Cell-Free DNA in Dermatology Research

Abstract

In various diseases, particularly cancer, cell-free DNA (cfDNA) has been widely studied as a marker of disease prognosis or to facilitate the detection of therapeutic targets. In dermatology, most studies have focused on melanoma; other skin diseases such as vascular malformations and psoriasis have also been examined. Genetic alterations unique to the tissue of origin such as sequence variations, copy number alterations, chromosomal rearrangements, differential DNA methylation patterns, and fragmentation patterns can be identified in circulation providing information on patient disease status. These alterations can be detected either by PCR-based methods or next-generation sequencing depending on the target of interest. In this article, we discuss the origins of cfDNA, the most common methods of detection, current studies assessing cfDNA as a biomarker, and cfDNA's potential clinical applications in melanoma and other skin diseases. In addition, we provide important factors to consider during blood processing and DNA extraction as well as limitations for each assay.

Figure 1:. Origins and clinical applications of cfDNA in Dermatology.

Non-encapsulated cfDNA can be present in any bodily fluid and derive from any cell type following normal cell turnover leading to apoptosis, necrosis or other mechanisms of cell death. In this example cfDNA is extracted from blood plasma.

Figure 2:. Methods to detect ctDNA in plasma.

Following cfDNA extraction, DNA alterations can be assessed via two main detection methods, droplet digital PCR (ddPCR) or next generation sequencing (NGS). ddPCR requires preparation of an amplification master mix with allele specific probes. The sample is partitioned into ~20,000 droplets. The targets of interest undergo end-point amplification within each droplet. Each droplet is analyzed by the droplet reader, providing absolute quantification. The workflow for NGS requires ligation of adaptors for each target, and a library preparation followed by an amplification step. Targets of interest are sequenced and analyzed using various bioinformatics tools.