Evidence map›Paper›PMID 42145083›Full record

ArticleClinical and translational medicine2026

A multi-centre, prospective trial of a methylation-based liquid biopsy for early detection of liver cancer in high-risk populations.

Ruohan Zhang, Xinrong Yang, Guangming Li, Yinan Deng, Jibing Liu, Hongjun Gao, Jie Zhao, Jianwen Cheng, Xiaofei Zhao, Yang Yang and 14 more

Abstract readMulticenter Study
In one paragraph

Article in Clinical and translational medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

24 authors.

Ruohan ZhangDepartment of Hepatobiliary Surgery, Xijing Hospital, Air Force Medical University, Xi'an, China.
Xinrong YangDepartment of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan Universi ty, and Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai, China.ORCID https://orcid.org/0000-0002-2716-9338
Guangming LiDepartment of General Surgery Center, Beijing Youan Hospital, Capital Medical University, Beijing, China.
Yinan DengDepartment of Hepatic Surgery & Liver Transplantation, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Jibing LiuDepartment of Interventional Therapy I, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China.ORCID https://orcid.org/0000-0002-3674-1447
Hongjun GaoDepartment of Clinical Laboratory, State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Chaoyang District, Beijing, China.
Jie ZhaoDepartment of Research & Development, BioChain (Beijing) Science & Technology, Inc., Beijing, China.
Jianwen ChengDepartment of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan Universi ty, and Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai, China.
Xiaofei ZhaoDepartment of General Surgery Center, Beijing Youan Hospital, Capital Medical University, Beijing, China.
Yang YangDepartment of Hepatic Surgery & Liver Transplantation, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Zhen WuDepartment of Research & Development, BioChain (Beijing) Science & Technology, Inc., Beijing, China.ORCID https://orcid.org/0000-0002-8870-500X
Shuangzhen GuDepartment of Research & Development, BioChain (Beijing) Science & Technology, Inc., Beijing, China.
Yang WuDepartment of Research & Development, BioChain (Beijing) Science & Technology, Inc., Beijing, China.
Zhongying MaDepartment of Pharmacy, Xijing Hospital, Air Force Medical University, Xi'an, China.ORCID https://orcid.org/0000-0002-5202-9775
Yanli LiuShandong Provincial Key Laboratory of Precision Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China.
Yan KangDepartment of Clinical Laboratory, Shanxi Province Cancer Hospital, Shanxi Hospital Chinese Academy of Medical Sciences, Taiyuan, Shanxi, China.
Guangpeng ZhouDepartment of Research & Development, BioChain (Beijing) Science & Technology, Inc., Beijing, China.
Hua LiDepartment of Hepatic Surgery & Liver Transplantation, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.ORCID https://orcid.org/0000-0002-0318-8892
Yonghong ZhangClinical Center for Liver Cancer, Capital Medical University, Beijing, China.
Xiaoliang HanDepartment of Research & Development, BioChain (Beijing) Science & Technology, Inc., Beijing, China.
Jia FanDepartment of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan Universi ty, and Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai, China.
Jian ZhouDepartment of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan Universi ty, and Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai, China.ORCID https://orcid.org/0000-0002-2118-1117
Kefeng DouDepartment of Hepatobiliary Surgery, Xijing Hospital, Air Force Medical University, Xi'an, China.
Kaishan TaoDepartment of Hepatobiliary Surgery, Xijing Hospital, Air Force Medical University, Xi'an, China.

Funding

Eastern Talent Program (Leading project)National Natural Science Foundation of ChinaNational Ten Thousand Talent ProgramOriginal Discovery Program of National Natural Science Foundation of ChinaShanghai Municipal Science and Technology Major ProjectThe Project from Shanghai Hospital Development CenterThe Project of Shanghai Municipal Health CommissionThe Projects from the Shanghai Science and Technology Commission
6 · The paper itself

Abstract

BACKGROUND AND

aimsExisting imaging and serum-marker assays miss many early liver cancers, especially in high-risk chronic liver disease carriers. We aimed to create a highly accurate, non-invasive, methylation-based liquid biopsy for early detection.

methodsWe used a comprehensive, multi-platform, multi-cohort strategy for marker discovery, starting with methylation profiling of hepatocellular carcinoma samples from TCGA and in-house cohorts. From 30 initial candidates, nine highly liver-specific methylation markers were shortlisted, and three optimal cfDNA markers (RNF135, CHFR, PAX5) were selected to develop a robust diagnostic model, tuned in a training set (N = 280) and locked in an internal testing set (N = 124). The model was then validated in a prospective, large-scale trial conducted at four geographically distinct Chinese centres.

resultsThe clinical trial included 1097 participants from two groups, (i) a diagnosing group (N = 646) that prospectively enrolled individuals without prior diagnostic results and represented a real-world high-risk population, and (ii) a diagnosed group recruited after pathology confirmation. Overall, the model achieved 94.43% (95% confidence interval, 92.12-96.09%) sensitivity and 95.16% (92.78-96.78%) specificity for liver cancer, with stage-I sensitivity of 93.10% (89.78-95.40%). Within the diagnosing group, overall sensitivity was 93.99% (91.28-95.90%), and for the 267 stage-I cases, it reached 92.88% (89.15-95.39%). As for specificity, it remained high across confounders: 92.78% (85.84-96.46%) in cirrhosis, 91.74% (85.46-95.45%) in other-cancer interference samples. Besides, the model outperformed the traditional liver cancer biomarker AFP and showed changes in methylation signals before and after surgery, suggesting a possible role in perioperative monitoring. Each centre independently reported sensitivities and specificities exceeding 90%, demonstrating robust geographic performance.

conclusionsUsing a systematic marker-discovery pipeline and a multi-centre prospective cohort, we developed a methylation-based liquid biopsy that reliably detects early liver cancer in high-risk populations. CLINICAL TRIAL NUMBER: Chictr.org identifier: ChiCTR2400092883. KEY POINTS: Three cfDNA methylation markers, RNF135, CHFR and PAX5, were identified for liver cancer liquid biopsy. A three-marker diagnostic model based on qMSP was established for highly accurate non-invasive detection of liver cancer. The LC-HMC model achieved 94.43% sensitivity and 95.16% specificity in the clinical trial. The model detected stage-I liver cancer with a sensitivity of 93.10%.

Indexed as

Carcinoma, HepatocellularDNA MethylationEarly Detection of CancerLiver NeoplasmsAgedBiomarkers, TumorFemaleHumansLiquid BiopsyMaleMiddle AgedProspective StudiesBiomarkers, TumorcfDNAearly detectionliquid biopsyliver cancer diagnosismethylation markernon‐invasive diagnosis

Identifiers

PMID42145083
PMCPMC13181335

What Socratic holds

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LicenceCC BY
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.