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"Wei Liu"

Original Articles
Fibrosis-4plus score: a novel machine learning-based tool for screening high-risk varices in compensated cirrhosis (CHESS2004): an international multicenter study
Bingtian Dong, Ruiling He, Shenghong Ju, Yuping Chen, Ivica Grgurevic, Jianzhong Ma, Ying Guo, Huizhen Fan, Qiang Yan, Chuan Liu, Huixiong Xu, Anita Madir, Kristian Podrug, Jia Wang, Linxue Qian, Zhengzi Geng, Shanghao Liu, Tao Ren, Guo Zhang, Kun Wang, Meiqin Su, Fei Chen, Sumei Ma, Liting Zhang, Zhaowei Tong, Yonghe Zhou, Xin Li, Fanbin He, Hui Huan, Wenjuan Wang, Yunxiao Liang, Juan Tang, Fang Ai, Tingyu Wang, Liyun Zheng, Zhongwei Zhao, Jiansong Ji, Wei Liu, Jiaojiao Xu, Bo Liu, Xuemei Wang, Yao Zhang, Qiong Yan, Hui Liu, Xiaomei Chen, Shuhua Zhang, Yihua Wang, Yang Liu, Li Yin, Yanni Liu, Yanqing Huang, Li Bian, Ping An, Xin Zhang, Shaoting Zhang, Jinhua Shao, Xiangman Zhang, Wei Rao, Chaoxue Zhang, Christoph Frank Dietrich, Won Kim, Xiaolong Qi
Clin Mol Hepatol 2025;31(3):881-898.
Published online February 5, 2025
DOI: https://doi.org/10.3350/cmh.2024.0898
Background/Aims
A large percentage of patients undergoing esophagogastroduodenoscopy (EGD) screening do not have esophageal varices (EV) or have only small EV. We evaluated a large, international, multicenter cohort to develop a novel score, termed FIB-4plus, by combining the fibrosis-4 (FIB-4) score, liver stiffness measurement (LSM), and spleen stiffness measurement (SSM) to identify high-risk EV (HRV) in compensated cirrhosis.
Methods
This international cohort study involved patients with compensated cirrhosis from 17 Chinese hospitals and one Croatian institution (NCT04546360). Two-dimensional shear wave elastography-derived LSM and SSM values, and components of the FIB-4 score (i.e., age, aspartate aminotransferase, alanine aminotransferase, and platelet count [PLT]) were combined using machine learning algorithms (logistic regression [LR] and extreme gradient boosting [XGBoost]) to develop the LR-FIB-4plus and XGBoost-FIB-4plus models, respectively. Shapley Additive exPlanations method was used to interpret the model predictions.
Results
We analyzed data from 502 patients with compensated cirrhosis who underwent EGD screening. The XGBoost-FIB-4plus score demonstrated superior predictive performance for HRV, with an area under the receiver operating characteristic curve (AUROC) of 0.927 (95% confidence interval [CI] 0.897–0.957) in the training cohort (n=268), and 0.919 (95% CI 0.843–0.995) and 0.902 (95% CI 0.820–0.984) in the first (n=118) and second (n=82) external validation cohorts, respectively. Additionally, the XGBoost-FIB-4plus score exhibited high AUROC values for predicting EV across all cohorts. The FIB-4plus score outperformed the individual parameters (LSM, SSM, PLT, and FIB-4).
Conclusions
The FIB-4plus score effectively predicted EV and HRV in patients with compensated cirrhosis, providing clinicians with a valuable tool for optimizing patient management and outcomes.

Citations

Citations to this article as recorded by  Crossref logo
  • The evolution of non-invasive strategies in cirrhosis management—from screening to precision monitoring: Editorial on “Fibrosis-4plus score: a novel machine learning-based tool for screening high-risk varices in compensated cirrhosis (CHESS2004): an inter
    Haiyu Wang, Jinjun Chen
    Clinical and Molecular Hepatology.2026; 32(1): 403.     CrossRef
  • Metabolic factor-based machine learning model for mortality prediction in acute hepatitis E: Development and validation from a dual-center cohort
    Haoshuang Fu, Shuying Song, Yuelin Xiao, Bingying Du, Gangde Zhao, Tianhui Zhou, Yanan Du
    Digestive and Liver Disease.2026; 58(5): 660.     CrossRef
  • Relative change rate of liver stiffness measurements predicts the risk of liver decompensation in compensated advanced chronic liver disease
    Yanqiu Li, Zihang Qiao, Jinze Li, Bingbing Zhu, Yu Lu, Ying Feng, Xianbo Wang
    Clinical and Experimental Medicine.2025;[Epub]     CrossRef
  • Artificial Intelligence Applications in the Diagnosis and Management of Cirrhosis and Portal Hypertension: A Narrative Review
    Amrit Khooblall, Satish E. Viswanath, Layth Khawaja, Sameer Gadani
    Techniques in Vascular and Interventional Radiology.2025; 28(4): 101078.     CrossRef
  • Liver stiffness measurement-based risk score for predicting liver decompensation risk: a single-center retrospective Chinese study
    Yanqiu Li, Zihang Qiao, Jinze Li, Yongqi Li, Ying Feng, Xianbo Wang
    Clinical and Experimental Medicine.2025;[Epub]     CrossRef
  • Metabolomics and metabolites in cancer diagnosis and treatment
    Minyi Cai, Haiyan Liu, Chen Shao, Tingting Li, Jun Jin, Yahui Liang, Jinhu Wang, Ji Cao, Bo Yang, Qiaojun He, Xuejing Shao, Meidan Ying
    Molecular Biomedicine.2025;[Epub]     CrossRef
  • 14,203 View
  • 309 Download
  • 6 Web of Science
  • Crossref

Significant down-regulation of growth hormone receptor expression revealed as a new unfavorable prognostic factor in hepatitis C virus-related hepatocellular carcinoma
Ching-Chih Lin, Ta-Wei Liu, Ming-Lun Yeh, Yi-Shan Tsai, Pei-Chien Tsai, Chung-Feng Huang, Jee-Fu Huang, Wan-Long Chuang, Chia-Yen Dai, Ming-Lung Yu
Clin Mol Hepatol 2021;27(2):313-328.
Published online December 14, 2020
DOI: https://doi.org/10.3350/cmh.2020.0247
Background/Aims
Growth hormone (GH) is the main regulator of somatic growth, metabolism, and gender dimorphism in the liver. GH receptor (GHR) signaling in cancer is derived from a large body of evidence, although the GHR signaling pathway involved in the prognosis of hepatocellular carcinoma (HCC) in patients with hepatitis C virus (HCV)-related HCC, remains unclear. We aimed to explore the expression of GHR and analyze its association with clinicopathologic features and prognosis of patients with chronic hepatitis C and HCC.
Methods
The expression of GHR mRNA was investigated by quantitative real-time polymerase chain reaction in paired tumors and adjacent non-tumorous (ANT) liver tissues of 200 patients with chronic hepatitis C and HCC. Western blotting and immunofluorescence assays using the HCV-infected Huh7.5.1 cell model was performed.
Results
GHR mRNA was significantly lower in HCV-HCC tissues than in corresponding ANT liver tissues. GHR mRNA and protein levels also decreased in the HCV-infected Huh7.5.1 cell model. Notably, lower GHR expression was associated with age of >60 years (P=0.0111) and worse clinicopathologic characteristics, including alpha-fetoprotein >100 ng/mL (P=0.0403), cirrhosis (P=0.0075), vascular invasion (P=0.0052), pathological stage II–IV (P=0.0002), and albumin ≤4.0 g/dL (P=0.0055), which were linked with poor prognosis of HCC. Most importantly, the high incidence of recurrence and poor survival rates in patients with a low ratio of tumor/ANT GHR (≤0.1) were observed, indicating that low expression levels of GHR had great risk for development of HCC in patients with chronic hepatitis C.
Conclusions
Our study demonstrates a significant down-regulation of GHR expression as a new unfavorable independent prognostic factor in patients with chronic hepatitis C and HCC.

Citations

Citations to this article as recorded by  Crossref logo
  • Integrated Multi-Omics Analysis Reveals Cytokine Network Dynamics and Prognostic Signatures in Hepatitis B Virus-Associated Hepatocellular Carcinoma
    Mo-Han Liu, Fu-Yong Zhang, Yuan-Jun Huang, Zhi-Hua Jiang, Qin-Yan Chen, Lu-Juan Zhang, Li-Ping Hu, Zhong-Liao Fang
    Applied Biochemistry and Biotechnology.2026; 198(3): 1591.     CrossRef
  • Comprehensive analysis and therapeutic implications of prognostic value of circadian rhythm genes in hepatocellular carcinoma
    Jichun Sun, Jiaxing Hou, Hongbo Xu, Zhiqiang Li, Zhen Deng, Zhi Yang, Wuqing Cao, Junning Hou, Xiaoxin Jin
    Journal of Physiology and Biochemistry.2026;[Epub]     CrossRef
  • Growth Hormone Action as a Target in Cancer: Significance, Mechanisms, and Possible Therapies
    Reetobrata Basu, Cesar L Boguszewski, John J Kopchick
    Endocrine Reviews.2025; 46(2): 224.     CrossRef
  • Deciphering the Oncogenic Landscape of Hepatocytes Through Integrated Single‐Nucleus and Bulk RNA‐Seq of Hepatocellular Carcinoma
    Huanhou Su, Xuewen Zhou, Guanchuan Lin, Chaochao Luo, Wei Meng, Cui Lv, Yuting Chen, Zebin Wen, Xu Li, Yongzhang Wu, Changtai Xiao, Jian Yang, Jiameng Lu, Xingguang Luo, Yan Chen, Paul KH Tam, Chuanjiang Li, Haitao Sun, Xinghua Pan
    Advanced Science.2025;[Epub]     CrossRef
  • Multiscale identification of DNASE1L3 as a key target in MASLD progression to hepatocellular carcinoma
    Lintao Xia, Xiuli Yan, Hui Zhang
    Pathology - Research and Practice.2025; 275: 156192.     CrossRef
  • Characterization and clinical verification of immune-related genes in hepatocellular carcinoma to aid prognosis evaluation and immunotherapy
    Jialin Qu, Fenghao Sun, Yichen Hou, Haoran Qi, Xiaorong Sun, Ligang Xing
    BMC Cancer.2023;[Epub]     CrossRef
  • Growth hormone receptor agonists and antagonists: From protein expression and purification to long‐acting formulations
    Yue Wang, Minah Kim, Chantal Buckley, Heather D. Maynard, Ries J. Langley, Jo K. Perry
    Protein Science.2023;[Epub]     CrossRef
  • Three E2F target-related genes signature for predicting prognosis, immune features, and drug sensitivity in hepatocellular carcinoma
    Baozhu Zhang, Boyang Chang, Lu Wang, Yuzhong Xu
    Frontiers in Molecular Biosciences.2023;[Epub]     CrossRef
  • Ring Finger Protein 125 Is an Anti-Proliferative Tumor Suppressor in Hepatocellular Carcinoma
    Takahiro Kodama, Michiko Kodama, Nancy A. Jenkins, Neal G. Copeland, Huanhuan Joyce Chen, Zhubo Wei
    Cancers.2022; 14(11): 2589.     CrossRef
  • Development and Verification of a Combined Immune- and Metabolism-Related Prognostic Signature for Hepatocellular Carcinoma
    Yuanyuan Guo, Jing Yang, Hua Gao, Xin Tian, Xiaojian Zhang, Quancheng Kan
    Frontiers in Immunology.2022;[Epub]     CrossRef
  • Down-regulation of hepatic expression of GHR/STAT5/IGF-1 signaling pathway fosters development and aggressiveness of HCV-related hepatocellular carcinoma: Crosstalk with Snail-1 and type 2 transforming growth factor-beta receptor
    Mona A. Abu El-Makarem, Mariana F. Kamel, Ahmed A. Mohamed, Hisham A. Ali, Mahmoud R. Mohamed, Alaa El-Deen M. Mohamed, Ahmed M. El-Said, Mahmoud G. Ameen, Alshymaa A. Hassnine, Hatem A. Hassan, Gianfranco D. Alpini
    PLOS ONE.2022; 17(11): e0277266.     CrossRef
  • MustSeq, an alternative approach for multiplexible strand-specific 3’ end sequencing of mRNA transcriptome confers high efficiency and practicality
    Liyao Mai, Yinbin Qiu, Zhiwei Lian, Caiming Chen, Linlin Wang, Yao Yin, Siqi Wang, Xiang Yang, Yazi Li, Wanwan Peng, Chaochao Luo, Xinghua Pan
    RNA Biology.2021; 18(sup1): 232.     CrossRef
  • 15,707 View
  • 177 Download
  • 14 Web of Science
  • Crossref