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Multimodal analysis of methylomics and fragmentomics in plasma cell-free DNA for multi-cancer early detection and localization

2023; eLife Sciences Publications Ltd; Volume: 12; Linguagem: Inglês

10.7554/elife.89083

2050-084X

Van Thien Chi Nguyen, Trong Hieu Nguyen, Nhu Nhat Tan Doan, Thi Mong Quynh Pham, Giang Nguyen, Thanh Dat Nguyen, Thuy Thi Thu Tran, Vo Duy Long, Thanh Hai Phan, Thanh Xuan Jasmine, Chu Van Nguyen, Huu Thinh Nguyen, Trieu Vu Nguyen, Thi Hue Hanh Nguyen, Le Anh Khoa Huynh, Trung Hieu Tran, Dang Quang Thong, Thuy Nguyen Doan, Anh Minh Tran, Viet Hai Nguyen, Vu Tuan Anh Nguyen, Le Minh Quoc Ho, Quang Dat Tran, Thi Thu Thuy Pham, Tan Dat Ho, Bao Toan Nguyen, Thanh Nhan Vo Nguyen, Thanh Dang Nguyen, Dung Thai Bieu Phu, Boi Hoan Huu Phan, Thi Loan Vo, Thi Huong Thoang Nai, Thuy Trang Tran, My Hoang Truong, Ngan Chau Tran, Trung Kien Le, Hương Thanh Trần, Minh Long Duong, Hoai Phuong Thi Bach, Van Vu Kim, The Anh Pham, Duc Huy Tran, Trinh Ngoc An Le, Truong Vinh Ngoc Pham, Minh Triết Lê, Dac Ho Vo, Thi Minh Thu Tran, Minh Nguyen Nguyen, Thi Tuong Vi Van, Anh Nhu Nguyen, Thi Trang Tran, Vu Uyen Tran, Minh Phong Le, Thi Thanh, Thi Van Phan, Lưu Hồng Đăng Nguyễn, Duy Sinh Nguyen, Van Thinh Cao, Thanh-Thuy Thi, Dinh Kiet Truong, Hung Sang Tang, Hoa Giang, Hoai-Nghia Nguyen, Minh‐Duy Phan, Le Son Tran,

Single-cell and spatial transcriptomics

Despite their promise, circulating tumor DNA (ctDNA)-based assays for multi-cancer early detection face challenges in test performance, due mostly to the limited abundance of ctDNA and its inherent variability. To address these challenges, published assays to date demanded a very high-depth sequencing, resulting in an elevated price of test. Herein, we developed a multimodal assay called SPOT-MAS (screening for the presence of tumor by methylation and size) to simultaneously profile methylomics, fragmentomics, copy number, and end motifs in a single workflow using targeted and shallow genome-wide sequencing (~0.55×) of cell-free DNA. We applied SPOT-MAS to 738 non-metastatic patients with breast, colorectal, gastric, lung, and liver cancer, and 1550 healthy controls. We then employed machine learning to extract multiple cancer and tissue-specific signatures for detecting and locating cancer. SPOT-MAS successfully detected the five cancer types with a sensitivity of 72.4% at 97.0% specificity. The sensitivities for detecting early-stage cancers were 73.9% and 62.3% for stages I and II, respectively, increasing to 88.3% for non-metastatic stage IIIA. For tumor-of-origin, our assay achieved an accuracy of 0.7. Our study demonstrates comparable performance to other ctDNA-based assays while requiring significantly lower sequencing depth, making it economically feasible for population-wide screening.