Utility of cfDNA Fragmentation Patterns in Designing the Liquid Biopsy Profiling Panels to Improve Their Sensitivity

Abstract

Genotyping of cell-free DNA (cfDNA) in plasma samples has the potential to allow for a noninvasive assessment of tumor biology, avoiding the inherent shortcomings of tissue biopsy. Next generation sequencing (NGS), a leading technology for liquid biopsy analysis, continues to be hurdled with several major issues with cfDNA samples, including low cfDNA concentration and high fragmentation. In this study, by employing Ion Torrent PGM semiconductor technology, we performed a comparison between two multi-biomarker amplicon-based NGS panels characterized by a substantial difference in average amplicon length. In course of the analysis of the peripheral blood from 13 diagnostic non-small cell lung cancer patients, equivalence of two panels, in terms of overall diagnostic sensitivity and specificity was shown. A pairwise comparison of the allele frequencies for the same somatic variants obtained from the pairs of panel-specific amplicons, demonstrated an identical analytical sensitivity in range of 140 to 170 bp amplicons in size. Further regression analysis between amplicon length and its coverage, illustrated that NGS sequencing of plasma cfDNA equally tolerates amplicons with lengths in the range of 120 to 170 bp. To increase the sensitivity of mutation detection in cfDNA, we performed a computational analysis of the features associated with genome-wide nucleosome maps, evident from the data on the prevalence of cfDNA fragments of certain sizes and their fragmentation patterns. By leveraging the support vector machine-based machine learning approach, we showed that a combination of nucleosome map associated features with GC content, results in the increased accuracy of prediction of high inter-sample sequencing coverage variation (areas under the receiver operating curve: 0.75, 95% CI: 0.750–0.752 vs. 0.65, 95% CI: 0.63–0.67). Thus, nucleosome-guided fragmentation should be utilized as a guide to design amplicon-based NGS panels for the genotyping of cfDNA samples.

Toward the Early Detection of Cancer by Decoding the Epigenetic and Environmental Fingerprints of Cell-Free DNA

“…For most of the cancer hallmarks, their effects on ctDNA release are still unknown, and the direct cause of ctDNA shortening has not been clearly demonstrated (Hanahan and Weinberg, 2011). Leveraging the Genome-wide Fragmentation of cfDNA Boosts Liquid Biopsy Despite these unknowns, the genome-wide fragmentation of cfDNA can be leveraged to boost existing methods and unlock new applications for liquid biopsy (Ivanov et al, 2015(Ivanov et al, , 2019Mouliere et al, 2018a;Snyder et al, 2016) (Figure 4B and Table 1). Mouliere et al developed a machine-learning method that can learn from the genome-wide fragmentation features of cfDNA to detect multiple cancer types in plasma (Mouliere et al, 2018a).…”

Properties and Application of Cell-Free DNA as a Clinical Biomarker

“…Both ALU and LINE1 sequences are distributed throughout the genome. In recent years, both n-cfDNA and mt-cfDNA have been used to examine mutations, methylation, copy-number variations (CNVs), cfDNA composition, and cfDNA fragmentation [97][98][99][100][101]. Some molecular biology techniques have been used to analyze cfDNA from plasma samples, including fluorescence [15], polymerase chain reaction (PCR) [9,14], quantitative real-time PCR (RT-qPCR) [16,[102][103][104][105][106][107][108][109][110], droplet digital PCR (ddPCR) [87,[111][112][113][114][115][116], array [111,117] and sequencing [86,[105][106][107]113,[117][118][119][120][121][122][123][124][125][126][127].…”

Fragmentomic cfDNA Patterns in Noninvasive Prenatal Testing and Beyond

“…Integrating cfDNA fragmentomic information has already been shown to improve testing sensitivity in noninvasive cancer diagnostics and screening. 92,93 One of the major hurdles in prenatal screening is the accurate determination of the fetal fraction. This review has touched upon several identified fragmentomic markers that can be used to approach the fetal fraction, or more generally, to determine the maternal or fetal origin of variants observed using NIPT.…”