108139
论文已发表
注册即可获取德孚的最新动态
IF 收录期刊
- 3.4 Breast Cancer (Dove Med Press)
- 3.2 Clin Epidemiol
- 2.6 Cancer Manag Res
- 2.9 Infect Drug Resist
- 3.7 Clin Interv Aging
- 5.1 Drug Des Dev Ther
- 3.1 Int J Chronic Obstr
- 6.6 Int J Nanomed
- 2.6 Int J Women's Health
- 2.9 Neuropsych Dis Treat
- 2.8 OncoTargets Ther
- 2.0 Patient Prefer Adher
- 2.2 Ther Clin Risk Manag
- 2.5 J Pain Res
- 3.0 Diabet Metab Synd Ob
- 3.2 Psychol Res Behav Ma
- 3.4 Nat Sci Sleep
- 1.8 Pharmgenomics Pers Med
- 2.0 Risk Manag Healthc Policy
- 4.1 J Inflamm Res
- 2.0 Int J Gen Med
- 3.4 J Hepatocell Carcinoma
- 3.0 J Asthma Allergy
- 2.2 Clin Cosmet Investig Dermatol
- 2.4 J Multidiscip Healthc
已发表论文
CT 影像组学结合代谢生物标志物可实现肝细胞癌早期复发预测
Authors Ren L , Chen D, Xu T , Wei R, Zhao B, Zhou Y , He Y, Liao M, Chen H , Liao W
Received 15 June 2025
Accepted for publication 16 September 2025
Published 29 September 2025 Volume 2025:12 Pages 2183—2196
DOI https://doi.org/10.2147/JHC.S547186
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr David Gerber
Liying Ren,1,2,* Dongbo Chen,2,* Tingfeng Xu,3,* Rongyu Wei,1 Bigeng Zhao,1 Yuanping Zhou,4 Yong He,5 Minjun Liao,2 Hongsong Chen,2 Weijia Liao1
1Laboratory of Hepatobiliary and Pancreatic Surgery, the First Affiliated Hospital of Guilin Medical University, Guilin, Guangxi, People’s Republic of China; 2Peking University Hepatology Institute, Peking University People’s Hospital, Beijing Key Laboratory of Hepatitis C and Immunotherapy for Liver Disease, Beijing, People’s Republic of China; 3Affiliation Department of Hepatobiliary Surgery, the First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, People’s Republic of China; 4Guangdong Provincial Key Laboratory of Gastroenterology, Department of Gastroenterology and Hepatology Unit, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, People’s Republic of China; 5Department of Radiology, the Second Affiliated Hospital of Guilin Medical University, Guilin, Guangxi, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Weijia Liao, Laboratory of Hepatobiliary and Pancreatic Surgery, the First Affiliated Hospital of Guilin Medical University, No. 15, Lequn Road, Xiufeng District, Guilin, Guangxi, 541001, People’s Republic of China, Email liaoweijia288@163.com Hongsong Chen, Peking University Hepatology Institute, Peking University People’s Hospital, No. 11 Xizhimen South Street, Beijing, 100044, People’s Republic of China, Email chenhongsong2999@163.com
Background: The prognosis of early recurrence of hepatocellular carcinoma (HCC) remains poor. This study aimed to develop and validate a radiomics model and determine potential biomarkers involved in biological pathways for early recurrence of HCC.
Methods: A total of 271 HCC patients from the First Affiliated Hospital of Guilin Medical University were enrolled as the training cohort. Recurrence related radiomics features were determined by analyzing contrast-enhanced CT images, which were used for the construction of Rad-score. For external validation, we utilized both imaging and transcriptome data from 34 HCC patients in TCGA database. The identified radiomics-related genes were further validated using two independent datasets (OEP000321 and GSE14520) and immunohistochemical analysis of EEF1E1 in 38 HCC tissue samples from training cohort.
Results: Rad-scores based on six radiomics features showed predictive value for early HCC recurrence in both cohorts (A465, A466, A839, V105, V250, V291). Relevant radiomics features are associated with metabolism, proliferation, and immune pathways. The most relevant recurrence-related radiomics gene module was determined via weighted correlation network analysis (WGCNA), which contained LRP12, GPD1L, GARS, EEF1E1, and DGKG. The model based on these genes could efficiently predict early HCC recurrence and was verified in the OEP000321 and GSE14520 datasets. Moreover, EEF1E1 was significantly associated with the Rad-score, illustrated prognostic value at the transcription level, and validated by immunohistochemical staining at the protein level.
Conclusion: Rad-score and radiomics gene signatures from enhanced CT effectively predicted early recurrence in HCC, while EEF1E1 might serve as an efficient biomarker for early recurrence prediction for hepatocellular carcinoma.
Keywords: contrast-enhanced CT, hepatocellular carcinoma, radiomics, early recurrence, EEF1E1
1Laboratory of Hepatobiliary and Pancreatic Surgery, the First Affiliated Hospital of Guilin Medical University, Guilin, Guangxi, People’s Republic of China; 2Peking University Hepatology Institute, Peking University People’s Hospital, Beijing Key Laboratory of Hepatitis C and Immunotherapy for Liver Disease, Beijing, People’s Republic of China; 3Affiliation Department of Hepatobiliary Surgery, the First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, People’s Republic of China; 4Guangdong Provincial Key Laboratory of Gastroenterology, Department of Gastroenterology and Hepatology Unit, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, People’s Republic of China; 5Department of Radiology, the Second Affiliated Hospital of Guilin Medical University, Guilin, Guangxi, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Weijia Liao, Laboratory of Hepatobiliary and Pancreatic Surgery, the First Affiliated Hospital of Guilin Medical University, No. 15, Lequn Road, Xiufeng District, Guilin, Guangxi, 541001, People’s Republic of China, Email liaoweijia288@163.com Hongsong Chen, Peking University Hepatology Institute, Peking University People’s Hospital, No. 11 Xizhimen South Street, Beijing, 100044, People’s Republic of China, Email chenhongsong2999@163.com
Background: The prognosis of early recurrence of hepatocellular carcinoma (HCC) remains poor. This study aimed to develop and validate a radiomics model and determine potential biomarkers involved in biological pathways for early recurrence of HCC.
Methods: A total of 271 HCC patients from the First Affiliated Hospital of Guilin Medical University were enrolled as the training cohort. Recurrence related radiomics features were determined by analyzing contrast-enhanced CT images, which were used for the construction of Rad-score. For external validation, we utilized both imaging and transcriptome data from 34 HCC patients in TCGA database. The identified radiomics-related genes were further validated using two independent datasets (OEP000321 and GSE14520) and immunohistochemical analysis of EEF1E1 in 38 HCC tissue samples from training cohort.
Results: Rad-scores based on six radiomics features showed predictive value for early HCC recurrence in both cohorts (A465, A466, A839, V105, V250, V291). Relevant radiomics features are associated with metabolism, proliferation, and immune pathways. The most relevant recurrence-related radiomics gene module was determined via weighted correlation network analysis (WGCNA), which contained LRP12, GPD1L, GARS, EEF1E1, and DGKG. The model based on these genes could efficiently predict early HCC recurrence and was verified in the OEP000321 and GSE14520 datasets. Moreover, EEF1E1 was significantly associated with the Rad-score, illustrated prognostic value at the transcription level, and validated by immunohistochemical staining at the protein level.
Conclusion: Rad-score and radiomics gene signatures from enhanced CT effectively predicted early recurrence in HCC, while EEF1E1 might serve as an efficient biomarker for early recurrence prediction for hepatocellular carcinoma.
Keywords: contrast-enhanced CT, hepatocellular carcinoma, radiomics, early recurrence, EEF1E1