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Spatial deconvolution from bulk DNA methylation profiles determines intratumoral epigenetic heterogeneity
Binbin Liu1,2,3, Yumo Xie1,2,3, Yu Zhang2,3,4
1Department of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510655, Guangdong, China.
Cell & Bioscience
|January 23, 2025
Summary
We developed a DNA methylation-based tool (MeHEG) to quickly assess epigenetic heterogeneity in tumors, revealing its link to poor survival and dynamic changes during treatment.
Area of Science:
- Oncology
- Genomics
- Epigenetics
Background:
- Intratumoral heterogeneity, driven by genetic and epigenetic changes, contributes to cancer treatment failure.
- Current methods for assessing epigenetic intratumoral heterogeneity (eITH) are not clinically practical.
- Developing a rapid and reliable eITH assessment tool is crucial for clinical applications.
Purpose of the Study:
- To develop a DNA methylation-based tool for evaluating intratumoral epigenetic heterogeneity (eITH).
- To assess the clinical relevance and potential applications of the developed eITH tool in colorectal cancer.
Main Methods:
- Genome-wide DNA methylation profiling of distinct colorectal cancer tumor regions (surface, central bulk, invasive front).
- Selection of 7 differentially methylated CpGs to build the DNA methylation-based heterogeneity (MeHEG) estimation tool using machine learning.
- Development of a quantitative analysis of DNA methylation (QASM) assay for rapid, single-base resolution eITH evaluation.
Main Results:
- The MeHEG algorithm accurately deconvolves tumor regions and correlates with genomic heterogeneity (mutation, copy number variation).
- Higher MeHEG scores are associated with worse disease-free and overall survival outcomes.
- Epigenetic heterogeneity shows dynamic changes in cancer cells under therapeutic drug treatment.
Conclusions:
- A 7-loci panel and QASM assay provide a valuable method for evaluating intratumoral heterogeneity.
- The MeHEG algorithm offers novel epigenetic insights into tumor complexity.
- This tool has potential for clinical and research applications in cancer biology.
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