## 4 Discussion
We cannot rule out PCR amplification bias or duplications as we have not included unique molecular identifiers (UMIs). It was not feasible to use UMIs in our current system as the amount of starting DNA was too small. To help control for PCR bias, we did ensure that the primers for all of our amplicons were located in regions that do not contain CpG sites. To adequately address the issue of biological variations, larger cohort studies with longitudinal sampling will be required. Based on the median of the fraction methylation for CpG sites within a particular target gene region, we were able to identify two genes, _PON3_ and _OLIG3_, for which increased methylation of circulating free DNA was shown to have the highest possible predictive value (AUC = 1.00 for ROC curves) for identifying patients with advanced melanoma. Our findings are supported by a previous study, which showed increased methylation of the promoter region of _PON3_ genomic DNA, independent of tumor thickness and ulceration, to be significantly associated with poor prognosis when comparing primary melanoma against benign nevi [24]. This study did not report on whether _PON3_ methylation patterns were independent of _BRAF_ or _NRAS_ mutational status [24]. Increased methylation of _OLIG3_ genomic DNA was also found to be associated with reduced overall survival in primary melanoma but was found not be significant in a subsequent multivariate analysis [24]. Based on increased methylation of circulating free DNA, we identified four other genes, _HOXA9_, _MEOX2_, _RASSF1_ and _GJB2_, that also have high predictive values for diagnosing metastatic melanoma patients (AUCs ranging from 0.8 to 0.96 for ROC curves). Increased methylation of _MEOX2_ genomic DNA was also found to be associated with reduced overall survival in primary melanoma but was found not be significant in a subsequent multivariate analysis [24]. This study also identified hypermethylation of _GJB2_ and _HOXA9_ along with _MEOX2_, to be associated with melanoma progression based on comparing primary versus metastatic melanoma [24]. A bioinformatics-based analysis has indicated that hypermethylation of the _RASSF1_ promoter region is associated with susceptibility to melanoma but is not in itself of prognostic value [36]. In our current study, we did not find any value associated with monitoring methylation of _TFAP2B_ in melanoma patients (AUC of 0.56 for a ROC curve). Reduced TFAP2B protein expression, presumably due to increased methylation, was found to be associated with shorter progression-free survival in melanoma patients but was found not to be significant in a multivariate analysis [24]. We also compared the levels of methylated CpG within the target genes to ctDNA copy number based on ddPCR and found significant correlation only for the genes _PON3_ and _MEOX2_. Generally, the levels of ctDNA in melanoma patients provide a predictor of tumor burden and response to therapy [6; 7; 48]. In our study, the hypermethylation of _PON3_ provided the highest predictive value for identifying metastatic melanoma patients, and this supports a previous study analyzing _PON3_ methylation using melanoma tissue-derived genomic DNA [24]. Changes in methylation of _PON3_, also based on analysis of genomic DNA, have been reported to be associated with drug resistance in esophageal cancer, adverse outcomes in prostate cancer and to be predictive of chemotherapy response in colorectal cancer [49; 50; 51]. Having established a viable workflow for detection of methylation using small amounts of low molecular weight circulating free DNA from plasma, we can now focus on larger cohorts and additional targets to establish the value of such a liquid biopsy as a biomarker in the diagnosis and monitoring of melanoma patients.