Abstract
Most ovarian cancers, despite improvement in management of cancer, are still diagnosed at an advanced stage. Early detection plays an essential role in reducing ovarian cancer mortality and, therefore, is critically needed. Liquid biopsies-based approaches hold significant promise for cancer detection. The present study investigates a panel of epigenetic biomarkers for the detection of epithelial ovarian cancer. A qPCR assay has been developed based on the assessment of DNA methylation markers in circulating cell-free DNA as a minimally invasive tool. Herein, the promoter methylation of seven ovarian cancer-specific genes (RASSF1A, DAPK1, SOX1, HOXA9, HIC1, SPARC, and SFRP1) was analyzed quantitatively in 120 tissue samples by MethyLight assay. The best-performing genes were further evaluated for their methylation status in 70 matched serum cell-free DNA of cancerous and non-cancerous samples. Additionally, DNA methylation patterns of these best-performing genes were validated by clonal bisulfite sequencing. The ROC (Receiver-operator characteristic) curves were constructed to evaluate the diagnostic performances of both individual and combined gene panels. The seven candidate genes displayed a methylation frequency of 61.0–88.0% in tissue samples. The promoter methylation frequencies for all the seven candidate genes were significantly higher in cancer samples than in normal matched controls. In tissue samples, the multiplex MethyLight assay for HOXA9, HIC1, and SOX1 were the best performing gene panels in terms of sensitivity and specificity. The three best-performing genes exhibited individual frequencies of 53.0–71.0% in serum CFDNA, and the multiplex assay for these genes were identified to discriminate serum from cancer patients and healthy individuals (area under the curve: HOXA9+HIC1 = 0.95, HIC1+SOX1 = 0.93 and HOXA9+SOX1 = 0.85). The results of MethyLight showed high concordance with clonal bisulfite sequencing results. Individual genes and combined panel exhibited better discriminatory efficiencies to identify ovarian cancer at various stages of disease when analyzed in tissue and serum cell-free DNA. We report a qPCR-based non-invasive epigenetic biomarker assay with high sensitivity and specificity for OC screening. Our findings also reveal the potential utility of methylation-based detection of circulating cell-free tumor DNA in the clinical management of ovarian cancer.
Highlights
Ovarian cancer (OC) is the fifth most incident and deadly gynecological malignancy affecting women worldwide, mainly under the age of 55–74
While in India, the incidence rate for OC is 5.7 per 100,000 women, affecting 5.4% of all female cancer patients. This lethal disease accounts for 2.5% of all female associated malignancies but 5% of cancer death in women due to lack of signs and symptoms at the early stage of the disease, lower survival rates mainly driven by advanced stage diagnosis, high recurrence rate, and limited success with existing early diagnosis methods (Siegel et al, 2015)
To examine the linearity and accuracy of the qMSP assay, standard curves for COL2A1, DAPK1, SOX1, RASSF1A, HOXA9, SFRP1, SPARC, and HIC1 were generated with the fully-methylated positive control (Supplementary File 1: Figure S1)
Summary
Ovarian cancer (OC) is the fifth most incident and deadly gynecological malignancy affecting women worldwide, mainly under the age of 55–74 It encompasses heterogeneity at the molecular, clinical, and histopathological level and exhibits the worst prognosis and highest mortality figures for cancer death in women. While in India, the incidence rate for OC is 5.7 per 100,000 women, affecting 5.4% of all female cancer patients Overall, this lethal disease accounts for 2.5% of all female associated malignancies but 5% of cancer death in women due to lack of signs and symptoms at the early stage of the disease, lower survival rates mainly driven by advanced stage diagnosis, high recurrence rate, and limited success with existing early diagnosis methods (Siegel et al, 2015). It is crucial to identify the most effective and reliable molecular biomarkers involved in ovarian cancer tumorigenesis at the genetic and epigenetic level, which could further aid in the early detection of OC
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