Integrated fragmentomic profile of capture-based low-pass sequencing data enables pan-cancer detection via cfDNA

Using epigenetic markers and fragmentomics of cell-free DNA for cancer detection has been proved applicable. We further combine the two features and explore the diagnostic potential of the features on pan-cancer detection. cfDNA fragmentomic features of 396 low-pass 5hmC sequencing cfDNA data from four common cancer types and controls and corresponding WGS data were investigated. We detected pan-cancer preferred end marker specificity between WGS data and low-pass 5hmC sequencing data. We identified aberrant ultra-long fragments of cancer samples in 5hmC sequencing data, both in size and coverage profile, and showed its dominant role in cancer prediction. We built an integrated model including 63 features for pan-cancer detection with high sensitivity and specificity (88.52% and 82.35%, respectively). We showed that fragmentomic information in 5hmC sequencing data is an ideal marker for cancer detection and that it shows high performance in low-pass sequencing data.