Spatial deconvolution from bulk DNA methylation profiles determines intratumoral epigenetic heterogeneity.

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.