## 4 Discussion  
In this study, we have utilized bisulfite-based methylation-specific region sequencing [19] to monitor methylation of circulating free DNA in metastatic melanoma patients. The key to the success of this approach is designing appropriate primers, which amplify regions capable of distinguishing healthy controls from patients with cutaneous melanoma using bisulfite converted DNA. Other techniques for monitoring circulating free DNA in the context of melanoma, such as targeted next generation, typically work with an input circulating free DNA of around 20 ng [14]. Although ddPCR is capable of working efficiently with circulating free DNA as low as 1 ng, it does require prior knowledge of the mutation and typically only follows one gene target. Our current methylation approach utilized comparable amounts of input circulating free DNA to that used in targeted sequencing and in addition, resulted in a bisulfite conversion efficiency that approached 100%. We were able to achieve meaningful methylation data on our cohort samples, consisting of five healthy control samples and five melanoma patient samples, using an average circulating free DNA input of ~19 ng with a resulting bisulfite conversion efficiency of 99.6% to 99.9% followed by successful amplification of all our targeted DNA regions. It should be noted that our methylation amplification control did not show the theoretical methylation levels of 50%. According to Qiagen (technical support communication) they cannot guarantee 100% methylation of the human genomic DNA used to generate this control, and their testing of this control does not use the same gene targets as used in this study. Furthermore, we cannot assume 50% methylation of our target genes in the mixed control sample considering there is evidence for bisulfite-induced selective degradation of DNA [43; 44]. We should also emphasize that in this study we were comparing the relative amounts of DNA methylation rather than absolute methylation quantitation. Our comparison included healthy controls versus melanoma cases that were treated and measured under the same conditions. We chose DNA target regions corresponding to the CpG rich regions of seven genes (_GJB2_, _HOXA9_, _MEOX2_, _OLG3_, _PON3_, _RASSF1_, _TEAP2B_) shown to be hypermethylated in late-stage melanoma patients [24; 25; 36; 37; 38; 39; 40]. These previous melanoma studies were based on genome wide methylation arrays using genomic DNA followed by validation with more targeted assays that captured methylation of individual CpG sites in one DNA strand. Our current workflow quantifies the levels of methylation for individual, targeted CpG sites using circulating free DNA and also maximizes the methylation information gained by separately interrogating the Watson and Crick strands of DNA. This provides additional discriminatory power to assess methylation of individual CpG sites, and data can be analyzed based on the fraction of methylation at individual CpG sites or based on the median of the fraction methylation of several CpG sites present in each target gene. Both approaches were found to have significant predictive value in discriminating between metastatic melanoma patients and healthy controls. Overall though, the approach based on methylation of CpG sites within a particular gene showed the most significance. We also observed symmetrical methylation in most of our target genes across our cohort, which supports previous reports that CpG sites are thought to be symmetrically methylated [45; 46; 47]. Designing primers for both DNA strands doubled the chances of obtaining an amplified product and also offers the significant advantage of looking at the methylation of both strands. We did observe variation in the symmetrical methylation across individual target genes, particularly _OLIG3_, as well as within individual melanoma patients. Although we can only speculate as to the cause of this variation, it may be indicative of PCR amplification bias or biological variation.