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