Purpose: A comparative quantitative methylation profiling of hepatocellular carcinoma and the most frequent benign liver tumor, hepatocellular adenoma, was set up for the identification of tumor-specific methylation patterns.
Experimental design: The quantitative methylation levels of nine genes (RASSF1A, cyclinD2, p16INK4a, DAP-K, APC, RIZ-1, HIN-1, GSTpi1, SOCS-1) were analyzed in hepatocellular carcinoma and adjacent normal tissue (n = 41), hepatocellular adenoma and adjacent normal tissue (n = 26), focal nodular hyperplasia (n = 10), and unrelated normal liver tissue (n = 28). Accumulated methylation data were analyzed using various statistical algorithms, including hierarchical clustering, to detect tumor-specific methylation patterns.
Results: Cluster analysis revealed that hepatocellular adenoma displays a methylation profile much more similar to that found in normal liver tissue and focal nodular hyperplasia than to that found in hepatocellular carcinoma. Many characteristic differences were not detected when using mere qualitative methylation assays. The cyclinD2 gene was identified as a new and frequent target for aberrant hypermethylation in hepatocellular carcinoma (68%). In the control group of 28 liver specimens from healthy donors, a clear correlation between age of patient and frequency and level of aberrant methylation was seen, which could not be detected in the group of hepatocellular carcinoma specimens.
Conclusions: Methylation profiling can clearly contribute to the unequivocal classification of suspicious lesions, but only if done in a quantitative manner applying cell type and gene-specific thresholds. In hepatocellular carcinoma, the altered methylation patterns accompanying malignant transformation override the age-dependent increase in gene methylation.