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已发表论文
基于三维增强 CT 影像组学模型预测肝细胞癌昼夜节律基因表达及预后的构建
Authors Zhao J , Zhou H , Wang C , Zhang W, Pang Y , Zheng H, Zhang L, Zhou J, Hu Z
Received 19 June 2025
Accepted for publication 6 December 2025
Published 25 December 2025 Volume 2025:12 Pages 2989—3009
DOI https://doi.org/10.2147/JHC.S545482
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr David Gerber
Jiaxin Zhao,1,* Huiying Zhou,1,* Cheng Wang,1 Wenluo Zhang,1 Yujiang Pang,1 Huilin Zheng,2 Lei Zhang,2 Jie Zhou,3 Zhenhua Hu1,3,4
1Department of Hepatobiliary and Pancreatic Surgery, Department of Surgery, the Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, Zhejiang University, Yiwu, Zhejiang, People’s Republic of China; 2Zhejiang Provincial Collaborative Innovation Center of Agricultural Biological Resource Biochemical Manufacturing, School of Biological and Chemical Engineering, Zhejiang University of Science and Technology, Hangzhou, Zhejiang, People’s Republic of China; 3Department of Hepatobiliary and Pancreatic Surgery, Department of Surgery, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, People’s Republic of China; 4Zhejiang Key Laboratory of Biomedical Intelligent Computing Technology, Hangzhou, Zhejiang, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Zhenhua Hu, Department of Hepatobiliary and Pancreatic Surgery, Department of Surgery, the Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, Zhejiang University, Yiwu, Zhejiang, People’s Republic of China, Tel/Fax +86-570-89935878, Email huzhenh@zju.edu.cn Jie Zhou, Department of Hepatobiliary and Pancreatic Surgery, Department of Surgery, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, People’s Republic of China, Tel +86-13429661721, Email jzhou329@zju.edu.cn
Purpose: Circadian disruption contributes to hepatocellular carcinoma (HCC) progression. This study aimed to develop a CT-based radiomics model to non-invasively predict circadian rhythm (CR) gene expression profiles for improved prognostic assessment.
Methods: Mendelian randomization (MR) analysis revealed a significant causal association between CR disorders and the risk of HCC. In Cohort 1 (TCGA database, n = 424), 32 CR-related genes were identified from an initial set of 71 genes. Univariate Cox regression analysis identified 18 prognosis-related genes, and a risk model containing 8 genes was constructed using LASSO and multivariate Cox regression. This model was then validated in Cohort 2 (ICGC database, n = 232). The gene CRTC2 was further validated in vitro. Radiomics features were constructed based on enhanced CT images from Cohort 3 (TCIA database, n = 45) to predict CR risk genes, and the prognostic value of the model was validated in Cohort 4 (The Fourth Affiliated Hospital of Zhejiang University School of Medicine, n = 38).
Results: The CR risk gene model stratified patients into high- and low-risk groups with significantly different survival outcomes in both TCGA and ICGC cohorts (TCGA: P < 0.001; ICGC: P = 0.029). The risk score was independently associated with overall survival (HR = 3.582, 95% CI: 2.101– 6.107, P < 0.001). Experimental results confirmed that knockdown of CRTC2 significantly inhibited HCC cell proliferation, migration, invasion, and induced apoptosis. The radiomics model achieved an AUC of 0.931 in the training set and 0.760 in the validation set for predicting CR gene expression. Importantly, in the clinical validation cohort, patients with low radiomics scores had significantly longer survival (P = 0.039).
Conclusion: Circadian rhythm-related gene expression, implicated in HCC development, can be non-invasively predicted via CT-based radiomics. The proposed model offers promise for prognostic stratification and personalized treatment planning in HCC.
Keywords: circadian rhythm, hepatocellular carcinoma, mendelian randomization, radiomics, LASSO, survival
1Department of Hepatobiliary and Pancreatic Surgery, Department of Surgery, the Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, Zhejiang University, Yiwu, Zhejiang, People’s Republic of China; 2Zhejiang Provincial Collaborative Innovation Center of Agricultural Biological Resource Biochemical Manufacturing, School of Biological and Chemical Engineering, Zhejiang University of Science and Technology, Hangzhou, Zhejiang, People’s Republic of China; 3Department of Hepatobiliary and Pancreatic Surgery, Department of Surgery, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, People’s Republic of China; 4Zhejiang Key Laboratory of Biomedical Intelligent Computing Technology, Hangzhou, Zhejiang, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Zhenhua Hu, Department of Hepatobiliary and Pancreatic Surgery, Department of Surgery, the Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, Zhejiang University, Yiwu, Zhejiang, People’s Republic of China, Tel/Fax +86-570-89935878, Email huzhenh@zju.edu.cn Jie Zhou, Department of Hepatobiliary and Pancreatic Surgery, Department of Surgery, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, People’s Republic of China, Tel +86-13429661721, Email jzhou329@zju.edu.cn
Purpose: Circadian disruption contributes to hepatocellular carcinoma (HCC) progression. This study aimed to develop a CT-based radiomics model to non-invasively predict circadian rhythm (CR) gene expression profiles for improved prognostic assessment.
Methods: Mendelian randomization (MR) analysis revealed a significant causal association between CR disorders and the risk of HCC. In Cohort 1 (TCGA database, n = 424), 32 CR-related genes were identified from an initial set of 71 genes. Univariate Cox regression analysis identified 18 prognosis-related genes, and a risk model containing 8 genes was constructed using LASSO and multivariate Cox regression. This model was then validated in Cohort 2 (ICGC database, n = 232). The gene CRTC2 was further validated in vitro. Radiomics features were constructed based on enhanced CT images from Cohort 3 (TCIA database, n = 45) to predict CR risk genes, and the prognostic value of the model was validated in Cohort 4 (The Fourth Affiliated Hospital of Zhejiang University School of Medicine, n = 38).
Results: The CR risk gene model stratified patients into high- and low-risk groups with significantly different survival outcomes in both TCGA and ICGC cohorts (TCGA: P < 0.001; ICGC: P = 0.029). The risk score was independently associated with overall survival (HR = 3.582, 95% CI: 2.101– 6.107, P < 0.001). Experimental results confirmed that knockdown of CRTC2 significantly inhibited HCC cell proliferation, migration, invasion, and induced apoptosis. The radiomics model achieved an AUC of 0.931 in the training set and 0.760 in the validation set for predicting CR gene expression. Importantly, in the clinical validation cohort, patients with low radiomics scores had significantly longer survival (P = 0.039).
Conclusion: Circadian rhythm-related gene expression, implicated in HCC development, can be non-invasively predicted via CT-based radiomics. The proposed model offers promise for prognostic stratification and personalized treatment planning in HCC.
Keywords: circadian rhythm, hepatocellular carcinoma, mendelian randomization, radiomics, LASSO, survival