High-throughput methylation profiling by MCA coupled to CpG island microarray

Abstract

An abnormal pattern of DNA methylation occurs at specific genes in almost all neoplasms. The lack of high-throughput methods with high specificity and sensitivity to detect changes in DNA methylation has limited its application for clinical profiling. Here we overcome this limitation and present an improved method to identify methylated genes genome-wide by hybridizing a CpG island microarray with amplicons obtained by the methylated CpG island amplification technique (MCAM). We validated this method in three cancer cell lines and 15 primary colorectal tumors, resulting in the discovery of hundreds of new methylated genes in cancer. The sensitivity and specificity of the method to detect hypermethylated loci were 88% and 96%, respectively, according to validation by bisulfite-PCR. Unsupervised hierarchical clustering segregated the tumors into the expected subgroups based on CpG island methylator phenotype classification. In summary, MCAM is a suitable technique to discover methylated genes and to profile methylation changes in clinical samples in a high-throughput fashion.

Figure 1.

Schematic diagram of the MCAM method. Enrichment for methylated DNA and reduction of genome complexity is achieved by serial digestion with SmaI (methylation sensitive) and XmaI (methylation insensitive) restriction enzymes, followed by ligation of adaptors and PCR amplification. The resulting amplicons, representative of the methylated fraction of tumor and normal cells, are labeled and cohybridized in a microarray platform. Image acquisition and data analysis allow identification of methylated and nonmethylated genes by comparing intensity values of Cy5 and Cy3 dyes for each pair of tumor and control samples.

Figure 2.

Detection of DNA methylation by MCAM. (A) Scatterplot of Cy5 versus Cy3 intensity values for each probe showing the segregation of methylated (red spots) from unmethylated (black spots) in the colon cancer cell line RKO compared to normal peripheral blood lymphocytes. (B) Venn diagram representing the overlap and differences in methylated probes for the cancer cell lines RKO, Raji, and C8161. Note that a large number of loci are exclusively methylated in each individual cell line. (C) Comparison of significant representation of altered functional categories in cancer cell lines inferred by the presence of methylated genes network. The most significant categories in each cell line are labeled with asterisks (*). Note that “Gene expression” function is affected in all three cell lines, which is because of a large fraction of methylated transcription factors among all identified genes by MCAM.

Figure 3.

Validation of methylation status of selected genes in cancer cell lines. (A) Representation of one identified methylated gene by MCAM. One of several possible MCA fragments (delimited by CCCGGG sequences) close to the transcription start site of the HAND1 gene overlaps with the DNA probe 91A2, allowing the investigation of this fragment in the microarray platform. Note that the remaining MCA fragments do not overlap additional probes, being therefore not investigated in this system but potentially investigated in other arrays with different probe collections. (Gray bar) The promoter region investigated by bisulfite PCR followed by pyrosequencing. (B) Representative pyrograms for HAND1. Four CpG sites close to the transcription start site were pyrosequenced, and a consistent pattern of high levels of methylation was observed for all of them in RKO, while in peripheral blood lymphocyte the methylation values were low, consistent with the MCAM results. The methylation density is presented in the top of each pyrogram as the averaged methylation of the four studied CpG sites. (C) Graphic representation of log₂ ratio and methylation analysis by bisulfite-PCR results for selected genes for validation of MCAM. (Black circles) Hypermethylation in tumor (as determined as log₂ ratio ≥ 1.3 in MCAM and methylation density >10% by bisulfite-PCR followed by pyrosequencing); (white circles) lack of methylation. Note the high concordance of methylation results between techniques.

Figure 4.

Reproducibility of MCAM experiments. (A) Overall correlation between independent replicates for cancer cell lines RKO (colon) and Raji (leukemia). (B) General concordance between data in replicate experiments (both methylation and lack of methylation) per log₂ ratio quantiles. The actual number of concordant loci is presented (above each bar).

Figure 5.

Global methylation analysis of colorectal carcinomas by MCAM. (A) Cluster analysis of MCAM data in primary colorectal carcinomas. A total of 4588 probe data was used for unsupervised hierarchical clustering analysis of 15 sample pairs (tumor compared to normal appearing mucosa), resulting in a classification that matched the known CIMP/MSI status of these samples. The terminal branches are color-coded to represent the CIMP/MSI status of the tumor sample: (red) CIMP⁺/MSI⁺; (blue) CIMP⁺/MSI⁻; (green) CIMP⁻/MSI⁻. (B) Probe clusters, which classifies CIMP⁺/MSI⁺ and CIMP⁺/MSI⁻ samples apart from each other, and CIMP⁺ in general (shared group) from CIMP⁻ samples. (C) Venn diagram of concordant probe methylation (at least 60% of samples methylated) for each CIMP/MSI group. The total number of methylated probes in each group is shown in parenthesis.

Figure 6.

Validation of methylation status of selected genes in primary colorectal carcinomas. (A) Correlation between delta methylation (methylation in tumor minus methylation in adjacent normal) and log₂ ratio for four genes investigated by bisulfite-PCR and pyrosequencing. (White circles) Genes with lower methylation in tumor compared to normal samples (log₂ ratio < 1.3) according to MCAM; (black circles) hypermethylated genes according this technique. (B) Average delta methylation per log₂ ratio. (Bar graphic) The average delta methylation of samples in the same log₂ ratio quartile window. Note that the difference in methylation between tested (colon tumor) and control (normal colon) increases with log₂ ratio deviation from zero, revealing the semiquantitative nature of the MCAM measurements.