Abstract B068: Inferring enhancer activity from cell-free DNA fragmentation patterns

Abstract We present a framework for inferring enhancer activity from cell-free DNA (cfDNA) fragmentation patterns, offering a novel feature set for cfDNA analysis that reflects gene regulation. Enhancers are promoter-distal regulatory elements that regulate gene expression programs that define cell types and cellular states. Despite advances in inferring gene regulation in cancer using liquid biopsy, it remains challenging to identify signals of enhancer activity from cell-free DNA (cfDNA). Active enhancers are characterized by transcription of short enhancer RNAs (eRNAs). Recent studies demonstrated that cfDNA from promoters of transcribed genes demonstrates high variation in DNA fragment length, or “fragmentation entropy”. We tested whether eRNA transcription can be inferred based on cfDNA fragmentation entropy. We quantified “enhancer fragmentation entropy” (EFE) to profile enhancer activity in plasma by measuring Shannon entropy of cfDNA fragments around enhancer transcription start sites (TSS). Using PRO-cap data from lymphoblastoid cell lines, we analyzed EFE signals at 70,000 transcribed enhancers and observed distinct patterns between active (expressed) and inactive enhancers in cfDNA from healthy individuals. cfDNA from patients with prostate cancer showed elevated EFE at enhancers activated in prostate cancer. EFE at these sites correlated with circulating tumor DNA (ctDNA) levels in a published cfDNA dataset of 41 prostate cancer plasma samples. Lower-dimensional projections of the entropy signals across 300 “modules” of co-regulated enhancers revealed tighter clustering of samples within the same cancer type, suggesting that these entropy patterns capture cell-type specific enhancer activity. Our findings suggest that enhancer fragmentation entropy captures cell-type specific signals and, when measured at cancer-specific enhancers in cfDNA, could serve as a promising biomarker for cancer detection and monitoring. Ongoing work is focused on validating these findings in larger cohorts and applying EFE to cancer monitoring and clinical subtyping. Citation Format: Alexis Yang. Inferring enhancer activity from cell-free DNA fragmentation patterns [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr B068.