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Updated: Nov 15, 2025
Genome-Wide Analysis of DNA Methylation in Gastrointestinal Cancer
Published on: September 18, 2020
DNA-methylation for the detection and distinction of 19 human malignancies
Ludmila Danilova1,2, John Wrangle3, James G Herman4
1Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Abstract:
The contribution of DNA-methylation based gene silencing to carcinogenesis is well established. Increasingly, DNA-methylation is examined using genome-wide techniques, with recent public efforts yielding immense data sets of diverse malignancies representing the vast majority of human cancer related disease burden. Whereas mutation events may group preferentially or in high frequency with a given histology, mutations are poor classifiers of tumour type. Here we examine the hypothesis that cancer-specific DNA-methylation reflects the tissue of origin or carcinogenic risk factor, and these methylation abnormalities may be used to faithfully classify tumours according to histology. We present an analysis of 7427 tumours representing 19 human malignancies and 708 normal samples demonstrating that specific tumour changes in methylation can correctly determine site of origin and tumour histology with 86% overall accuracy. Examination of misclassified tumours reveals underlying shared biology as the source of misclassifications, including common cell of origin or risk factors.
Insights
DNA methylation patterns can accurately classify tumor types and origins. This study analyzed 7427 tumors, showing methylation abnormalities reliably identify cancer histology, aiding in diagnosis.
Area of Science:
- Oncology
- Epigenetics
- Genomics
Background:
- DNA methylation-based gene silencing is a known factor in cancer development.
- Genome-wide methylation analysis is increasingly used for large-scale cancer studies.
- Tumor mutations are often insufficient for precise tumor classification.
Purpose of the Study:
- To test if cancer-specific DNA methylation patterns can accurately classify tumors by histology.
- To determine if methylation abnormalities reflect tissue of origin or carcinogenic risk factors.
Main Methods:
- Analysis of 7427 tumors across 19 human malignancies.
- Comparison with 708 normal tissue samples.
- Genome-wide DNA methylation profiling.
Main Results:
- DNA methylation patterns correctly determined tumor site of origin and histology with 86% overall accuracy.
- Misclassified tumors often shared common biological characteristics, such as cell of origin or risk factors.
- Specific methylation changes serve as reliable biomarkers for tumor classification.
Conclusions:
- Cancer-specific DNA methylation is a powerful tool for classifying tumor types.
- Methylation profiling can aid in identifying the tissue of origin for unknown primary tumors.
- Understanding shared biology in misclassified tumors offers insights into cancer development.
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