Identification of a four-gene methylation biomarker panel in high-grade serous ovarian carcinoma.
Clin Chem Lab Med
; 58(8): 1332-1340, 2020 07 28.
Article
em En
| MEDLINE
| ID: mdl-32145055
ABSTRACT
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.
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Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Diagnostic_studies
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Prognostic_studies
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Screening_studies
Limite:
Female
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Humans
Idioma:
En
Ano de publicação:
2020
Tipo de documento:
Article