Cell-free DNA end characteristics enable accurate and sensitive cancer diagnosis
The fragmentation patterns of cell-free DNA (cfDNA) in plasma can potentially be utilized as diagnostic biomarkers in liquid biopsy. However, our knowledge of this biological process and the information encoded in fragmentation patterns remains preliminary. Here, we investigated the cfDNA fragmentomic characteristics against nucleosome positioning patterns in hematopoietic cells. cfDNA molecules with ends located within nucleosomes were relatively shorter with altered end motif patterns, demonstrating the feasibility of enriching tumor-derived cfDNA in patients with cancer through the selection of molecules possessing such ends. We then developed three cfDNA fragmentomic metrics after end selection, which showed significant alterations in patients with cancer and enabled cancer diagnosis. By incorporating machine learning, we further built high-performance diagnostic models, which achieved an overall area under the curve of 0.95 and 85.1% sensitivity at 95% specificity. Hence, our investigations explored the end characteristics of cfDNA fragmentomics and their merits in building accurate and sensitive cancer diagnostic models.
Authors
- Yunyun An (ORCID: https://orcid.org/0000-0001-8662-5535)
- Zhaohua Xia
- Dingxue Hu (ORCID: https://orcid.org/0000-0003-3137-4331)
- Jia Ju
- Kun Sun (ORCID: https://orcid.org/0000-0002-9883-1616)
- Xiaoyi Liu (ORCID: https://orcid.org/0009-0006-5862-2031)
- Xin Zhao (ORCID: https://orcid.org/0000-0003-2860-5899)
- Fei Fan (ORCID: https://orcid.org/0000-0002-1738-9150)
- Wanqiu Wang (ORCID: https://orcid.org/0000-0002-2748-5867)
- Ziteng Zhang (ORCID: https://orcid.org/0009-0001-0851-0502)
- Mengqi Yang (ORCID: https://orcid.org/0009-0005-8228-4565)
- Yuqi Pan
Institutions
- Union Hospital (HK)
- Southern University of Science and Technology (CN)
- Shenzhen Bay Laboratory (CN)
- Shenzhen Second People's Hospital (CN)
- Huazhong University of Science and Technology (CN)
Publication Details
- Journal
- Cell Reports Methods
- Published
- 2024-10-01
- DOI
- https://doi.org/10.1016/j.crmeth.2024.100877
- Citations
- 19
- Primary Topic
- Cancer Genomics and Diagnostics
- Type
- article
- Field-Weighted Citation Impact
- 5.42
Funders
- National Natural Science Foundation of China
- Science, Technology and Innovation Commission of Shenzhen Municipality
- Shenzhen Bay Laboratory
- Key Technologies Research and Development Program
- Basic and Applied Basic Research Foundation of Guangdong Province