Cancer-related features in cell-free DNA (cfDNA) fragments have gradually been identified and play essential roles for non-invasive early cancer detection. Integrated analysis of several cfDNA features have proven to achieve enhanced detection sensitivity as compared to single feature.~This study aims to develop and validate a novel blood-based whole methylome sequencing followed with a multi-dimensional model to analyze several features of cfDNA for GC early detection. Specifically, blood samples will be prospectively collected before gastroscopy. Cases and controls will be randomly divided into a training and a testing dataset at a ratio of 2:1. Plasma cfDNA will be isolated and extracted, followed with a bisulfite-free low-depth whole methylome sequencing. A multi-dimensional model named THorough Epigenetic Marker Integration Solution (THEMIS) including methylation, fragmentation, and chromosomal copy number alternation will be constructed in the training dataset. The performance of the model in differentiating cancer patients from non-cancer controls will then be evaluated in the testing dataset.
To facilitate the early gastric cancer diagnosis, an assay based on assessing large-scale methylation and fragmentation profiles of the plasma cell free (cfDNA) will be developed and validated.