Early detection and prognosis evaluation for hepatocellular carcinoma by circulating tumour DNA methylation: A multicentre cohort study

Author:

Guo De‐Zhen1ORCID,Huang Ao1,Wang Ying‐Chao2,Zhou Shuang3,Wang Hui3,Xing Xiang‐Lei4,Zhang Shi‐Yu1,Cheng Jian‐Wen1,Xie Ke‐Hui3,Yang Qi‐Chang3,Ma Cheng‐Cheng3,Li Qing5,Chen Yan6,Su Zhi‐Xi3,Fan Jia1,Liu Rui3,Liu Xiao‐Long2ORCID,Zhou Jian1,Yang Xin‐Rong1ORCID

Affiliation:

1. Department of Liver Surgery and Transplantation Liver Cancer Institute Zhongshan Hospital, Fudan University; Key Laboratory of Carcinogenesis and Cancer Invasion (Fudan University), Ministry of Education Shanghai China

2. The United Innovation of Mengchao Hepatobiliary Technology Key Laboratory of Fujian Province Mengchao Hepatobiliary Hospital of Fujian Medical University Fuzhou P. R. China

3. Singlera Genomics Ltd. Shanghai China

4. Biliary Tract Surgery Department IV Eastern Hepatobiliary Surgery Hospital Shanghai China

5. Department of Clinical Pharmacology Xiangya Hospital, Central South University Changsha Hunan China

6. XiangYa Medical Laboratory Central South University Changsha Hunan China

Abstract

AbstractBackgroundEarly diagnosis of hepatocellular carcinoma (HCC) can significantly improve patient survival. We aimed to develop a blood‐based assay to aid in the diagnosis, detection and prognostic evaluation of HCC.MethodsA three‐phase multicentre study was conducted to screen, optimise and validate HCC‐specific differentially methylated regions (DMRs) using next‐generation sequencing and quantitative methylation‐specific PCR (qMSP).ResultsGenome‐wide methylation profiling was conducted to identify DMRs distinguishing HCC tumours from peritumoural tissues and healthy plasmas. The twenty most effective DMRs were verified and incorporated into a multilocus qMSP assay (HepaAiQ). The HepaAiQ model was trained to separate 293 HCC patients (Barcelona Clinic Liver Cancer (BCLC) stage 0/A, 224) from 266 controls including chronic hepatitis B (CHB) or liver cirrhosis (LC) (CHB/LC, 96), benign hepatic lesions (BHL, 23), and healthy controls (HC, 147). The model achieved an area under the curve (AUC) of 0.944 with a sensitivity of 86.0% in HCC and a specificity of 92.1% in controls. Blind validation of the HepaAiQ model in a cohort of 523 participants resulted in an AUC of 0.940 with a sensitivity of 84.4% in 205 HCC cases (BCLC stage 0/A, 167) and a specificity of 90.3% in 318 controls (CHB/LC, 100; BHL, 102; HC, 116). When evaluated in an independent test set, the HepaAiQ model exhibited a sensitivity of 70.8% in 65 HCC patients at BCLC stage 0/A and a specificity of 89.5% in 124 patients with CHB/LC. Moreover, HepaAiQ model was assessed in paired pre‐ and postoperative plasma samples from 103 HCC patients and correlated with 2‐year patient outcomes. Patients with high postoperative HepaAiQ score showed a higher recurrence risk (Hazard ratio, 3.33, p < .001).ConclusionsHepaAiQ, a noninvasive qMSP assay, was developed to accurately measure HCC‐specific DMRs and shows great potential for the diagnosis, detection and prognosis of HCC, benefiting at‐risk populations.

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Shanghai Municipal Health Commission

Publisher

Wiley

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