Abstract
Background: Colorectal cancer (CRC) presents a major health burden worldwide, and there has been a consistent increase in CRC incidence, particularly in younger people (age < 50 years) where the disease is often presented at an advanced stage. Prognosis and survival of CRC patients rely heavily on the stage at diagnosis—the earlier, the better. Epigenetic changes are a universal and hallmark feature of cancer, and recent studies from ourselves and others have provided strong evidence that epigenetic drivers play a key role in cancer progression and could be used as early markers. Further, the development of cell-free tumour DNA (ctDNA) methylation analysis represents a major step towards improving the diagnosis and management of cancer.
Results: We have streamlined and utilised genome-scale DNA methylation analysis methods (using reduced representation bisulfite sequencing or RRBS) for clinical samples along with RNA-Sequencing for functional epigenomic analysis on tissue samples. In addition, we have streamlined RRBS technology to generate ultra-low-input (5 ng) DNA methylome in critical clinical samples such as formalin-fixed paraffin-embedded (FFPE) tissues and cell-free DNA. We are also developing novel machine-learning-based algorithm to analyse large epigenomic data. Our study led to the identification of epigenetic (DNA methylation) drivers for both early and late stages of CRC. These putative methylation driver regions were associated with critical cancer cell pathways and function. Our CRISPR-based DNA methylation editing work indicates that many of these drivers can directly control gene expression without any changes to the underlying DNA sequence. In our cell-free DNA methylome work, we are able to generate robust and reproducible data from small amount of ctDNA. Our results showed discriminatory methylation difference between malignant and non-malignant conditions and demonstrated high sensitivity and specificity.
Conclusions: We were able to identify epigenetic driver in both tissue and ctDNA from patient samples. For future clinical application, our research will contribute to the development and application of sensitive methylation-based non-invasive methods for the detection and monitoring of cancer and potentially will identify new epigenetic targets for therapeutic benefits, which will contribute to improved patient outcome.