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Methylome sequencing of cell-free DNA and RRBS of solid tissue

Early cancer detection by cell-free DNA (cfDNA) faces multiple challenges: low fraction of tumor cfDNA, molecular heterogeneity of cancer, and sample sizes not sufficient to reflect diverse patient population. We develop a cancer detection approach to address these challenges. It consists of an assay, cfMethyl-Seq, for cost-effective sequencing of cfDNA methylome (with >12-fold enrichment over whole genome bisulfite sequencing in CpG islands), and a computational method to extract methylation information and diagnose patients. Applying our system to 408 colon, liver, lung, and stomach cancer patients and controls, at 97.9% specificity we achieve 80.7% and 74.5% sensitivity in detecting all-stage and early-stage cancer, and 89.1% and 85.0% accuracy for locating tissue-of-origin of all-stage and early-stage cancer, respectively. Our approach cost-effectively retains methylome profiles of cancer abnormalities, thereby permitting the classification models to learn new features as training cohorts grow, and expanding their scope to other cancer types.

Click on a Dataset ID in the table below to learn more, and to find out who to contact about access to these data

Dataset ID Description Technology Samples
EGAD00001009001 HiSeq X Ten 328
EGAD00001009003 HiSeq X Ten 479
Publications Citations
Cost-effective methylome sequencing of cell-free DNA for accurately detecting and locating cancer.
Nat Commun 13: 2022 5566
Comprehensive tissue deconvolution of cell-free DNA by deep learning for disease diagnosis and monitoring.
Proc Natl Acad Sci U S A 120: 2023 e2305236120