Rapid identification of promoter hypermethylation in hepatocellular carcinoma by pyrosequencing of etiologically homogeneous sample pools

Abstract

Aberrant DNA methylation patterns have been identified in a variety of human diseases, particularly cancer. Pyrosequencing has evolved in recent years as a sensitive and accurate method for the analysis and quantification of the degree of DNA methylation in specific target regions. However, the number of candidate genes that can be analyzed in clinical specimens is often restricted by the limited amount of sample available. Here, we present a novel screening approach that enables the rapid identification of differentially methylated regions such as promoters by pyrosequencing of etiologically homogeneous sample pools after bisulfite treatment. We exemplify its use by the analysis of five genes (CDKN2A, GSTP1, MLH1, IGF2, and CTNNB1) involved in the pathogenesis of human hepatocellular carcinoma using pools stratified for different parameters of clinical importance. Results were confirmed by the individual analysis of the samples. The screening identified all genes displaying differential methylation successfully, and no false positives occurred. Quantitative comparison of the pools and the samples in the pool analyzed individually showed a deviation of approximately 1.5%, making the method ideally suited for the identification of diagnostic markers based on DNA methylation while saving precious DNA material.

Figure 1

Pyrograms obtained by the analysis of mixtures with a known degree of methylation in the promoter of CDKN2A with 0% (A), 2% (B), 5% (C), and 10% (D) of methylation. E: The linearity of the signal for the sixth CpG position shown in A–D is demonstrated. Quantitative differences as low as 2 to 5% can be detected by pyrosequencing. Similar linear regression coefficients were obtained for the other five CpGs. CpG 1: y = 1.3 x + 2.3, R² = 0.998; CpG 2: y = 1.57 x + 2.3, R² = 0.997; CpG 3: y = 1.20 x + 1.0, R² = 0.984; CpG 4: y = 0.88 x + 6.6, R² = 0.978; CpG 5: y = 0.79 x + 4.2, R² = 0.998. F: The linearity of the signal throughout the entire dynamic range (0 to 100%) for the sixth CpG position is shown. All assays were performed in triplicate. The resolution and linear correlation is similar for IGF2 as demonstrated in G.

Figure 2

Graphical representation (boxplots) of the results obtained by the analysis of the individual samples for 112 CpGs in five genes (CDKN2A, GSTP1, MLH1, IGF2, and CTNNB1) and the level of statistical significance for differential methylation values. *P < 0.05, **P < 0.005, and ***P < 0.0005.