Early Diagnosis and Prognostic Prediction of Colorectal Cancer through Plasma Methylation Regions

Cell-free DNA (cfDNA) methylation is a valuable biomarker in various cancers including colorectal cancer (CRC), but marker for both early diagnosis and prognostic prediction remain a critical unmet need. Here, we report the development of a 27-DMR (differentially methylated regions) plasma panel with dual diagnostic and prognostic functions. We first identified CRC-specific methylation features from 119 tissue samples and 161 plasma samples. Machine learning algorithms were then applied to develop diagnosis and prognosis models using the plasma samples in training cohort. In the tissue external validation cohort (GSE48684), the cfDNA methylation diagnosis model conducted with the panel, achieved an area under the curve (AUC) of 0.983, and for the plasma cfDNA model in the external validation cohort, the sensitivities for NAA, AA and CRC 0 - II are 48.4%, 52.2% and 66.7% respectively, with a specificity of 88%. Beyond its diagnostic capabilities, the methylation panel was also a powerful predictor of distant metastasis (AUC = 0.955) and patient prognosis (AUC = 0.867). Using normal samples as control, the changes in methylation score in both tissue and plasma were consistent across different lesions, although the degree of alterations varied with severity. The methylation scores vary between paired tissue and blood samples, suggesting distinct mechanisms of migration from tumor tissue to blood for the 27 DMRs. Together, our cfDNA methylation models based on 27 DMRs can identify different stages of CRC and predict metastasis and prognosis, ultimately enabling early intervention and risk stratification for CRC patients.