DNA methylation is a common epigenetic modification that maintains the integrity of the DNA sequence while profoundly influencing gene expression and phenotypic variation. Aberrant DNA methylation has been associated with the onset and progression of diseases, including cancer, metabolic disorders, and neurodevelopmental disorders. Recent advancements in detection technology led to a gradual increase in the exploration of DNA methylation as a valuable biomarker for cancer diagnosis and therapy. Single-base resolution has been achieved for whole-genome methylation analyses through second-generation sequencing technology, significantly enhancing detection efficiency. Additionally, PCR-based methods offer simple and feasible solutions for methylation analysis. In this review, we discuss various methods for detecting DNA methylation, focusing on bisulfite conversion-based techniques, methylation-sensitive restriction enzyme methods, enzyme conversion-based methods, third-generation sequencing approaches, and artificial intelligence. Furthermore, we briefly summarize the methylation biomarkers used for tumor diagnosis and the corresponding sample types employed. We believe that this information provides valuable insights for selecting and optimizing DNA methylation analysis tools.
Yang et al. (Mon,) studied this question.