Design of the project: 1) Participants who sign informed consent forms will complete the disease history information collection;2) Collect samples of cancer tissue and corresponding paracancer samples, as well as peripheral blood; 3) Using the MONOD patent detection data of the company's previous research and combining with literature retrieval, to analyze the tissue samples of digestive system cancers to screen the methylation mutation sites;4) ctDNA methylation markers are preliminarily screened by plasma of healthy persons paired with tissues;5) Using the screened blood ctDNA specific methylation markers together with other molecular markers to establish a targeted detection method for early digestive system cancer lesions;6) Retain the most distinguishing targets in the original panel test and establish the second version of the panel;7) Establish and validate predictive models to finalize multitype molecular target detection for peripheral blood DNA;8) Construct statistical learning models based on ctDNA methylation and fragment features, miRNA7™ and CTC, and optimize the models respectively;9) Evaluate the sensitivity and specificity of the models in cancer early detection.
This is a single blind, case control, multicenter study jointly developed by Zhongshan Hospital of Fudan University, Shanghai Public Health Clinical Center, Shanghai Xuhui Central Hospital, Qingpu Branch of Zhongshan Hospital Affiliated to Fudan University, and Shanghai Singlera Genomics Company. The enrolled population will include positive group, precancerous lesions and healthy control group, which is expected to enroll 2,430 participants. The primary objective is to establish molecular testing methods for non-invasive screening and early diagnosis of digestive system cancers through ctDNA methylation and mutation, cfDNA and ctDNA fragment size, and end motif based model (for esophageal, gastric, colorectal cancer), and through ctDNA methylation detection, ctDNA low-pass WGS, miRNA7 and CTC detection and analysis technology based model (for hepatocellular carcinoma). The sensitivity and specificity of the models in cancer early detection will be evaluated.