Integrated fragmentomic profile and 5-Hydroxymethylcytosine of capture-based low-pass sequencing data enables pan-cancer detection via cfDNA

•In terms of 5hmC sequencing data, cancer samples contained lower proportion of ultra-long fragments than control, and ultra-long fragments showed the largest deviation to control in coverage profile.•cfDNA hydroxymethylation and fragmentomic markers for cancer detection can be simultaneously detected in low-pass 5hmC sequencing data.•An integrated model combined fragmentomic features and hydroxymethylation signatures for pan-cancer detection with high sensitivity and specificity was built, which was based on low-pass 5hmC sequencing data.•Ultra-long fragments related features dominated the high sensitivity and specificity pan-cancer detection model. Using epigenetic markers and fragmentomics of cell-free DNA for cancer detection has been proven applicable. We further investigated the diagnostic potential of combining two features (epigenetic markers and fragmentomic information) of cell-free DNA for detecting various types of cancers. To do this, we extracted cfDNA fragmentomic features from 191 whole-genome sequencing data and studied them in 396 low-pass 5hmC sequencing data, which included four common cancer types and control samples. In our analysis of 5hmC sequencing data from cancer samples, we observed aberrant ultra-long fragments (220–500 bp) that differed from normal samples in terms of both size and coverage profile. These fragments played a significant role in predicting cancer. Leveraging the ability to detect cfDNA hydroxymethylation and fragmentomic markers simultaneously in low-pass 5hmC sequencing data, we developed an integrated model that incorporated 63 features representing both fragmentomic features and hydroxymethylation signatures. This model achieved high sensitivity and specificity for pan-cancer detection (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.