Abstract
Background: The relationship between epigenetic abnormalities and tumorigenesi has been investigated in the past decade and made major advances, particularly the abnormal expression of small RNAs, DNA methylation, and histone modification in cancer. In many tumor-related studies, the regulatory changes in DNA methylation during cancer development and the development of resistance to anticancer drugs have show that DNA methylation can be used as a biomarker for cancer diagnosis and concomitant diagnosis, but there is a lack of clinically useful biomarkers associated with hepatic carcinoma. Using high-throughput sequencing technology, appropriate testing and validation can be carried out in large samples. The relationship between DNA methylation and tumor development can be explored, contributing to clinical diagnosis and personalized treatment of hepatic carcinoma. Methods: In this study, we implemented and evaluated the effectiveness of high-throughput sequencing for DNA methylation analysis in hepatic carcinoma. For the relationship between DNA methylation and gene expression, Pearson correlation analysis was used to evaluate the correlation. Twenty-five isolated genomic regions were amplified by PCR using bisulfite-transformed liver cancer tissue (Ca) and paracancer tissue (T) as template DNA. PCR final product sequence information was obtained by sequence analysis using Illumina Hiseq/Miseq platform. Results: The average depth of coverage across all amplicons was 30,548 for T and 29,346 for Ca, with a maximum of 3,675 at the ARID1A amplicon and a minimum of 65 at the PTEN amplicon. Methylation spectra were obtained for each genomic locus of the two groups of samples, and the results showed that methylation was significantly different at the X target loci and slightly different at the Y target loci. Cluster analysis showed that all T tissues were clustered in one group (except tissues T2 and T3), while Ca tissues were clustered on the other side. The results showed that DNA methylation at the loci may be closely related to liver cancer, providing references for the research and development of biomarkers in clinical diagnosis. Conclusions: The study demonstrates that high-throughput sequencing technology is a powerful and cost-effective method for methylation analysis of target DNA in cancer tissues.
Quantitative DNA Methylation Analysis: The Promise of High-Throughput Epigenomic Diagnostic Testing in Human Neoplastic Disease