{"title":"Revealing distinct DNA methylation patterns in hepatic carcinoma through high-throughput sequencing","authors":"Guangmou Zhang, Kefeng Zhang, Meng Yuan, Yichen Li, Jiahui Li, Zhiqing Yuan","doi":"10.1515/tjb-2023-0151","DOIUrl":null,"url":null,"abstract":"\n \n \n To study the relationship between DNA methylation and tumour development and provide experimental evidence for the personalized diagnosis and treatment of hepatic carcinoma.\n \n \n \n The DNA of hepatic carcinoma tissue (Ca group) and adjacent normal tissue (T group) were extracted using the phenol-chloroform method and then treated with bisulfite. Twenty-five genes including 45 subtypes were amplified by PCR. The PCR products were sequenced via the Illumina 450k methylation array assay. The changes of methylated DNA performance were analysed through principal component analysis (PCA). Cluster analysis was used to evaluate the classification of methylated DNA regions. Haplotype abundance variation was tested for methylation differences. Statistical analysis was performed using the chi-square (χ2) test or Fisher’s exact test.\n \n \n \n Sequencing discoveries indicated CG-type methylation pervading all amplicons. However, CHG-type and CHH-type methylations were confined to only four amplicons (or nine subtypes). The methylation ratios of three specific amplicons (DAB2IP, PRDM14-1, Rab31-1) out of 45 amplicon subtypes in the Ca group significantly increased (over 10 %) compared to the T group (p<0.05). Nineteen amplicons demonstrated minor distinction (methylation pattern variations between 1 and 10 %), with the remaining 23 amplicons showing only minimal disparities (under 1 %). PCA and cluster analysis unveiled a marked difference in methylation levels between cancerous and healthy tissues (p<0.05).\n \n \n \n The changes in haplotypes and methylation sites could serve as a biomarker for the clinical diagnosis of hepatic carcinoma. Methylation patterns might play an important role in the occurrence and development of hepatic carcinoma.\n","PeriodicalId":23344,"journal":{"name":"Turkish Journal of Biochemistry","volume":"351 1‐3","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Turkish Journal of Biochemistry","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1515/tjb-2023-0151","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
To study the relationship between DNA methylation and tumour development and provide experimental evidence for the personalized diagnosis and treatment of hepatic carcinoma.
The DNA of hepatic carcinoma tissue (Ca group) and adjacent normal tissue (T group) were extracted using the phenol-chloroform method and then treated with bisulfite. Twenty-five genes including 45 subtypes were amplified by PCR. The PCR products were sequenced via the Illumina 450k methylation array assay. The changes of methylated DNA performance were analysed through principal component analysis (PCA). Cluster analysis was used to evaluate the classification of methylated DNA regions. Haplotype abundance variation was tested for methylation differences. Statistical analysis was performed using the chi-square (χ2) test or Fisher’s exact test.
Sequencing discoveries indicated CG-type methylation pervading all amplicons. However, CHG-type and CHH-type methylations were confined to only four amplicons (or nine subtypes). The methylation ratios of three specific amplicons (DAB2IP, PRDM14-1, Rab31-1) out of 45 amplicon subtypes in the Ca group significantly increased (over 10 %) compared to the T group (p<0.05). Nineteen amplicons demonstrated minor distinction (methylation pattern variations between 1 and 10 %), with the remaining 23 amplicons showing only minimal disparities (under 1 %). PCA and cluster analysis unveiled a marked difference in methylation levels between cancerous and healthy tissues (p<0.05).
The changes in haplotypes and methylation sites could serve as a biomarker for the clinical diagnosis of hepatic carcinoma. Methylation patterns might play an important role in the occurrence and development of hepatic carcinoma.