Investigating Pathogenic and Hepatocarcinogenic Mechanisms from Normal Liver to HCC by Constructing Genetic and Epigenetic Networks via Big Genetic and Epigenetic Data Mining and Genome-Wide NGS Data Identification.
Cheng-Wei LiYu-Kai ChiuBor-Sen ChenPublished in: Disease markers (2018)
The prevalence of hepatocellular carcinoma (HCC) is still high worldwide because liver diseases could develop into HCC. Recent reports indicate nonalcoholic fatty liver disease and nonalcoholic steatohepatitis (NAFLD&NASH) and primary biliary cirrhosis and primary sclerosing cholangitis (PBC&PSC) are significant of HCC. Therefore, understanding the cellular mechanisms of the pathogenesis and hepatocarcinogenesis from normal liver cells to HCC through NAFLD&NASH or PBC&PSC is a priority to prevent the progression of liver damage and reduce the risk of further complications. By the genetic and epigenetic data mining and the system identification through next-generation sequencing data and its corresponding DNA methylation profiles of liver cells in normal, NAFLD&NASH, PBC&PSC, and HCC patients, we identified the genome-wide real genetic and epigenetic networks (GENs) of normal, NAFLD&NASH, PBC&PSC, and HCC patients. In order to get valuable insight into these identified genome-wide GENs, we then applied a principal network projection method to extract the corresponding core GENs for normal liver cells, NAFLD&NASH, PBC&PSC, and HCC. By comparing the signal transduction pathways involved in the identified core GENs, we found that the hepatocarcinogenesis through NAFLD&NASH was induced through DNA methylation of HIST2H2BE, HSPB1, RPL30, and ALDOB and the regulation of miR-21 and miR-122, and the hepatocarcinogenesis through PBC&PSC was induced through DNA methylation of RPL23A, HIST2H2BE, TIMP1, IGF2, RPL30, and ALDOB and the regulation of miR-29a, miR-21, and miR-122. The genetic and epigenetic changes in the pathogenesis and hepatocarcinogenesis potentially serve as potential diagnostic biomarkers and/or therapeutic targets.
Keyphrases
- dna methylation
- genome wide
- copy number
- cell proliferation
- long non coding rna
- gene expression
- induced apoptosis
- long noncoding rna
- end stage renal disease
- big data
- electronic health record
- cell cycle arrest
- chronic kidney disease
- ejection fraction
- oxidative stress
- newly diagnosed
- prognostic factors
- risk factors
- signaling pathway
- endoplasmic reticulum stress
- pi k akt
- machine learning
- risk assessment
- magnetic resonance
- peritoneal dialysis
- binding protein
- magnetic resonance imaging
- high glucose
- drug induced
- patient reported outcomes
- heat stress
- contrast enhanced
- data analysis
- cell death
- human health
- climate change
- circulating tumor cells
- adverse drug
- circulating tumor