Abstract Background: Cell-free DNA (cfDNA) profiling has emerged as a promising tool in cancer detection. Methods include the identification of circulating tumor DNA (ctDNA), the profiling of cfDNA methylation, and the analysis of cfDNA fragments, including fragment size and position. We previously showed that fragment size diversity is strongly correlated with gene expression (Esfahani et al, 2022). We subsequently developed a mechanistic model for the cfDNA fragmentation process to enhance gene expression inference from cfDNA (Liu et al, 2025). However, analysis of cfDNA fragment size distribution alone leaves out useful information about fragment position. Since fragment position arises from nucleosome position, we incorporate prior knowledge about nucleosome positioning to improve our cfDNA fragmentation models. We hypothesize that incorporating cell-type-specific nucleosome patterns can progress cfDNA models towards cell-type deconvolution. Methods: In order to incorporate prior knowledge about cell-type-specific nucleosome organization into our cfDNA fragmentation model, we use Micrococcal Nuclease sequencing (MNase-seq) data from (Valouev et al, 2011) and MNase-Transcription Start Site Sequence Capture method (mTSS-seq) data from (Druliner et al, 2016). For each transcription start site (TSS), we leverage this prior knowledge about nucleosome organization to simulate well-positioned nucleosomes. Then, we generate additional nucleosomes given the gene’s strand information and cell type. Next, we generate cuts, and generate a mixture of simulated fragments from various cell types. Results: In order to evaluate the efficacy of our updated cfDNA fragmentation model, we calculate the coverage over 10 bp intervals within a window of the TSS, and compare it with the coverage for cfDNA control samples. We also calculate the coverage for simulated cfDNA fragments using our previous model, and compare it with the coverage for cfDNA control samples. Our updated model incorporating prior knowledge about nucleosome organization outperformed our previous model in simulating cfDNA fragmentation. Conclusions: We show that integrating cell-type-specific nucleosome patterns improves cfDNA fragmentation models. Further improvements can be made given nucleosome organization information from additional cell types. We envision that this model-based approach will enhance tissue-of-origin classification and cancer detection. Citation Format: Brian Sun Liu, Mengran Zhang, Mohammad Shahrokh Esfahani, . Using cell-type-specific nucleosome patterns to improve cell-free DNA fragmentation models in lung cancer abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 6845.
Liu et al. (Fri,) studied this question.