Abstract
62 Background: In an era marked by a global rise in cancer-related morbidity and mortality, the development of liquid biopsy screening tests that can detect and localize cancer at an early stage holds tremendous potential to revolutionize cancer diagnosis and therapy. However, challenges in test performance and cost must still be overcome, due mostly to the limited abundance of circulating tumor DNA and its inherent variability. To address these challenges, published liquid biopsy assays to date demanded a very high-depth sequencing or a combination of protein and genetic biomarkers, resulting in an elevated price of test. Methods: 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 (with a depth coverage of ~0.55X) of cell-free DNA. We applied SPOT-MAS to 738 nonmetastatic patients with breast, colorectal, gastric, lung and liver cancer, and 1,550 healthy controls to extract multiple discriminative signatures for detecting and locating cancer. Results: SPOT-MAS detected the five cancer types with an overall sensitivity of 72.4% (range: 49.3% to 91.1%) at a specificity of 97.0%. The sensitivities for detecting early-stage cancers including stage I and II were 62.3% and 73.9%, respectively, increasing to 88.3% for nonmetastatic cancers (stage IIIA). For tumor-of-origin, a graph convolutional neural network was adopted and could achieve an accuracy of 70%. Conclusions: Our study demonstrates comparable performance to other early cancer detection assays while requiring significantly lower sequencing depth, making it economically feasible for population-wide screening in low-income countries.
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