Cost-effective methylome sequencing of cell-free DNA for accurately detecting and locating cancer
| Title: | 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, Pp 1-12 (2022) |
| Publisher Information: | Nature Portfolio, 2022. |
| Publication Year: | 2022 |
| Collection: | LCC:Science |
| Subject Terms: | Science |
| Description: | 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. |
| Document Type: | article |
| File Description: | electronic resource |
| Language: | English |
| ISSN: | 2041-1723 |
| Relation: | https://doaj.org/toc/2041-1723 |
| DOI: | 10.1038/s41467-022-32995-6 |
| Access URL: | https://doaj.org/article/20fb32eadefd4ac09f8fb1699d2139b7 |
| Accession Number: | edsdoj.20fb32eadefd4ac09f8fb1699d2139b7 |
| Database: | Directory of Open Access Journals |