Background: It is widely known that cell-free DNA (cfDNA) molecules maintain cell type-specific genetic and epigenetic characteristics. Molecular information from cell-free (cf)DNA is rapidly becoming the target of choice for noninvasive screening, diagnosis, treatment, and monitoring of human tumors. Liquid biopsy approaches currently implemented clinically are mostly based on detecting genetic differences in cfDNA molecules in healthy and diseased cells. Their diagnostic potential is limited to pathologies associated with genetic alterations due to the low proportion of cfDNA molecules carrying mutations compared to the total cfDNA pool and the detection limits of the techniques used. Recent research efforts have turned to the epigenetic signature of cfDNA molecules and discovered that the organization of origin of individual cfDNA molecules can be inferred from their epigenetic signature. For example, the cellular or tissue of origin of individual cfDNA molecules has been determined through analysis of methylation patterns, nucleosome or transcription factor binding site occupancy, fragment size distribution, or fragment terminal motifs and histone modifications. This tissue-of-origin analysis allows us to expand the portfolio of liquid biopsies beyond genetics by estimating the contribution of different tissues to the overall cfDNA pool in body fluids and finding tissues with increased apoptosis (a pathological condition).

Methods: Here, we describe an integrated workflow to analyze the genetic and epigenetic characteristics of a very small amount of cfDNA. We generated NGS data on genomic and epigenomic targets using a single strand-based DNA library prep method and report the results of analysis performance evaluation using target probes for 40 cancer genes and the Alliance Pan-cancer Methylation panel.

Results: Using 10ng and 20 ng of cell-free DNA, this assay demonstrated high sensitivity and low variant detection variability down to a single nucleotide variant VAF of 0.1% in standard samples, and was further supported by epigenetic signature analysis.

Conclusions: This method emphasizes the value of constructing a diverse gene panel for a wider range of diseases and easily analyzing genetic and epigenetic characteristics from a very small amount of cfDNA samples, obtaining and analyzing them in a comprehensive manner and using them for screening or diagnosis.