Abstract
Traditional DNA methylation profiling techniques, such as whole-genome bisulfite sequencing (WGBS) and Illumina methylation arrays, rely on bisulfite conversion of DNA. While these methods are commonly used, bisulfite conversion introduces significant challenges. The harsh chemical conditions lead to DNA degradation, which is especially problematic for circulating tumor DNA (CtDNA) due to its already low and fragmented nature. Moreover, WGBS offers comprehensive profiling but is costly, and Illumina arrays, such as those used in The Cancer Genome Atlas (TCGA), cover only 1% of the human methylome, limiting their ability to discover biomarkers.
A promising alternative is third-generation methylation sequencing using Oxford Nanopore Technologies (ONT), which directly detects DNA modifications without the need for bisulfite treatment. ONT can distinguish between methyl- and hydroxymethyl-modified bases with over 92% accuracy and provides coverage of around 95% of CpG sites at base-pair resolution. This enables a more comprehensive analysis of methylation patterns, making it an attractive tool for biomarker discovery in cancer research.
In this project, we aim to leverage ONT long-read sequencing to expand the number of CpG sites analyzed, improving the precision and accuracy of cancer prediction models. Given that methylation differences across various cancer types are distributed throughout the methylome, this approach is expected to enhance our ability to accurately classify cancers. To achieve this, we have initiated a collaboration with UZA and Maria Middelares Hospital (Ghent) to obtain clinical samples from patients with different cancer types for sequencing experiments.
This project will also support the development of a novel, minimally invasive methylation assay being created by colleagues in the lab. Using ONT data, we will validate previously identified CpG markers and uncover additional, more comprehensive marker sets. These markers will then be incorporated into a multiplexed biomarker panel, which will be applied to CtDNA from liquid biopsies. Our ultimate goal is to refine cancer detection methodologies through the integration of more robust and comprehensive methylation data, thereby contributing to improved diagnostic and prognostic tools in oncology.
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