Liquid biopsy-based multi-omics approach for early detection of hepatocellular carcinoma (ASCEND-Hep): a multiphase prospective development and validation study

医学 肝细胞癌 预测值 前瞻性队列研究 肿瘤科 内科学 阶段(地层学) DNA甲基化 肝细胞癌 试验预测值 癌症 甲基化 金标准(测试) 肝癌 曲线下面积 曲线下面积 接收机工作特性 生物标志物 周转时间 病理 生物信息学
作者
Ce Wang,Lei Cai,Yi Yang,W D Wang,Kunli Zhao,Wenchuan Xie,Qiaoxia Zhou,Q F Zhang,Cheng Zhang,Meihai Deng,Shiyun Bao,Jiangang Bi,Xuefang Chen,Haorong Xie,付顺军,Guolin He,Yuan Cheng,Kaihang Zhong,Yaohong Wen,Y Xu
出处
期刊:BMC Medicine [BioMed Central]
标识
DOI:10.1186/s12916-026-05032-2
摘要

Hepatocellular carcinoma (HCC), the third leading cause of cancer deaths, urgently requires innovative early detection strategies. This prospective study aimed to evaluate the feasibility of cell-free DNA (cfDNA) methylation, mutation, and/or alpha-fetoprotein (AFP) for HCC early detection model development. Peripheral blood samples were prospectively collected from 635 participants (288 HCC, 347 non-HCC), who were randomly assigned (6:4) to the training and validation sets to develop and validate a multi-omics early detection (MOED) model. The model was externally validated on 797 subjects (160 HCC, 637 non-HCC) and further blindly tested on 452 community-recruited high-risk individuals. The methylation-based model showed superior performance over AFP and mutation-based models in the training set. In the validation set, the MOED model, integrating methylation with AFP levels ≥ 400 ng/mL, slightly increased sensitivity from 87.1% (95% CI: 79.6%-92.6%) to 88.8% (95% CI: 81.6%-93.9%) at 95.7% specificity (95% CI: 91.0%-98.4%), whereas adding mutation data did not improve the performance. In the independent validation set, the locked MOED exhibited 91.9% (95% CI: 86.5%-95.6%) overall sensitivity, 83.3% (95% CI: 51.6%-97.9%) stage 0 sensitivity, and 98.4% overall specificity (95% CI: 97.1%-99.2%). In high-risk individuals, the model demonstrated 92.9% (95% CI: 64.2%-99.6%) sensitivity, 90.6% (95% CI: 87.4%-93.1%) specificity, 24.1% (95% CI: 13.9%-37.9%) positive predictive value (PPV) and 99.7% (95% CI: 98.4%-100.0%) negative predictive value (NPV). The MOED model, integrating cfDNA methylation and AFP, is highly effective for HCC detection and promising for screening in high-risk populations.
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