Most detection methods analyzing DNA methylation rely on bis

Most detection methods analyzing DNA methylation rely on bisulfite conversion of DNA allowing for the detection of single CpGs while at the same time impeding further PCR amplification and thus, analysis of additional regions of interest. This limits detection of methyl-specific priming (MSP) to 10 simultaneous performed reactions Sanders et al., 2012 and less than 5 for MethyLight™, respectively Fackler et al., 2014; Olkhov-Mitsel et al., 2014. In order to address as many methylation changes as possible in limited clinical samples, we chose high multiplexing methyl-sensitive restriction enzyme (MSRE) qPCR for stabilization of prediction and diagnostic accuracy Weinhaeusel et al., 2008; Melnikov et al., 2005 which allowed for the simultaneous performance of 96 qPCRs in cfDNA from 400μl plasma.
Methods
Results
Discussion The goal of our study was to identify methylation biomarkers for cfDNA that permit an effective discrimination between overlapping and multifactorial lung diseases, such as cancer, ILD, and COPD (Table 1). Given the complex and intertwined pathology of these diseases, it is likely that epigenetic mechanisms, such as CpG dinucleotide methylation, contribute to their clinical phenotypes. Aberrant methylation has already been demonstrated for diseases like lung cancer, autoimmunity, immunodeficiency and neuronal regeneration defects Robertson, 2005. Yet, both detection and monitoring of such complex clinical states remain a considerable challenge Crowley et al., 2013. This is also true for the group of fibrotic ILD and for COPD, which currently accounts for 260 million patients worldwide and an annual pgi2 comparable to that of cancer Organization WH, 2011. Given the fact that both diseases show an increased risk of cancer development Tomassetti et al., 2015; Koshiol et al., 2009, it is conceivable that comparable epigenetic regulations will contribute to their pathologies in spite of existing phenotypical differences. It is unlikely that a molecular discrimination between these diseases can be achieved using a single marker. Therefore, there is a need for a directed modeling of marker panels Brock et al., 2008; Bruse et al., 2014; Nikolaidis et al., 2012; Begum et al., 2011 as shown in our approach. Analysis of DNA methylation in plasma samples is well suited for such a goal Crowley et al., 2013; Fleischhacker et al., 2013. DNA methylation analysis largely relies on bisulfite conversion of cfDNA. This technique is characterized by an unavoidable degradation of DNA and a substantial loss of sequence complexity resulting in decreased sensitivity and specificity during PCR-based biomarker detection Egger et al., 2012. To overcome these technical limitations, we used a multiplexed MSRE enrichment strategy allowing for the reduction of unmethylated background DNA followed by simultaneous amplification of 96 targets (Supplemental Fig. S11). Prior to any classification efforts based on patients DNA methylation, the contribution of the cfDNA amount was removed from the data by delta Ct normalization to be specific for disease derived methylation changes (Supplemental Figs. S6 & S7). The elevated cfDNA levels, however, were included as a separate predictor with in the study. Such an increase of cfDNA was frequently observed for diverse cancers Wielscher et al., 2011; Jung et al., 2004; Dawson et al., 2013 and late stage COPD patients Gormally et al., 2004. The presence of DNA exhibiting disease marks in serum may be due to an interplay of several mechanisms Schwarzenbach et al., 2011. Necrosis of diseased cells, but also apoptotic cell death driven by inflammation or tissue repair, leads to increased DNA amounts Choi et al., 2005; Schulte-Hermann et al., 1995 in fibrosis patients and COPD patients (Fig. 2A). For cancer, additionally, the active release of DNA by cancer cells may be a reason for increased DNA amounts in patient sera Stroun and Anker, 2005.