Multimodal analysis of methylomics and fragmentomics in plasma cell-free DNA for multi-cancer early detection and localization
Abstract
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 (∼0.55X) 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. 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 62.3% and 73.9% for stage I and II, respectively, increasing to 88.3% for nonmetastatic 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.
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