Abstract B033: Mapping subclonal epigenetic evolution in colorectal cancer by spatial analysis of DNA hypermethylation

Abstract

Abstract Aberrant patterns of DNA methylation (DNAme) have long been noted in colorectal cancer (CRC). Early studies found overall hypomethylation of the cancer genome, while subsequent work revealed focal hypermethylation at specific loci, especially CpG-rich promoters. Loci occupied by polycomb repressive complex 2 in stem cells are remarkably enriched in cancer-specific hypermethylation events. These Polycomb Target Genes (PTGs) include important transcriptional regulators of lineage specification and differentiation, suggesting that hypermethylation-mediated silencing of PTGs could play an active role in CRC initiation or progression. Despite these findings, we have limited knowledge of when, where, and how this hypermethylation arises. Preliminary evidence from bulk tumor samples in the Cancer Genome Atlas suggests that many of these PTG hypermethylation events may be almost completely clonal. Additionally, we have noted rare, densely methylated reads covering PTGs in cancer-adjacent, histologically normal tissue. These observations suggest that PTG hypermethylation may be a very early event in carcinogenesis and may play a permissive or even active role in that process. To better understand the timing and evolution of PTG hypermethylation events in CRC, we have developed a protocol that allows us to extract dozens of small (20µL), spatially annotated mini-bulk samples from live tumors. These mini-bulks may be frozen or dissociated to viable single-cell suspensions. Remaining tumor tissue is preserved in the form of spatially annotated FFPE blocks, which can be used for analyses such as high-plex immunofluorescence or spatial transcriptomics. Using this process, we have collected over 500 spatially annotated samples from 6 CRC cases, including 196 micro-bulk samples profiled using the Infinium MethylationEPIC array. Additionally, we have profiled DNAme in 147 single cells using a dramatically improved single-cell whole-genome bisulfite sequencing protocol developed in our lab. Analysis of EPIC array data reveals wide variation in DNAme heterogeneity between tumors. While in some tumors, the vast majority of DNA hypermethylation events are clonal, other tumors reveal significant intra-tumor heterogeneity, including two or more prominent DNAme subclones as well as a substantial number of ‘private’ hypermethylation events that occur in only one sample. Mapping DNAme information back onto our spatial data reveals that in at least one case, DNAme clones are spatially partitioned and are associated with distinct histology. Ongoing work includes inference of phylogenetic trees from DNA hypermethylation events using non-reversible models of methylation accumulation, allowing us to measure the relative timing of hypermethylation events, as well as integration of array, whole-genome, and single-cell methylation data to more completely characterize DNAme subclones, characterize cellular DNAme heterogeneity at variably methylated sites, and shed further light on the evolution of cancer-related DNA hypermethylation. Citation Format: Nathan J. Spix, Hsiao-yun Milliron, Manpreet Kalkat, Emily Eugster, David W. Chesla, David Sokol, Emily Jung, Paula Nolte, Kelly K. Krzyzanowski, Toshinori Hinoue, Hui Shen, Peter W. Laird. Mapping subclonal epigenetic evolution in colorectal cancer by spatial analysis of DNA hypermethylation [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr B033.