Pan-cancer landscape of abnormal ctDNA methylation across human tumors

Background: The aim of this paper is to explore the correlation between circulating tumor DNA (ctDNA) methylation and mutations and its value in clinical early cancer screening. Methods: We performed target region methylation sequencing and genome sequencing on plasma samples. Methylation models to distinguish cancer from healthy individuals have been developed using hypermethylated genes in tumors and validated in training set and prediction set. Results: We found that patients with cancer had higher levels of ctDNA methylation compared to healthy individuals. The level of ctDNA methylation in cell cycle, p53, Notch pathway in pan-cancer was significantly correlated with the number of mutations, and mutation frequency. Methylation burden in some tumors was significantly correlated with tumor mutational burden (TMB), microsatellite instability (MSI) and PD-L1. The ctDNA methylation differences in cancer patients were mainly concentrated in the Herpes simplex virus 1 infection pathway. The area under curve (AUC) of the training and prediction sets of the methylation model distinguishing cancer from healthy individuals were 0.93 and 0.92, respectively. Conclusion: Our study provides a landscape of methylation levels of important pathways in pan-cancer. ctDNA methylation significantly correlates with mutation type, frequency and number, providing a reference for clinical application of ctDNA methylation in early cancer screening. (c) 2022 Published by Elsevier Inc.