CMS: a web-based system for visualization and analysis of genome-wide methylation data of human cancers

Abstract

Background: DNA methylation of promoter CpG islands is associated with gene suppression, and its unique genome-wide profiles have been linked to tumor progression. Coupled with high-throughput sequencing technologies, it can now efficiently determine genome-wide methylation profiles in cancer cells. Also, experimental and computational technologies make it possible to find the functional relationship between cancer-specific methylation patterns and their clinicopathological parameters.

Methodology/principal findings: Cancer methylome system (CMS) is a web-based database application designed for the visualization, comparison and statistical analysis of human cancer-specific DNA methylation. Methylation intensities were obtained from MBDCap-sequencing, pre-processed and stored in the database. 191 patient samples (169 tumor and 22 normal specimen) and 41 breast cancer cell-lines are deposited in the database, comprising about 6.6 billion uniquely mapped sequence reads. This provides comprehensive and genome-wide epigenetic portraits of human breast cancer and endometrial cancer to date. Two views are proposed for users to better understand methylation structure at the genomic level or systemic methylation alteration at the gene level. In addition, a variety of annotation tracks are provided to cover genomic information. CMS includes important analytic functions for interpretation of methylation data, such as the detection of differentially methylated regions, statistical calculation of global methylation intensities, multiple gene sets of biologically significant categories, interactivity with UCSC via custom-track data. We also present examples of discoveries utilizing the framework.

Conclusions/significance: CMS provides visualization and analytic functions for cancer methylome datasets. A comprehensive collection of datasets, a variety of embedded analytic functions and extensive applications with biological and translational significance make this system powerful and unique in cancer methylation research. CMS is freely accessible at: http://cbbiweb.uthscsa.edu/KMethylomes/.

Figure 1. Genomic view of CMS.

This webpage is designed for the genome-wide visualization and analysis of methylation intensity (A, B, C). Methylation intensity is pre-calculated for a 100 bp bin size and is shown using a red gradient heatmap. A variety of genomic annotations and functional toolbars give users more options in browsing the webpage. Statistical methods were imbedded, including DMR analysis (A) and statistical calculation (C). Links to UCSC genome browser (D) and to gene view (E) are available for further analysis.

Figure 2. Gene centric view of CMS.

This webpage is designed for visualization and analysis of methylation intensity at the gene level. In the toolbar, four layers of options are available to enable specific selections gene sets. Methylation intensities for promoter regions of genes (+/− 2 kb around TSS region) were pre-calculated and were shown using a red gradient heatmap. A white/green box on the side of gene symbol shows the promoter regions of this particular gene with or without CpG island(s). Clicking on the gene symbol on the left side of the heatmap panel will bring the user back to the genomic viewer centered on the selected gene, allowing visualization of detail methylation patterns.

Figure 3. Discovery of tumor specific methylation profiles.

HOXB2 was hypermethylated in breast tumors compared with breast normal (A), while hypomethylated in endometrial cancer tumors compared with endometrial normal (B).

Figure 4. Discovery of methylation correlated genes.

Gene set with similar methylation profiles of HOXB2 were found by choosing the “Correlated gene” gene sets in the gene centric view. Most of the genes are hypermethylated in breast tumors (blue dash box), and with no significant difference in endometrial samples (green dash box).

Figure 5. Discovery of differentially methylated gene sets within a pathway.

The “Androgen-mediated Signaling” gene set which contains HOX cluster genes were selected as an example. Several genes within the blue dash box are hypermethylated in breast tumors compared to normal tissues, while others show no significant difference. For endometrial samples, no significant difference is found for any of the gene between tumors and normals.

Figure 6. Visualization of DNA methylation and histone modification data.

The TSS region of DLC1 is used as an example. 4 samples were randomly selected by marking the check box on the right side of the webpage for breast samples (e.g., brn80, brt22, brt69 and brt37). The “full” option for every custom track and the Broad Histone tracks was selected for the comparison of DNA methylation and histone modification marks. Similar results were obtained as previous report . An exception (the 3^rd track, brt22) was found which shows patient specific patterns (A); and there was no increased methylation found for endometrial samples (B).