Methylation and ovarian cancer: Can DNA methylation be of diagnostic use?

Comprehensive DNA methylation profiling by MeDIP-NGS identifies potential genes and pathways for epithelial ovarian cancer

Ovarian cancer, among all gynecologic malignancies, exhibits the highest incidence and mortality rate, primarily because it is often presents with non-specific or no symptoms during its early stages. For the advancement of Ovarian Cancer Diagnosis, it is crucial to identify the potential molecular signatures that could significantly differentiate between healthy and ovarian cancerous tissues and can be used further as a diagnostic biomarker for detecting ovarian cancer. In this study, we investigated the genome-wide methylation patterns in ovarian cancer patients using Methylated DNA Immunoprecipitation (MeDIP-Seq) followed by NGS. Identified differentially methylated regions (DMRs) were further validated by targeted bisulfite sequencing for CpG site-specific methylation profiles. Furthermore, expression validation of six genes by Quantitative Reverse Transcriptase-PCR was also performed. Out of total 120 differentially methylated genes (DMGs), 68 genes were hypermethylated, and 52 were hypomethylated in their promoter region. After analysis, we identified the top 6 hub genes, namely POLR3B, PLXND1, GIGYF2, STK4, BMP2 and CRKL. Interestingly we observed Non-CpG site methylation in the case of POLR3B and CRKL which was statistically significant in discriminating ovarian cancer samples from normal controls. The most significant pathways identified were focal adhesion, the MAPK signaling pathway, and the Ras signaling pathway. Expression analysis of hypermethylated genes was correlated with the downregulation of the genes. POLR3B and GIGYF2 turned out to be the novel genes associated with the carcinogenesis of EOC. Our study demonstrated that methylation profiling through MeDIP-sequencing has effectively identified six potential hub genes and pathways that might exacerbate our understanding of underlying molecular mechanisms of ovarian carcinogenesis.

Precision gynecologic oncology: circulating cell free DNA epigenomic analysis, artificial intelligence and the accurate detection of ovarian cancer

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.

Prognostic Significance of SLFN11 Methylation in Plasma Cell-Free DNA in Advanced High-Grade Serous Ovarian Cancer

Background: Epigenetic alterations in ctDNA are highly promising as a source of novel potential liquid biopsy biomarkers and comprise a very promising liquid biopsy approach in ovarian cancer, for early diagnosis, prognosis and response to treatment. Methods: In the present study, we examined the methylation status of six gene promoters (BRCA1, CST6, MGMT, RASSF10, SLFN11 and USP44) in high-grade serous ovarian cancer (HGSOC). We evaluated the prognostic significance of DNA methylation of these six gene promoters in primary tumors (FFPEs) and plasma cfDNA samples from patients with early, advanced and metastatic HGSOC. Results: We report for the first time that the DNA methylation of SLFN11 in plasma cfDNA was significantly correlated with worse PFS (p = 0.045) in advanced stage HGSOC. Conclusions: Our results strongly indicate that SLFN11 epigenetic inactivation could be a predictor of resistance to platinum drugs in ovarian cancer. Our results should be further validated in studies based on a larger cohort of patients, in order to further explore whether the DNA methylation of SLFN11 promoter could serve as a potential prognostic DNA methylation biomarker and a predictor of resistance to platinum-based chemotherapy in ovarian cancer.

Epigenetic Silencing of miR-33b Promotes Peritoneal Metastases of Ovarian Cancer by Modulating the TAK1/FASN/CPT1A/NF-κB Axis

Peritoneal metastases are frequently found in high-grade serous carcinoma (HGSOC) patients and are commonly associated with a poor prognosis. The tumor microenvironment (TME) is a complex milieu that plays a critical role in epigenetic alterations driving tumor development and metastatic progression. However, the impact of epigenetic alterations on metastatic ovarian cancer cells in the harsh peritoneal microenvironment remains incompletely understood. Here, we identified that miR-33b is frequently silenced by promoter hypermethylation in HGSOC cells derived from metastatic omental tumor tissues. Enforced expression of miR-33b abrogates the oncogenic properties of ovarian cancer cells cocultured in omental conditioned medium (OCM), which mimics the ascites microenvironment, and in vivo tumor growth. Of note, restoration of miR-33b inhibited OCM-upregulated de novo lipogenesis and fatty acid β-oxidation in ovarian cancer cells, indicating that miR-33b may play a novel tumor suppressor role in the lipid-mediated oncogenic properties of metastatic ovarian cancer cells found in the omentum. Mechanistic studies demonstrated that miR-33b directly targets transforming growth factor beta-activated kinase 1 (TAK1), thereby suppressing the activities of fatty acid synthase (FASN) and carnitine palmitoyltransferase 1A (CPT1A) in modulating lipid metabolic activities and simultaneously inhibiting the phosphorylation of NF-κB signaling to govern the oncogenic behaviors of ovarian cancer cells. Thus, our data suggest that a lipid-rich microenvironment may cause epigenetic silencing of miR-33b, which negatively modulates ovarian cancer peritoneal metastases, at least in part, by suppressing TAK1/FASN/CPT1A/NF-κB signaling.

Identification of a four-gene methylation biomarker panel in high-grade serous ovarian carcinoma

Background The lack of effective biomarkers for the screening and early detection of ovarian cancer (OC) is one of the most pressing problems in oncogynecology. Because epigenetic alterations occur early in the cancer development, they provide great potential to serve as such biomarkers. In our study, we investigated a potential of a four-gene methylation panel (including CDH13, HNF1B, PCDH17 and GATA4 genes) for the early detection of high-grade serous ovarian carcinoma (HGSOC). Methods For methylation detection we used methylation sensitive high-resolution melting analysis and real-time methylation specific analysis. We also investigated the relation between gene hypermethylation and gene relative expression using the 2-ΔΔCt method. Results The sensitivity of the examined panel reached 88.5%. We were able to detect methylation in 85.7% (12/14) of early stage tumors and in 89.4% (42/47) of late stage tumors. The total efficiency of the panel was 94.4% and negative predictive value reached 90.0%. The specificity and positive predictive value achieved 100% rates. Our results showed lower gene expression in the tumor samples in comparison to control samples. The more pronounced downregulation was measured in the group of samples with detected methylation. Conclusions In our study we designed the four-gene panel for HGSOC detection in ovarian tissue with 100% specificity and sensitivity of 88.5%. The next challenge is translation of the findings to the less invasive source for biomarker examination, such as plasma. Our results indicate that combination of examined genes deserve consideration for further testing in clinical molecular diagnosis of HGSOC.

Electrochemical Detection of Global DNA Methylation Using Biologically Assembled Polymer Beads

DNA methylation is a cell-type-specific epigenetic marker that is essential for transcriptional regulation, silencing of repetitive DNA and genomic imprinting. It is also responsible for the pathogenesis of many diseases, including cancers. Herein, we present a simple approach for quantifying global DNA methylation in ovarian cancer patient plasma samples based on a new class of biopolymer nanobeads. Our approach utilises the immune capture of target DNA and electrochemical quantification of global DNA methylation level within the targets in a three-step strategy that involves (i) initial preparation of target single-stranded DNA (ss-DNA) from the plasma of the patients' samples, (ii) direct adsorption of polymer nanobeads on the surface of a bare screen-printed gold electrode (SPE-Au) followed by the immobilisation of 5-methylcytosine (5mC)-horseradish peroxidase (HRP) antibody, and (iii) immune capture of target ss-DNA onto the electrode-bound PHB/5mC-HRP antibody conjugates and their subsequent qualification using the hydrogen peroxide/horseradish peroxidase/hydroquinone (H2O2/HRP/HQ) redox cycling system. In the presence of methylated DNA, the enzymatically produced (in situ) metabolites, i.e., benzoquinone (BQ), binds irreversibly to cellular DNA resulting in the unstable formation of DNA adducts and induced oxidative DNA strand breakage. These events reduce the available BQ in the system to support the redox cycling process and sequel DNA saturation on the platform, subsequently causing high Coulombic repulsion between BQ and negatively charged nucleotide strands. Thus, the increase in methylation levels on the electrode surface is inversely proportional to the current response. The method could successfully detect as low as 5% methylation level. In addition, the assay showed good reproducibility (% RSD ≤ 5%) and specificity by analysing various levels of methylation in cell lines and plasma DNA samples from patients with ovarian cancer. We envision that our bioengineered polymer nanobeads with high surface modification versatility could be a useful alternative platform for the electrochemical detection of varying molecular biomarkers.

Long reads capture simultaneous enhancer-promoter methylation status for cell-type deconvolution

MOTIVATION

While promoter methylation is associated with reinforcing fundamental tissue identities, the methylation status of distant enhancers was shown by genome-wide association studies to be a powerful determinant of cell-state and cancer. With recent availability of long reads that report on the methylation status of enhancer-promoter pairs on the same molecule, we hypothesized that probing these pairs on the single-molecule level may serve the basis for detection of rare cancerous transformations in a given cell population. We explore various analysis approaches for deconvolving cell-type mixtures based on their genome-wide enhancer-promoter methylation profiles.

RESULTS

To evaluate our hypothesis we examine long-read optical methylome data for the GM12878 cell line and myoblast cell lines from two donors. We identified over 100 000 enhancer-promoter pairs that co-exist on at least 30 individual DNA molecules. We developed a detailed methodology for mixture deconvolution and applied it to estimate the proportional cell compositions in synthetic mixtures. Analysis of promoter methylation, as well as enhancer-promoter pairwise methylation, resulted in very accurate estimates. In addition, we show that pairwise methylation analysis can be generalized from deconvolving different cell types to subtle scenarios where one wishes to resolve different cell populations of the same cell-type.

AVAILABILITY AND IMPLEMENTATION

The code used in this work to analyze single-molecule Bionano Genomics optical maps is available via the GitHub repository https://github.com/ebensteinLab/Single_molecule_methylation_in_EP.

Differential expression analysis in ovarian cancer: A functional genomics and systems biology approach

BACKGROUND

Ovarian cancer is one of the rarest lethal oncologic diseases that have hardly any specific biomarkers. The availability of high-throughput genomic data and advancement in bioinformatics tools allow us to predict gene biomarkers and apply systems biology approaches to get better diagnosis, and prognosis of the disease with a tentative drug that may be repurposed.

OBJECTIVE

To perform genome-wide association studies using microarray gene expression of ovarian cancer and identify gene biomarkers, construction and analyze networks, perform survival analysis, and drug interaction studies for better diagnosis, prognosis, and treatment of ovarian cancer.

METHOD

The gene expression profiles of both healthy and serous ovarian cancer epithelial samples were considered. We applied a series of bioinformatics methods and tools, including fold-change statistics for differential expression analysis, DisGeNET and NCBI-Gene databases for gene-disease association mapping, DAVID 6.8 for GO enrichment analysis, GeneMANIA for network construction, Cytoscape 3.8 with its plugins for network visualization, analysis, and module detection, the UALCAN for patient survival analysis, and PubChem, DrugBank and DGIdb for gene-drug interaction.

RESULTS

We identified 8 seed genes that were subjected for drug-gene interaction studies. Because of over-expression in all the four stages of ovarian cancer, we discern that genes HMGA1 and PSAT1 are potential therapeutic biomarkers for its diagnosis at an early stage (stage I). Our analysis suggests that there are 11 drugs common in the seed genes. However, hypermethylated seed genes HMGA1 and PSAT1 showcased a good interaction affinity with drugs cisplatin, cyclosporin, bisphenol A, progesterone, and sunitinib, and are crucial in the proliferation of ovarian cancer.

CONCLUSION

Our study reveals that HMGA1 and PSAT1 can be deployed for initial screening of ovarian cancer and drugs cisplatin, bisphenol A, cyclosporin, progesterone, and sunitinib are effective in curbing the epigenetic alteration.

LAMA3 DNA methylation and transcriptome changes associated with chemotherapy resistance in ovarian cancer

Objective

LAMA3 is a widely studied methylated gene in multiple tumors, but the relationship between chemotherapy resistance in ovarian cancer is unclear. In this study, LAMA3 methylation was predicted by bioinformatics, and the ability of LAMA3 methylation to predict the chemotherapy resistance and prognosis of ovarian cancer was confirmed in experiments.

Methods

Multiple databases have performed the bioinformatics analysis of methylation and transcription factor binding site (TFBS) on the promoter region of LAMA3 gene. Pyrosequencing detected the methylation of LAMA3. QRT-PCR and immunohistochemistry detected the expression of LAMA3. Real Time Cell Analyzer (RTCA) detects changes in cell proliferation, migration and invasion ability. Flow cytometry was used to detect apoptosis.

Results

CPG islands of 176 bp, 134 bp, 125 bp and 531 bp were predicted in the promoter region of LAMA3 gene. The 4 prediction results are basically overlapped. 7 transcription factor binding sites were predicted, and the one with the highest score was on the predicted CpG island located in the proximal promoter region. LAMA3 hypermethylation and low expression are both associated with chemotherapy resistance and poor prognosis in ovarian cancer. LAMA3 methylation was negatively correlated with expression. After upregulation of LAMA3, the proliferation ability of chemoresistant ovarian cancer cell decreased, while the ability of apoptosis, invasion and migration increased.

Conclusion

LAMA3 hypermethylation is associated with chemotherapy resistance and poor prognosis. As a typical CpG island gene, LAMA3(cg20937934) and LAMA3(cg13270625) hypermethylation is negatively correlated with low expression. LAMA3 promotes the invasion, migration and apoptosis of SKOV3DDP. In the future, the mechanism of LAMA3 methylation in ovarian cancer will need to be further studied.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13048-021-00807-y.

Comprehensive analysis of regulation of DNA methyltransferase isoforms in human breast tumors

Significant reprogramming of epigenome is widely described during pathogenesis of breast cancer. Transformation of normal cell to hyperplastic cell and to neoplastic phenotype is associated with aberrant DNA (de)methylation, which, through promoter and enhancer methylation changes, activates oncogenes and silence tumor suppressor genes in variety of tumors including breast. DNA methylation, one of the major epigenetic mechanisms is catalyzed by evolutionarily conserved isoforms namely, DNMT1, DNMT3A and DNMT3B in humans. Over the years, studies have demonstrated intricate and complex regulation of DNMT isoforms at transcriptional, translational and post-translational levels. The recent findings of allosteric regulation of DNMT isoforms and regulation by other interacting chromatin modifying proteins emphasizes functional integrity and their contribution for the development of breast cancer and progression. DNMT isoforms are regulated by several intrinsic and extrinsic parameters. In the present review, we have extensively performed bioinformatics analysis of expression of DNMT isoforms along with their transcriptional and post-transcriptional regulators such as transcription factors, interacting proteins, hormones, cytokines and dietary elements along with their significance during pathogenesis of breast tumors. Our review manuscript provides a comprehensive understanding of key factors regulating DNMT isoforms in breast tumor pathology and documents unsolved issues.

Development of a novel transcription factors-related prognostic signature for serous ovarian cancer

Growing evidence suggest that transcription factors (TFs) play vital roles in serous ovarian cancer (SOC). In the present study, TFs mRNA expression profiles of 564 SOC subjects in the TCGA database, and 70 SOC subjects in the GEO database were screened. A 17-TFs related prognostic signature was constructed using lasso cox regression and validated in the TCGA and GEO cohorts. Consensus clustering analysis was applied to establish a cluster model. The 17-TFs related prognostic signature, risk score and cluster models were effective at accurately distinguishing the overall survival of SOC. Analysis of genomic alterations were used to elaborate on the association between the 17-TFs related prognostic signature and genomic aberrations. The GSEA assay results suggested that there was a significant difference in the inflammatory and immune response pathways between the high-risk and low-risk score groups. The potential immune infiltration, immunotherapy, and chemotherapy responses were analyzed due to the significant difference in the regulation of lymphocyte migration and T cell-mediated cytotoxicity between the two groups. The results indicated that patients with low-risk score were more likely to respond anti-PD-1, etoposide, paclitaxel, and veliparib but not to gemcitabine, doxorubicin, docetaxel, and cisplatin. Also, the prognostic nomogram model revealed that the risk score was a good prognostic indicator for SOC patients. In conclusion, we explored the prognostic values of TFs in SOC and developed a 17-TFs related prognostic signature to predict the survival of SOC patients.

Epigenetic Regulation of Claudin-1 in the Development of Ovarian Cancer Recurrence and Drug Resistance

Over 21,000 women are diagnosed with ovarian cancer (OC) in the United States each year and over half that number succumb to this disease annually, often due to recurrent disease. A deeper understanding of the molecular events associated with recurrent disease is needed to identify potential targets. Using genome-scale DNA methylation and gene expression data for 16 matched primary-recurrent advanced stage serous epithelial OCs, we discovered that Claudin-1 (CLDN1), a tight junction protein, shows a stronger correlation between expression and methylation in recurrent versus primary OC at multiple CpG sites (R= –0.47 to −0.64 versus R= -0.32 to −0.57, respectively). An independent dataset showed that this correlation is stronger in tumors from short-term (<3y) survivors than in tumors from long-term (>7y) survivors (R= −0.41 to −0.46 versus R= 0.06 to −0.19, respectively). The presence of this inverse correlation in short-term survivors and recurrent tumors suggests an important role for this relationship and potential predictive value for disease prognosis. CLDN1 expression increased following pharmacologic inhibition of DNA methyltransferase activity (p< 0.001), thus validating the role of methylation in CLDN1 gene inhibition. CLDN1 knockdown enhanced chemosensitivity and suppressed cell proliferation, migration, and wound healing (p< 0.05). Stable CLDN1 knockdown in vivo resulted in reduced xenograft tumor growth but did not reach significance. Our results indicate that the relationship between CLDN1 methylation and expression plays an important role in OC aggressiveness and recurrence.

Circulating Cell-Free DNA Methylation Profiles in the Early Detection of Ovarian Cancer: A Scoping Review of the Literature

Simple Summary

There are limited non-invasive methods for detecting epithelial ovarian cancer despite early detection and treatment dramatically increasing survival. As alterations in serum or plasma cell-free (cf)DNA methylation occur early in cancer development, they are promising biomarkers for ovarian cancer. Our literature review includes 18 studies depicting a wide array of gene targets and techniques. The data suggest a good performance of these cfDNA methylation tests, with accuracies up to 91% in detecting ovarian cancer in serum or plasma.

Abstract

Epithelial ovarian cancer is the most lethal gynecologic malignancy and has few reliable non-invasive tests for early detection or diagnosis. Recent advances in genomic techniques have bolstered the utility of cell-free DNA (cfDNA) evaluation from peripheral blood as a viable cancer biomarker. For multiple reasons, comparing alterations in DNA methylation is particularly advantageous over other molecular assays. We performed a literature review for studies exploring cfDNA methylation in serum and plasma for the early diagnosis of ovarian cancer. The data suggest that serum/plasma cfDNA methylation tests have strong diagnostic accuracies for ovarian cancer (median 85%, range 40–91%). Moreover, there is improved diagnostic performance if multiple genes are used and if the assays are designed to compare detection of ovarian cancer with benign pelvic masses. We further highlight the vast array of possible gene targets and techniques, and a need to include more earlier-stage ovarian cancer samples in test development. Overall, we show the promise of cfDNA methylation analysis in the development of a viable diagnostic biomarker for ovarian cancer.

Cell lineage-specific methylome and genome alterations in gout

In this study, we examined data from 69 gout patients and 1,455 non-gout controls using a MethylationEPIC BeadChip assay and Illumina HiSeq platform to identify lineage-specific epigenetic alterations and associated genetic factors that contributed to gouty inflammation. Cell lineage-specific differentially methylated sites were identified using CellDMC after adjusting for sex, age, alcohol drinking, smoking status, and smoking history (total pack-years). Different cell lineages displayed distinct differential methylation. Ingenuity Pathway Analysis and NetworkAnalyst indicated that many differential methylated sites were associated with interleukin-1β expression in monocytes. On the UCSC Genome Browser and WashU Epigenome Browser, metabolic trait, cis-methylation quantitative trait loci, genetic, and functional annotation analyses identified nine methylation loci located in interleukin-1β-regulating genes (PRKCZ, CIDEC, VDAC1, CPT1A, BIRC2, BRCA1, STK11, and NLRP12) that were associated specifically with gouty inflammation. All nine sites mapped to active regulatory elements in monocytes. MoLoTool and ReMap analyses indicated that the nine methylation loci overlapped with binding sites of several transcription factors that regulated interleukin-1β production and gouty inflammation. Decreases in PRKCZ and STK11 methylation were also associated with higher numbers of first-degree relatives who also had gout. The gouty-inflammation specific methylome and genome alterations could potentially aid in the identification of novel therapeutic targets.

PPAR-α Modulators as Current and Potential Cancer Treatments

Cancer is one of the leading causes of mortality worldwide. PPAR modulators may hold great potential for the management of cancer patients. Indeed, PPARs are critical sensors and regulators of lipid, and they are able to promote eNOS activation, regulate immunity and inflammation response, and affect proliferation and differentiation of cancer cells. Cancer, a name given to a group of diseases, is characterized by multiple distinctive biological behaviors, including angiogenesis, abnormal cell proliferation, aerobic glycolysis, inflammation, etc. In the last decade, emerging evidence has shown that PPAR-α, a nuclear hormone receptor, can modulate carcinogenesis via exerting effects on one or several characteristic pathological behaviors of cancer. Therefore, the multi-functional PPAR modulators have substantial promise in various types of cancer therapies. This review aims to consolidate the functions of PPAR-α, as well as discuss the current and potential applications of PPAR-α agonists and antagonists in tackling cancer.

PARP Inhibitors: Clinical Relevance, Mechanisms of Action and Tumor Resistance

The Poly (ADP-ribose) polymerase (PARP) family has many essential functions in cellular processes, including the regulation of transcription, apoptosis and the DNA damage response. PARP1 possesses Poly (ADP-ribose) activity and when activated by DNA damage, adds branched PAR chains to facilitate the recruitment of other repair proteins to promote the repair of DNA single-strand breaks. PARP inhibitors (PARPi) were the first approved cancer drugs that specifically targeted the DNA damage response in BRCA1/2 mutated breast and ovarian cancers. Since then, there has been significant advances in our understanding of the mechanisms behind sensitization of tumors to PARP inhibitors and expansion of the use of PARPi to treat several other cancer types. Here, we review the recent advances in the proposed mechanisms of action of PARPi, biomarkers of the tumor response to PARPi, clinical advances in PARPi therapy, including the potential of combination therapies and mechanisms of tumor resistance.

Differential DNA methylation in high-grade serous ovarian cancer (HGSOC) is associated with tumor behavior

The epigenome offers an additional facet of cancer that can help categorize patients into those at risk of disease, recurrence, or treatment failure. We conducted a retrospective, nested, case-control study of advanced and recurrent high-grade serous ovarian cancer (HGSOC) patients in which we assessed epigenome-wide association using Illumina methylationEPIC arrays to characterize DNA methylation status and RNAseq to evaluate gene expression. Comparing HGSOC tumors with normal fallopian tube tissues we observe global hypomethylation but with skewing towards hypermethylation when interrogating gene promoters. In total, 5,852 gene interrogating probes revealed significantly different methylation. Within HGSOC, 57 probes highlighting 17 genes displayed significant differential DNA methylation between primary and recurrent disease. Between optimal vs suboptimal surgical outcomes 99 probes displayed significantly different methylation but only 29 genes showed an inverse correlation between methylation status and gene expression. Overall, differentially methylated genes point to several pathways including RAS as well as hippo signaling in normal vs primary HGSOC; valine, leucine, and isoleucine degradation and endocytosis in primary vs recurrent HGSOC; and pathways containing immune driver genes in optimal vs suboptimal surgical outcomes. Thus, differential DNA methylation identified numerous genes that could serve as potential biomarkers and/or therapeutic targets in HGSOC.

Aberrant Methylation Status of Tumour Suppressor Genes in Ovarian Cancer Tissue and Paired Plasma Samples

Ovarian cancer is a highly heterogeneous disease and its formation is affected by many epidemiological factors. It has typical lack of early signs and symptoms, and almost 70% of ovarian cancers are diagnosed in advanced stages. Robust, early and non-invasive ovarian cancer diagnosis will certainly be beneficial. Herein we analysed the regulatory sequence methylation profiles of the RASSF1, PTEN, CDH1 and PAX1 tumour suppressor genes by pyrosequencing in healthy, benign and malignant ovarian tissues, and corresponding plasma samples. We recorded statistically significant higher methylation levels (p < 0.05) in the CDH1 and PAX1 genes in malignant tissues than in controls (39.06 ± 18.78 versus 24.22 ± 6.93; 13.55 ± 10.65 versus 5.73 ± 2.19). Higher values in the CDH1 gene were also found in plasma samples (22.25 ± 14.13 versus 46.42 ± 20.91). A similar methylation pattern with positive correlation between plasma and benign lesions was noted in the CDH1 gene (r = 0.886, p = 0.019) and malignant lesions in the PAX1 gene (r = 0.771, p < 0.001). The random forest algorithm combining methylation indices of all four genes and age determined 0.932 AUC (area under the receiver operating characteristic (ROC) curve) prediction power in the model classifying malignant lesions and controls. Our study results indicate the effects of methylation changes in ovarian cancer development and suggest that the CDH1 gene is a potential candidate for non-invasive diagnosis of ovarian cancer.