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Updated: May 11, 2026
Genome-Wide Analysis of DNA Methylation in Gastrointestinal Cancer
Published on: September 18, 2020
CMS: a web-based system for visualization and analysis of genome-wide methylation data of human cancers
Fei Gu1, Mark S Doderer, Yi-Wen Huang
1Department of Molecular Medicine/Institute of Biotechnology, University of Texas Health Science Center at San Antonio, San Antonio, Texas, United States of America.
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/.
Insights
The Cancer Methylome System (CMS) is a new database for analyzing cancer DNA methylation. It offers visualization and analytical tools for breast and endometrial cancers, aiding research.
Area of Science:
- Genomics
- Epigenetics
- Bioinformatics
Background:
- DNA methylation in promoter CpG islands is linked to gene suppression and tumor progression.
- High-throughput sequencing enables efficient genome-wide methylation profiling in cancer cells.
- Experimental and computational methods facilitate the study of cancer-specific methylation patterns and their clinical relevance.
Purpose of the Study:
- To develop a web-based database application for visualizing, comparing, and analyzing human cancer-specific DNA methylation.
- To provide comprehensive, genome-wide epigenetic portraits of human breast and endometrial cancers.
- To offer tools for understanding methylation at genomic and gene levels and facilitate data interpretation.
Main Methods:
- Utilized MBDCap-sequencing to obtain methylation intensities.
- Stored pre-processed data in a web-based database application (Cancer Methylome System - CMS).
- Included data from 191 patient samples (169 tumor, 22 normal) and 41 breast cancer cell lines, totaling approximately 6.6 billion mapped sequence reads.
Main Results:
- The CMS database provides comprehensive, genome-wide epigenetic profiles for breast and endometrial cancers.
- Features include two distinct views for analyzing methylation structure and systemic alterations.
- Integrated annotation tracks and analytical functions like differential methylation detection and global intensity calculation.
Conclusions:
- The Cancer Methylome System (CMS) offers powerful visualization and analytical capabilities for cancer methylome datasets.
- Its comprehensive datasets, analytical functions, and applications hold significant biological and translational value for cancer research.
- CMS is freely accessible online, promoting wider use in the scientific community.
