April 1, 2007 (Vol. 27, No. 7)

Profiling 1,536 CpG Sites per Assay with 96-Sample Throughput

Curing cancer relies not only on understanding genetic variations, but also on epigenetic alterations. DNA methylation is an epigenetic modification where a methyl group is added to the cytosine (C), which can occur when the C is followed by guanine (G). It does not change the genetic code but can affect chromosomal stability and gene expression.

Carcinogenesis is often associated with global hypomethylation and/or more localized hypermethylation of CpG islands— stretches of DNA containing clusters of CpG dinucleotides. The transcriptional silencing of tumor suppressor genes by promoter CpG island hypermethylation or chromosomal instability associated with global hypomethylation can contribute to oncogenesis.

Early Detection of Cancer

From a clinical perspective, DNA methylation changes in cancer represent an attractive therapeutic target as epigenetic alterations are, in principle, more readily reversible than genetic events. Another area of great promise is in molecular diagnostics and early detection. Cancer-specific DNA methylation patterns can be detected in tumor-derived free DNA in the bloodstream and in epithelial tumor cells shed into the lumen.

The complexity of varying distributions of methylated cytosines across the approximately 50 million CpG dinucleotides of each diploid mammalian genome in a DNA sample derived from a heterogeneous tissue sample is a diagnostic dream and an analytical nightmare. Methylation profiles yield information on the methylation status across many sites in the genome, providing a unique approach to genome-wide molecular diagnostics.

Most microarray-based DNA methylation analysis platforms rely on methylation-sensitive restriction enzyme digestion or on enrichment using methylcytosine antibodies or methyl-binding domain protein columns. These methods can assay a relatively large number of features (loci) when combined with high-density tiling or promoter microarrays, but are limited in their sample throughput capacity, and generally require large amounts of high-quality input DNA. Most other DNA methylation analysis techniques use bisulfite-based conversion of unmethylated cytosines into uracils to turn epigenetic differences into sequence-based information. Many bisulfite-based techniques such as methylation-specific PCR (MSP) and MethyLight can accommodate large numbers of samples, but are limited in the number of loci that can be interrogated.

By relying on the collective address-tagged amplification of 1,536 CpG sites and hybridization on a BeadArray™ substrate, the GoldenGate DNA methylation analysis platform recently introduced by Illumina (www.illimina.com) retains the high sample throughput and large number of loci that can be interrogated simultaneously (Table).

The methylation platform assesses the methylation status of up to 1,536 independent CpG sites per assay across 96 samples. It advances methylation research and biomarker discovery with high reproducibility (average r2 Ž 0.98), flexible content design, strong correlation to MSP and high sensitivity to detect small differences in methylation status between biological samples. Differential methylation analysis can be accomplished in less than one week from bisulfite conversion to data analysis.

To assay DNA methylation status, cytosine is converted to uracil with bisulfite treatment. The fact that 5-methylcytosine is unreactive under the same conditions is important for the assay’s utility. The standard assay used for methylation profiling is an adaptation of the GoldenGate Assay for genotyping (Figure 1). Bisulfite-converted DNAs are biotinylated and immobilized on paramagnetic beads. Query oligonucleotides are hybridized to the DNA and then washed to remove excess or mishybridized oligonucleotides. The hybridized oligos are then extended and ligated to create amplifiable templates. The PCR that follows uses fluorescently labeled universal PCR primers. Methylation status of the interrogated CpG sites is determined by comparing the ratio of the fluorescent signal from the methylated allele to the sum of the fluorescent signals of both methylated and unmethylated alleles.

Figure 1

Golden Gate Methylation Cancer Panel

The first standard panel, GoldenGate Methylation Cancer Panel I, spans 1,505 CpG loci selected from 807 genes, where 28.6% contain one CpG site per gene, 57.3% contain two CpG sites, and 14.1% have three or more sites. Selected genes fall into various classes, including tumor suppressor genes, oncogenes, genes involved in DNA repair, cell cycle control, differentiation, apoptosis, X-linked, and imprinted genes.

Illumina’s methylation technology is based on the BeadArray platform, which supports a range of applications including SNP genotyping, gene expression profiling, copy number variation analysis, and methylation analysis. This enables researchers to perform cross-application analysis such as the ability to integrate gene expression data with DNA methylation data. BeadStudio software enables researchers to view vast amounts of data in a single graph such as heat map, scatter plot, and line plot. These tools and the BeadStudio Genome Browser show chromosomal coordinates, percent of GC content, location in a CpG island, and methylation values. Figure 2 shows the heat map tool: this subsection displays distinct methylation profiles of bisulfite-converted genomic DNA from normal and cancerous cell lines.

Figure 2

Markers in Lung Adenocarcinomas

The methylation status of 1,536 CpG sites from 371 cancer-related genes in 23 lung adenocarcinoma tissues and 23 normal lung tissues was measured. We first identified 55 significantly differentially methylated sites from a training set of samples, 11 lung adenocarcinomas, and 11 matching normal tissue samples (Figure 3a). Among these markers, more were hypermethylated in adenocarcinoma; methylation at some of these genes, e.g., CDH13, HOXA5, RUNX3, and TP73, is known to be associated with tumor progression in various types of cancer.

To assess the power of the selected methylation markers for reliable classification of prospective cancer and normal samples, we clustered an independent test set of samples—12 normal and 12 adenocarcinoma samples—based on the methylation profiles of the 55 markers. We obtained 100% specificity (12/12) and 92% sensitivity (11/12; Figure 3b). This demonstrated the value of the Illumina BeadArray platform and the GoldenGate Assay for Methylation for biomarker discovery. The ability to analyze DNA methylation patterns in a large number of genes or the entire genome should greatly facilitate the understanding of cancer, normal development, aging, diabetes, psychiatric diseases, and other human diseases, as well as the role of the environment in human health.

Figure 3

Peter W. Laird, Ph.D., is associate professor at USC Keck School of Medicine. Marina Bibikova, Ph.D., is staff scientist and Jian-Bing Fan, Ph.D., is director of research collaboration at Illumina. Web: www.illumina.com. Phone: (858) 202-4669. E-mail: [email protected].

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