Background: Hepatocellular carcinoma (HCC) is common in HCV cirrhotic patients and tumor surveillance lack accuracy in patients waiting for liver transplantation (LT). Herein integrated genomic and epigenetic factors were studied in non-tumor HCV-cirrhotic tissue to identify early events associated with HCC development.

Methods: Liver biopsy samples from 40 HCV-cirrhotic patients with (wHCC, n = 24) and without (woHCC = 16) HCC were evaluated for genome-wide methylation and gene expression. DNA and total RNA were isolated, labeled, and used for Illumina GoldenGate Methylation BeadArray Cancer Panel I and genomic microarrays hybridization, respectively. Gene expression and methylation comparison analysis between wHCC vs. woHCC patients were fit using two sample t-test. The p-values were adjusted for multiple comparisons by calculating the false discovery rate using the q-value method by controlling a FDR < 0.20. A p-value < 0.01 were considered significant. Spearman’s rank correlation was used for methylation/gene expression comparison. Biological data integration and canonical pathway analyses were performed suing IPA tool.

Results: No significant demographic and clinical differences were observed between study groups. From the analysis, 30 CpG sites were found differently methylated from HCV-cirrhotic tissue associated with HCC. Top 10 genes with differentially CpG site increased methylation included ESR1, MME, GSTM2, BMP4, TGFB2, FGF2, MFAP4, COL1A1, TYK2, and HOXB13. Interestingly, ESR1 gene demonstrated the most significant negative correlation between percent methylation and gene expression values (r=-0.50). Deregulation of these genes was found related to cancer and malignancies development, liver detoxification, and hepatic fibrosis and wound repair. Moreover, gene expression analyses determined downregulation of those genes in HCV-cirrhotic tissue from patients with HCC. In addition, several genes previously identified as important in hepatocellular carcinoma development were significantly negative correlated and included CDNK2A, FLT1, HGF, HPSE, MGMT, PDGFRB, and PYCARD. Marker validation was performed using MethyLight assay.

Conclusions: Integrating epigenetics and transcriptome dataset in cirrhotic tissue demonstrated to provide a useful tool to identify early events associated with HCC development in HCV cirrhotic patients. Different methylation patterns appear to be potential biomarkers for HCC surveillance.

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