Optimization of DNA methylation analysis using cell-free DNA for early detection of prostate cancer

Prostate cancer is the most commonly diagnosed cancer for men in the UK. The current diagnostic pathway for prostate cancer is imprecise and emerging protocols that include mpMRI offer an incomplete solution for early detection of clinically significant cancers. An accurate minimally invasive test is therefore needed to improve the detection of potentially lethal cancers. The analysis of circulating tumour DNA (ctDNA) has been increasingly used to detect genomic markers as it reflects the genomic landscape of active tumour in real-time. However, ctDNA can be present at low allelic-fractions and low absolute counts. In addition, commonly used methods that focus on hotspot mutations have narrow utility for prostate cancer, due to the limited number of recurrent mutations in this disease. To overcome the limited number of driver mutations and by-pass the hard limit of detection in earlier stage cancers, we have integrated highly recurrent stem events in the epigenome of prostate tumours to identify the most abundant ctDNA signals in plasma samples from prostate cancer patients. To explore empirical the limit of detection for methylation markers in cfDNA, we systematically evaluated (i) the errors imposed in specific steps, (ii) the recovery of informative cfDNA molecules, and (iii) the sequencing quality and complexity. We explore these parameters in our optimisation of cfDNA bisulfite conversion, library preparation and target enrichment methods. We will present a comprehensive summary of considerations for DNA methylation analysis in cfDNA, highlighted by the patterns of errors, as well as approaches to measure and overcome these errors by optimising bisulfite conversion and computational analyses. Our study aims to drive technical improvements in bisulfite sequencing technology and enhance the analysis of methylation in plasma DNA at thousands of targets, using prostate cancer ctDNA analysis as an exemplar.