Table 1.
Clinicopathological data for 59 HCC patients.
Figure 1.
Clustering analysis of 59 HCC tumors reveals 3 subgroups.
(A) Consensus matrix (B) 2D hierarchical clustering of 170 probes that overlapped between 4416 differentially methylated CpG sites (between tumors and adjacent non-tumorous tissues) and 199 CpG loci that divided tumors into three subgroups. Subgroups were labeled as Group-1 (red), Group-2 (blue), Group-3 (green) and adjacent non-tumorous tissues, NT (white). Group A represents both Group-1 and Group-3, while Group B is Group-2. (C) Survival curves for the original 3 subgroups identified by CHC-FS. (D) Survival curve for Group B versus Group A. P-value was calculated by generalised Wilcoxon method. OS, overall survival; DFS, disease free survival.
Table 2.
Univariate analysis of clinicopathological variables for overall survival (OS) and disease-free survival (DFS) in 58 patients (one patient did not have survival information).
Figure 2.
Methylation profiling of 59 HCC patients.
(A) Hierarchical clustering of 4416 most significantly differentially methylated CpG probes between tumor and adjacent non-tumorous tissues. (B) Volcano plot for DNA methylation profiles of 59 patients. Y-axis indicates the minus log10 of p-value for each probe, and X-axis shows the mean methylation difference between tumor and adjacent non-tumor. CpG sites that were statistically significant (FDR adjusted p-value<0.05) and had |Δβ|>0.1, were labeled in red. (C) Characteristics of differentially methylated CpG sites. Percentage of significantly hyper- or hypo-methylated CpG sites located in CGI were compared against overall CpG sites in Infinium HumanMethylation27 BeadChip. (D) Top 10 biological functions that are most significantly enriched in our dataset using IPA. X-axis shows the minus log10 of FDR adjusted p-value for Fisher’s exact test.
Figure 3.
Validation of aberrantly methylated genes in tumors compared to adjacent non-tumorous tissues.
Validation of methylation data was done using pyrosequencing. T-test was used to test the difference between tumors and adjacent non-tumorous tissues. Correlation between Infinium’s β-values and pyrosequencing’s percentage of methylation was measured using Pearson’s method. R2 is the squared value of the Pearson correlation coefficient.
Figure 4.
Integrated analysis of methylation and gene expression in 59 HCC patients.
(A) Hierarchical clustering of the 3185 most significantly differentially expressed genes between tumors and adjacent non-tumorous tissues. (B) Starburst plot was constructed by plotting transformed log10 p-value of differentially expressed genes (Y-axis) versus transformed log10 p-value of methylation difference (X-axis) between tumor and adjacent non-tumorous tissues. Genes with FDR adjusted p-value<0.05 were labeled in black. Genes with absolute fold change >1.2, difference in β-value greater than 0.1 and which met the statistical cut-off (FDR adjusted p-value<0.05) were labeled in red. Directional change of expression and methylation are indicated by the black arrow head. Table at lower panel shows the percentage of genes with significant positive and negative correlations between gene expression and methylation data. (C) Validation results for SH3YL1, CYB5R2, SPINT2 and GSTP1. Methylation and gene expression data were validated by pyrosequencing and quantitative PCR respectively. T-test was used to compare the difference in methylation or gene expression between two groups; Pearson correlation was used to measure association between pyrosequencing and Infinium data, and between gene expression and methylation data. (D) Top network derived from the 536 aberrantly methylated and deregulated genes where NFκB complex served as primary node. (E) Predicted upstream regulators from IPA. Eleven upstream regulators (including NFκB complex) were associated with the NFκB pathway. Red spheres indicate genes that were upregulated in tumor; green spheres indicate downregulated genes in tumor compared to adjacent non-tumorous tissues; grey boxes represent complexes and white spheres represent upstream regulators.