Abstract 6079: Spatial deconvolution from bulk DNA methylation profiles determines intratumoral epigenetic heterogeneity

Abstract Purpose: Intratumoral heterogeneity emerges from accumulating genetic and epigenetic changes during tumorigenesis, which may contribute to therapeutic failure and drug resistance. We aimed to develop a tool that can evaluate the intratumoral epigenetic heterogeneity using the DNA methylation profiles from bulk tumors. Methods: Ggenomic DNA of three laser micro-dissected tumor regions, including digestive tract surface (DTS), central bulk (CB), and invasive margin (IM), was extracted from formalin-fixed paraffin-embedded (FFPE) sections of 98 colorectal cancer patients. The genome-wide methylation profiles were generated with methylation array. The most variable methylated probes were selected to construct a DNA methylation-based heterogeneity (MeHEG) estimation tool that can deconvolve the proportion of each reference tumor region with the support vector machine model-based method. A PCR-based assay for quantitative analysis of DNA methylation (QASM) was developed to specifically determine the methylation status of each CpG in MeHEG assay at single-base resolution to realize fast evaluation of epigenetic heterogeneity. Results: In the discovery set with 79 patients, the differentially methylated CpGs among the three tumor regions were found. The 7 most representative CpGs were identified by random forest analysis and subsequently selected to develop the MeHEG algorithm. We validated its performance of deconvolution of tumor regions in an independent cohort with 19 patients. In addition, we showed the significant association of MeHEG-based epigenetic heterogeneity with the genomic heterogeneity in mutation and copy number variation in our in-house and TCGA cohorts. Finally, we found that the patients with higher MeHEG score had worse disease-free and overall survival outcomes. Conclusion: By constructing a 7-loci panel with a machine learning approach and QASM assay to facilitate its use in a PCR manner, we developed a valuable method to evaluate the intratumoral epigenetic heterogeneity. The MeHEG algorithm provides innovative insights into the intratumoral heterogeneity from the epigenetic perspective that may add valuable sources to current knowledge about tumor heterogeneity. Citation Format: Yumo Xie, Yu Zhang, Guannan Tang, Xiaolin Wang, Meijin Huang, Yanxin Luo, Huichuan Yu. Spatial deconvolution from bulk DNA methylation profiles determines intratumoral epigenetic heterogeneity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 6079.