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Cost-effective methylome sequencing of cell-free DNA for accurately detecting and locating cancer

Authors :
Mary L. Stackpole
Weihua Zeng
Shuo Li
Chun-Chi Liu
Yonggang Zhou
Shanshan He
Angela Yeh
Ziye Wang
Fengzhu Sun
Qingjiao Li
Zuyang Yuan
Asli Yildirim
Pin-Jung Chen
Paul Winograd
Benjamin Tran
Yi-Te Lee
Paul Shize Li
Zorawar Noor
Megumi Yokomizo
Preeti Ahuja
Yazhen Zhu
Hsian-Rong Tseng
James S. Tomlinson
Edward Garon
Samuel French
Clara E. Magyar
Sarah Dry
Clara Lajonchere
Daniel Geschwind
Gina Choi
Sammy Saab
Frank Alber
Wing Hung Wong
Steven M. Dubinett
Denise R. Aberle
Vatche Agopian
Steven-Huy B. Han
Xiaohui Ni
Wenyuan Li
Xianghong Jasmine Zhou
Source :
Nature communications, vol 13, iss 1
Publication Year :
2022
Publisher :
Springer Science and Business Media LLC, 2022.

Abstract

Early cancer detection by cell-free DNA faces multiple challenges: low fraction of tumor cell-free DNA, molecular heterogeneity of cancer, and sample sizes that are not sufficient to reflect diverse patient populations. Here, we develop a cancer detection approach to address these challenges. It consists of an assay, cfMethyl-Seq, for cost-effective sequencing of the cell-free DNA 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 approach 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, allowing us to learn new features and expand to other cancer types as training cohorts grow.

Details

ISSN :
20411723
Volume :
13
Database :
OpenAIRE
Journal :
Nature Communications
Accession number :
edsair.doi.dedup.....3c6409ec866b5275eb7216b559d171e0