Comput Struct Biotechnol J. 2022 ;20
26-39
Cell-free DNA(cfDNA) methylation profiling is considered promising and potentially reliable for liquid biopsy to study progress of diseases and develop reliable and consistent diagnostic and prognostic biomarkers. There are several different mechanisms responsible for the release of cfDNA in blood plasma, and henceforth it can provide information regarding dynamic changes in the human body. Due to the fragmented nature, low concentration of cfDNA, and high background noise, there are several challenges in its analysis for regular use in diagnosis of cancer. Such challenges in the analysis of the methylation profile of cfDNA are further aggravated due to heterogeneity, biomarker sensitivity, platform biases, and batch effects. This review delineates the origin of cfDNA methylation, its profiling, and associated computational problems in analysis for diagnosis. Here we also contemplate upon the multi-marker approach to handle the scenario of cancer heterogeneity and explore the utility of markers for 5hmC based cfDNA methylation pattern. Further, we provide a critical overview of deconvolution and machine learning methods for cfDNA methylation analysis. Our review of current methods reveals the potential for further improvement in analysis strategies for detecting early cancer using cfDNA methylation.
Keywords: Cancer heterogeneity; Cell free DNA; Computation; DMP, Differentially methylated base position; DMR, Differentially methylated regions; Diagnosis; HELP-seq, HpaII-tiny fragment Enrichment by Ligation-mediated PCR sequencing; MBD-seq, Methyl-CpG Binding Domain Protein Capture Sequencing; MCTA-seq, Methylated CpG tandems amplification and sequencing; MSCC, Methylation Sensitive Cut Counting; MSRE, methylation sensitive restriction enzymes; MeDIP-seq, Methylated DNA Immunoprecipitation Sequencing; RRBS, Reduced-Representation Bisulfite Sequencing; WGBS, Whole Genome Bisulfite Sequencing; cfDNA, cell free DNA; ctDNA, circulating tumor DNA; dPCR, digital polymerase chain reaction; ddMCP, droplet digital methylation-specific PCR; ddPCR, droplet digital polymerase chain reaction; scCGI, methylated CGIs at single cell level