TY - JOUR
T1 - Multimodal analysis of cell-free DNA whole-methylome sequencing for cancer detection and localization
AU - Bie, Fenglong
AU - Wang, Zhijie
AU - Li, Yulong
AU - Guo, Wei
AU - Hong, Yuanyuan
AU - Han, Tiancheng
AU - Lv, Fang
AU - Yang, Shunli
AU - Li, Suxing
AU - Li, Xi
AU - Nie, Peiyao
AU - Xu, Shun
AU - Zang, Ruochuan
AU - Zhang, Moyan
AU - Song, Peng
AU - Feng, Feiyue
AU - Duan, Jianchun
AU - Bai, Guangyu
AU - Li, Yuan
AU - Huai, Qilin
AU - Zhou, Bolun
AU - Huang, Yu S.
AU - Chen, Weizhi
AU - Tan, Fengwei
AU - Gao, Shugeng
N1 - Publisher Copyright:
© 2023, Springer Nature Limited.
PY - 2023/12
Y1 - 2023/12
N2 - Multimodal epigenetic characterization of cell-free DNA (cfDNA) could improve the performance of blood-based early cancer detection. However, integrative profiling of cfDNA methylome and fragmentome has been technologically challenging. Here, we adapt an enzyme-mediated methylation sequencing method for comprehensive analysis of genome-wide cfDNA methylation, fragmentation, and copy number alteration (CNA) characteristics for enhanced cancer detection. We apply this method to plasma samples of 497 healthy controls and 780 patients of seven cancer types and develop an ensemble classifier by incorporating methylation, fragmentation, and CNA features. In the test cohort, our approach achieves an area under the curve value of 0.966 for overall cancer detection. Detection sensitivity for early-stage patients achieves 73% at 99% specificity. Finally, we demonstrate the feasibility to accurately localize the origin of cancer signals with combined methylation and fragmentation profiling of tissue-specific accessible chromatin regions. Overall, this proof-of-concept study provides a technical platform to utilize multimodal cfDNA features for improved cancer detection.
AB - Multimodal epigenetic characterization of cell-free DNA (cfDNA) could improve the performance of blood-based early cancer detection. However, integrative profiling of cfDNA methylome and fragmentome has been technologically challenging. Here, we adapt an enzyme-mediated methylation sequencing method for comprehensive analysis of genome-wide cfDNA methylation, fragmentation, and copy number alteration (CNA) characteristics for enhanced cancer detection. We apply this method to plasma samples of 497 healthy controls and 780 patients of seven cancer types and develop an ensemble classifier by incorporating methylation, fragmentation, and CNA features. In the test cohort, our approach achieves an area under the curve value of 0.966 for overall cancer detection. Detection sensitivity for early-stage patients achieves 73% at 99% specificity. Finally, we demonstrate the feasibility to accurately localize the origin of cancer signals with combined methylation and fragmentation profiling of tissue-specific accessible chromatin regions. Overall, this proof-of-concept study provides a technical platform to utilize multimodal cfDNA features for improved cancer detection.
UR - http://www.scopus.com/inward/record.url?scp=85173100948&partnerID=8YFLogxK
U2 - 10.1038/s41467-023-41774-w
DO - 10.1038/s41467-023-41774-w
M3 - Article
C2 - 37758728
AN - SCOPUS:85173100948
SN - 2041-1723
VL - 14
JO - Nature Communications
JF - Nature Communications
IS - 1
M1 - 6042
ER -
