AUTHOR=Zhang Mingguang , Dong Shuohui , Rao Wei , Mei Shiwen , Hu Gang , Liu Ling , Wang Zhen , Tang Jianqiang 

TITLE=Comprehensive fragmentation of cell-free repetitive DNA for enhanced cancer detection in plasma

JOURNAL=Frontiers in Cell and Developmental Biology

VOLUME=Volume 13 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/cell-and-developmental-biology/articles/10.3389/fcell.2025.1630231

DOI=10.3389/fcell.2025.1630231

ISSN=2296-634X

ABSTRACT=BackgroundRepetitive elements account for a large proportion of the human genome and undergo alterations during early tumorigenesis. However, the exclusive fragmentation pattern of DNA-derived cell-free repetitive elements (cfREs) remains unclear.MethodsThis study enrolled 32 healthy volunteers and 112 patients with five types of cancer. A novel repetitive fragmentomics approach was proposed to profile cfREs using low-pass whole genome sequencing (WGS). Five innovative repetitive fragmentomic features were designed: fragment ratio, fragment length, fragment distribution, fragment complexity, and fragment expansion. A machine learning-based multimodal model was developed using these features.ResultsThe multimodal model achieved high prediction performance for early tumor detection, even at ultra-low sequencing depths (0.1×, AUC = 0.9824). Alu and short tandem repeat (STR) were identified as the primary cfREs after filtering out low-efficiency subfamilies. Characterization of cfREs within tumor-specific regulatory regions enabled accurate tissue-of-origin (TOO) prediction (0.1×, accuracy = 0.8286) and identified aberrantly transcribed tumor driver genes.ConclusionThis study highlights the abundance of repetitive DNA in plasma. The innovative fragmentomics approach provides a sensitive, robust, and cost-effective method for early tumor detection and localization.