Abstract Background: The genome-wide pattern of cell-free DNA (cfDNA) is influenced by fragmentation enzymes, nucleosome occupancy, and epigenetic factors, as well as cell death mechanisms. Better modeling of these factors and their interactions will be essential for more sensitive detection of tumor-specific features and tissue-of-origin. Methods: To obtain mechanistic insights into cfDNA fragmentation, we developed a fragmentomics signature analysis framework. Our fragmenTopics algorithm (i) decomposes contributions of different fragment lengths and end-motif signatures using topic modeling and (ii) learns the dependencies of signature rates on the epigenome. The second component utilizes gradient boosting, enabling the modeling of non-linear dependencies and feature interactions. Both large-scale features, such as histone marks and DNase activity, and meso-scale features, such as transcription start sites (TSSs), nucleosome positions, and secondary DNA structures, are included in the model. Results: Using de novo signature discovery from 726 samples across five datasets, we built a comprehensive catalog of fragment length and end-motif signatures and studied determinants of their activity across the genome. The most common length and end-motif signatures reflected the mononucleosomal fragmentation by DNASE1L3. These signatures, as well as the dinucleotide length signature and motif signatures associated with known motifs of DNase enzymes, such as DFFB, showed lower abundance in cancer and further decreased with increasing tumor fraction. Instead, cancer samples manifested a higher diversity of processes, many of which are of unknown origin. Notably, two cancer-enriched length signatures were, on average, 20 bp shorter fragments with respect to mono- and di-nucleosome peaks. These signatures correlated with H3K4me1 and the compartment eigenvector, and may be linked to tighter nucleosome wrapping in euchromatin. Two cancer-enriched signatures (190-240 bp and 240-300 bp) had higher rates in TSSs; in addition to the two tight mono- and di-nucleosomal signatures, which were also enriched. Cancer-enriched end-motifs were A/T-rich, and these did not correspond to known DNase motifs. The increased diversity in end-motifs may be due to non-apoptotic cell death or tissue- or cancer-specific activity of less-studied cleavage enzymes; our results on their epigenome correlations can inform further investigations into their etiology. Conclusion: Our signature-based fragmentomics framework, which decouples the contributions of distinct processes while identifying the epigenomic determinants of their genome-wide rates, can improve our understanding of cell-free DNA fragmentation in cancer. Citation Format: Yoo-Na Kim, Sangmi Lee, Allen Lynch, Tae Hee Kim, Peter J Park, Doga Gulhan. A novel framework for epigenome-dependent multimodal fragment-signature analysis reveals insights into cell-free DNA generation in cancer [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 PR020.
Read full abstract