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

Abstract

<jats:title>Abstract</jats:title><jats:sec id="j_cclm-2019-1319_s_999_w2aab3b8b1b1b7b1aab1c13b1Aa"><jats:title>Background</jats:title><jats:p>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 <jats:italic>CDH13</jats:italic>, <jats:italic>HNF1B</jats:italic>, <jats:italic>PCDH17</jats:italic> and <jats:italic>GATA4</jats:italic> genes) for the early detection of high-grade serous ovarian carcinoma (HGSOC).</jats:p></jats:sec><jats:sec id="j_cclm-2019-1319_s_998_w2aab3b8b1b1b7b1aab1c13b2Aa"><jats:title>Methods</jats:title><jats:p>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<jats:sup>−ΔΔCt</jats:sup> method.</jats:p></jats:sec><jats:sec id="j_cclm-2019-1319_s_997_w2aab3b8b1b1b7b1aab1c13b3Aa"><jats:title>Results</jats:title><jats:p>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.</jats:p></jats:sec><jats:sec id="j_cclm-2019-1319_s_996_w2aab3b8b1b1b7b1aab1c13b4Aa"><jats:title>Conclusions</jats:title><jats:p>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.</jats:p></jats:sec>

PCDH17 gene promoter methylation status in a cohort of Egyptian women with epithelial ovarian cancer

“…Furthermore, loss of PCDH17 was described to favor metastasis in hepatocellular carcinoma [ 17 ]. More research on PCDH17 in ovarian cancer is still needed to verify our findings as well as those of Baranova and her colleagues [ 20 , 21 ].…”

“…In addition, the same group recently investigated PCDH17 gene methylation (with other genes namely CDH13 , HNF1B and GATA4 ) in high grade serous ovarian carcinoma [ 21 ]. They reported a 100% specificity and an 88.5% sensitivity for the four-gene panel.…”

Tissue-Specific Methylation Biosignatures for Monitoring Diseases: An In Silico Approach

“…Several studies have shown that liquid biopsy biomaterials such as ccfDNA retain the tissue/cell- or disease-specific methylation profile, opening the way for biomarker discovery [ 17 , 71 ]. Gene methylation panels examined in liquid biopsy are implemented for the clinical management of some diseases, limited so far to a few cancer types [ 82 , 83 , 84 ]. To this end, building new highly performing panels that can be applicable to ccfDNA is of utmost importance.…”

DNA methylation-based profiling reveals distinct clusters with survival heterogeneity in high-grade serous ovarian cancer

“…It is universally acknowledged that DNA methylation alterations are potential molecular markers for cancer progression [30][31][32][33]. Several studies of ovarian cancer have reported that DNA methylation signatures play a pivotal role in the molecular classification, survival status, and adjuvant chemotherapy response [34][35][36][37][38][39][40][41]. Despite increasing knowledge of the most common type of ovarian cancer, HGSOC, there are no effective methylation-based molecular signatures [42].…”