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

Abstract

Using epigenetic markers and fragmentomics of cell-free DNA for cancer detection has been proven applicable. We further combine the two features and explore the diagnostic potential of the features on pan-cancer detection. We extracted cfDNA fragmentomic features from 191 whole-genome sequencing data and investigated them in 396 low-pass 5hmC sequencing data from four common cancer types and controls. We identified aberrant ultra-long fragments (220-500bp) of cancer samples in 5hmC sequencing data, both in size and coverage profile, and showed its dominant role in cancer prediction. Since cfDNA hydroxymethylation and fragmentomic markers can be detected simultaneously in low-pass 5hmC sequencing data, we built an integrated model including 63 features of both fragmentomic features and hydroxymethylation signatures 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.