Objective: DNA Methylation of the tumour suppressor gene leading to gene silencing plays an important role in thyroid tumour development. The purpose was to determine the DNA methylation status of phosphatase and tensin homolog (PTEN) and death-associated protein kinase (DAPK) in patients with thyroid nodules and to explore whether they can be used as molecular diagnostic tools to differentiate benign and malignant thyroid nodules.
Design, Patients And Measurements: Thyroid tissue and blood samples were obtained from normal healthy individuals (controls) and patients suffering from clinically diagnosed thyroid nodular disease [papillary thyroid carcinoma (PTC), adenoma and nodular goitre]. DNA methylation level, mRNA expression and protein expression of PTEN and DAPK in the thyroid tissues and peripheral blood were detected using methylation-specific PCR, semi-quantitative reverse transcription PCR and Western blot, respectively. Diagnostic sensitivity, specific and accuracy of detection were evaluated between blood and thyroid tissue.
Results: There was a significant increase in the level of DNA methylation of PTEN and DAPK in PTC (P < .05) compared with controls and other types of thyroid nodules. Levels of the mRNA of both PTEN and DAPK were lower in PTC in both peripheral blood and tissue samples compared with controls, while there was concomitant decrease of both PTEN and DAPK protein expression in PTC tissues (P < .05). There was no significant difference in diagnostic specificity, sensitivity and accuracy between blood sample and thyroid tissues.
Conclusions: Hypermethylated status of both PTEN and DAPK in peripheral blood and tissue samples can be useful biomarkers for clinical diagnosis and, distinguishing of benign and malignant thyroid nodules.
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http://dx.doi.org/10.1111/cen.14192 | DOI Listing |
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The advancement of epigenetics has highlighted DNA methylation as an intermediate-omic influencing gene regulation and phenotypic expression. With emerging technologies enabling the large-scale and affordable capture of methylation data, there is growing interest in integrating this information into genetic evaluation models for animal breeding. This study used methylome information from six dairy cows to simulate the methylation profile of 13,183 genotyped animals.
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