. THz demethylation downregulates FOS, JUN, and CXCL8 genes, which are involved in cancer and apoptosis pathways. Our results show that THz demethylation has the potential to be a gene expression modifier with promising applications in cancer treatment.

Noninvasive detection of aberrant DNA methylation could provide invaluable biomarkers for earlier detection of triple-negative breast cancer (TNBC) which could help clinicians with easier and more efficient treatment options. We evaluated genome-wide DNA methylation data derived from TNBC and normal breast tissues, peripheral blood of TNBC cases and controls and reference samples of sorted blood and mammary cells. Differentially methylated regions (DMRs) between TNBC and normal breast tissues were stringently selected, verified and externally validated. A machine-learning algorithm was applied to select the top DMRs, which then were evaluated on plasma-derived circulating cell-free DNA (cfDNA) samples of TNBC patients and healthy controls. We identified 23 DMRs accounting for the methylation profile of blood cells and reference mammary cells and then selected six top DMRs for cfDNA analysis. We quantified un-/methylated copies of these DMRs by droplet digital PCR analysis in a plasma test set from TNBC patients and healthy controls and confirmed our findings obtained on tissues. Differential cfDNA methylation was confirmed in an independent validation set of plasma samples. A methylation score combining signatures of the top three DMRs overlapping with the SPAG6, LINC10606 and TBCD/ZNF750 genes had the best capability to discriminate TNBC patients from controls (AUC = 0.78 in the test set and AUC = 0.74 in validation set). Our findings demonstrate the usefulness of cfDNA-based methylation signatures as noninvasive liquid biopsy markers for the diagnosis of TNBC.

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.

Epithelial ovarian cancer (EOC) is the deadliest gynaecological malignancy and the eighth most prevalent cancer in women, with an abysmal mortality rate of two million worldwide. The existence of multiple overlapping symptoms with other gastrointestinal, genitourinary, and gynaecological maladies often leads to late-stage diagnosis and extensive extra-ovarian metastasis. Due to the absence of any clear early-stage symptoms, current tools only aid in the diagnosis of advanced-stage patients, wherein the 5-year survival plummets further to less than 30%. Therefore, there is a dire need for the identification of novel approaches that not only allow early diagnosis of the disease but also have a greater prognostic value. Toward this, biomarkers provide a gamut of powerful and dynamic tools to allow the identification of a spectrum of different malignancies. Both serum cancer antigen 125 (CA-125) and human epididymis 4 (HE4) are currently being used in clinics not only for EOC but also peritoneal and GI tract cancers. Screening of multiple biomarkers is gradually emerging as a beneficial strategy for early-stage diagnosis, proving instrumental in administration of first-line chemotherapy. These novel biomarkers seem to exhibit an enhanced potential as a diagnostic tool. This review summarizes existing knowledge of the ever-growing field of biomarker identification along with potential future ones, especially for ovarian cancer.

Ovarian cancer is a leading cause of female mortality. Epigenetic changes occur in early stages of carcinogenesis and represent a marker for cancer diagnosis. Protocadherin 17 (PCDH17) is a tumor suppressor gene involved in cell adhesion and apoptosis. The methylation of PCDH17 gene promoter has been described in several cancers including ovarian cancer. The aim of the study was to compare the methylation status of PCDH17 gene promoter between females diagnosed with epithelial ovarian cancer and a control group composed of normal and benign ovarian lesions.

Fifty female subjects were included in our study (25 ovarian cancer patients and 25 controls). DNA was extracted from Formalin-Fixed Paraffin-Embedded (FFPE) tissues of the subjects. Methylation levels for six CpG sites in the PCDH17 gene promoter were assessed by pyrosequencing.

The methylation levels at five out of six sites were significantly higher in females with epithelial ovarian cancer compared to the control group. Moreover, the same applies for the mean methylation level with p value 0.018.

Methylation of PCDH17 gene promoter plays a role in ovarian carcinogenesis and can be used for diagnosis and early detection.

Ovarian cancer is the deadliest gynecological cancer. 70% of the cases are diagnosed at late stages with already developed metastases due to the absence of easily noticeable symptoms. Early-stage ovarian cancer has a good prognosis with a 5-year survival rate reaching 95%, hence the identification of effective biomarkers for early diagnosis is important. Advances in liquid biopsy-based methods can have a significant impact not just on the development of an efficient screening strategy, but also in clinical decision-making with additional molecular profiling and genetic alterations linked to therapy resistance. Despite the well-known advantages of liquid biopsy, there are still challenges that need to be addressed before its routine use in clinical practice. Various liquid biopsy-based biomarkers have been investigated in ovarian cancer; however, in this review, we are concentrating on the current use of cell-free DNA (cfDNA) and circulating tumor cells (CTCs) in disease management, focusing on their emerging importance in clinical practice. We also discuss the technical aspects of these workflows. The analysis of cfDNA is often chosen for the detection of mutations, copy number aberrations, and DNA methylation changes, whereas CTC analysis provides a unique opportunity to study whole cells, thus allowing DNA, RNA, and protein-based molecular profiling as well as in vivo studies. Combined solutions which merge the strengths of cfDNA and CTC approaches should be developed to maximize the potential of liquid biopsy technology.

High-grade serous ovarian carcinoma (HGSOC) represents the most common form of epithelial ovarian carcinoma. The absence of specific symptoms leads to late-stage diagnosis, making HGSOC one of the gynecological cancers with the worst prognosis. The cellular origin of HGSOC and the role of reproductive hormones, genetic traits (such as alterations in P53 and DNA-repair mechanisms), chromosomal instability, or dysregulation of crucial signaling pathways have been considered when evaluating prognosis and response to therapy in HGSOC patients. However, the detection of HGSOC is still based on traditional methods such as carbohydrate antigen 125 (CA125) detection and ultrasound, and the combined use of these methods has yet to support significant reductions in overall mortality rates. The current paradigm for HGSOC management has moved towards early diagnosis via the non-invasive detection of molecular markers through liquid biopsies. This review presents an integrated view of the relevant cellular and molecular aspects involved in the etiopathogenesis of HGSOC and brings together studies that consider new horizons for the possible early detection of this gynecological cancer.

Ovarian cancer is a fatal gynecological cancer due to the lack of effective screening strategies at early stage. This study explored the utility of DNA methylation profiling of blood samples for the detection of ovarian cancer.

Targeted bisulfite sequencing was performed on tissue (n = 152) and blood samples (n = 373) obtained from healthy women, women with benign ovarian tumors, or malignant epithelial ovarian tumors. Based on the tissue-derived differentially-methylated regions, a supervised machine learning algorithm was implemented and cross-validated using the blood-derived DNA methylation profiles of the training cohort (n = 178) to predict and classify each blood sample as malignant or non-malignant. The model was further evaluated using an independent test cohort (n = 184).

Comparison of the DNA methylation profiles of normal/benign and malignant tumor samples identified 1272 differentially-methylated regions, with 49.4% hypermethylated regions and 50.6% hypomethylated regions. Five-fold cross-validation of the model using the training dataset yielded an area under the curve of 0.94. Using the test dataset, the model accurately predicted non-malignancy in 96.2% of healthy women (n = 53) and 93.5% of women with benign tumors (n = 46). For patients with malignant tumors, the model accurately predicted malignancy in 44.4% of stage I-II (n = 9), 86.4% of stage III (n = 59), 100.0% of stage IV tumors (n = 6), and 81.8% of tumors with unknown stage (n = 11). Overall, the model yielded a predictive accuracy of 89.5%.

Our study demonstrates the potential clinical application of blood-based DNA methylation profiling for the detection of ovarian cancer.