The Illumina Infinium HumanMethylation450 BeadChip is a new platform for high-throughput DNA methylation analysis. Several methods for normalization and processing of these data have been published recently. Here we present an integrated analysis pipeline offering a choice of the most popular normalization methods while also introducing new methods for calling differentially methylated regions and detecting copy number aberrations. Availability and implementation: ChAMP is implemented as a Bioconductor package in R. The package and the vignette can be downloaded at bioconductor.org Contact:tiffany.morris@ucl.ac.uk

In this article, we show that high resolution melting analysis (HRM) is a sensitive and specific method for the detection of methylation. Methylated DNA and unmethylated DNA acquire different sequences after bisulphite treatment resulting in PCR products with markedly different melting profiles. We used PCR to amplify both methylated and unmethylated sequences and assessed HRM for the determination of the methylation status of the MGMT promoter region. Reconstruction experiments showed that MGMT methylation could be detected at levels as low as 0.1%. Moreover, MS-HRM allows for estimation of the methylation level by comparing the melting profiles of unknown PCR products to the melting profiles of PCR products derived from standards with a known unmethylated to methylated template ratio. We used MS-HRM for the analysis of eight cell lines of known methylation status and a panel of colorectal cancer specimens. The simplicity and high reproducibility of the MS-HRM protocol makes MS-HRM the method of choice for methylation assessment in many diagnostic and research applications.

Purpose: Epigenetic alterations are common and can now be addressed in a parallel fashion. We investigated the methylation in bladder cancer with respect to location in genome, consistency, variation in metachronous tumors, impact on transcripts, chromosomal location, and usefulness as urinary markers. Experimental Design: A microarray assay was utilized to analyze methylation in 56 samples. Independent validation was conducted in 63 samples by a PCR-based method and bisulfite sequencing. The methylation levels in 174 urine specimens were quantified. Transcript levels were analyzed using expression microarrays and pathways were analyzed using dedicated software. Results: Global methylation patterns were established within and outside CpG islands. We validated methylation of the eight tumor markers genes ZNF154 (P < 0.0001), HOXA9 (P < 0.0001), POU4F2 (P < 0.0001), EOMES (P = 0.0005), ACOT11 (P = 0.0001), PCDHGA12 (P = 0.0001), CA3 (P = 0.0002), and PTGDR (P = 0.0110), the candidate marker of disease progression TBX4 (P < 0.04), and other genes with stage-specific methylation. The methylation of metachronous tumors was stable and targeted to certain pathways. The correlation to expression was not stringent. Chromosome 21 showed most differential methylation (P < 0.0001) and specifically hypomethylation of keratins, which together with keratin-like proteins were epigenetically regulated. In DNA from voided urine, we detected differential methylation of ZNF154 (P < 0.0001), POU4F2 (P < 0.0001), HOXA9 (P < 0.0001), and EOMES (P < 0.0001), achieving 84% sensitivity and 96% specificity. Conclusions: We initiated a detailed mapping of the methylome in metachronous bladder cancer. Novel genes with tumor, chromosome, as well as pathway-specific differential methylation in bladder cancer were identified. The methylated genes were promising cancer markers for early detection of bladder cancer. Clin Cancer Res; 17(17); 5582–92. ©2011 AACR.

In our study, whole‐genome methylation arrays were applied to identify novel genes with tumor specific DNA methylation of promoter CpG islands in pre‐malignant and malignant colorectal lesions. Using a combination of Illumina HumanMethylation27 beadchips, Methylation‐Sensitive High Resolution Melting (MS‐HRM) analysis, and Exon arrays (Affymetrix) the DNA methylation pattern of ∼14,000 genes and their transcript levels were investigated in six normal mucosas, six adenomas and 30 MSI and MSS carcinomas. Sixty eight genes with tumor‐specific hypermethylation were identified (p < 0.005). Identified hypermethylated sites were validated in an independent sample set of eight normal mucosas, 12 adenomas, 40 MSS and nine MSI cancer samples. The methylation patterns of 15 selected genes, hypermethylated in adenomas and carcinomas (FLI1, ST6GALNAC5, TWIST1, ADHFE1, JAM2, IRF4, CNRIP1, NRG1 and EYA4), in carcinomas only (ABHD9, AOX1 and RERG), or in MSI but not MSS carcinomas (RAMP2, DSC3 and MLH1) were validated using MS‐HRM. Four of these genes (MLH1, AOX1, EYA4 and TWIST1) had previously been reported to be hypermethylated in CRC. Eleven genes, not previously known to be affected by CRC specific hypermethylation, were identified and validated. Inverse correlation to gene expression was observed for six of the 15 genes with Spearman correlation coefficients ranging from −0.39 to −0.60. For six of these genes the altered methylation patterns had a profound transcriptional association, indicating that methylation of these genes may play a direct regulatory role. The hypermethylation changes often occurred already in adenomas, indicating that they may be used as biomarkers for early detection of CRC.

Primer design for PCR-based methylation analysis following bisulfite conversion of DNA is considerably more complex than primer design for regular PCR. The choice of the optimal primer set is critical to the performance and correct interpretation of the results. Most methodologies in methylation analysis utilize primers that theoretically amplify methylated and unmethylated templates at the same time. The proportional amplification of all templates is critical but difficult to achieve due to PCR bias favouring the amplification of the unmethylated template. The focus of this brief communication is to point out the important criteria needed for the successful choice of primers that will enable the control of PCR bias in bisulfite based methylation-screening protocols.