Towards comprehensive DNA methylation analysis using molecular inversion probes

Abstract

Methylation of cytosine is emerging as a potential biomarker of cancer because it has been associated with ‘lifestyle’ induced changes to DNA. Despite its potential, monitoring methylation of cytosine in genomic DNA is complicated by transient and/or heterogeneous methylation within a region of interest. As a result, conventional analytical technologies often only reveal cytosine methylation in selected DNA sequences or ‘epialleles’. This can confound any association between methylation and the development and progression of cancer. Therefore, to enable a comprehensive methylation analysis, this thesis outlines the development of a novel technique designed to detect cytosine methylation in bisulfite-treated DNA. The technique utilises the multiplexability and specificity of molecular inversion probes (MIPs). It is anticipated that this may serve as a useful method to validate DNA methylation biomarkers, which may be used to better diagnose the onset and progression of breast cancer. This thesis demonstrates the adaption of MIP technology to detect cytosine methylation in genomic DNA extracts. The methylation signature of a cytosine in genomic DNA has been analysed. The cytosine methylation was rapidly quantified with high, sensitivity and specificity over a large dynamic range. The assay has been shown to be multiplexible by using microbead DNA biosensors with a rapid flow cytometric readout. In addition, the technology has been shown to be useful for the analysis of a cytosine methylation found within a complex methylation landscape. This was achieved using MIPs containing universal nucleotide bases (inosine) that were designed to complement suspected methylation sites that were adjacent to the region of interest. Finally, this thesis demonstrates how the methylation pattern of cytosines could be analysed using MIPs to reveal different epialleles. This involved designing MIPs that could be used with a DNA polymerase that replicated all epialleles in the region of interest. This level of molecular analysis has the potential to be used for screening epigenetic changes important for cancer and, in turn, may aid in directing treatments for applications of personalised therapy.