Abstract
The use of non-invasive liquid biopsy-based cell-free DNA (cfDNA) analysis is an emerging method of cancer detection and intervention. Different analytical methodologies are used to investigate cfDNA characteristics, resulting in costly and long analysis processes needed for combining different data. This study investigates the possibility of using cfDNA data converted for methylation analysis for combining the cfDNA fragment size with copy number variation (CNV) in the context of early colorectal cancer detection. Specifically, we focused on comparing enzymatically and bisulfite-converted data for evaluating cfDNA fragments belonging to chromosome 18. Chromosome 18 is often reported to be deleted in colorectal cancer. We used counts of short and medium cfDNA fragments of chromosome 18 and trained a linear model (LDA) on a set of 2959 regions to predict early-stage (I-IIA) colorectal cancer on an independent test set. In total, 87.5% sensitivity and 92% specificity were obtained on the enzymatically converted libraries. Repeating the same workflow on bisulfite-converted data yielded lower accuracy results with 58.3% sensitivity, implying that enzymatic conversion preserves the cancer fragmentation footprint in whole genome data better than bisulfite conversion. These results could serve as a promising new avenue for the early detection of colorectal cancer using fragmentation and methylation approaches on the same datasets.