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Schmauch B, Elsoukkary SS, Moro A, Raj R, Wehrle CJ, Sasaki K, Calderaro J, Sin-Chan P, Aucejo F, Roberts DE. Combining a deep learning model with clinical data better predicts hepatocellular carcinoma behavior following surgery. J Pathol Inform 2024; 15:100360. [PMID: 38292073 PMCID: PMC10825615 DOI: 10.1016/j.jpi.2023.100360] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 12/10/2023] [Accepted: 12/23/2023] [Indexed: 02/01/2024] Open
Abstract
Hepatocellular carcinoma (HCC) is among the most common cancers worldwide, and tumor recurrence following liver resection or transplantation is one of the highest contributors to mortality in HCC patients after surgery. Using artificial intelligence (AI), we developed an interdisciplinary model to predict HCC recurrence and patient survival following surgery. We collected whole-slide H&E images, clinical variables, and follow-up data from 300 patients with HCC who underwent transplant and 169 patients who underwent resection at the Cleveland Clinic. A deep learning model was trained to predict recurrence-free survival (RFS) and disease-specific survival (DSS) from the H&E-stained slides. Repeated cross-validation splits were used to compute robust C-index estimates, and the results were compared to those obtained by fitting a Cox proportional hazard model using only clinical variables. While the deep learning model alone was predictive of recurrence and survival among patients in both cohorts, integrating the clinical and histologic models significantly increased the C-index in each cohort. In every subgroup analyzed, we found that a combined clinical and deep learning model better predicted post-surgical outcome in HCC patients compared to either approach independently.
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Affiliation(s)
| | - Sarah S. Elsoukkary
- Owkin Lab, Owkin, Inc., New York, NY, USA
- Department of Pathology, Cleveland Clinic, Cleveland, OH, USA
| | - Amika Moro
- Department of Surgery, Cleveland Clinic, Cleveland, OH, USA
| | - Roma Raj
- Department of Surgery, Cleveland Clinic, Cleveland, OH, USA
| | | | - Kazunari Sasaki
- Department of Surgery, Stanford University, Palo Alto, CA, USA
| | - Julien Calderaro
- Department of Pathology, Henri Mondor University Hospital, Créteil, France
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Lu YX, Zhao JP, Zhang WG. Is ALPPS still appropriate for large or locally advanced hepatocellular carcinoma in an era of targeted agents and immunotherapy? Updates Surg 2024; 76:899-910. [PMID: 38526694 DOI: 10.1007/s13304-024-01789-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2023] [Accepted: 02/25/2024] [Indexed: 03/27/2024]
Abstract
Therapeutic options for large or locally advanced hepatocellular carcinoma (HCC) have limited efficacy. This study investigated the efficacy and safety of drug-eluting beads trans-arterial chemo-embolization (dTACE), portal vein embolization (PVE), tyrosine kinase inhibitor (TKI), and immune checkpoint inhibitors (ICI) compared to Associating Liver Partition and Portal vein ligation for Staged hepatectomy (ALPPS) for large or locally advanced HCC.Data regarding clinicopathological details, safety, and oncological outcomes were reviewed for the quadruple therapy (dTACE-PVE-TKI-ICI) and compared with ALPPS.From 2019 to 2020, 10 patients with large or locally advanced HCC underwent future remnant liver (FRL) modulation (dTACE-PVE-TKI-ICI: 5; ALPPS: 5). All five dTACE-PVE-TKI-ICI cases responded well, with patients #4 and #5 achieving complete tumor necrosis. The overall response rate (ORR) was 5/5. Patients #1-4 underwent hepatectomy, while #5 declined surgery due to complete tumor necrosis. Mean FRL volume increased by 75.3% (range 60.0%-89.4%) in 2-4 months, compared to 104.6% (range 51.3%-160.8%) in 21-37 days for ALPPS (P = 0.032). Major postoperative complications occurred in 1/5 ALPPS patients. Resection rates were 4/4 for quadruple therapy and 5/5 for ALPPS. 2-year progression free survival for dTACE-PVE-TKI-ICI and ALPPS were 5/5 and 3/5, respectively.Quadruple therapy is a feasible, effective strategy for enhancing resectability by downsizing tumors and inducing FRL hypertrophy, with manageable complications and improved long-term prognosis. In addition, it provokes the re-examination of the application of ALPPS in an era of molecular and immune treatments.
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Affiliation(s)
- Yuan-Xiang Lu
- Hepatic Surgery Center, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan, 430030, Hubei Province, China
| | - Jian-Ping Zhao
- Hepatic Surgery Center, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan, 430030, Hubei Province, China
| | - Wan-Guang Zhang
- Hepatic Surgery Center, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan, 430030, Hubei Province, China.
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Wang F, Zhan G, Chen QQ, Xu HY, Cao D, Zhang YY, Li YH, Zhang CJ, Jin Y, Ji WB, Ma JB, Yang YJ, Zhou W, Peng ZY, Liang X, Deng LP, Lin LF, Chen YW, Hu HJ. Multitask deep learning for prediction of microvascular invasion and recurrence-free survival in hepatocellular carcinoma based on MRI images. Liver Int 2024; 44:1351-1362. [PMID: 38436551 DOI: 10.1111/liv.15870] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Revised: 01/11/2024] [Accepted: 02/07/2024] [Indexed: 03/05/2024]
Abstract
BACKGROUND AND AIMS Accurate preoperative prediction of microvascular invasion (MVI) and recurrence-free survival (RFS) is vital for personalised hepatocellular carcinoma (HCC) management. We developed a multitask deep learning model to predict MVI and RFS using preoperative MRI scans. METHODS Utilising a retrospective dataset of 725 HCC patients from seven institutions, we developed and validated a multitask deep learning model focused on predicting MVI and RFS. The model employs a transformer architecture to extract critical features from preoperative MRI scans. It was trained on a set of 234 patients and internally validated on a set of 58 patients. External validation was performed using three independent sets (n = 212, 111, 110). RESULTS The multitask deep learning model yielded high MVI prediction accuracy, with AUC values of 0.918 for the training set and 0.800 for the internal test set. In external test sets, AUC values were 0.837, 0.815 and 0.800. Radiologists' sensitivity and inter-rater agreement for MVI prediction improved significantly when integrated with the model. For RFS, the model achieved C-index values of 0.763 in the training set and ranged between 0.628 and 0.728 in external test sets. Notably, PA-TACE improved RFS only in patients predicted to have high MVI risk and low survival scores (p < .001). CONCLUSIONS Our deep learning model allows accurate MVI and survival prediction in HCC patients. Prospective studies are warranted to assess the clinical utility of this model in guiding personalised treatment in conjunction with clinical criteria.
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Affiliation(s)
- Fang Wang
- Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Gan Zhan
- College of Information Science and Engineering, Ritsumeikan University, Kusatsu, Japan
| | - Qing-Qing Chen
- Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Hou-Yun Xu
- Department of Radiology, The Fourth Affiliated Hospital, Zhejiang University School of Medicine, Yiwu, China
| | - Dan Cao
- Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Department of Radiology, The Fourth Affiliated Hospital, Zhejiang University School of Medicine, Yiwu, China
| | | | - Yin-Hao Li
- College of Information Science and Engineering, Ritsumeikan University, Kusatsu, Japan
| | - Chu-Jie Zhang
- Research Center for Healthcare Data Science, Zhejiang Lab, Hangzhou, China
| | - Yao Jin
- Department of Radiology, Ningbo Medical Center Li Huili Hospital, Ningbo, China
| | - Wen-Bin Ji
- Department of Radiology, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Taizhou, China
| | - Jian-Bing Ma
- Department of Radiology, The First Hospital of Jiaxing, The Affiliated Hospital of Jiaxing University, Jiaxing, China
| | - Yun-Jun Yang
- Department of Radiology, The First Affiliated Hospital, Wenzhou Medical University, Wenzhou, China
| | - Wei Zhou
- Department of Radiology, Huzhou Central Hospital, Affiliated to Huzhou University, Huzhou, China
| | - Zhi-Yi Peng
- Department of Radiology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xiao Liang
- Department of General Surgery, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Li-Ping Deng
- Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Lan-Fen Lin
- College of Computer Science and Technology, Zhejiang University, Hangzhou, China
| | - Yen-Wei Chen
- College of Information Science and Engineering, Ritsumeikan University, Kusatsu, Japan
| | - Hong-Jie Hu
- Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Medical Imaging International Scientific and Technological Cooperation Base of Zhejiang Province, Hangzhou, China
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Fukushima R, Harimoto N, Okuyama T, Seki T, Hoshino K, Hagiwara K, Kawai S, Ishii N, Tsukagoshi M, Igarashi T, Araki K, Tomonaga H, Higuchi T, Shimokawa M, Shirabe K. New predictors of microvascular invasion for small hepatocellular carcinoma ≤ 3 cm. Int J Clin Oncol 2024:10.1007/s10147-024-02553-9. [PMID: 38769190 DOI: 10.1007/s10147-024-02553-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2024] [Accepted: 05/07/2024] [Indexed: 05/22/2024]
Abstract
BACKGROUND Microvascular invasion (MVI) is a risk factor for postoperative recurrence of hepatocellular carcinoma (HCC), even in early-stage HCC. In small HCC ≤ 3 cm, treatment options include anatomical resection or non-anatomical resection, and MVI has a major effect on treatment decisions. We aimed to identify the predictors of MVI in small HCC ≤ 3 cm. METHODS We retrospectively studied 129 patients with very early or early-stage HCC ≤ 3 cm who had undergone 18F-fluorodeoxyglucose positron emission tomography/computed tomography and subsequent hepatic resection from January 2016 to August 2023. These patients were divided into the derivation cohort (n = 86) and validation cohort (n = 43). We examined the risk factors for MVI using logistic regression analysis, and established a predictive scoring system in the derivation cohort. We evaluated the accuracy of our scoring system in the validation cohort. RESULTS In the derivation cohort, a Lens culinaris agglutinin-reactive fraction of alpha-fetoprotein (AFP-L3), prothrombin induced by vitamin K deficiency or antagonist-II (PIVKA-II), and metabolic tumor volume (MTV) were independent predictors of MVI. We established the scoring system using these three factors. In the validation test, there were no MVI-positive cases with a score of 0 and 1, and all cases were MVI-positive with a score of 4. Moreover, with a score ≥ 2, the sensitivity, specificity, and accuracy of our scoring system were 100%, 71.4%, and 81.4%, respectively. CONCLUSIONS Our scoring system can accurately predict MVI in small HCC ≤ 3 cm, and could contribute to establishing an appropriate treatment strategy.
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Affiliation(s)
- Ryosuke Fukushima
- Division of Hepatobiliary and Pancreatic Surgery, Department of General Surgical Science, Graduate School of Medicine, Gunma University, 3-39-22 Showamachi, Maebashi, Japan
| | - Norifumi Harimoto
- Division of Hepatobiliary and Pancreatic Surgery, Department of General Surgical Science, Graduate School of Medicine, Gunma University, 3-39-22 Showamachi, Maebashi, Japan.
| | - Takayuki Okuyama
- Division of Hepatobiliary and Pancreatic Surgery, Department of General Surgical Science, Graduate School of Medicine, Gunma University, 3-39-22 Showamachi, Maebashi, Japan
| | - Takaomi Seki
- Division of Hepatobiliary and Pancreatic Surgery, Department of General Surgical Science, Graduate School of Medicine, Gunma University, 3-39-22 Showamachi, Maebashi, Japan
| | - Kouki Hoshino
- Division of Hepatobiliary and Pancreatic Surgery, Department of General Surgical Science, Graduate School of Medicine, Gunma University, 3-39-22 Showamachi, Maebashi, Japan
| | - Kei Hagiwara
- Division of Hepatobiliary and Pancreatic Surgery, Department of General Surgical Science, Graduate School of Medicine, Gunma University, 3-39-22 Showamachi, Maebashi, Japan
| | - Shunsuke Kawai
- Division of Hepatobiliary and Pancreatic Surgery, Department of General Surgical Science, Graduate School of Medicine, Gunma University, 3-39-22 Showamachi, Maebashi, Japan
| | - Norihiro Ishii
- Division of Hepatobiliary and Pancreatic Surgery, Department of General Surgical Science, Graduate School of Medicine, Gunma University, 3-39-22 Showamachi, Maebashi, Japan
| | - Mariko Tsukagoshi
- Division of Hepatobiliary and Pancreatic Surgery, Department of General Surgical Science, Graduate School of Medicine, Gunma University, 3-39-22 Showamachi, Maebashi, Japan
| | - Takamichi Igarashi
- Division of Hepatobiliary and Pancreatic Surgery, Department of General Surgical Science, Graduate School of Medicine, Gunma University, 3-39-22 Showamachi, Maebashi, Japan
| | - Kenichiro Araki
- Division of Hepatobiliary and Pancreatic Surgery, Department of General Surgical Science, Graduate School of Medicine, Gunma University, 3-39-22 Showamachi, Maebashi, Japan
| | - Hiroyasu Tomonaga
- Department of Diagnostic Radiology and Nuclear Medicine, Graduate School of Medicine, Gunma University, 3-39-22 Showamachi, Maebashi, Japan
| | - Tetsuya Higuchi
- Department of Diagnostic Radiology and Nuclear Medicine, Graduate School of Medicine, Gunma University, 3-39-22 Showamachi, Maebashi, Japan
| | - Mototsugu Shimokawa
- Department of Biostatistics, Yamaguchi University Graduate School of Medicine, 1-1-1 Minamikogushi, Ube, Japan
| | - Ken Shirabe
- Division of Hepatobiliary and Pancreatic Surgery, Department of General Surgical Science, Graduate School of Medicine, Gunma University, 3-39-22 Showamachi, Maebashi, Japan
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Bo Z, Song J, He Q, Chen B, Chen Z, Xie X, Shu D, Chen K, Wang Y, Chen G. Application of artificial intelligence radiomics in the diagnosis, treatment, and prognosis of hepatocellular carcinoma. Comput Biol Med 2024; 173:108337. [PMID: 38547656 DOI: 10.1016/j.compbiomed.2024.108337] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Revised: 03/04/2024] [Accepted: 03/17/2024] [Indexed: 04/17/2024]
Abstract
Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer, with an increasing incidence and poor prognosis. In the past decade, artificial intelligence (AI) technology has undergone rapid development in the field of clinical medicine, bringing the advantages of efficient data processing and accurate model construction. Promisingly, AI-based radiomics has played an increasingly important role in the clinical decision-making of HCC patients, providing new technical guarantees for prediction, diagnosis, and prognostication. In this review, we evaluated the current landscape of AI radiomics in the management of HCC, including its diagnosis, individual treatment, and survival prognosis. Furthermore, we discussed remaining challenges and future perspectives regarding the application of AI radiomics in HCC.
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Affiliation(s)
- Zhiyuan Bo
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Jiatao Song
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Qikuan He
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Bo Chen
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Ziyan Chen
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Xiaozai Xie
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Danyang Shu
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Kaiyu Chen
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
| | - Yi Wang
- Department of Epidemiology and Biostatistics, School of Public Health and Management, Wenzhou Medical University, Wenzhou, China.
| | - Gang Chen
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China; Zhejiang-Germany Interdisciplinary Joint Laboratory of Hepatobiliary-Pancreatic Tumor and Bioengineering, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China.
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Jiang S, Gao X, Tian Y, Chen J, Wang Y, Jiang Y, He Y. The potential of 18F-FDG PET/CT metabolic parameter-based nomogram in predicting the microvascular invasion of hepatocellular carcinoma before liver transplantation. Abdom Radiol (NY) 2024; 49:1444-1455. [PMID: 38265452 DOI: 10.1007/s00261-023-04166-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2023] [Revised: 06/17/2023] [Accepted: 12/16/2023] [Indexed: 01/25/2024]
Abstract
PURPOSE Microvascular invasion (MVI) is a critical factor in predicting the recurrence and prognosis of hepatocellular carcinoma (HCC) after liver transplantation (LT). However, there is a lack of reliable preoperative predictors for MVI. The purpose of this study is to evaluate the potential of an 18F-FDG PET/CT-based nomogram in predicting MVI before LT for HCC. METHODS 83 HCC patients who obtained 18F-FDG PET/CT before LT were included in this retrospective research. To determine the parameters connected to MVI and to create a nomogram for MVI prediction, respectively, Logistic and Cox regression models were applied. Analyses of the calibration curve and receiver operating characteristic (ROC) curves were used to assess the model's capability to differentiate between clinical factors and metabolic data from PET/CT images. RESULTS Among the 83 patients analyzed, 41% were diagnosed with histologic MVI. Multivariate logistic regression analysis revealed that Child-Pugh stage, alpha-fetoprotein, number of tumors, CT Dmax, and Tumor-to-normal liver uptake ratio (TLR) were significant predictors of MVI. A nomogram was constructed using these predictors, which demonstrated strong calibration with a close agreement between predicted and actual MVI probabilities. The nomogram also showed excellent differentiation with an AUC of 0.965 (95% CI 0.925-1.000). CONCLUSION The nomogram based on 18F-FDG PET/CT metabolic characteristics is a reliable preoperative imaging biomarker for predicting MVI in HCC patients before undergoing LT. It has demonstrated excellent efficacy and high clinical applicability.
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Affiliation(s)
- Shengpan Jiang
- Department of Nuclear Medicine, Zhongnan Hospital of Wuhan University, No. 169 Donghu Road, Wuchang District, Wuhan, 430071, China
- Department of Interventional Medicine, Wuhan Third Hospital (Tongren Hospital of Wuhan University), 216 Guanshan Avenue, Wuhan, 430074, China
| | - Xiaoqing Gao
- Clinical Laboratory Department, Wuhan Third Hospital (Tongren Hospital of Wuhan University), 216 Guanshan Avenue, Wuhan, 430074, China
| | - Yueli Tian
- Department of Nuclear Medicine, Zhongnan Hospital of Wuhan University, No. 169 Donghu Road, Wuchang District, Wuhan, 430071, China
| | - Jie Chen
- Department of Nuclear Medicine, Zhongnan Hospital of Wuhan University, No. 169 Donghu Road, Wuchang District, Wuhan, 430071, China
| | - Yichun Wang
- Department of Nuclear Medicine, Zhongnan Hospital of Wuhan University, No. 169 Donghu Road, Wuchang District, Wuhan, 430071, China
| | - Yaqun Jiang
- Department of Nuclear Medicine, Zhongnan Hospital of Wuhan University, No. 169 Donghu Road, Wuchang District, Wuhan, 430071, China
| | - Yong He
- Department of Nuclear Medicine, Zhongnan Hospital of Wuhan University, No. 169 Donghu Road, Wuchang District, Wuhan, 430071, China.
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Zhang R, Wang Y, Li Z, Shi Y, Yu D, Huang Q, Chen F, Xiao W, Hong Y, Feng Z. Dynamic radiomics based on contrast-enhanced MRI for predicting microvascular invasion in hepatocellular carcinoma. BMC Med Imaging 2024; 24:80. [PMID: 38584254 PMCID: PMC11000376 DOI: 10.1186/s12880-024-01258-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Accepted: 03/26/2024] [Indexed: 04/09/2024] Open
Abstract
OBJECTIVE To exploit the improved prediction performance based on dynamic contrast-enhanced (DCE) MRI by using dynamic radiomics for microvascular invasion (MVI) in hepatocellular carcinoma (HCC). METHODS We retrospectively included 175 and 75 HCC patients who underwent preoperative DCE-MRI from September 2019 to August 2022 in institution 1 (development cohort) and institution 2 (validation cohort), respectively. Static radiomics features were extracted from the mask, arterial, portal venous, and equilibrium phase images and used to construct dynamic features. The static, dynamic, and dynamic-static radiomics (SR, DR, and DSR) signatures were separately constructed based on the feature selection method of LASSO and classification algorithm of logistic regression. The receiver operating characteristic (ROC) curves and the area under the curve (AUC) were plotted to evaluate and compare the predictive performance of each signature. RESULTS In the three radiomics signatures, the DSR signature performed the best. The AUCs of the SR, DR, and DSR signatures in the training set were 0.750, 0.751 and 0.805, respectively, while in the external validation set, the corresponding AUCs were 0.706, 0756 and 0.777. The DSR signature showed significant improvement over the SR signature in predicting MVI status (training cohort: P = 0.019; validation cohort: P = 0.044). After external validation, the AUC value of the SR signature decreased from 0.750 to 0.706, while the AUC value of the DR signature did not show a decline (AUCs: 0.756 vs. 0.751). CONCLUSIONS The dynamic radiomics had an improved effect on the MVI prediction in HCC, compared with the static DCE MRI-based radiomics models.
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Affiliation(s)
- Rui Zhang
- Department of Radiology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yao Wang
- Department of Ultrasound, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Zhi Li
- Department of Radiology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yushu Shi
- Department of Radiology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Danping Yu
- Department of Radiology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Qiang Huang
- Department of Radiology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Feng Chen
- Department of Radiology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Wenbo Xiao
- Department of Radiology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yuan Hong
- College of Mathematical Medicine, Zhejiang Normal University School, Jinhua, China
| | - Zhan Feng
- Department of Radiology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
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Wen Y, Lu L, Mei J, Ling Y, Guan R, Lin W, Wei W, Guo R. Hepatic Arterial Infusion Chemotherapy vs Transcatheter Arterial Chemoembolization as Adjuvant Therapy Following Surgery for MVI-Positive Hepatocellular Carcinoma: A Multicenter Propensity Score Matching Analysis. J Hepatocell Carcinoma 2024; 11:665-678. [PMID: 38596593 PMCID: PMC11001557 DOI: 10.2147/jhc.s453250] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Accepted: 03/17/2024] [Indexed: 04/11/2024] Open
Abstract
Background Microvascular invasion (MVI) is a significant pathological feature in hepatocellular carcinoma (HCC), adjuvant hepatic arterial infusion chemotherapy (a-HAIC) and adjuvant transcatheter arterial chemoembolization (a-TACE), are commonly used for HCC patients with MVI. This study aims to evaluate the efficacies of two adjuvant therapies after surgical treatment for HCC, compare them, and identify the significant factors. Methods Clinical data from two randomized controlled trials involving HCC patients with MVI after surgical treatment were retrospectively reviewed. Propensity score matching (PSM) analysis was performed to balance baseline differences between patients who received a-HAIC or a-TACE, and control groups who underwent hepatectomy alone. Disease-free survival (DFS) and overall survival (OS) rates were compared. Results In total of 549 patients were collected from two randomized controlled trials. Using the PSM and Kaplan-Meier method, the median DFS of the a-HAIC, a-TACE, and control groups was 63.2, 21.7, and 11.2 months (P<0.05). The a-HAIC group show significantly better 1-, 3-, and 5-year OS rates compared to the a-TACE and control groups (96.3%, 80.0%, 72.8% vs 84.4%, 57.0%, 29.8% vs 84.5%, 62.8%, 53.4%, P<0.05). But the OS rates of a-TACE and control groups showed no significant difference (P=0.279). Multivariate analysis identified a-HAIC (HR=0.449, P=0.000) and a-TACE (HR=0.633, P=0.007) as independent protective factors. For OS, a-HAIC (HR=0.388, P=0.003) was identified as an independent protective factor, too. Conclusion Compared to a-TACE and the control group, a-HAIC demonstrated greater benefits in preventing tumor recurrence and improving survival in HCC patients with MVI.
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Affiliation(s)
- Yuhua Wen
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, People’s Republic of China
- Department of Liver Surgery, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, People’s Republic of China
| | - Lianghe Lu
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, People’s Republic of China
- Department of Liver Surgery, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, People’s Republic of China
| | - Jie Mei
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, People’s Republic of China
- Department of Liver Surgery, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, People’s Republic of China
| | - Yihong Ling
- Department of Liver Surgery, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, People’s Republic of China
- Department of Pathology of Sun Yat-sen University Cancer Center, Guangzhou, 510060, People’s Republic of China
| | - Renguo Guan
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, People’s Republic of China
- Department of Liver Surgery, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, People’s Republic of China
| | - Wenping Lin
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, People’s Republic of China
- Department of Liver Surgery, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, People’s Republic of China
| | - Wei Wei
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, People’s Republic of China
- Department of Liver Surgery, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, People’s Republic of China
| | - Rongping Guo
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, People’s Republic of China
- Department of Liver Surgery, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, People’s Republic of China
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Zheng L, Wang Y, Liu Z, Wang Z, Tao C, Wu A, Li H, Xiao T, Li Z, Rong W. Identification of molecular characteristics of hepatocellular carcinoma with microvascular invasion based on deep targeted sequencing. Cancer Med 2024; 13:e7043. [PMID: 38572921 PMCID: PMC10993708 DOI: 10.1002/cam4.7043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 01/29/2024] [Accepted: 02/13/2024] [Indexed: 04/05/2024] Open
Abstract
BACKGROUND As an indicator of tumor invasiveness, microvascular invasion (MVI) is a crucial risk factor for postoperative relapse, metastasis, and unfavorable prognosis in hepatocellular carcinoma (HCC). Nevertheless, the genetic mechanisms underlying MVI, particularly for Chinese patients, remain mostly uncharted. METHODS We applied deep targeted sequencing on 66 Chinese HCC samples. Focusing on the telomerase reverse transcriptase (TERT) promoter (TERTp) and TP53 co-mutation (TERTp+/TP53+) group, gene set enrichment analysis (GSEA) was used to explore the potential molecular mechanisms of the TERTp+/TP53+ group on tumor progression and metastasis. Additionally, we evaluated the tumor immune microenvironment of the TERTp+/TP53+ group in HCC using multiplex immunofluorescence (mIF) staining. RESULTS Among the 66 HCC samples, the mutated genes that mostly appeared were TERT, TP53, and CTNNB1. Of note, we found 10 cases with TERTp+/TP53+, of which nine were MVI-positive and one was MVI-negative, and there was a co-occurrence of TERTp and TP53 (p < 0.05). Survival analysis demonstrated that patients with the TERTp+/TP53+ group had lower the disease-free survival (DFS) (p = 0.028). GSEA results indicated that telomere organization, telomere maintenance, DNA replication, positive regulation of cell cycle, and negative regulation of immune response were significantly enriched in the TERTp+/TP53+ group (all adjusted p-values (p.adj) < 0.05). mIF revealed that the TERTp+/TP53+ group decreased CD8+ T cells infiltration (p = 0.25) and enhanced PDL1 expression (p = 0.55). CONCLUSIONS TERTp+/TP53+ was significantly enriched in MVI-positive patients, leading to poor prognosis for HCC patients by promoting proliferation of HCC cell and inhibiting infiltration of immune cell surrounding HCC. TERTp+/TP53+ can be utilized as a potential indicator for predicting MVI-positive patients and poor prognosis, laying a preliminary foundation for further exploration of co-mutation in HCC with MVI and clinical treatment.
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Affiliation(s)
- Linlin Zheng
- Department of Hepatobiliary Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Yaru Wang
- State Key Laboratory of Molecular Oncology, Department of Etiology and Carcinogenesis, National Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Zhenrong Liu
- State Key Laboratory of Molecular Oncology, Department of Etiology and Carcinogenesis, National Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Zhihao Wang
- Department of Hepatobiliary Hernia SurgeryLiaocheng Dongcangfu People's HospitalLiaochengChina
| | - Changcheng Tao
- Department of Hepatobiliary Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Anke Wu
- Department of Hepatobiliary Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Haiyang Li
- Department of Hepatobiliary Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Ting Xiao
- State Key Laboratory of Molecular Oncology, Department of Etiology and Carcinogenesis, National Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Zhuo Li
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Weiqi Rong
- Department of Hepatobiliary Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
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Zhang Y, Sheng R, Dai Y, Yang C, Zeng M. The value of varying diffusion curvature MRI for assessing the microvascular invasion of hepatocellular carcinoma. Abdom Radiol (NY) 2024; 49:1154-1164. [PMID: 38311671 DOI: 10.1007/s00261-023-04168-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Revised: 12/13/2023] [Accepted: 12/14/2023] [Indexed: 02/06/2024]
Abstract
PURPOSE Varying diffusion curvature (VDC) MRI is an emerging diffusion-weighted imaging (DWI) technique that can capture non-Gaussian diffusion behavior and reflect tissue heterogeneity. However, its clinical utility has hardly been evaluated. We aimed to investigate the value of the VDC technique in noninvasively assessing microvascular invasion (MVI) in hepatocellular carcinoma (HCC). METHODS 74 patients with HCCs, including 39 MVI-positive and 35 MVI-negative HCCs were included into this prospective study. Quantitative metrics between subgroups, clinical risk factors, as well as diagnostic performance were evaluated. The power analysis was also carried out to determine the statistical power. RESULTS MVI-positive HCCs exhibited significantly higher VDC-derived structural heterogeneity measure, D1 (0.680 ± 0.100 × 10-3 vs 0.572 ± 0.148 × 10-3 mm2/s, p = 0.001) and lower apparent diffusion coefficient (ADC) (1.350 ± 0.166 × 10-3 vs 1.471 ± 0.322 × 10-3 mm2/s, p = 0.0495) compared to MVI-negative HCCs. No statistical significance was observed for VDC-derived diffusion coefficient, D0 between the subgroups (p = 0.562). Tumor size (odds ratio (OR) = 1.242) and alpha-fetoprotein (AFP) (OR = 2.527) were identified as risk factors for MVI. A predictive nomogram was constructed based on D1, ADC, tumor size, and AFP, which exhibited the highest diagnostic accuracy (AUC = 0.817), followed by D1 (AUC = 0.753) and ADC (AUC = 0.647). The diagnostic performance of the nomogram-based model was also validated by the calibration curve and decision curve. CONCLUSION VDC can aid in the noninvasive and preoperative diagnosis of HCC with MVI, which may result in the clinical benefit in terms of prognostic prediction and clinical decision-making.
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Affiliation(s)
- Yunfei Zhang
- Shanghai Institute of Medical Imaging, Fudan University, 180 Fenglin Road, Shanghai, 200032, China
- Department of Radiology, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, China
| | - Ruofan Sheng
- Shanghai Institute of Medical Imaging, Fudan University, 180 Fenglin Road, Shanghai, 200032, China
- Department of Radiology, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, China
| | - Yongming Dai
- School of Biomedical Engineering, ShanghaiTech Univerisity, Shanghai, 200032, China
| | - Chun Yang
- Shanghai Institute of Medical Imaging, Fudan University, 180 Fenglin Road, Shanghai, 200032, China.
- Department of Radiology, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, China.
| | - Mengsu Zeng
- Shanghai Institute of Medical Imaging, Fudan University, 180 Fenglin Road, Shanghai, 200032, China.
- Department of Radiology, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, China.
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11
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Peng H, Lei SY, Fan W, Dai Y, Zhang Y, Chen G, Xiong TT, Liu TZ, Huang Y, Wang XF, Xu JH, Luo XH. Assessing recent recurrence after hepatectomy for hepatitis B-related hepatocellular carcinoma by a predictive model based on sarcopenia. World J Gastroenterol 2024; 30:1727-1738. [PMID: 38617742 PMCID: PMC11008376 DOI: 10.3748/wjg.v30.i12.1727] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Revised: 01/30/2024] [Accepted: 03/13/2024] [Indexed: 03/28/2024] Open
Abstract
BACKGROUND Sarcopenia may be associated with hepatocellular carcinoma (HCC) following hepatectomy. But traditional single clinical variables are still insufficient to predict recurrence. We still lack effective prediction models for recent recurrence (time to recurrence < 2 years) after hepatectomy for HCC. AIM To establish an interventable prediction model to estimate recurrence-free survival (RFS) after hepatectomy for HCC based on sarcopenia. METHODS We retrospectively analyzed 283 hepatitis B-related HCC patients who underwent curative hepatectomy for the first time, and the skeletal muscle index at the third lumbar spine was measured by preoperative computed tomography. 94 of these patients were enrolled for external validation. Cox multivariate analysis was per-formed to identify the risk factors of postoperative recurrence in training cohort. A nomogram model was developed to predict the RFS of HCC patients, and its predictive performance was validated. The predictive efficacy of this model was evaluated using the receiver operating characteristic curve. RESULTS Multivariate analysis showed that sarcopenia [Hazard ratio(HR) = 1.767, 95%CI: 1.166-2.678, P < 0.05], alpha-fetoprotein ≥ 40 ng/mL (HR = 1.984, 95%CI: 1.307-3.011, P < 0.05), the maximum diameter of tumor > 5 cm (HR = 2.222, 95%CI: 1.285-3.842, P < 0.05), and hepatitis B virus DNA level ≥ 2000 IU/mL (HR = 2.1, 95%CI: 1.407-3.135, P < 0.05) were independent risk factors associated with postoperative recurrence of HCC. Based on the sarcopenia to assess the RFS model of hepatectomy with hepatitis B-related liver cancer disease (SAMD) was established combined with other the above risk factors. The area under the curve of the SAMD model was 0.782 (95%CI: 0.705-0.858) in the training cohort (sensitivity 81%, specificity 63%) and 0.773 (95%CI: 0.707-0.838) in the validation cohort. Besides, a SAMD score ≥ 110 was better to distinguish the high-risk group of postoperative recurrence of HCC. CONCLUSION Sarcopenia is associated with recent recurrence after hepatectomy for hepatitis B-related HCC. A nutritional status-based prediction model is first established for postoperative recurrence of hepatitis B-related HCC, which is superior to other models and contributes to prognosis prediction.
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Affiliation(s)
- Hong Peng
- Department of Infectious Diseases, Guizhou Provincial People’s Hospital, Guiyang 550002, Guizhou Province, China
| | - Si-Yi Lei
- Department of Infectious Diseases, Guizhou Provincial People’s Hospital, Guiyang 550002, Guizhou Province, China
| | - Wei Fan
- Department of Hepatobiliary Surgery, Guizhou Provincial People’s Hospital, Guiyang 550002, Guizhou Province, China
| | - Yu Dai
- Department of Hepatobiliary Surgery, Guizhou Provincial People’s Hospital, Guiyang 550002, Guizhou Province, China
| | - Yi Zhang
- Department of Hepatobiliary Surgery, Guizhou Provincial People’s Hospital, Guiyang 550002, Guizhou Province, China
| | - Gen Chen
- Department of Hepatobiliary Surgery, Guizhou Provincial People’s Hospital, Guiyang 550002, Guizhou Province, China
| | - Ting-Ting Xiong
- Department of Infectious Diseases, Guizhou Provincial People’s Hospital, Guiyang 550002, Guizhou Province, China
| | - Tian-Zhao Liu
- Department of Infectious Diseases, Guizhou Provincial People’s Hospital, Guiyang 550002, Guizhou Province, China
| | - Yue Huang
- Department of Infectious Diseases, Guizhou Provincial People’s Hospital, Guiyang 550002, Guizhou Province, China
| | - Xiao-Feng Wang
- Department of Infectious Diseases, Guizhou Provincial People’s Hospital, Guiyang 550002, Guizhou Province, China
| | - Jin-Hui Xu
- Department of Infectious Diseases, Guizhou Provincial People’s Hospital, Guiyang 550002, Guizhou Province, China
| | - Xin-Hua Luo
- Department of Infectious Diseases, Guizhou Provincial People’s Hospital, Guiyang 550002, Guizhou Province, China
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12
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Zhang Y, Sheng R, Yang C, Dai Y, Zeng M. Detecting microvascular invasion in hepatocellular carcinoma using the impeded diffusion fraction technique to sense macromolecular coordinated water. Abdom Radiol (NY) 2024:10.1007/s00261-024-04230-x. [PMID: 38526597 DOI: 10.1007/s00261-024-04230-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2023] [Revised: 01/27/2024] [Accepted: 01/29/2024] [Indexed: 03/26/2024]
Abstract
OBJECTIVES Impeded diffusion fraction (IDF) is a novel and promising diffusion-weighted imaging (DWI) technique that allows for the detection of various diffusion compartments, including macromolecular coordinated water, free diffusion, perfusion, and cellular free water. This study aims to investigate the clinical potential of IDF-DWI in detecting microvascular invasion (MVI) in hepatocellular carcinoma (HCC). METHODS 66 patients were prospectively included. Metrics derived from IDF-DWI and the apparent diffusion coefficient (ADC) were calculated. Multivariate logistic regression was employed to identify clinical risk factors. Diagnostic performance was evaluated using the area under the receiver operating characteristics curve (AUC-ROC), the area under the precision-recall curve (AUC-PR), and the calibration error (cal-error). Additionally, a power analysis was conducted to determine the required sample size. RESULTS The results suggested a significantly higher fraction of impeded diffusion (FID) originating from IDF-DWI in MVI-positive HCCs (p < 0.001). Moreover, the ADC was found to be significantly lower in MVI-positive HCCs (p = 0.019). Independent risk factors of MVI included larger tumor size and elevated alpha-fetoprotein (AFP) levels. The nomogram model incorporating ADC, FID, tumor size, and AFP level yielded the highest diagnostic accuracy for MVI (AUC-PR = 0.804, AUC-ROC = 0.783, cal-error = 0.044), followed by FID (AUC-PR = 0.693, AUC-ROC = 0.760, cal-error = 0.060) and ADC (AUC-PR = 0.570, AUC-ROC = 0.651, cal-error = 0.164). CONCLUSION IDF-DWI shows great potential in noninvasively, accurately, and preoperatively detecting MVI in HCC and may offer clinical benefits for prognostic prediction and determination of treatment strategy.
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Affiliation(s)
- Yunfei Zhang
- Shanghai Institute of Medical Imaging, Fudan University, 180 Fenglin Road, Shanghai, 200032, China
- Department of Radiology, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, China
| | - Ruofan Sheng
- Shanghai Institute of Medical Imaging, Fudan University, 180 Fenglin Road, Shanghai, 200032, China
- Department of Radiology, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, China
| | - Chun Yang
- Department of Radiology, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, China
| | - Yongming Dai
- School of Biomedical Engineering, State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech Univerisity, Shanghai, 200032, China.
| | - Mengsu Zeng
- Shanghai Institute of Medical Imaging, Fudan University, 180 Fenglin Road, Shanghai, 200032, China.
- Department of Radiology, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, China.
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13
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Ma YN, Jiang X, Song P, Tang W. Neoadjuvant therapies in resectable hepatocellular carcinoma: Exploring strategies to improve prognosis. Biosci Trends 2024; 18:21-41. [PMID: 38382930 DOI: 10.5582/bst.2023.01436] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/23/2024]
Abstract
Hepatocellular carcinoma (HCC), a challenging malignancy, often necessitates surgical intervention, notably liver resection. However, the high recurrence rate, reaching 70% within 5 years post-resection, significantly impacts patient outcomes. Neoadjuvant therapies aim to preoperatively address this challenge, reducing lesion size, improving surgical resection rates, deactivating potential micro-metastases, and ultimately lowering postoperative recurrence rates. This review concentrates on advances in research on and clinical use of neoadjuvant therapies for HCC, with particular attention to the use of immune checkpoint inhibitors (ICIs) targeting programmed cell death-1 (PD-1), programmed cell death ligand-1 (PD-L1), and cytotoxic T-lymphocyte-associated protein-4 (CTLA-4). Ongoing clinical studies exploring immunotherapy combined with a tyrosine kinase inhibitor (TKI), interventional therapy, radiotherapy, and other modalities offer promising insights into overcoming resistance to monotherapies. In summary, neoadjuvant therapies hold significant promise in terms of improving the prognosis for patients with HCC and enhancing long-term survival, particularly through innovative combination strategies.
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Affiliation(s)
- Ya-Nan Ma
- National Center for Global Health and Medicine, Tokyo, Japan
- Department of Gastroenterology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, China
| | - Xuemei Jiang
- Department of Gastroenterology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, China
| | - Peipei Song
- National Center for Global Health and Medicine, Tokyo, Japan
| | - Wei Tang
- National Center for Global Health and Medicine, Tokyo, Japan
- Haikou Affiliated Hospital of Central South University Xiangya School of Medicine, Haikou, China
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Peng Y, Yu J, Liu F, Tang L, Li B, Zhang W, Chen K, Zhang H, Wei Y, Ma X, Shi H. Accumulation of TOX high mobility group box family member 3 promotes the oncogenesis and development of hepatocellular carcinoma through the MAPK signaling pathway. MedComm (Beijing) 2024; 5:e510. [PMID: 38463397 PMCID: PMC10924639 DOI: 10.1002/mco2.510] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2023] [Revised: 02/12/2024] [Accepted: 02/12/2024] [Indexed: 03/12/2024] Open
Abstract
Microvascular invasion (MVI) has been widely valued in the field of liver surgery because MVI positivity indicates poor prognosis in hepatocellular carcinoma (HCC) patients. However, the potential molecular mechanism underlying the poor prognosis of MVI-positive HCC patients is unclear. Therefore, this study focused on identifying the key genes leading to poor prognosis in patients with a high degree of malignancy of HCC by examining the molecular signaling pathways in MVI-positive HCC patients. Through RNA sequencing, TOX high mobility group box family member 3 (TOX3) was demonstrated to be significantly highly expressed in MVI-positive HCC tissues, which was associated with poor prognosis. The results of in vivo and in vitro showed that TOX3 can promote the oncogenesis and development of HCC by targeting key molecules of the MAPK and EMT signaling pathways. The IP-MS results indicated that proteasome degradation of TOX3 in HCC cells is potentially mediated by a tripartite motif containing 56 (TRIM56, an E3 ligase) in HCC cells. Inhibiting TRIM56 enhances TOX3 protein levels. Overall, our study identified TOX3 as a key gene in the MAPK and EMT signaling pathways in HCC, and its overexpression confers significant proliferation and invasiveness to tumor cells.
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Affiliation(s)
- Yufu Peng
- Division of Liver Surgery Department of General Surgery West China Hospital Sichuan University Chengdu China
- Laboratory of Integrative Medicine Clinical Research Center for Breast State Key Laboratory of Biotherapy West China Hospital Sichuan University and Collaborative Innovation Center Chengdu China
| | - Jing Yu
- Laboratory of Integrative Medicine Clinical Research Center for Breast State Key Laboratory of Biotherapy West China Hospital Sichuan University and Collaborative Innovation Center Chengdu China
| | - Fei Liu
- Division of Liver Surgery Department of General Surgery West China Hospital Sichuan University Chengdu China
| | - Leyi Tang
- Laboratory of Integrative Medicine Clinical Research Center for Breast State Key Laboratory of Biotherapy West China Hospital Sichuan University and Collaborative Innovation Center Chengdu China
| | - Bo Li
- Division of Liver Surgery Department of General Surgery West China Hospital Sichuan University Chengdu China
| | - Wei Zhang
- Department of Critical Care Medicine State Key Laboratory of Biotherapy and Cancer Center West China Hospital Sichuan University, China
| | - Kefei Chen
- Division of Liver Surgery Department of General Surgery West China Hospital Sichuan University Chengdu China
| | - Haili Zhang
- Division of Liver Surgery Department of General Surgery West China Hospital Sichuan University Chengdu China
| | - Yonggang Wei
- Division of Liver Surgery Department of General Surgery West China Hospital Sichuan University Chengdu China
| | - Xuelei Ma
- Department of Biotherapy West China Hospital and State Key Laboratory of Biotherapy Sichuan University Chengdu China
| | - Hubing Shi
- Laboratory of Integrative Medicine Clinical Research Center for Breast State Key Laboratory of Biotherapy West China Hospital Sichuan University and Collaborative Innovation Center Chengdu China
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15
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Zhang X, Yu X, Liang W, Zhang Z, Zhang S, Xu L, Zhang H, Feng Z, Song M, Zhang J, Feng S. Deep learning-based accurate diagnosis and quantitative evaluation of microvascular invasion in hepatocellular carcinoma on whole-slide histopathology images. Cancer Med 2024; 13:e7104. [PMID: 38488408 PMCID: PMC10941532 DOI: 10.1002/cam4.7104] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2023] [Revised: 12/13/2023] [Accepted: 03/03/2024] [Indexed: 03/18/2024] Open
Abstract
BACKGROUND Microvascular invasion (MVI) is an independent prognostic factor that is associated with early recurrence and poor survival after resection of hepatocellular carcinoma (HCC). However, the traditional pathology approach is relatively subjective, time-consuming, and heterogeneous in the diagnosis of MVI. The aim of this study was to develop a deep-learning model that could significantly improve the efficiency and accuracy of MVI diagnosis. MATERIALS AND METHODS We collected H&E-stained slides from 753 patients with HCC at the First Affiliated Hospital of Zhejiang University. An external validation set with 358 patients was selected from The Cancer Genome Atlas database. The deep-learning model was trained by simulating the method used by pathologists to diagnose MVI. Model performance was evaluated with accuracy, precision, recall, F1 score, and the area under the receiver operating characteristic curve. RESULTS We successfully developed a MVI artificial intelligence diagnostic model (MVI-AIDM) which achieved an accuracy of 94.25% in the independent external validation set. The MVI positive detection rate of MVI-AIDM was significantly higher than the results of pathologists. Visualization results demonstrated the recognition of micro MVIs that were difficult to differentiate by the traditional pathology. Additionally, the model provided automatic quantification of the number of cancer cells and spatial information regarding MVI. CONCLUSIONS We developed a deep learning diagnostic model, which performed well and improved the efficiency and accuracy of MVI diagnosis. The model provided spatial information of MVI that was essential to accurately predict HCC recurrence after surgery.
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Affiliation(s)
- Xiuming Zhang
- Department of Pathology, The First Affiliated Hospital, College of MedicineZhejiang UniversityHangzhouP. R. China
| | - Xiaotian Yu
- Department of Computer Science and TechnologyZhejiang UniversityHangzhouP. R. China
| | - Wenjie Liang
- Department of Radiology, The First Affiliated Hospital, College of MedicineZhejiang UniversityHangzhouP. R. China
| | - Zhongliang Zhang
- School of ManagementHangzhou Dianzi UniversityHangzhouP. R. China
| | - Shengxuming Zhang
- Department of Computer Science and TechnologyZhejiang UniversityHangzhouP. R. China
| | - Linjie Xu
- Department of Pathology, The First Affiliated Hospital, College of MedicineZhejiang UniversityHangzhouP. R. China
| | - Han Zhang
- Department of Pathology, The First Affiliated Hospital, College of MedicineZhejiang UniversityHangzhouP. R. China
| | - Zunlei Feng
- Department of Computer Science and TechnologyZhejiang UniversityHangzhouP. R. China
| | - Mingli Song
- Department of Computer Science and TechnologyZhejiang UniversityHangzhouP. R. China
| | - Jing Zhang
- Department of Pathology, The First Affiliated Hospital, College of MedicineZhejiang UniversityHangzhouP. R. China
| | - Shi Feng
- Department of Pathology, The First Affiliated Hospital, College of MedicineZhejiang UniversityHangzhouP. R. China
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Wang F, Yan CY, Qin Y, Wang ZM, Liu D, He Y, Yang M, Wen L, Zhang D. Multiple Machine-Learning Fusion Model Based on Gd-EOB-DTPA-Enhanced MRI and Aminotransferase-to-Platelet Ratio and Gamma-Glutamyl Transferase-to-Platelet Ratio to Predict Microvascular Invasion in Solitary Hepatocellular Carcinoma: A Multicenter Study. J Hepatocell Carcinoma 2024; 11:427-442. [PMID: 38440051 PMCID: PMC10911084 DOI: 10.2147/jhc.s449737] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Accepted: 02/20/2024] [Indexed: 03/06/2024] Open
Abstract
Background Currently, it is still confused whether preoperative aminotransferase-to-platelet ratio (APRI) and gamma-glutamyl transferase-to-platelet ratio (GPR) can predict microvascular invasion (MVI) in solitary hepatocellular carcinoma (HCC). We aimed to develop and validate a machine-learning integration model for predicting MVI using APRI, GPR and gadoxetic acid disodium (Gd-EOB-DTPA) enhanced MRI. Methods A total of 314 patients from XinQiao Hospital of Army Medical University were divided chronologically into training set (n = 220) and internal validation set (n = 94), and recurrence-free survival was determined to follow up after surgery. Seventy-three patients from Chongqing University Three Gorges Hospital and Luzhou People's Hospital served as external validation set. Overall, 387 patients with solitary HCC were analyzed as whole dataset set. Least absolute shrinkage and selection operator, tenfold cross-validation and multivariate logistic regression were used to gradually filter features. Six machine-learning models and an ensemble of the all models (ENS) were built. The area under the receiver operating characteristic curve (AUC) and decision curve analysis were used to evaluate model's performance. Results APRI, GPR, HBPratio3 ([liver SI‒tumor SI]/liver SI), PLT, peritumoral enhancement, non-smooth margin and peritumoral hypointensity were independent risk factors for MVI. Six machine-learning models showed good performance for predicting MVI in training set (AUCs range, 0.793-0.875), internal validation set (0.715-0.832), external validation set (0.636-0.746) and whole dataset set (0.756-0.850). The ENS achieved the highest AUCs (0.879 vs 0.858 vs 0.839 vs 0.851) in four cohorts with excellent calibration and more net benefit. Subgroup analysis indicated that ENS obtained excellent AUCs (0.900 vs 0.809 vs 0.865 vs 0.908) in HCC >5cm, ≤5cm, ≤3cm and ≤2cm cohorts. Kaplan‒Meier survival curves indicated that ENS achieved excellent stratification for MVI status. Conclusion The APRI and GPR may be new potential biomarkers for predicting MVI of HCC. The ENS achieved optimal performance for predicting MVI in different sizes HCC and may aid in the individualized selection of surgical procedures.
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Affiliation(s)
- Fei Wang
- Department of Radiology, XinQiao Hospital of Army Medical University, Chongqing, 400037, People’s Republic of China
- Department of Medical Imaging, Luzhou People’s Hospital, Luzhou, 646000, People’s Republic of China
| | - Chun Yue Yan
- Department of Emergency Medicine, Luzhou People’s Hospital, Luzhou, 646000, People’s Republic of China
| | - Yuan Qin
- Department of Radiology, Chongqing University Three Gorges Hospital, Chongqing, 404031, People’s Republic of China
| | - Zheng Ming Wang
- Department of Radiology, XinQiao Hospital of Army Medical University, Chongqing, 400037, People’s Republic of China
| | - Dan Liu
- Department of Radiology, XinQiao Hospital of Army Medical University, Chongqing, 400037, People’s Republic of China
| | - Ying He
- Department of Radiology, XinQiao Hospital of Army Medical University, Chongqing, 400037, People’s Republic of China
| | - Ming Yang
- Department of Medical Imaging, Luzhou People’s Hospital, Luzhou, 646000, People’s Republic of China
| | - Li Wen
- Department of Radiology, XinQiao Hospital of Army Medical University, Chongqing, 400037, People’s Republic of China
| | - Dong Zhang
- Department of Radiology, XinQiao Hospital of Army Medical University, Chongqing, 400037, People’s Republic of China
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Shi R, Wang J, Zeng X, Luo H, Yang X, Guo Y, Yi L, Deng H, Yang P. Effect of anatomical liver resection on early postoperative recurrence in patients with hepatocellular carcinoma assessed based on a nomogram: a single-center study in China. Front Oncol 2024; 14:1365286. [PMID: 38476367 PMCID: PMC10929612 DOI: 10.3389/fonc.2024.1365286] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Accepted: 02/07/2024] [Indexed: 03/14/2024] Open
Abstract
Introduction We aimed to investigate risk factors for early postoperative recurrence in patients with hepatocellular carcinoma (HCC) and determine the effect of surgical methods on early recurrence to facilitate predicting the risk of early postoperative recurrence in such patients and the selection of appropriate treatment methods. Methods We retrospectively analyzed clinical data concerning 428 patients with HCC who had undergone radical surgery at Mianyang Central Hospital between January 2015 and August 2022. Relevant routine preoperative auxiliary examinations and regular postoperative telephone or outpatient follow-ups were performed to identify early postoperative recurrence. Risk factors were screened, and predictive models were constructed, including patients' preoperative ancillary tests, intra- and postoperative complications, and pathology tests in relation to early recurrence. The risk of recurrence was estimated for each patient based on a prediction model, and patients were categorized into low- and high-risk recurrence groups. The effect of anatomical liver resection (AR) on early postoperative recurrence in patients with HCC in the two groups was assessed using survival analysis. Results In total, 353 study patients were included. Multifactorial logistic regression analysis findings suggested that tumor diameter (≥5/<5 cm, odds ratio [OR] 2.357, 95% confidence interval [CI] 1.368-4.059; P = 0.002), alpha fetoprotein (≥400/<400 ng/L, OR 2.525, 95% CI 1.334-4.780; P = 0.004), tumor number (≥2/<2, OR 2.213, 95% CI 1.147-4.270; P = 0.018), microvascular invasion (positive/negative, OR 3.230, 95% CI 1.880-5.551; P < 0.001), vascular invasion (positive/negative, OR 4.472, 95% CI 1.395-14.332; P = 0.012), and alkaline phosphatase level (>125/≤125 U/L, OR 2.202, 95% CI 1.162-4.173; P = 0.016) were risk factors for early recurrence following radical HCC surgery. Model validation and evaluation showed that the area under the curve was 0.813. Hosmer-Lemeshow test results (X 2 = 1.225, P = 0.996 > 0.05), results from bootstrap self-replicated sampling of 1,000 samples, and decision curve analysis showed that the model also discriminated well, with potentially good clinical utility. Using this model, patients were stratified into low- and high-risk recurrence groups. One-year disease-free survival was compared between the two groups with different surgical approaches. Both groups benefited from AR in terms of prevention of early postoperative recurrence, with AR benefits being more pronounced and intraoperative bleeding less likely in the high-risk recurrence group. Discussion With appropriate surgical techniques and with tumors being realistically amenable to R0 resection, AR is a potentially useful surgical procedure for preventing early recurrence after radical surgery in patients with HCC.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Pei Yang
- Department of Hepatobiliary Surgery, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, China
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Liang Y, Zhong D, Yang Q, Tang Y, Qin Y, Su Y, Huang X, Shang J. Single-Cell RNA Sequencing Revealed That the Enrichment of TPI1 + Malignant Hepatocytes Was Linked to HCC Metastasis and Immunosuppressive Microenvironment. J Hepatocell Carcinoma 2024; 11:373-383. [PMID: 38410699 PMCID: PMC10896104 DOI: 10.2147/jhc.s453249] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Accepted: 02/18/2024] [Indexed: 02/28/2024] Open
Abstract
Background Tumor metastasis is the leading cause of high mortality in hepatocellular carcinoma (HCC). The metastasis-related HCC microenvironment is characterized by high heterogeneity. Single-cell RNA sequencing (scRNA-seq) may aid in determining specific cell clusters involved in regulating the immune microenvironment of HCC. Methods The scRNA-seq data of 10 HCC samples were collected from the Gene Expression Omnibus (GEO) database GSE124395. Correlations between key gene expression and clinicopathological data were determined using public databases. HCC tissues and matched tumor-adjacent and normal tissue samples were obtained by surgical resection at Sichuan Cancer Hospital. Immune cell infiltration analysis was performed and verified by immunohistochemistry and immunofluorescent staining. Results Nine malignant hepatocyte clusters with different marker genes and biological functions were identified. C3_Hepatocyte-SERF2 and C6_Hepatocyte-IL13RA2 were mainly involved in the regulation of the immune microenvironment, which was also a significant pathway in regulating HCC metastasis. Key genes in malignant hepatocyte clusters that associated with HCC metastasis were further screened by LASSO regression analysis. TPI1, a key gene in C6_Hepatocyte-IL13RA2 and HCC metastasis, could participate in regulating the HCC immune microenvironment in The Cancer Genome Atlas (TCGA) and Tumor Immune Estimation Resource (TIMER) databases. Moreover, immunohistochemistry analysis demonstrated that TPI1 expression was positively correlated with HCC metastasis and poor prognosis, while negatively correlated with CD8+ T cell infiltration. The negative correlation between TPI1 expression and CD8+ T cell infiltration was further confirmed by immunofluorescence staining. Conclusion In summary, a cluster of TPI1+ malignant hepatocytes was associated with the suppression of CD8+ T cell infiltration and HCC metastasis, providing novel insights into potential biomarkers for immunotherapy in HCC.
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Affiliation(s)
- Yuxin Liang
- Liver Transplantation Center and HBP Surgery, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, People's Republic of China
| | - Deyuan Zhong
- Liver Transplantation Center and HBP Surgery, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, People's Republic of China
| | - Qinyan Yang
- Liver Transplantation Center and HBP Surgery, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, People's Republic of China
| | - Yuan Tang
- Liver Transplantation Center and HBP Surgery, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, People's Republic of China
| | - Yingying Qin
- School of Pharmacy, Faculty of Medicine, Macau University of Science and Technology, Macau, SAR, People's Republic of China
| | - Yuhao Su
- Liver Transplantation Center and HBP Surgery, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, People's Republic of China
| | - Xiaolun Huang
- Liver Transplantation Center and HBP Surgery, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, People's Republic of China
| | - Jin Shang
- Liver Transplantation Center and HBP Surgery, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, People's Republic of China
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Chen H, Ye H, Ye L, Lin F, Shi Y, Zhong A, Guan G, Zhuang J. Novel nomograms based on microvascular invasion grade for early-stage hepatocellular carcinoma after curative hepatectomy. Sci Rep 2024; 14:3470. [PMID: 38342950 PMCID: PMC10859376 DOI: 10.1038/s41598-024-54260-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2023] [Accepted: 02/10/2024] [Indexed: 02/13/2024] Open
Abstract
Microvascular invasion (MVI) is a critical risk factor for postoperative recurrence of hepatocellular carcinoma (HCC). This study aimed to firstly develop and validate nomograms based on MVI grade for predicting recurrence, especially early recurrence, and overall survival in patients with early-stage HCC after curative resection. We retrospectively reviewed the data of patients with early-stage HCC who underwent curative hepatectomy in the First Affiliated Hospital of Fujian Medical University (FHFU) and Mengchao Hepatobiliary Hospital of Fujian Medical University (MHH). Kaplan-Meier curves and Cox proportional hazards regression models were used to analyse disease-free survival (DFS) and overall survival (OS). Nomogram models were constructed on the datasets from the 70% samples of and FHFU, which were validated using bootstrap resampling with 30% samples as internal validation and data of patients from MHH as external validation. A total of 703 patients with early-stage HCC were included to create a nomogram for predicting recurrence or metastasis (DFS nomogram) and a nomogram for predicting survival (OS nomogram). The concordance indexes and calibration curves in the training and validation cohorts showed optimal agreement between the predicted and observed DFS and OS rates. The predictive accuracy was significantly better than that of the classic HCC staging systems.
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Affiliation(s)
- Hengkai Chen
- Department of Colorectal Surgery, The First Affiliated Hospital of Fujian Medical University, 20th, Chazhong Road, Fuzhou, 350005, China
- Department of Colorectal Surgery, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350212, China
| | - Honghao Ye
- Fuzhou University, Fuzhou, 350108, China
- Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou, 350025, China
| | - Linfang Ye
- Zhongshan Hospital Xiamen University, Xiamen, 361004, China
| | - Fangzhou Lin
- Fuzhou University, Fuzhou, 350108, China
- Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou, 350025, China
| | - Yingjun Shi
- Fuzhou University, Fuzhou, 350108, China
- Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou, 350025, China
| | - Aoxue Zhong
- Fuzhou University, Fuzhou, 350108, China
- Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou, 350025, China
| | - Guoxian Guan
- Department of Colorectal Surgery, The First Affiliated Hospital of Fujian Medical University, 20th, Chazhong Road, Fuzhou, 350005, China.
- Department of Colorectal Surgery, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350212, China.
| | - Jinfu Zhuang
- Department of Colorectal Surgery, The First Affiliated Hospital of Fujian Medical University, 20th, Chazhong Road, Fuzhou, 350005, China.
- Department of Colorectal Surgery, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350212, China.
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Lao Q, Wu X, Zheng X, Hu J, Huang S, Li D, Du Y, Yang N, Zhu H. Effect of Tacrolimus Time in Therapeutic Range on Postoperative Recurrence in Patients Undergoing Liver Transplantation for Liver Cancer. Ther Drug Monit 2024; 46:42-48. [PMID: 37315150 PMCID: PMC10769175 DOI: 10.1097/ftd.0000000000001119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Accepted: 05/02/2023] [Indexed: 06/16/2023]
Abstract
BACKGROUND AND OBJECTIVE Liver cancer is the second highest cause of cancer-related deaths worldwide. It is commonly treated with liver transplantation, where tacrolimus is typically used as an antirejection immunosuppressant. The purpose of this study was to evaluate the effect of tacrolimus time in therapeutic range (TTR) on liver cancer recurrence in liver transplant recipients and to compare the performance of TTRs calculated according to the target ranges recommended in published guidelines. METHODS A total of 84 patients who underwent liver transplantation for liver cancer were retrospectively included. Tacrolimus TTR was calculated using linear interpolation from the date of transplantation until recurrence or the last follow-up according to target ranges recommended in the Chinese guideline and international expert consensus. RESULT Twenty-four recipients developed liver cancer recurrence after liver transplantation. The CTTR (TTR calculated according to the Chinese guideline) for the recurrence group was significantly lower than that of the nonrecurrence group (26.39% vs. 50.27%, P < 0.001), whereas the ITTR (TTR calculated according to the international consensus) was not significantly different between the two groups (47.81% vs. 56.37%, P = 0.165). Multivariate survival analysis revealed that age, microvascular invasion, hepatocellular carcinoma, CTTR, and mean tacrolimus trough concentration were independent predictors of liver cancer recurrence after liver transplantation. CONCLUSIONS TTR predicts liver cancer recurrence in liver transplant recipients. The range of tacrolimus concentrations recommended in the Chinese guideline was more beneficial than that recommended in the international consensus for Chinese patients undergoing liver transplantation for liver cancer.
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Affiliation(s)
- Qianying Lao
- Department of Pharmacy, Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China
| | - Xuanyu Wu
- Department of Pharmacy, Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China
| | - Xinxin Zheng
- Department of Pharmacy, Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China
| | - Jinwei Hu
- Department of Pharmacy, Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China
| | - Siqi Huang
- Department of Pharmacy, Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China
| | - Danying Li
- Department of Pharmacy, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu, China; and
- Nanjing Medical Center for Clinical Pharmacy, Nanjing, China
| | - Yao Du
- Department of Pharmacy, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu, China; and
- Nanjing Medical Center for Clinical Pharmacy, Nanjing, China
| | - Na Yang
- Department of Pharmacy, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu, China; and
- Nanjing Medical Center for Clinical Pharmacy, Nanjing, China
| | - Huaijun Zhu
- Department of Pharmacy, Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China
- Department of Pharmacy, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu, China; and
- Nanjing Medical Center for Clinical Pharmacy, Nanjing, China
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Liu Y, He M, Ke X, Chen Y, Zhu J, Tan Z, Chen J. Centrosome amplification-related signature correlated with immune microenvironment and treatment response predicts prognosis and improves diagnosis of hepatocellular carcinoma by integrating machine learning and single-cell analyses. Hepatol Int 2024; 18:108-130. [PMID: 37154991 DOI: 10.1007/s12072-023-10538-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Accepted: 04/08/2023] [Indexed: 05/10/2023]
Abstract
BACKGROUND Centrosome amplification is a well-recognized oncogenic driver of tumor initiation and progression across a variety of malignancies and has been linked with tumor aggressiveness, metastasis, and adverse prognosis. Nevertheless, the significance of centrosome amplification in HCC is not well understood. METHODS The TCGA dataset was downloaded for centrosome amplification-related signature construction using the LASSO-penalized Cox regression algorithm, while the ICGC dataset was obtained for signature validation. Single-cell RNA sequencing from GSE149614 was analyzed to profile gene expression and the liver tumor niche. RESULTS A total of 134 centrosome amplification-related prognostic genes in HCC were detected and 6 key prognostic genes (SSX2IP, SPAG4, SAC3D1, NPM1, CSNK1D, and CEP55) among them were screened out to construct a signature with both high sensitivity and specificity in diagnosis and prognosis of HCC patients. The signature, as an independent factor, was associated with frequent recurrences, high mortality rates, advanced clinicopathologic features, and high vascular invasions. Moreover, the signature was intimately associated with cell cycle-related pathways and TP53 mutation profile, suggesting its underlying role in accelerating cell cycle progression and leading to liver cancer development. Meanwhile, the signature was also closely correlated with immunosuppressive cell infiltration and immune checkpoint expression, making it a vital immunosuppressive factor in the tumor microenvironment. Upon single-cell RNA sequencing, SSX2IP and SAC3D1 were found to be specially expressed in liver cancer stem-like cells, where they promoted cell cycle progression and hypoxia. CONCLUSIONS This study provided a direct molecular link of centrosome amplification with clinical characteristics, tumor microenvironment, and clinical drug-response, highlighting the critical role of centrosome amplification in liver cancer development and therapy resistance, thereby providing valuable insights into prognostic prediction and therapeutic response of HCC.
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Affiliation(s)
- Yanli Liu
- Guangzhou Key Laboratory for Research and Development of Nano-Biomedical Technology for Diagnosis and Therapy & Guangdong Provincial Education Department Key Laboratory of Nano-Immunoregulation Tumour Microenvironment, Department of Oncology & Translational Medicine Center, The Second Affiliated Hospital, Guangzhou Medical University, Guangzhou, 510260, People's Republic of China
- Central Laboratory, The Second Affiliated Hospital, Guangzhou Medical University, Guangzhou, 510260, Guangdong, People's Republic of China
| | - Min He
- Guangzhou Key Laboratory for Research and Development of Nano-Biomedical Technology for Diagnosis and Therapy & Guangdong Provincial Education Department Key Laboratory of Nano-Immunoregulation Tumour Microenvironment, Department of Oncology & Translational Medicine Center, The Second Affiliated Hospital, Guangzhou Medical University, Guangzhou, 510260, People's Republic of China
- Central Laboratory, The Second Affiliated Hospital, Guangzhou Medical University, Guangzhou, 510260, Guangdong, People's Republic of China
| | - Xinrong Ke
- Guangzhou Key Laboratory for Research and Development of Nano-Biomedical Technology for Diagnosis and Therapy & Guangdong Provincial Education Department Key Laboratory of Nano-Immunoregulation Tumour Microenvironment, Department of Oncology & Translational Medicine Center, The Second Affiliated Hospital, Guangzhou Medical University, Guangzhou, 510260, People's Republic of China
- Central Laboratory, The Second Affiliated Hospital, Guangzhou Medical University, Guangzhou, 510260, Guangdong, People's Republic of China
| | - Yuting Chen
- State Key Laboratory of Respiratory Disease, The Second Clinical Medical School, Guangzhou Medical University, Guangzhou, 510180, Guangdong, People's Republic of China
| | - Jie Zhu
- State Key Laboratory of Respiratory Disease, The Second Clinical Medical School, Guangzhou Medical University, Guangzhou, 510180, Guangdong, People's Republic of China
| | - Ziqing Tan
- State Key Laboratory of Respiratory Disease, The Second Clinical Medical School, Guangzhou Medical University, Guangzhou, 510180, Guangdong, People's Republic of China
| | - Jingqi Chen
- Guangzhou Key Laboratory for Research and Development of Nano-Biomedical Technology for Diagnosis and Therapy & Guangdong Provincial Education Department Key Laboratory of Nano-Immunoregulation Tumour Microenvironment, Department of Oncology & Translational Medicine Center, The Second Affiliated Hospital, Guangzhou Medical University, Guangzhou, 510260, People's Republic of China.
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Liu Y, Li J. Circular RNA 0016142 Knockdown Induces Ferroptosis in Hepatocellular Carcinoma Cells via Modulation of the MicroRNA-188-3p/Glutathione Peroxidase 4 Axis. Biochem Genet 2024; 62:333-351. [PMID: 37344692 DOI: 10.1007/s10528-023-10417-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Accepted: 06/06/2023] [Indexed: 06/23/2023]
Abstract
Hepatocellular carcinoma (HCC) has high incidence and mortality rates, and it is characterized by invasiveness, poor prognosis, and limited treatment opportunities. The objective of our research was to assess the role of circ_0016142 in HCC. The ferroptosis inducer RSL3 and the iron chelator deferoxamine were used to treat cells to induce or inhibit ferroptosis, respectively, and cell viability and proliferation were assessed in Hep3B and HA22T cells by CCK8 and EdU assays, respectively. ROS, MDA, GSH, and Fe2+ levels were determined using commercial kits. RT-qPCR and western blotting were performed to determine the relative expression levels of entities of interest. Dual-luciferase reporter and RNA pull-down assays were performed to assess the relationship between circ_0016142/GPX4 and miR-188-3p. The results showed that circ_0016142/GPX4 was overexpressed, whereas miR-188-3p was downregulated in HCC. Circ_0016142 silencing reduced cell proliferation and GSH levels and increased ROS, MDA, and Fe2+ levels in HCC cells, and this was reversed by the miR-188-3p inhibitor. GPX4-overexpression abolished the effect of miR-188-3p mimic in HCC cells. In conclusion, circ_0016142 silencing suppressed HCC cell proliferation by inducing ferroptosis via the miR-188-3p/GPX4 axis.
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Affiliation(s)
- Yangjun Liu
- Department of General Surgery, The First Affiliated Hospital of Jinzhou Medical University, No. 2, Section 5, Renmin Street, Guta District, Jinzhou City, 121000, Liaoning Province, China
| | - Jinan Li
- Department of General Surgery, The First Affiliated Hospital of Jinzhou Medical University, No. 2, Section 5, Renmin Street, Guta District, Jinzhou City, 121000, Liaoning Province, China.
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Yu Z, Liu Y, Dai X, Cui E, Cui J, Ma C. Enhancing preoperative diagnosis of microvascular invasion in hepatocellular carcinoma: domain-adaptation fusion of multi-phase CT images. Front Oncol 2024; 14:1332188. [PMID: 38333689 PMCID: PMC10851167 DOI: 10.3389/fonc.2024.1332188] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Accepted: 01/09/2024] [Indexed: 02/10/2024] Open
Abstract
Objectives In patients with hepatocellular carcinoma (HCC), accurately predicting the preoperative microvascular invasion (MVI) status is crucial for improving survival rates. This study proposes a multi-modal domain-adaptive fusion model based on deep learning methods to predict the preoperative MVI status in HCC. Materials and methods From January 2008 to May 2022, we collected 163 cases of HCC from our institution and 42 cases from another medical facility, with each case including Computed Tomography (CT) images from the pre-contrast phase (PCP), arterial phase (AP), and portal venous phase (PVP). We divided our institution's dataset (n=163) into training (n=119) and test sets (n=44) in an approximate 7:3 ratio. Additionally, we included cases from another institution (n=42) as an external validation set (test1 set). We constructed three single-modality models, a simple concatenated multi-modal model, two current state-of-the-art image fusion model and a multi-modal domain-adaptive fusion model (M-DAFM) based on deep learning methods. We evaluated and analyzed the performance of these constructed models in predicting preoperative MVI using the area under the receiver operating characteristic curve (AUC), decision curve analysis (DCA), and net reclassification improvement (NRI) methods. Results In comparison with all models, M-DAFM achieved the highest AUC values across the three datasets (0.8013 for the training set, 0.7839 for the test set, and 0.7454 for the test1 set). Notably, in the test set, M-DAFM's Decision Curve Analysis (DCA) curves consistently demonstrated favorable or optimal net benefits within the 0-0.65 threshold probability range. Additionally, the Net Reclassification Improvement (NRI) values between M-DAFM and the three single-modal models, as well as the simple concatenation model, were all greater than 0 (all p < 0.05). Similarly, the NRI values between M-DAFM and the two current state-of-the-art image fusion models were also greater than 0. These findings collectively indicate that M-DAFM effectively integrates valuable information from multi-phase CT images, thereby enhancing the model's preoperative predictive performance for MVI. Conclusion The M-DAFM proposed in this study presents an innovative approach to improve the preoperative predictive performance of MVI.
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Affiliation(s)
- Zhaole Yu
- School of Automation, Guangxi University of Science and Technology, Liuzhou, Guangxi, China
| | - Yu Liu
- Laboratory of Artificial Intelligence of Biomedicine, Guilin University of Aerospace Technology, Guilin, Guangxi, China
| | - Xisheng Dai
- School of Automation, Guangxi University of Science and Technology, Liuzhou, Guangxi, China
| | - Enming Cui
- Department of Radiology, Jiangmen Central Hospital, Jiangmen, Guangdong, China
| | - Jin Cui
- Department of Radiology, Jiangmen Central Hospital, Jiangmen, Guangdong, China
| | - Changyi Ma
- Department of Radiology, Jiangmen Central Hospital, Jiangmen, Guangdong, China
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Wang H, Chen JJ, Yin SY, Sheng X, Wang HX, Lau WY, Dong H, Cong WM. A Grading System of Microvascular Invasion for Patients with Hepatocellular Carcinoma Undergoing Liver Resection with Curative Intent: A Multicenter Study. J Hepatocell Carcinoma 2024; 11:191-206. [PMID: 38283692 PMCID: PMC10822140 DOI: 10.2147/jhc.s447731] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Accepted: 01/15/2024] [Indexed: 01/30/2024] Open
Abstract
Background Microvascular invasion (MVI) is closely correlated with poor clinical outcomes in patients with hepatocellular carcinoma (HCC). A grading system of MVI is needed to assist in the management of HCC patient. Methods Multicenter data of HCC patients who underwent liver resection with curative intent was analyzed. This grading system was established by detected number and distance from tumor boundary of MVI. Survival outcomes were compared among patients in each group. This system was verified by time-receiver operating characteristic curve, time-area under the curve, calibration curve, and decision curve analyses. Cox regression analysis was performed to study the associated factors of prognosis. Logistic analysis was used to study the predictive factors of MVI. Results All patients were classified into 4 groups: M0: no MVI; M1: 1~5 proximal MVIs (≤1 cm from tumor boundary); M2a: >5 proximal MVIs (≤1 cm from tumor boundary); M2b: ≥1 distal MVIs (>1 cm from tumor boundary). The recurrence-free survival (RFS), overall survival (OS), and early RFS rates among all the individual groups were significantly different. Based on the number of proximal MVI (0~5 vs >5), patients in the M2b group were further divided into two subgroups which also showed different prognosis. Multiple methods showed this grading system to be significantly better than the MVI two-tiered system in prognostic evaluation. Four multivariate models for RFS, OS, early RFS, late RFS, and a predictive model of MVI were then established and were shown to satisfactorily evaluate prognosis and have a great discriminatory power, respectively. Conclusion This MVI grading system could precisely evaluate prognosis of HCC patients after liver resection with curative intent and it could be employed in routine pathological reports. The severity of MVI from both adjacent and distant from tumor boundary should be stated. A hypothesis about two occurrence modes of distal MVI was proposed.
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Affiliation(s)
- Han Wang
- Department of Pathology, Shanghai Eastern Hepatobiliary Surgery Hospital, Naval Medical University, Shanghai, People’s Republic of China
| | - Jun-Jie Chen
- Department of Radiology, Shanghai Eastern Hepatobiliary Surgery Hospital, Naval Medical University, Shanghai, People’s Republic of China
| | - Shu-Yi Yin
- Department of Pathology, Shanghai Changhai Hospital, Naval Medical University, Shanghai, People’s Republic of China
| | - Xia Sheng
- Department of Pathology, Minhang Hospital, Fudan University, Shanghai, People’s Republic of China
| | - Hong-Xia Wang
- Department of Pathology, Jiading District Central Hospital, Shanghai University of Medicine & Health Sciences, Shanghai, People’s Republic of China
| | - Wan Yee Lau
- Faculty of Medicine, Chinese University of Hong Kong, Hong Kong, China
| | - Hui Dong
- Department of Pathology, Shanghai Eastern Hepatobiliary Surgery Hospital, Naval Medical University, Shanghai, People’s Republic of China
| | - Wen-Ming Cong
- Department of Pathology, Shanghai Eastern Hepatobiliary Surgery Hospital, Naval Medical University, Shanghai, People’s Republic of China
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Zhou L, Chen Y, Li Y, Wu C, Xue C, Wang X. Diagnostic value of radiomics in predicting Ki-67 and cytokeratin 19 expression in hepatocellular carcinoma: a systematic review and meta-analysis. Front Oncol 2024; 13:1323534. [PMID: 38234405 PMCID: PMC10792117 DOI: 10.3389/fonc.2023.1323534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Accepted: 12/11/2023] [Indexed: 01/19/2024] Open
Abstract
Background Radiomics have been increasingly used in the clinical management of hepatocellular carcinoma (HCC), such as markers prediction. Ki-67 and cytokeratin 19 (CK-19) are important prognostic markers of HCC. Radiomics has been introduced by many researchers in the prediction of these markers expression, but its diagnostic value remains controversial. Therefore, this review aims to assess the diagnostic value of radiomics in predicting Ki-67 and CK-19 expression in HCC. Methods Original studies were systematically searched in PubMed, EMBASE, Cochrane Library, and Web of Science from inception to May 2023. All included studies were evaluated by the radiomics quality score. The C-index was used as the effect size of the performance of radiomics in predicting Ki-67and CK-19 expression, and the positive cutoff values of Ki-67 label index (LI) were determined by subgroup analysis and meta-regression. Results We identified 34 eligible studies for Ki-67 (18 studies) and CK-19 (16 studies). The most common radiomics source was magnetic resonance imaging (MRI; 25/34). The pooled C-index of MRI-based models in predicting Ki-67 was 0.89 (95% CI:0.86-0.92) in the training set, and 0.87 (95% CI: 0.82-0.92) in the validation set. The pooled C-index of MRI-based models in predicting CK-19 was 0.86 (95% CI:0.81-0.90) in the training set, and 0.79 (95% CI: 0.73-0.84) in the validation set. Subgroup analysis suggested Ki-67 LI cutoff was a significant source of heterogeneity (I 2 = 0.0% P>0.05), and meta-regression showed that the C-index increased as Ki-67 LI increased. Conclusion Radiomics shows promising diagnostic value in predicting positive Ki-67 or CK-19 expression. But lacks standardized guidelines, which makes the model and variables selection dependent on researcher experience, leading to study heterogeneity. Therefore, standardized guidelines are warranted for future research. Systematic Review Registration https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42023427953.
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Affiliation(s)
- Lu Zhou
- Traditional Chinese Medicine (Zhong Jing) School, Henan University of Chinese Medicine, Zhengzhou, Henan, China
| | - Yiheng Chen
- Traditional Chinese Medicine (Zhong Jing) School, Henan University of Chinese Medicine, Zhengzhou, Henan, China
| | - Yan Li
- Traditional Chinese Medicine (Zhong Jing) School, Henan University of Chinese Medicine, Zhengzhou, Henan, China
| | - Chaoyong Wu
- Shenzhen Hospital of Beijing University of Chinese Medicine, Shenzhen, China
| | - Chongxiang Xue
- Graduate School, Beijing University of Chinese Medicine, Beijing, China
| | - Xihong Wang
- The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, Henan, China
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Zhou G, Zhou Y, Xu X, Zhang J, Xu C, Xu P, Zhu F. MRI-based radiomics signature: a potential imaging biomarker for prediction of microvascular invasion in combined hepatocellular-cholangiocarcinoma. Abdom Radiol (NY) 2024; 49:49-59. [PMID: 37831165 DOI: 10.1007/s00261-023-04049-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 09/03/2023] [Accepted: 09/04/2023] [Indexed: 10/14/2023]
Abstract
PURPOSE To investigate the potential of radiomics analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in preoperatively predicting microvascular invasion (MVI) in patients with combined hepatocellular-cholangiocarcinoma (cHCC-CC) before surgery. METHODS A cohort of 91 patients with histologically confirmed cHCC-CC who underwent preoperative liver DCE-MRI were enrolled and divided into a training cohort (27 MVI-positive and 37 MVI-negative) and a validation cohort (11 MVI-positive and 16 MVI-negative). Clinical characteristics and MR features of the patients were evaluated. Radiomics features were extracted from DCE-MRI, and a radiomics signature was built using the least absolute shrinkage and selection operator (LASSO) algorithm in the training cohort. Prediction performance of the developed radiomics signature was evaluated by utilizing the receiver operating characteristic (ROC) analysis. RESULTS Larger tumor size and higher Radscore were associated with the presence of MVI in the training cohort (p = 0.026 and < 0.001, respectively), and theses findings were also confirmed in the validation cohort (p = 0.040 and 0.001, respectively). The developed radiomics signature, composed of 4 stable radiomics features, showed high prediction performance in both the training cohort (AUC = 0.866, 95% CI 0.757-0.938, p < 0.001) and validation cohort (AUC = 0.841, 95% CI 0.650-0.952, p < 0.001). CONCLUSIONS The radiomics signature developed from DCE-MRI can be a reliable imaging biomarker to preoperatively predict MVI in cHCC-CC.
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Affiliation(s)
- Guofeng Zhou
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Yang Zhou
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, No 300, Guangzhou Road, Nanjing, 210029, Jiangsu Province, China
| | - Xun Xu
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, No 300, Guangzhou Road, Nanjing, 210029, Jiangsu Province, China
| | - Jiulou Zhang
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, No 300, Guangzhou Road, Nanjing, 210029, Jiangsu Province, China
| | - Chen Xu
- Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Pengju Xu
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
- Department of Radiology, Zhongshan Hospital, Shanghai Institute of Medical Imaging, Fudan University, No. 180 Fenglin Road, Xuhui District, Shanghai, 200032, China.
| | - Feipeng Zhu
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, No 300, Guangzhou Road, Nanjing, 210029, Jiangsu Province, China.
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Xiang C, Shen X, Zeng X, Zhang Y, Ma Z, Zhang G, Song X, Huang T, Yang J. Effect of transarterial chemoembolization as postoperative adjuvant therapy for intermediate-stage hepatocellular carcinoma with microvascular invasion: a multicenter cohort study. Int J Surg 2024; 110:315-323. [PMID: 37812183 PMCID: PMC10793739 DOI: 10.1097/js9.0000000000000805] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2023] [Accepted: 09/18/2023] [Indexed: 10/10/2023]
Abstract
BACKGROUND Intermediate-stage hepatocellular carcinoma (HCC) with microvascular invasion (MVI) is associated with high recurrence rates and poor survival outcomes after surgery. This study aimed to evaluate the efficacy of postoperative transarterial chemoembolization (TACE) on prognosis of intermediate-stage HCC patients with MVI after curative liver resection (LR). MATERIALS AND METHODS Patients who had intermediate-stage HCC with MVI and underwent curative LR between January 2013 and December 2019 at three institutions in China were identified for further analysis. Overall survival (OS) and recurrence-free survival (RFS) were compared between patients treated with and without postoperative TACE by propensity score-matching. RESULTS A total of 246 intermediate-stage HCC patients with MVI were enrolled, 137 entered into the LR group and 109 entered into the LR+TACE group. The 1-year, 3-year, and 5-year RFS rates were 42.0, 27.2, and 17.8% in LR+TACE group, and 31.8, 18.2, and 8.7% in LR group. The 1-year, 3-year, and 5-year OS rates were 81.7, 47.2, and 26.1% in the LR+TACE group, and 67.3, 35.6, and 18.5% in the LR group. Compared with LR alone, LR+TACE was associated with significantly better RFS [hazard ratio (HR), 1.443; 95% CI: 1.089-1.914; P =0.009] and OS (HR, 1.438; 95% CI: 1.049-1.972; P =0.023). No difference was observed with RFS and OS in single TACE and multiple TACE in the matched cohort. CONCLUSION Postoperative adjuvant TACE could be beneficial for intermediate-stage HCC patients with MVI.
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Affiliation(s)
| | - Xianbo Shen
- Department of Hepatobiliary Surgery, Hunan Provincial People’s Hospital (The First Affiliated Hospital of Hunan Normal University) Changsha
| | - Xinxin Zeng
- Department of Hepatobiliary Surgery, Hunan Provincial People’s Hospital (The First Affiliated Hospital of Hunan Normal University) Changsha
| | - Yuzhong Zhang
- Department of Hepatobiliary Surgery, Hunan Provincial People’s Hospital (The First Affiliated Hospital of Hunan Normal University) Changsha
| | - Zhongzhi Ma
- Department of Hepatobiliary Surgery, Hunan Provincial People’s Hospital (The First Affiliated Hospital of Hunan Normal University) Changsha
| | - Guocan Zhang
- Department of Hepatobiliary Surgery, Hunan Provincial People’s Hospital (The First Affiliated Hospital of Hunan Normal University) Changsha
| | - Xin Song
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Jishou University, Jishou, Hunan province
| | - Tao Huang
- Department of Minimally Invasive Intervention, Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China, Guangzhou, Guangdong province, People’s Republic of China
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Huang W, Wei S, Dong X, Tang Y, Tang Y, Liu H, Huang J, Yang J. Preoperative albumin-alkaline phosphatase ratio affects the prognosis of patients undergoing hepatocellular carcinoma surgery. Cancer Biomark 2024; 39:15-26. [PMID: 37334579 PMCID: PMC10977408 DOI: 10.3233/cbm-230108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2023] [Accepted: 05/22/2023] [Indexed: 06/20/2023]
Abstract
BACKGROUND The correlation between the preoperative albuminalkaline phosphatase ratio (AAPR) and the prognosis of hepatocellular carcinoma (HCC) patients after radical resection is still not comprehensive. OBJECTIVE This study aims to observe the correlation between preoperative AAPR and the prognosis of HCC patients after radical resection. METHODS We constructed a retrospective cohort study and included 656 HCC patients who underwent radical resection. The patients were grouped after determining an optimum AAPR cut-off value. We used the Cox proportional regression model to assess the correlation between preoperative AAPR and the prognosis of HCC patients after radical resection. RESULTS The optimal cut-off value of AAPR for assessing the prognosis of HCC patients after radical resection was 0.52 which was acquired by using X-tile software. Kaplan-Meier analysis curves showed that a low AAPR (⩽ 0.52) had a significantly lower rate of overall survival (OS) and recurrence-free survival (RFS) (P< 0.05). Multiple Cox proportional regression showed that an AAPR > 0.52 was a protective factor for OS (HR = 0.66, 95%CI 0.45-0.97, p= 0.036) and RFS (HR = 0.70, 95% CI 0.53-0.92, p= 0.011). CONCLUSIONS The preoperative AAPR level was related to the prognosis of HCC patients after radical resection and can be used as a routine preoperative test, which is important for early detection of high-risk patients and taking personalized adjuvant treatment.
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Affiliation(s)
- Wei Huang
- Department of Hepatobiliary, Pancreas and Spleen Surgery, Guangxi Academy of Medical Sciences, the People’s Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China
| | - Suosu Wei
- Department of Hepatobiliary, Pancreas and Spleen Surgery, Guangxi Academy of Medical Sciences, the People’s Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China
- Institute of Health Management, Guangxi Academy of Medical Sciences, the People’s Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China
| | - Xiaofeng Dong
- Department of Hepatobiliary, Pancreas and Spleen Surgery, Guangxi Academy of Medical Sciences, the People’s Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China
| | - Yuntian Tang
- Department of Hepatobiliary, Pancreas and Spleen Surgery, Guangxi Academy of Medical Sciences, the People’s Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China
| | - Yi Tang
- Department of Hepatobiliary, Pancreas and Spleen Surgery, Guangxi Academy of Medical Sciences, the People’s Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China
| | - Hongjun Liu
- Department of Hepatobiliary, Pancreas and Spleen Surgery, Guangxi Academy of Medical Sciences, the People’s Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China
| | - Junzhang Huang
- Department of Hepatobiliary, Pancreas and Spleen Surgery, Guangxi Academy of Medical Sciences, the People’s Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China
| | - Jianrong Yang
- Department of Hepatobiliary, Pancreas and Spleen Surgery, Guangxi Academy of Medical Sciences, the People’s Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China
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Zhou H, Zheng H, Wang Y, Lao M, Shu H, Huang M, Ou C. Nomogram for Predicting Postoperative Pulmonary Metastasis in Hepatocellular Carcinoma Based on Inflammatory Markers. Cancer Control 2024; 31:10732748241236333. [PMID: 38425007 PMCID: PMC10908236 DOI: 10.1177/10732748241236333] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Revised: 01/14/2024] [Accepted: 02/08/2024] [Indexed: 03/02/2024] Open
Abstract
BACKGROUND Uncertainty surrounds the usefulness of inflammatory markers in hepatocellular carcinoma (HCC) patients for predicting postoperative pulmonary metastasis (PM). The purpose of this study was to assess the predictive value of inflammatory markers as well as to create a new nomogram model for predicting PM. METHODS Cox regression was utilized to identify independent prognostic variables and to create a nomogram that predicted PM for comparison with a validation cohort and other prediction systems. We retrospectively analyzed a total of 1109 cases with HCC were included. RESULTS The systemic inflammatory response index (SIRI) and aspartate aminotransferase-to-platelet ratio index (APRI) were independent risk factors for PM, with a concordance index of .78 (95% CI: .74-.81) for the nomogram. The areas under the curve of the nomograms for PM predicted at 1-, 3-, and 5-year were .82 (95% CI: .77-.87), .82 (95% CI: .78-.87) and .81 (95% CI: .75-.86), respectively, which were better than those of Barcelona Clinic Liver Cancer and China liver cancer stage. Decision curve analyses demonstrated a broader range of nomogram threshold probabilities. CONCLUSION A nomogram based on SIRI and APRI can accurately predict postoperative PM in HCC.
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Affiliation(s)
- Huanjie Zhou
- Department of Clinical Laboratory, Guangxi Medical University Cancer Hospital, Nanning, People’s Republic of China
| | - Haiping Zheng
- Department of Oncology, The First Affiliated Hospital of Guangxi Medical University, Nanning, People’s Republic of China
| | - Ying Wang
- Department of Clinical Laboratory, Guangxi Medical University Cancer Hospital, Nanning, People’s Republic of China
| | - Ming Lao
- Department of Clinical Laboratory, Guangxi Medical University Cancer Hospital, Nanning, People’s Republic of China
| | - Hong Shu
- Department of Clinical Laboratory, Guangxi Medical University Cancer Hospital, Nanning, People’s Republic of China
| | - Meifang Huang
- Department of Clinical Laboratory, Guangxi Medical University Cancer Hospital, Nanning, People’s Republic of China
| | - Chao Ou
- Department of Clinical Laboratory, Guangxi Medical University Cancer Hospital, Nanning, People’s Republic of China
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Wang Y, Meng B, Wang X, Wu A, Li X, Qian X, Wu J, Ying W, Xiao T, Rong W. Noninvasive urinary protein signatures combined clinical information associated with microvascular invasion risk in HCC patients. BMC Med 2023; 21:481. [PMID: 38049860 PMCID: PMC10696877 DOI: 10.1186/s12916-023-03137-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 10/30/2023] [Indexed: 12/06/2023] Open
Abstract
BACKGROUND Microvascular invasion (MVI) is the main factor affecting the prognosis of patients with hepatocellular carcinoma (HCC). The aim of this study was to identify accurate diagnostic biomarkers from urinary protein signatures for preoperative prediction. METHODS We conducted label-free quantitative proteomic studies on urine samples of 91 HCC patients and 22 healthy controls. We identified candidate biomarkers capable of predicting MVI status and combined them with patient clinical information to perform a preoperative nomogram for predicting MVI status in the training cohort. Then, the nomogram was validated in the testing cohort (n = 23). Expression levels of biomarkers were further confirmed by enzyme-linked immunosorbent assay (ELISA) in an independent validation HCC cohort (n = 57). RESULTS Urinary proteomic features of healthy controls are mainly characterized by active metabolic processes. Cell adhesion and cell proliferation-related pathways were highly defined in the HCC group, such as extracellular matrix organization, cell-cell adhesion, and cell-cell junction organization, which confirms the malignant phenotype of HCC patients. Based on the expression levels of four proteins: CETP, HGFL, L1CAM, and LAIR2, combined with tumor diameter, serum AFP, and GGT concentrations to establish a preoperative MVI status prediction model for HCC patients. The nomogram achieved good concordance indexes of 0.809 and 0.783 in predicting MVI in the training and testing cohorts. CONCLUSIONS The four-protein-related nomogram in urine samples is a promising preoperative prediction model for the MVI status of HCC patients. Using the model, the risk for an individual patient to harbor MVI can be determined.
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Affiliation(s)
- Yaru Wang
- Department of Hepatobiliary Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
- State Key Laboratory of Molecular Oncology, Department of Etiology and Carcinogenesis, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
- Department of Clinical Trial Research Center, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, 100005, China
| | - Bo Meng
- State Key Laboratory of Proteomics, National Center for Protein Sciences (Beijing), Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing, 102206, China
- Center for Advanced Measurement Science, National Institute of Metrology, Beijing, 100029, China
| | - Xijun Wang
- State Key Laboratory of Molecular Oncology, Department of Etiology and Carcinogenesis, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Anke Wu
- Department of Hepatobiliary Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Xiaoyu Li
- State Key Laboratory of Proteomics, National Center for Protein Sciences (Beijing), Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing, 102206, China
- College of Life Science and Bioengineering, Beijing University of Technology, Beijing, 100124, China
| | - Xiaohong Qian
- State Key Laboratory of Proteomics, National Center for Protein Sciences (Beijing), Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing, 102206, China
- College of Life Science and Bioengineering, Beijing University of Technology, Beijing, 100124, China
| | - Jianxiong Wu
- Department of Hepatobiliary Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Wantao Ying
- State Key Laboratory of Proteomics, National Center for Protein Sciences (Beijing), Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing, 102206, China.
- College of Life Science and Bioengineering, Beijing University of Technology, Beijing, 100124, China.
| | - Ting Xiao
- State Key Laboratory of Molecular Oncology, Department of Etiology and Carcinogenesis, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
| | - Weiqi Rong
- Department of Hepatobiliary Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
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Liu HF, Wang M, Lu YJ, Wang Q, Lu Y, Xing F, Xing W. CEMRI-Based Quantification of Intratumoral Heterogeneity for Predicting Aggressive Characteristics of Hepatocellular Carcinoma Using Habitat Analysis: Comparison and Combination of Deep Learning. Acad Radiol 2023:S1076-6332(23)00659-1. [PMID: 38057182 DOI: 10.1016/j.acra.2023.11.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 11/13/2023] [Accepted: 11/15/2023] [Indexed: 12/08/2023]
Abstract
RATIONALE AND OBJECTIVES To explore both an intratumoral heterogeneity (ITH) model based on habitat analysis and a deep learning (DL) model based on contrast-enhanced magnetic resonance imaging (CEMRI) and validate its efficiency for predicting microvascular invasion (MVI) and pathological differentiation in hepatocellular carcinoma (HCC). METHODS CEMRI images were retrospectively obtained from 277 HCCs in 265 patients. Habitat analysis and DL features were extracted from the CEMRI images and selected with the least absolute shrinkage and selection operator approach to develop ITH and DL models, respectively, and these robust features were then integrated to design a fusion model for predicting MVI and poorly differentiated HCC (pHCC). The predictive value of the three models was assessed using the area under the receiver operating characteristic curve (AUC). RESULTS The training and validation sets comprised 221 HCCs and 56 HCCs, respectively. The ITH and DL models presented AUC values of (0.90 vs. 0.87) for predicting MVI in the training set, with AUC values of 0.86 and 0.83 in the validation set. The AUC values of the ITH model to predict pHCC were 0.90 and 0.86 in the two sets, respectively; they were 0.84 and 0.80 for the DL model. The fusion model yielded the best performance for predicting MVI and pHCC in the training set (AUC=0.95, 0.90) and in the validation set (AUC=0.89, 0.87), respectively. CONCLUSION A fusion model integrating ITH and DL features derived from CEMRI images can serve as an excellent imaging biomarker for predicting aggressive characteristics in HCC.
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Affiliation(s)
- Hai-Feng Liu
- Department of Radiology, Third Affiliated Hospital of Soochow University, No.185, Juqian ST, Tianning District, Changzhou, 213000, Jiangsu, China (H.-F.L., Y.-J.L., Q.W., Y.L., W.X.)
| | - Min Wang
- Department of Anesthesiology, The Second People's Hospital of Changzhou, Affiliated Hospital of Nanjing Medical University, Changzhou, Jiangsu, China (M.W.)
| | - Yu-Jie Lu
- Department of Radiology, Third Affiliated Hospital of Soochow University, No.185, Juqian ST, Tianning District, Changzhou, 213000, Jiangsu, China (H.-F.L., Y.-J.L., Q.W., Y.L., W.X.)
| | - Qing Wang
- Department of Radiology, Third Affiliated Hospital of Soochow University, No.185, Juqian ST, Tianning District, Changzhou, 213000, Jiangsu, China (H.-F.L., Y.-J.L., Q.W., Y.L., W.X.)
| | - Yang Lu
- Department of Radiology, Third Affiliated Hospital of Soochow University, No.185, Juqian ST, Tianning District, Changzhou, 213000, Jiangsu, China (H.-F.L., Y.-J.L., Q.W., Y.L., W.X.)
| | - Fei Xing
- Department of Radiology, Nantong Third People's Hospital, Nantong, Jiangsu, China (F.X.)
| | - Wei Xing
- Department of Radiology, Third Affiliated Hospital of Soochow University, No.185, Juqian ST, Tianning District, Changzhou, 213000, Jiangsu, China (H.-F.L., Y.-J.L., Q.W., Y.L., W.X.).
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Piccolo G, Barabino M, Santambrogio R, Lecchi F, Di Gioia G, Opocher E, Bianchi PP. Correlation Between Indocyanine Green Fluorescence Patterns and Grade of Differentiation of Hepatocellular Carcinoma: A Western Prospective Cohort Study. Surg Innov 2023; 30:770-778. [PMID: 36840625 DOI: 10.1177/15533506231157171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/26/2023]
Abstract
Background. Most of the available evidence on the use of indocyanine green (ICG) fluorescence in clinical practice consists of articles published by surgeons of the Asian-Pacific area. We performed a prospective cohort study to assess the patterns of ICG fluorescence in Western hepatocellular carcinoma (HCC) counterparts.Methods. From April 2019 to January 2022, a total of 31 consecutive patients who underwent laparoscopic liver resection (LLR) for superficial HCC were enrolled in this prospective study. All patients underwent laparoscopic staging with both laparoscopic ultrasound (LUS) and ICG fluorescence imaging.Results. A total of 38 hepatocellular carcinomas (HCCs) were enrolled: 23 superficial (surfacing at the liver's Glissonian capsule), 5 exophytic, 5 shallow (<8 mm from the hepatic surface) and 5 deep (>10 mm from the hepatic surface). The detection rate with preoperative imaging (abdominal CT/MRI), LUS, ICG fluorescence and combined modalities (ICG and LUS) was 97.4%, 94.9%, 89.7% and 100%, respectively. The five deep seated lesions underwent ultrasound-guided laparoscopic thermal ablation. The other 33 HCCs were treated with minimally invasive liver resection. Intraoperative ultrasound patterns were registered for each single nodule resected. The ICG fluorescence pattern was classified in two types: total fluorescence (all the tumoral tissue showed strong and homogeneous fluorescence), n = 9/33 (27.3%), and non-total fluorescence (partial and rim fluorescence), n = 24/33 (72.7%). There was a statistical correlation between ICG patterns and grade of differentiation. Almost all lesions with uniform fluorescence pattern were well-differentiated HCCs (G1-G2), while partial and rim-type fluorescence pattern were more common among moderately and poorly differentiated HCCs (G3-G4) (88.9% vs 11.1%, 37.5% vs 62.5%, P = .025, respectively).Conclusions. ICG fluorescence imaging could be used to identify early the grade of HCC, ie intraoperatively, thus influencing the intraoperative treatment.
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Affiliation(s)
- Gaetano Piccolo
- General Surgery Unit, Department of Health Sciences, San Paolo Hospital, University of Milan, Milan, Italy
| | - Matteo Barabino
- General Surgery Unit, Department of Health Sciences, San Paolo Hospital, University of Milan, Milan, Italy
| | | | - Francesca Lecchi
- General Surgery Residency Program, University of Milan, Milan, Italy
| | - Giulio Di Gioia
- General Surgery Unit, Department of Health Sciences, San Paolo Hospital, University of Milan, Milan, Italy
| | - Enrico Opocher
- General Surgery Unit, Department of Health Sciences, San Paolo Hospital, University of Milan, Milan, Italy
| | - Paolo Pietro Bianchi
- General Surgery Unit, Department of Health Sciences, San Paolo Hospital, University of Milan, Milan, Italy
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Zhou C, Weng J, Liu S, Zhou Q, Hu Z, Yin Y, Lv P, Sun J, Li H, Yi Y, Shen Y, Ye Q, Shi Y, Dong Q, Liu C, Zhu X, Ren N. Whole-exome sequencing reveals the metastatic potential of hepatocellular carcinoma from the perspective of tumor and circulating tumor DNA. Hepatol Int 2023; 17:1461-1476. [PMID: 37217808 DOI: 10.1007/s12072-023-10540-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/29/2023] [Accepted: 04/15/2023] [Indexed: 05/24/2023]
Abstract
BACKGROUND Relapse of hepatocellular carcinoma (HCC) due to vascular invasion is common, but the genomic mechanisms remain unclear, and molecular determinants of high-risk relapse cases are lacking. We aimed to reveal the evolutionary trajectory of microvascular invasion (MVI) and develop a predictive signature for relapse in HCC. METHODS Whole-exome sequencing was performed on tumor and peritumor tissues, portal vein tumor thrombus (PVTT), and circulating tumor DNA (ctDNA) to compare the genomic profiles between 5 HCC patients with MVI and 5 patients without MVI. We conducted an integrated analysis of exome and transcriptome to develop and validate a prognostic signature in two public cohorts and one cohort from Zhongshan Hospital, Fudan University. RESULTS Shared genomic landscapes and identical clonal origins among tumor, PVTT, and ctDNA were observed in MVI ( +) HCC, suggesting that genomic changes favoring metastasis occur at the primary tumor stage and are inherited in metastatic lesions and ctDNA. There was no clonal relatedness between the primary tumor and ctDNA in MVI ( - ) HCC. HCC had dynamic mutation alterations during MVI and exhibited genetic heterogeneity between primary and metastatic tumors, which can be comprehensively reflected by ctDNA. A relapse-related gene signature named RGSHCC was developed based on the significantly mutated genes associated with MVI and shown to be a robust classifier of HCC relapse. CONCLUSIONS We characterized the genomic alterations during HCC vascular invasion and revealed a previously undescribed evolution pattern of ctDNA in HCC. A novel multiomics-based signature was developed to identify high-risk relapse populations.
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Affiliation(s)
- Chenhao Zhou
- Department of Liver Surgery and Transplantation, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Liver Cancer Institute, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, People's Republic of China
- Department of Molecular and Cellular Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
- Key Laboratory of Whole-Period Monitoring and Precise Intervention of Digestive Cancer of Shanghai Municipal Health Commission, Shanghai, 201199, People's Republic of China
| | - Jialei Weng
- Department of Liver Surgery and Transplantation, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Liver Cancer Institute, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, People's Republic of China
- Key Laboratory of Whole-Period Monitoring and Precise Intervention of Digestive Cancer of Shanghai Municipal Health Commission, Shanghai, 201199, People's Republic of China
| | - Shaoqing Liu
- Department of Liver Surgery and Transplantation, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Liver Cancer Institute, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, People's Republic of China
- Key Laboratory of Whole-Period Monitoring and Precise Intervention of Digestive Cancer of Shanghai Municipal Health Commission, Shanghai, 201199, People's Republic of China
| | - Qiang Zhou
- Department of Liver Surgery and Transplantation, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Liver Cancer Institute, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, People's Republic of China
- Key Laboratory of Whole-Period Monitoring and Precise Intervention of Digestive Cancer of Shanghai Municipal Health Commission, Shanghai, 201199, People's Republic of China
| | - Zhiqiu Hu
- Key Laboratory of Whole-Period Monitoring and Precise Intervention of Digestive Cancer of Shanghai Municipal Health Commission, Shanghai, 201199, People's Republic of China
- Institute of Fudan-Minhang Academic Health System, Minhang Hospital, Fudan University, Shanghai, 201199, People's Republic of China
| | - Yirui Yin
- Department of Liver Surgery, Xiamen Branch, Zhongshan Hospital, Fudan University, Xiamen, 361015, People's Republic of China
| | - Peng Lv
- Department of Liver Surgery, Xiamen Branch, Zhongshan Hospital, Fudan University, Xiamen, 361015, People's Republic of China
| | - Jialei Sun
- Department of Liver Surgery and Transplantation, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Liver Cancer Institute, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, People's Republic of China
| | - Hui Li
- Department of Liver Surgery and Transplantation, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Liver Cancer Institute, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, People's Republic of China
| | - Yong Yi
- Department of Liver Surgery and Transplantation, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Liver Cancer Institute, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, People's Republic of China
| | - Yinghao Shen
- Department of Liver Surgery and Transplantation, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Liver Cancer Institute, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, People's Republic of China
| | - Qinghai Ye
- Department of Liver Surgery and Transplantation, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Liver Cancer Institute, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, People's Republic of China
| | - Yi Shi
- Biomedical Research Centre, Zhongshan Hospital, Fudan University, Shanghai, 200032, People's Republic of China
| | - Qiongzhu Dong
- Key Laboratory of Whole-Period Monitoring and Precise Intervention of Digestive Cancer of Shanghai Municipal Health Commission, Shanghai, 201199, People's Republic of China
- Institute of Fudan-Minhang Academic Health System, Minhang Hospital, Fudan University, Shanghai, 201199, People's Republic of China
| | - Chunxiao Liu
- Department of Molecular and Cellular Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Xiaoqiang Zhu
- State Key Laboratory for Oncogenes and Related Genes, Division of Gastroenterology and Hepatology, Key Laboratory of Gastroenterology and Hepatology, School of Medicine, Ministry of Health, Shanghai Institute of Digestive Disease, Renji Hospital, Shanghai Jiao Tong University, Shanghai, 200001, People's Republic of China.
- School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, 999077, People's Republic of China.
| | - Ning Ren
- Department of Liver Surgery and Transplantation, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Liver Cancer Institute, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, People's Republic of China.
- Key Laboratory of Whole-Period Monitoring and Precise Intervention of Digestive Cancer of Shanghai Municipal Health Commission, Shanghai, 201199, People's Republic of China.
- Institute of Fudan-Minhang Academic Health System, Minhang Hospital, Fudan University, Shanghai, 201199, People's Republic of China.
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Zhang K, Zhang L, Li WC, Xie SS, Cui YZ, Lin LY, Shen ZW, Zhang HM, Xia S, Ye ZX, He K, Shen W. Radiomics nomogram for the prediction of microvascular invasion of HCC and patients' benefit from postoperative adjuvant TACE: a multi-center study. Eur Radiol 2023; 33:8936-8947. [PMID: 37368104 DOI: 10.1007/s00330-023-09824-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Revised: 03/15/2023] [Accepted: 03/26/2023] [Indexed: 06/28/2023]
Abstract
OBJECTIVES To evaluate the performance of a radiomics nomogram developed based on gadolinium-ethoxybenzyl-diethylenetriamine penta-acetic acid (Gd-EOB-DTPA) MRI for preoperative prediction of microvascular invasion (MVI) of hepatocellular carcinoma (HCC), and to identify patients who may benefit from the postoperative adjuvant transarterial chemoembolization (PA-TACE). METHODS A total of 260 eligible patients were retrospectively enrolled from three hospitals (140, 65, and 55 in training, standardized external, and non-standardized external validation cohort). Radiomics features and image characteristics were extracted from Gd-EOB-DTPA MRI image before hepatectomy for each lesion. In the training cohort, a radiomics nomogram which incorporated the radiomics signature and radiological predictors was developed. The performance of the radiomics nomogram was assessed with respect to discrimination calibration, and clinical usefulness with external validation. A score (m-score) was constructed to stratify the patients and explored whether it could accurately predict patient who benefit from PA-TACE. RESULTS A radiomics nomogram integrated with the radiomics signature, max-D(iameter) > 5.1 cm, peritumoral low intensity (PTLI), incomplete capsule, and irregular morphology had favorable discrimination in the training cohort (AUC = 0.982), the standardized external validation cohort (AUC = 0.969), and the non-standardized external validation cohort (AUC = 0.981). Decision curve analysis confirmed the clinical usefulness of the novel radiomics nomogram. The log-rank test revealed that PA-TACE significantly decreased the early recurrence in the high-risk group (p = 0.006) with no significant effect in the low-risk group (p = 0.270). CONCLUSIONS The novel radiomics nomogram combining the radiomics signature and clinical radiological features achieved preoperative non-invasive MVI risk prediction and patient benefit assessment after PA-TACE, which may help clinicians implement more appropriate interventions. CLINICAL RELEVANCE STATEMENT Our radiomics nomogram could represent a novel biomarker to identify patients who may benefit from the postoperative adjuvant transarterial chemoembolization, which may help clinicians to implement more appropriate interventions and perform individualized precision therapies. KEY POINTS • The novel radiomics nomogram developed based on Gd-EOB-DTPA MRI achieved preoperative non-invasive MVI risk prediction. • An m-score based on the radiomics nomogram could stratify HCC patients and further identify individuals who may benefit from the PA-TACE. • The radiomics nomogram could help clinicians to implement more appropriate interventions and perform individualized precision therapies.
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Affiliation(s)
- Kun Zhang
- Department of Radiology, Medical Imaging Institute of Tianjin, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin, 300192, China
| | - Lei Zhang
- Department of Radiology, The First Hospital of Jilin University, No. 71 Xinmin Street, Changchun, 130012, China
| | - Wen-Cui Li
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
- Tianjin's Clinical Research Center for Cancer, Tianjin, 300060, China
| | - Shuang-Shuang Xie
- Department of Radiology, Tianjin First Central Hospital, Tianjin Institute of Imaging Medicine, 24 Fukang Road, Nankai District, Tianjin, 300192, China
| | - Ying-Zhu Cui
- Department of Radiology, The First Hospital of Jilin University, No. 71 Xinmin Street, Changchun, 130012, China
| | - Li-Ying Lin
- Department of Radiology, Tianjin First Central Hospital, Tianjin Institute of Imaging Medicine, 24 Fukang Road, Nankai District, Tianjin, 300192, China
| | - Zhi-Wei Shen
- Philips Healthcare, Beijing, The World Profit Centre, No. 16 Tianze Road, Chaoyang District, Beijing, 100125, China
| | - Hui-Mao Zhang
- Department of Radiology, The First Hospital of Jilin University, No. 71 Xinmin Street, Changchun, 130012, China
| | - Shuang Xia
- Department of Radiology, Medical Imaging Institute of Tianjin, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin, 300192, China
| | - Zhao-Xiang Ye
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.
- Tianjin's Clinical Research Center for Cancer, Tianjin, 300060, China.
| | - Kan He
- Department of Radiology, The First Hospital of Jilin University, No. 71 Xinmin Street, Changchun, 130012, China.
| | - Wen Shen
- Department of Radiology, Tianjin First Central Hospital, Tianjin Institute of Imaging Medicine, 24 Fukang Road, Nankai District, Tianjin, 300192, China.
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Kocheise L, Schoenlein M, Behrends B, Joerg V, Casar C, Fruendt TW, Renné T, Heumann A, Li J, Huber S, Lohse AW, Pantel K, Riethdorf S, Wege H, Schulze K, von Felden J. EpCAM-positive circulating tumor cells and serum AFP levels predict outcome after curative resection of hepatocellular carcinoma. Sci Rep 2023; 13:20827. [PMID: 38012205 PMCID: PMC10682153 DOI: 10.1038/s41598-023-47580-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Accepted: 11/14/2023] [Indexed: 11/29/2023] Open
Abstract
Hepatocellular carcinoma (HCC) has high recurrence rates exceeding 50% despite curative resection. The serum biomarker alpha-fetoprotein (AFP) is a well-known prognostic marker for HCC. EpCAM-positive circulating tumor cells (CTC) have a high predictive value for early HCC recurrence after curatively intended resection, most likely indicating micro-metastases at the time of resection. However, sensitivity remains low. The objective of this study was to evaluate a composite test comprising both CTC and AFP to identify patients at high risk for early HCC recurrence. We prospectively enrolled 58 patients undergoing curative intended resection for HCC at a tertiary referral center. Blood specimens were obtained prior to resection and analyzed for EpCAM-positive CTC and serum AFP levels. A positive result was defined as either detection of CTC or AFP levels ≥ 400 ng/ml. Eight patients tested positive for CTC, seven for AFP, and two for both markers. A positive composite test was significantly associated with shorter early recurrence-free survival (5 vs. 16 months, p = 0.005), time to recurrence (5 vs. 16 months, p = 0.011), and overall survival (37 vs. not reached, p = 0.034). Combining CTC and AFP identified patients with poor outcome after surgical resection, for whom adjuvant or neoadjuvant therapies may be particularly desirable.
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Affiliation(s)
- Lorenz Kocheise
- I. Department of Medicine, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany
| | - Martin Schoenlein
- Department of Oncology, Hematology and Bone Marrow Transplantation with Section Pneumology, Hubertus Wald University Comprehensive Cancer Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Berit Behrends
- Institute of Clinical Chemistry and Laboratory Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Vincent Joerg
- I. Department of Medicine, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany
| | - Christian Casar
- I. Department of Medicine, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany
- Bioinformatics Core, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Thorben W Fruendt
- I. Department of Medicine, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany
| | - Thomas Renné
- Institute of Clinical Chemistry and Laboratory Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Irish Centre for Vascular Biology, School of Pharmacy and Biomolecular Sciences, Royal College of Surgeons in Ireland, Dublin, Ireland
- Center for Thrombosis and Hemostasis (CTH), Johannes Gutenberg University Medical Center, Mainz, Germany
| | - Asmus Heumann
- Department of General, Visceral and Thoracic Surgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Jun Li
- Department of General, Visceral and Thoracic Surgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Samuel Huber
- I. Department of Medicine, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany
| | - Ansgar W Lohse
- I. Department of Medicine, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany
| | - Klaus Pantel
- Department of Tumor Biology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Sabine Riethdorf
- Department of Tumor Biology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Henning Wege
- I. Department of Medicine, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany
- Cancer Center Esslingen, Klinikum Esslingen, Esslingen, Germany
| | - Kornelius Schulze
- I. Department of Medicine, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany
| | - Johann von Felden
- I. Department of Medicine, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany.
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Zhang YB, Yang G, Bu Y, Lei P, Zhang W, Zhang DY. Development of a machine learning-based model for predicting risk of early postoperative recurrence of hepatocellular carcinoma. World J Gastroenterol 2023; 29:5804-5817. [PMID: 38074914 PMCID: PMC10701309 DOI: 10.3748/wjg.v29.i43.5804] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/26/2023] [Revised: 10/07/2023] [Accepted: 11/03/2023] [Indexed: 11/20/2023] Open
Abstract
BACKGROUND Surgical resection is the primary treatment for hepatocellular carcinoma (HCC). However, studies indicate that nearly 70% of patients experience HCC recurrence within five years following hepatectomy. The earlier the recurrence, the worse the prognosis. Current studies on postoperative recurrence primarily rely on postoperative pathology and patient clinical data, which are lagging. Hence, developing a new pre-operative prediction model for postoperative recurrence is crucial for guiding individualized treatment of HCC patients and enhancing their prognosis. AIM To identify key variables in pre-operative clinical and imaging data using machine learning algorithms to construct multiple risk prediction models for early postoperative recurrence of HCC. METHODS The demographic and clinical data of 371 HCC patients were collected for this retrospective study. These data were randomly divided into training and test sets at a ratio of 8:2. The training set was analyzed, and key feature variables with predictive value for early HCC recurrence were selected to construct six different machine learning prediction models. Each model was evaluated, and the best-performing model was selected for interpreting the importance of each variable. Finally, an online calculator based on the model was generated for daily clinical practice. RESULTS Following machine learning analysis, eight key feature variables (age, intratumoral arteries, alpha-fetoprotein, pre-operative blood glucose, number of tumors, glucose-to-lymphocyte ratio, liver cirrhosis, and pre-operative platelets) were selected to construct six different prediction models. The XGBoost model outperformed other models, with the area under the receiver operating characteristic curve in the training, validation, and test datasets being 0.993 (95% confidence interval: 0.982-1.000), 0.734 (0.601-0.867), and 0.706 (0.585-0.827), respectively. Calibration curve and decision curve analysis indicated that the XGBoost model also had good predictive performance and clinical application value. CONCLUSION The XGBoost model exhibits superior performance and is a reliable tool for predicting early postoperative HCC recurrence. This model may guide surgical strategies and postoperative individualized medicine.
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Affiliation(s)
- Yu-Bo Zhang
- Department of Hepatobiliary Surgery, General Hospital of Ningxia Medical University, Yinchuan 750003, Ningxia Hui Autonomous Region, China
| | - Gang Yang
- Department of Hepatobiliary Surgery, General Hospital of Ningxia Medical University, Yinchuan 750003, Ningxia Hui Autonomous Region, China
| | - Yang Bu
- Department of Hepatobiliary Surgery, People's Hospital of Ningxia Hui Autonomous Region, Yinchuan 750003, Ningxia Hui Autonomous Region, China
| | - Peng Lei
- Department of Hepatobiliary Surgery, General Hospital of Ningxia Medical University, Yinchuan 750003, Ningxia Hui Autonomous Region, China
| | - Wei Zhang
- Department of Hepatobiliary Surgery, General Hospital of Ningxia Medical University, Yinchuan 750003, Ningxia Hui Autonomous Region, China
| | - Dan-Yang Zhang
- Department of Hepatobiliary Surgery, General Hospital of Ningxia Medical University, Yinchuan 750003, Ningxia Hui Autonomous Region, China
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Zhang L, Su K, Liu Q, Li B, Wang Y, Cheng C, Li Y, Xu C, Chen J, Wu H, Zhu M, Mai X, Cao Y, Peng J, Yue Y, Ding Y, Yu D. Kidney-type glutaminase is a biomarker for the diagnosis and prognosis of hepatocellular carcinoma: a prospective study. BMC Cancer 2023; 23:1081. [PMID: 37946141 PMCID: PMC10633901 DOI: 10.1186/s12885-023-11601-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Accepted: 11/01/2023] [Indexed: 11/12/2023] Open
Abstract
PURPOSE The pathological diagnosis and prognosis prediction of hepatocellular carcinoma (HCC) is challenging due to the lack of specific biomarkers. This study aimed to validate the diagnostic and prognostic efficiency of Kidney-type glutaminase (GLS1) for HCC in prospective cohorts with a large sample size. METHODS A total of 1140 HCC patients were enrolled in our prospective clinical trials. Control cases included 114 nontumour tissues. The registered clinical trial (ChiCTR-DDT-14,005,102, chictr.org.cn) was referred to for the exact protocol. GLS1 immunohistochemistry was performed on the whole tumour section. The diagnostic and prognostic performances of GLS1 was evaluated by the receiver operating characteristic curve and Cox regression model. RESULTS The sensitivity, specificity, positive predictive value, negative predictive value, Youden index, and area under the curve of GLS1 for the diagnosis of HCC were 0.746, 0.842, 0.979, 0.249, 0.588, and 0.814, respectively, which could be increased to 0.846, 0.886, 0.987,0.366, 0.732, and 0.921 when combined with glypican 3 (GPC3) and alpha-fetoprotein (AFP), indicating better diagnostic performance. Further, we developed a nomogram with GPC3 and GLS1 for identifying HCC which showed good discrimination and calibration. GLS1 expression was also related with age, T stage, TNM stage, Edmondson-Steiner grade, microvascular invasion, Ki67, VEGFR2, GPC3, and AFP expression in HCC. GLS1 expression was negatively correlated with disease-free survival (P < 0.001) probability of patients with HCC. CONCLUSIONS It was validated that GLS1 was a sensitive and specific biomarker for pathological diagnosis of HCC and had prognostic value, thus having practical value for clinical application.
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Affiliation(s)
- Laizhu Zhang
- Division of Hepatobiliary and Transplantation Surgery, Department of General Surgery, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Ke Su
- Division of Hepatobiliary and Transplantation Surgery, Department of General Surgery, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Qi Liu
- Division of Hepatobiliary and Transplantation Surgery, Department of General Surgery, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Binghua Li
- Division of Hepatobiliary and Transplantation Surgery, Department of General Surgery, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Ye Wang
- Division of Hepatobiliary and Transplantation Surgery, Department of General Surgery, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Chunxiao Cheng
- Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine, Nanjing, China
| | - Yunzheng Li
- Division of Hepatobiliary and Transplantation Surgery, Department of General Surgery, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Chun Xu
- Department of Pathology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Jun Chen
- Department of Pathology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Hongyan Wu
- Department of Pathology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Mengxia Zhu
- Department of Radiology, Nanjing Drum Tower Clinical Medical School, the Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Xiaoli Mai
- Department of Radiology, Nanjing Drum Tower Clinical Medical School, the Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Yajuan Cao
- Division of Hepatobiliary and Transplantation Surgery, Department of General Surgery, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Jin Peng
- Division of Hepatobiliary and Transplantation Surgery, Department of General Surgery, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Yang Yue
- Division of Hepatobiliary and Transplantation Surgery, Department of General Surgery, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Yitao Ding
- Division of Hepatobiliary and Transplantation Surgery, Department of General Surgery, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Decai Yu
- Division of Hepatobiliary and Transplantation Surgery, Department of General Surgery, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China.
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Liu J, Zhuang G, Bai S, Hu Z, Xia Y, Lu C, Wang J, Wang C, Liu L, Li F, Wu Y, Shen F, Wang K. The Comparison of Surgical Margins and Type of Hepatic Resection for Hepatocellular Carcinoma With Microvascular Invasion. Oncologist 2023; 28:e1043-e1051. [PMID: 37196175 PMCID: PMC10628578 DOI: 10.1093/oncolo/oyad124] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Accepted: 04/11/2023] [Indexed: 05/19/2023] Open
Abstract
OBJECTIVE The objective of this study was to investigate the impact of surgical margin and hepatic resection on prognosis and compare their importance on prognosis in patients with hepatocellular carcinoma (HCC). METHODS The clinical data of 906 patients with HCC who underwent hepatic resection in our hospital from January 2013 to January 2015 were collected retrospectively. All patients were divided into anatomical resection (AR) (n = 234) and nonanatomical resection (NAR) group (n = 672) according to type of hepatic resection. The effects of AR and NAR and wide and narrow margins on overall survival (OS) and time to recurrence (TTR) were analyzed. RESULTS In all patients, narrow margin (1.560, 1.278-1.904; 1.387, 1.174-1.639) is an independent risk factor for OS and TTR, and NAR is not. Subgroup analysis showed that narrow margins (2.307, 1.699-3.132; 1.884, 1.439-2.468), and NAR (1.481, 1.047-2.095; 1.372, 1.012-1.860) are independent risk factors for OS and TTR in patients with microvascular invasion (MVI)-positive. Further analysis showed that for patients with MVI-positive HCC, NAR with wide margins was a protective factor for OS and TTR compared to AR with narrow margins (0.618, 0.396-0.965; 0.662, 0.448-0.978). The 1, 3, and 5 years OS and TTR rate of the two group were 81%, 49%, 29% versus 89%, 64%, 49% (P = .008) and 42%, 79%, 89% versus 32%, 58%, 74% (P = .024), respectively. CONCLUSIONS For patients with MVI-positive HCC, AR and wide margins were protective factors for prognosis. However, wide margins are more important than AR on prognosis. In the clinical setting, if the wide margins and AR cannot be ensured at the same time, the wide margins should be ensured first.
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Affiliation(s)
- Jianwei Liu
- Department of Hepatic Surgery II, Third Affiliated Hospital of Naval Medical University (Eastern Hepatobiliary Surgery Hospital), Shanghai, People's Republic of China
| | - Guokun Zhuang
- Department of Hepatic Surgery II, Third Affiliated Hospital of Naval Medical University (Eastern Hepatobiliary Surgery Hospital), Shanghai, People's Republic of China
| | - Shilei Bai
- Department of Hepatic Surgery II, Third Affiliated Hospital of Naval Medical University (Eastern Hepatobiliary Surgery Hospital), Shanghai, People's Republic of China
| | - Zhiliang Hu
- Department of Hepatic Surgery II, Third Affiliated Hospital of Naval Medical University (Eastern Hepatobiliary Surgery Hospital), Shanghai, People's Republic of China
| | - Yong Xia
- Department of Hepatic Surgery IV, Third Affiliated Hospital of Naval Medical University (Eastern Hepatobiliary Surgery Hospital), Shanghai, People's Republic of China
| | - Caixia Lu
- Department of Hepatic Surgery II, Third Affiliated Hospital of Naval Medical University (Eastern Hepatobiliary Surgery Hospital), Shanghai, People's Republic of China
| | - Jie Wang
- Department of Hepatic Surgery II, Third Affiliated Hospital of Naval Medical University (Eastern Hepatobiliary Surgery Hospital), Shanghai, People's Republic of China
| | - Chunyan Wang
- Department of Hepatic Surgery II, Third Affiliated Hospital of Naval Medical University (Eastern Hepatobiliary Surgery Hospital), Shanghai, People's Republic of China
| | - Liu Liu
- Department of Hepatic Surgery II, Third Affiliated Hospital of Naval Medical University (Eastern Hepatobiliary Surgery Hospital), Shanghai, People's Republic of China
| | - Fengwei Li
- Department of Hepatic Surgery II, Third Affiliated Hospital of Naval Medical University (Eastern Hepatobiliary Surgery Hospital), Shanghai, People's Republic of China
| | - Yeye Wu
- Department of Hepatic Surgery II, Third Affiliated Hospital of Naval Medical University (Eastern Hepatobiliary Surgery Hospital), Shanghai, People's Republic of China
| | - Feng Shen
- Department of Hepatic Surgery IV, Third Affiliated Hospital of Naval Medical University (Eastern Hepatobiliary Surgery Hospital), Shanghai, People's Republic of China
- Department of Hepatic Surgery II, Third Affiliated Hospital of Naval Medical University (Eastern Hepatobiliary Surgery Hospital), Shanghai, People's Republic of China
| | - Kui Wang
- Department of Hepatic Surgery II, Third Affiliated Hospital of Naval Medical University (Eastern Hepatobiliary Surgery Hospital), Shanghai, People's Republic of China
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Sun B, Ji WD, Wang WC, Chen L, Ma JY, Tang EJ, Lin MB, Zhang XF. Circulating tumor cells participate in the formation of microvascular invasion and impact on clinical outcomes in hepatocellular carcinoma. Front Genet 2023; 14:1265866. [PMID: 38028589 PMCID: PMC10652898 DOI: 10.3389/fgene.2023.1265866] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Accepted: 10/20/2023] [Indexed: 12/01/2023] Open
Abstract
Hepatocellular carcinoma (HCC) is a common malignant tumor worldwide. Although the treatment strategies have been improved in recent years, the long-term prognosis of HCC is far from satisfactory mainly due to high postoperative recurrence and metastasis rate. Vascular tumor thrombus, including microvascular invasion (MVI) and portal vein tumor thrombus (PVTT), affects the outcome of hepatectomy and liver transplantation. If vascular invasion could be found preoperatively, especially the risk of MVI, more reasonable surgical selection will be chosen to reduce the risk of postoperative recurrence and metastasis. However, there is a lack of reliable prediction methods, and the formation mechanism of MVI/PVTT is still unclear. At present, there is no study to explore the possibility of tumor thrombus formation from a single circulating tumor cell (CTC) of HCC, nor any related study to describe the possible leading role and molecular mechanism of HCC CTCs as an important component of MVI/PVTT. In this study, we review the current understanding of MVI and possible mechanisms, discuss the function of CTCs in the formation of MVI and interaction with immune cells in the circulation. In conclusion, we discuss implications for potential therapeutic targets and the prospect of clinical treatment of HCC.
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Affiliation(s)
- Bin Sun
- Center for Clinical Research and Translational Medicine, Yangpu Hospital, Tongji University School of Medicine, Shanghai, China
| | - Wei-Dan Ji
- Department of Molecular Oncology, Eastern Hepatobiliary Surgical Hospital and National Center for Liver Cancer, Navy Military Medical University, Shanghai, China
| | - Wen-Chao Wang
- Department of General Surgery, Yangpu Hospital, Tongji University School of Medicine, Shanghai, China
| | - Lei Chen
- Department of General Surgery, Yangpu Hospital, Tongji University School of Medicine, Shanghai, China
| | - Jun-Yong Ma
- Department of Hepatic Surgery, Eastern Hepatobiliary Surgery Hospital, Navy Military Medical University, Shanghai, China
| | - Er-Jiang Tang
- Center for Clinical Research and Translational Medicine, Yangpu Hospital, Tongji University School of Medicine, Shanghai, China
| | - Mou-Bin Lin
- Department of General Surgery, Yangpu Hospital, Tongji University School of Medicine, Shanghai, China
| | - Xiao-Feng Zhang
- Department of Hepatic Surgery, Eastern Hepatobiliary Surgery Hospital, Navy Military Medical University, Shanghai, China
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Deng W, Chen F, Li Y, Xu L. Development of a clinical scoring model to predict the overall and relapse‑free survival of patients with hepatocellular carcinoma following a hepatectomy. Mol Clin Oncol 2023; 19:87. [PMID: 37854326 PMCID: PMC10580259 DOI: 10.3892/mco.2023.2683] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 09/08/2023] [Indexed: 10/20/2023] Open
Abstract
Hepatocellular carcinoma (HCC) is a highly lethal disease, and surgical resection is one of the major treatment methods used. However, to date, at least to the best of our knowledge, there is no effective prognostic scoring system for the overall survival (OS) and relapse-free survival (RFS) of patients following hepatectomy. The present study developed a low-cost and easy-to-use model based on the clinicopathological characteristics of patients with HCC for assessment of outcome prediction and risk stratification. A total of 690 patients with HCC undergoing surgery were included and randomly divided into two cohorts (n=345). Cox regression analysis was conducted to investigate the association between the clinicopathological and treatment features, and patient survival. Multivariate analysis revealed that ascites, vascular tumor thrombus, low tumor differentiation and extrahepatic metastasis were independent risk factors for OS. Extrahepatic metastasis and multiple tumors were independent risk factors to predict tumor recurrence. These variables were weighted to construct the ascites, vascular tumor thrombus, low tumor differentiation, extrahepatic metastasis and multiple tumors (AVLEM) score based on the cumulative incidence (CuI) of the aforementioned variables, and the patients were classified into grade 0 (CuI=0), grade 1 (CuI=1 for OS and CuI ≥1 for RFS), and grade 2 (CuI ≥2) subgroups, respectively. Kaplan-Meier analysis revealed that the OS and RFS differed significantly among the subgroups; however, the survival rate between the two cohorts did not exhibit any marked differences. On the whole, the present study demonstrates that with this AVLEM scoring system, patients with HCC with a high score had a poor OS and RFS; thus, it is suggested that such patients undergo imaging examinations following a hepatectomy more frequently.
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Affiliation(s)
- Wanyu Deng
- College of Life Science, Shangrao Normal University, Shangrao, Jiangxi 334001, P.R. China
- Department of Pancreato-Biliary Surgery, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, Guangdong 510120, P.R. China
| | - Fu Chen
- College of Life Science, Shangrao Normal University, Shangrao, Jiangxi 334001, P.R. China
| | - Yuanxiang Li
- College of Life Science, Shangrao Normal University, Shangrao, Jiangxi 334001, P.R. China
| | - Leibo Xu
- Department of Pancreato-Biliary Surgery, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, Guangdong 510120, P.R. China
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Wang L, Cong R, Chen Z, Li D, Feng B, Liang M, Wang S, Ma X, Zhao X. Determination of prognostic predictors in patients with solitary hepatocellular carcinoma: histogram analysis of multiparametric MRI. Abdom Radiol (NY) 2023; 48:3362-3372. [PMID: 37561148 DOI: 10.1007/s00261-023-04015-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2023] [Revised: 07/20/2023] [Accepted: 07/24/2023] [Indexed: 08/11/2023]
Abstract
PURPOSE To evaluate the histogram parameters of preoperative multiparametric magnetic resonance imaging (MRI) and clinical-radiological (CR) characteristics as prognostic predictors in patients with solitary hepatocellular carcinoma ≤ 5 cm and to determine the optimal time window for histogram analysis. METHODS We retrospectively included 151 patients who underwent preoperative MRI between January 2012 and December 2017. All patients were randomly separated into training and validation cohorts (n = 105 and 46). Eight whole-lesion histogram parameters were extracted from T2-weighted images, apparent diffusion coefficient maps, and dynamic contrast-enhanced images. Univariate and multivariate logistic regression analyses were performed to evaluate these histogram parameters and CR variables related to early recurrence (ER) and recurrence-free survival. A nomogram was derived from the clinical-radiological-histogram (CRH) model that incorporated these risk factors. Kaplan-Meier survival analysis was performed to evaluate the prognostic performance of the CRH model. RESULTS In total, 151 patients (male: female, 130: 21; median age, 54.46 ± 9.09 years) were evaluated. Multivariate logistic regression analysis revealed that the significant risk factors of ER were Mean Absolute Deviation and Minimum in the histogram analysis of the delayed phase images, as well as three important CR variables: albumin-bilirubin grade, microvascular invasion, and tumor size. The nomogram built by incorporating these risk factors showed satisfactory predictive ability in the training and validation cohorts with AUC values of 0.747 and 0.765, respectively. Furthermore, the prognostic nomogram can effectively classify patients into high- and low-risk groups (p < 0.05). CONCLUSION Multiparametric MRI-derived histogram parameters provide additional value in predicting patient prognosis. The CRH model may be a useful and noninvasive method for achieving prognostic stratification and personalized disease management.
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Affiliation(s)
- Leyao Wang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Rong Cong
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Zhaowei Chen
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Dengfeng Li
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Bing Feng
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Meng Liang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Sicong Wang
- Magnetic Resonance Imaging Research, General Electric Healthcare (China), Beijing, 100176, China
| | - Xiaohong Ma
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
| | - Xinming Zhao
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
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Zhao X, Wang Y, Xia H, Liu S, Huang Z, He R, Yu L, Meng N, Wang H, You J, Li J, Yam JWP, Xu Y, Cui Y. Roles and Molecular Mechanisms of Biomarkers in Hepatocellular Carcinoma with Microvascular Invasion: A Review. J Clin Transl Hepatol 2023; 11:1170-1183. [PMID: 37577231 PMCID: PMC10412705 DOI: 10.14218/jcth.2022.00013s] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/10/2022] [Revised: 01/18/2023] [Accepted: 03/21/2023] [Indexed: 07/03/2023] Open
Abstract
Hepatocellular carcinoma (HCC) being a leading cause of cancer-related death, has high associated mortality and recurrence rates. It has been of great necessity and urgency to find effective HCC diagnosis and treatment measures. Studies have shown that microvascular invasion (MVI) is an independent risk factor for poor prognosis after hepatectomy. The abnormal expression of biomacromolecules such as circ-RNAs, lncRNAs, STIP1, and PD-L1 in HCC patients is strongly correlated with MVI. Deregulation of several markers mentioned in this review affects the proliferation, invasion, metastasis, EMT, and anti-apoptotic processes of HCC cells through multiple complex mechanisms. Therefore, these biomarkers may have an important clinical role and serve as promising interventional targets for HCC. In this review, we provide a comprehensive overview on the functions and regulatory mechanisms of MVI-related biomarkers in HCC.
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Affiliation(s)
- Xudong Zhao
- Department of Hepatopancreatobiliary Surgery, Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China
| | - Yudan Wang
- Department of Pathology, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Haoming Xia
- Department of Hepatopancreatobiliary Surgery, Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China
| | - Shuqiang Liu
- Department of Hepatopancreatobiliary Surgery, Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China
| | - Ziyue Huang
- Department of Hepatopancreatobiliary Surgery, Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China
| | - Risheng He
- Department of Hepatopancreatobiliary Surgery, Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China
| | - Liang Yu
- Department of Hepatopancreatobiliary Surgery, Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China
- Department of Pathology, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Nanfeng Meng
- Department of Hepatopancreatobiliary Surgery, Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China
| | - Hang Wang
- Department of Hepatopancreatobiliary Surgery, Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China
| | - Junqi You
- Department of Hepatopancreatobiliary Surgery, Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China
| | - Jinglin Li
- Department of Hepatopancreatobiliary Surgery, Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China
| | - Judy Wai Ping Yam
- Department of Pathology, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Yi Xu
- Department of Hepatopancreatobiliary Surgery, Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China
- Department of Pathology, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
- Key Laboratory of Basic Pharmacology of Ministry of Education, Zunyi Medical University, Zunyi, Guizhou, China
- Key Laboratory of Functional and Clinical Translational Medicine, Fujian Province University, Xiamen Medical College, Xiamen, Fujian, China
- Jiangsu Province Engineering Research Center of Tumor Targeted Nano Diagnostic and Therapeutic Materials, Yancheng Teachers University, Yancheng, Jiangsu, China
- Key Laboratory of Biomarkers and In Vitro Diagnosis Translation of Zhejiang province, Hangzhou, Zhejiang, China
- Key Laboratory of Gastrointestinal Cancer (Fujian Medical University), Ministry of Education, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, Fujian, China
- State Key Laboratory of Chemical Oncogenomics, Key Laboratory of Chemical Genomics, Peking University Shenzhen Graduate School, Shenzhen, Guangdong, China
- Key Laboratory of Intelligent Pharmacy and Individualized Therapy of Huzhou, Department of Pharmacy, Changxing People’s Hospital, Changxing, Zhejiang, China
| | - Yunfu Cui
- Department of Hepatopancreatobiliary Surgery, Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China
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Wang Y, Zhu GQ, Yang R, Wang C, Qu WF, Chu TH, Tang Z, Yang C, Yang L, Zhou CW, Miao GY, Liu WR, Shi YH, Zeng MS. Deciphering intratumoral heterogeneity of hepatocellular carcinoma with microvascular invasion with radiogenomic analysis. J Transl Med 2023; 21:734. [PMID: 37853415 PMCID: PMC10583459 DOI: 10.1186/s12967-023-04586-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Accepted: 10/03/2023] [Indexed: 10/20/2023] Open
Abstract
BACKGROUND AND AIMS The recurrence and metastasis of hepatocellular carcinoma (HCC) are mainly caused by microvascular invasion (MVI). Our study aimed to uncover the cellular atlas of MVI+ HCC and investigate the underlying immune infiltration patterns with radiomics features. METHODS Three MVI positive HCC and three MVI negative HCC samples were collected for single-cell RNA-seq analysis. 26 MVI positive HCC and 30 MVI negative HCC tissues were underwent bulk RNA-seq analysis. For radiomics analysis, radiomics features score (Radscore) were built using preoperative contrast MRI for MVI prediction and overall survival prediction. We deciphered the metabolism profiles of MVI+ HCC using scMetabolism and scFEA. The correlation of Radscore with the level of APOE+ macrophages and iCAFs was identified. Whole Exome Sequencing (WES) was applied to distinguish intrahepatic metastasis (IM) and multicentric occurrence (MO). Transcriptome profiles were compared between IM and MO. RESULTS Elevated levels of APOE+ macrophages and iCAFs were detected in MVI+ HCC. There was a strong correlation between the infiltration of APOE+ macrophages and iCAFs, as confirmed by immunofluorescent staining. MVI positive tumors exhibited increased lipid metabolism, which was attributed to the increased presence of APOE+ macrophages. APOE+ macrophages and iCAFs were also found in high levels in IM, as opposed to MO. The difference of infiltration level and Radscore between two nodules in IM was relatively small. Furthermore, we developed Radscore for predicting MVI and HCC prognostication that were also able to predict the level of infiltration of APOE+ macrophages and iCAFs. CONCLUSION This study demonstrated the interactions of cell subpopulations and distinct metabolism profiles in MVI+ HCC. Besides, MVI prediction Radscore and MVI prognostic Radscore were highly correlated with the infiltration of APOE+ macrophages and iCAFs, which helped to understand the biological significance of radiomics and optimize treatment strategy for MVI+ HCC.
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Affiliation(s)
- Yi Wang
- Department of Liver Surgery and Transplantation, Zhongshan Hospital, Liver Cancer Institute, Fudan University, 180 FengLin Road, Shanghai, 200032, China
| | - Gui-Qi Zhu
- Department of Liver Surgery and Transplantation, Zhongshan Hospital, Liver Cancer Institute, Fudan University, 180 FengLin Road, Shanghai, 200032, China
| | - Rui Yang
- Department of Liver Surgery and Transplantation, Zhongshan Hospital, Liver Cancer Institute, Fudan University, 180 FengLin Road, Shanghai, 200032, China
| | - Cheng Wang
- Department of Radiology, Zhongshan Hospital, Shanghai Institute of Medical Imaging, Fudan University, Xuhui District, Shanghai, 200032, China
| | - Wei-Feng Qu
- Department of Liver Surgery and Transplantation, Zhongshan Hospital, Liver Cancer Institute, Fudan University, 180 FengLin Road, Shanghai, 200032, China
| | - Tian-Hao Chu
- Department of Liver Surgery and Transplantation, Zhongshan Hospital, Liver Cancer Institute, Fudan University, 180 FengLin Road, Shanghai, 200032, China
| | - Zheng Tang
- Department of Liver Surgery and Transplantation, Zhongshan Hospital, Liver Cancer Institute, Fudan University, 180 FengLin Road, Shanghai, 200032, China
| | - Chun Yang
- Department of Radiology, Zhongshan Hospital, Shanghai Institute of Medical Imaging, Fudan University, Xuhui District, Shanghai, 200032, China
| | - Li Yang
- Department of Radiology, Zhongshan Hospital, Shanghai Institute of Medical Imaging, Fudan University, Xuhui District, Shanghai, 200032, China
| | - Chang-Wu Zhou
- Department of Radiology, Zhongshan Hospital, Shanghai Institute of Medical Imaging, Fudan University, Xuhui District, Shanghai, 200032, China
| | - Geng-Yun Miao
- Department of Radiology, Zhongshan Hospital, Shanghai Institute of Medical Imaging, Fudan University, Xuhui District, Shanghai, 200032, China
| | - Wei-Ren Liu
- Department of Liver Surgery and Transplantation, Zhongshan Hospital, Liver Cancer Institute, Fudan University, 180 FengLin Road, Shanghai, 200032, China
| | - Ying-Hong Shi
- Department of Liver Surgery and Transplantation, Zhongshan Hospital, Liver Cancer Institute, Fudan University, 180 FengLin Road, Shanghai, 200032, China.
| | - Meng-Su Zeng
- Department of Radiology, Zhongshan Hospital, Shanghai Institute of Medical Imaging, Fudan University, Xuhui District, Shanghai, 200032, China.
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Lin Q, Jiang Z, Mo D, Liu F, Qin Y, Liang Y, Cheng Y, Huang H, Fang M. Beta2-Microglobulin as Predictive Biomarkers in the Prognosis of Hepatocellular Carcinoma and Development of a New Nomogram. J Hepatocell Carcinoma 2023; 10:1813-1825. [PMID: 37850078 PMCID: PMC10577246 DOI: 10.2147/jhc.s425344] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 10/04/2023] [Indexed: 10/19/2023] Open
Abstract
Background Accurate prognosis is crucial for improving hepatocellular carcinoma (HCC) patients, clinical management, and outcomes post-liver resection. However, the lack of reliable prognostic indicators poses a significant challenge. This study aimed to develop a user-friendly nomogram to predict HCC patients' post-resection prognosis. Methods We retrospectively analyzed the data from 1091 HCC patients, randomly split into training (n=767) and validation (n=324) cohorts. Receiver operating characteristic (ROC) curves determined the optimal cut-off value for alpha1-microglobulin (α1MG) and Beta2-microglobulin (β2MG). Kaplan-Meier analysis assessed microglobulin's impact on survival, followed by Cox regression to identify prognostic factors and construct a nomogram. The predictive accuracy and discriminative ability of the nomogram were measured by the concordance index (C-index), calibration curves, area under the ROC curve (AUC), and decision curve analysis (DCA), and were compared with the BCLC staging system, Edmondson grade, or BCLC stage plus Edmondson grade. Results Patients with high β2MG (≥2.395mg/L) had worse overall survival (OS). The nomogram integrated β2MG, BCLC stage, Edmondson grade, microvascular invasion (MVI), and serum carbohydrate antigen 199 (CA199) levels. C-index for training and validation cohorts (0.712 and 0.709) outperformed the BCLC stage (0.660 and 0.657), Edmondson grade (0.579 and 0.564), and the combination of BCLC stage with Edmondson grade (0.681 and 0.668), improving prognosis prediction. Calibration curves demonstrated good agreement between predicted and observed survival. AUC values exceeded 0.700 over time, highlighting the nomogram's discriminative ability. DCA revealed superior overall net income compared to other systems, emphasizing its clinical utility. Conclusion Our β2MG-based nomogram accurately predicts HCC patients' post-resection prognosis, aiding intervention and follow-up planning. Significantly, our nomogram surpasses existing prognostic indicators, including BCLC stage, Edmondson grade, and the combination of BCLC stage with Edmondson grade, by demonstrating superior predictive performance.
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Affiliation(s)
- Qiumei Lin
- Department of Clinical Laboratory, Guangxi Medical University Cancer Hospital, Nanning, People’s Republic of China
| | - Zongwei Jiang
- Department of Clinical Laboratory, Guangxi Medical University Cancer Hospital, Nanning, People’s Republic of China
| | - Dan Mo
- Department of Breast, Guangxi Zhuang Autonomous Region Maternal and Child Health Care Hospital, Nanning, 530025, People’s Republic of China
| | - Fengfei Liu
- Department of Clinical Laboratory, Guangxi Medical University Cancer Hospital, Nanning, People’s Republic of China
| | - Yuling Qin
- Department of Clinical Laboratory, Guangxi Medical University Cancer Hospital, Nanning, People’s Republic of China
| | - Yihua Liang
- Department of Clinical Laboratory, Guangxi Medical University Cancer Hospital, Nanning, People’s Republic of China
| | - Yuchen Cheng
- Department of Clinical Laboratory, Wuzhou Maternal and Child Health-Care Hospital, Wuzhou, People’s Republic of China
| | - Hao Huang
- Department of Clinical Laboratory, Guangxi Medical University Cancer Hospital, Nanning, People’s Republic of China
| | - Min Fang
- Department of Clinical Laboratory, Guangxi Medical University Cancer Hospital, Nanning, People’s Republic of China
- Engineering Research Center for Tissue & Organ Injury and Repair Medicine, Guangxi Medical University Cancer Hospital, Nanning, People’s Republic of China
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Yu B, Zhang N, Feng Y, Zhang Y, Zhang T, Wang L. Hepatectomy After Conversion Therapy with Hepatic Arterial Infusion Chemotherapy, Tyrosine Kinase Inhibitors and Anti-PD-1 Antibodies for Initially Unresectable Hepatocellular Carcinoma. J Hepatocell Carcinoma 2023; 10:1709-1721. [PMID: 37817914 PMCID: PMC10560606 DOI: 10.2147/jhc.s432062] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Accepted: 09/27/2023] [Indexed: 10/12/2023] Open
Abstract
Background Most patients with hepatocellular carcinoma (HCC) are not candidates for liver resection. We investigated the clinicopathological characteristics and prognosis of patients with initially unresectable HCC who underwent hepatectomy after conversion therapy with hepatic arterial infusion chemotherapy (HAIC), tyrosine kinase inhibitors (TKIs), and anti-PD-1 antibodies. Materials and Methods Patients with initially unresectable HCC who received HAIC combined with TKIs and anti-PD-1 antibodies followed by hepatectomy between December 2020 and December 2022, were retrospectively analyzed. Patient characteristics, tumor characteristics, treatment efficacy, perioperative characteristics, pathological characteristics, and survival outcomes were summarized and analyzed. Results 67 patients were enrolled in this study. Patients were treated with 3 sessions (range:2-6 sessions) of combination therapy and were performed with hepatectomy in 4 months (range:1.4-17.8 months) after the initiation of the combination therapy. The median size of tumor shrinkage was 4.7 cm (range:0.9-11.7 cm). A pathological complete response (pCR) was achieved in 34.3% of the patients (n = 23). The median recurrence-free survival (RFS) was 19.3 months and the median overall survival (OS) was 28.7 months. Patients who achieved pCR had a better RFS (P = 0.004) and those without microscopic vascular invasion (MVI) had a better prognosis (RFS, P = 0.011; OS, P = 0.023). Multivariable logistic analysis revealed that the tumor number was associated with pCR. Conclusion Hepatectomy after conversion therapy with HAIC, TKIs, and anti-PD-1 antibodies is a feasible treatment strategy for patients with unresectable HCC. This treatment strategy is associated with a promising prognosis.
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Affiliation(s)
- Bingran Yu
- Department of Hepatic Surgery, Shanghai Cancer Center, Shanghai Medical College, Fudan University, Shanghai, People’s Republic of China
| | - Ning Zhang
- Department of Hepatic Surgery, Shanghai Cancer Center, Shanghai Medical College, Fudan University, Shanghai, People’s Republic of China
| | - Yun Feng
- Department of Hepatic Surgery, Shanghai Cancer Center, Shanghai Medical College, Fudan University, Shanghai, People’s Republic of China
| | - Yongfa Zhang
- Department of Hepatic Surgery, Shanghai Cancer Center, Shanghai Medical College, Fudan University, Shanghai, People’s Republic of China
| | - Ti Zhang
- Department of Hepatic Surgery, Shanghai Cancer Center, Shanghai Medical College, Fudan University, Shanghai, People’s Republic of China
| | - Lu Wang
- Department of Hepatic Surgery, Shanghai Cancer Center, Shanghai Medical College, Fudan University, Shanghai, People’s Republic of China
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Auer TA, Halskov S, Fehrenbach U, Nevermann NF, Pelzer U, Mohr R, Hamm B, Schöning W, Horst D, Ihlow J, Geisel D. Gd-EOB MRI for HCC subtype differentiation in a western population according to the 5 th edition of the World Health Organization classification. Eur Radiol 2023; 33:6902-6915. [PMID: 37115216 PMCID: PMC10511376 DOI: 10.1007/s00330-023-09669-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 03/29/2023] [Accepted: 04/10/2023] [Indexed: 04/29/2023]
Abstract
OBJECTIVES To investigate the value of gadoxetic acid (Gd-EOB)-enhanced magnetic resonance imaging (MRI) for noninvasive subtype differentiation of HCCs according to the 5th edition of the WHO Classification of Digestive System Tumors in a western population. METHODS This retrospective study included 262 resected lesions in 240 patients with preoperative Gd-EOB-enhanced MRI. Subtypes were assigned by two pathologists. Gd-EOB-enhanced MRI datasets were assessed by two radiologists for qualitative and quantitative imaging features, including imaging features defined in LI-RADS v2018 and area of hepatobiliary phase (HBP) iso- to hyperintensity. RESULTS The combination of non-rim arterial phase hyperenhancement with non-peripheral portal venous washout was more common in "not otherwise specified" (nos-ST) (88/168, 52%) than other subtypes, in particular macrotrabecular massive (mt-ST) (3/15, 20%), chromophobe (ch-ST) (1/8, 13%), and scirrhous subtypes (sc-ST) (2/9, 22%) (p = 0.035). Macrovascular invasion was associated with mt-ST (5/16, p = 0.033) and intralesional steatosis with steatohepatitic subtype (sh-ST) (28/32, p < 0.001). Predominant iso- to hyperintensity in the HBP was only present in nos-ST (16/174), sh-ST (3/33), and clear cell subtypes (cc-ST) (3/13) (p = 0.031). Associations were found for the following non-imaging parameters: age and sex, as patients with fibrolamellar subtype (fib-ST) were younger (median 44 years (19-66), p < 0.001) and female (4/5, p = 0.023); logarithm of alpha-fetoprotein (AFP) was elevated in the mt-ST (median 397 µg/l (74-5370), p < 0.001); type II diabetes mellitus was more frequent in the sh-ST (20/33, p = 0.027). CONCLUSIONS Gd-EOB-MRI reproduces findings reported in the literature for extracellular contrast-enhanced MRI and CT and may be a valuable tool for noninvasive HCC subtype differentiation. CLINICAL RELEVANCE STATEMENT Better characterization of the heterogeneous phenotypes of HCC according to the revised WHO classification potentially improves both diagnostic accuracy and the precision of therapeutic stratification for HCC. KEY POINTS • Previously reported imaging features of common subtypes in CT and MRI enhanced with extracellular contrast agents are reproducible with Gd-EOB-enhanced MRI. • While uncommon, predominant iso- to hyperintensity in the HBP was observed only in NOS, clear cell, and steatohepatitic subtypes. • Gd-EOB-enhanced MRI offers imaging features that are of value for HCC subtype differentiation according to the 5th edition of the WHO Classification of Digestive System Tumors.
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Affiliation(s)
- Timo A Auer
- Department of Radiology, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany.
- Berlin Institute of Health (BIH), Anna-Louisa-Karsch-Straße 2, 10178, Berlin, Germany.
| | - Sebastian Halskov
- Department of Radiology, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Uli Fehrenbach
- Department of Radiology, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Nora F Nevermann
- Department of Surgery - CVK/CCM, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Uwe Pelzer
- Department of Hematology, Oncology and Cancer Immunology, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Raphael Mohr
- Department of Hepatology and Gastroenterology, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Bernd Hamm
- Department of Radiology, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Wenzel Schöning
- Department of Surgery - CVK/CCM, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
| | - David Horst
- Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität Zu Berlin, Charitéplatz 1, 10117, Berlin, Germany
| | - Jana Ihlow
- Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität Zu Berlin, Charitéplatz 1, 10117, Berlin, Germany
| | - Dominik Geisel
- Department of Radiology, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
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Zhu Y, Yang L, Wang M, Pan J, Zhao Y, Huang H, Sun K, Chen F. Preoperative MRI features to predict vessels that encapsulate tumor clusters and microvascular invasion in hepatocellular carcinoma. Eur J Radiol 2023; 167:111089. [PMID: 37713969 DOI: 10.1016/j.ejrad.2023.111089] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Revised: 08/28/2023] [Accepted: 09/06/2023] [Indexed: 09/17/2023]
Abstract
OBJECTIVE To estimate the potential of preoperative MRI features in the prediction of the integration patterns of vessels that encapsulate tumor clusters (VETC) and microvascular invasion (MVI) (VM) patterns in hepatocellular carcinoma (HCC) patients after resection and to assess the prognostic value of VM patterns. MATERIALS AND METHODS Patients who underwent surgical resection for HCC between July 2019 and July 2020 were retrospectively included in the training cohort and validation cohort. In the training cohort, patients were classified into VM-positive HCC (VM-HCC) and VM-negative HCC (non-VM HCC). Predictors associated with VM-HCC were determined by using logistic regression analyses and used to build a prediction model of VM-HCC. The model was tested in the validation cohort by area under the receiver operating characteristic curve (AUC) analysis. Prognostic factors associated with early recurrence of HCC were evaluated by use of Cox logistic regression analyses. RESULTS Alpha-fetoprotein (AFP) level higher than 400 ng/mL (odds ratio [OR] = 8.0; 95% CI: 2.6-25.2; P < 0.001), non-smooth tumor margin (OR = 3.1; 95% CI: 1.4-6.0; P < 0.001) and peritumoral arterial enhancement (OR = 2.9; 95% CI: 1.4-6.2; P = 0.004) were independent predictors of VM-HCC. The AUCs of the prediction model for VM-HCC were 0.81 for the training cohort and 0.79 for the validation cohort. The high risk of VM-HCC predicted by the three preoperative predictors derived from the prediction model (hazard ratio [HR] 2.0; 95% CI: 1.3, 3.2; P = 0.003) were independently associated with early recurrence, while pathologically confirmed VM-HCC (HR 2.8; 95% CI: 1.6, 3.8; P < 0.001) and satellite nodules (HR 1.8; 95% CI: 1.1, 3.1; P = 0.025) were independently associated with early recurrence after surgical resection. CONCLUSION The predictive model can be used to predict VM patterns. VM-HCC is associated with increased risk of early recurrence after surgical resection in HCC.
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Affiliation(s)
- Yanyan Zhu
- Department of Radiology, The First Affiliated Hospital, Zhejiang University School of Medicine, China.
| | - Lili Yang
- Department of Radiology, The First Affiliated Hospital, Zhejiang University School of Medicine, China.
| | - Meng Wang
- Department of Pathology, the First Affiliated Hospital, Zhejiang University School of Medicine, China
| | - Junhan Pan
- Department of Radiology, The First Affiliated Hospital, Zhejiang University School of Medicine, China.
| | - Yanci Zhao
- Department of Radiology, The First Affiliated Hospital, Zhejiang University School of Medicine, China.
| | - Huizhen Huang
- Department of Radiology, The First Affiliated Hospital, Zhejiang University School of Medicine, China.
| | - Ke Sun
- Department of Pathology, the First Affiliated Hospital, Zhejiang University School of Medicine, China.
| | - Feng Chen
- Department of Radiology, The First Affiliated Hospital, Zhejiang University School of Medicine, China.
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Zhang Y, Dong Y, Yu W, Chen S, Yu H, Li B, Shi H. Combined early dynamic 18F-FDG PET/CT and conventional whole-body 18F-FDG PET/CT in hepatocellular carcinoma. Abdom Radiol (NY) 2023; 48:3127-3134. [PMID: 37439840 DOI: 10.1007/s00261-023-03986-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Revised: 11/16/2021] [Accepted: 11/17/2021] [Indexed: 07/14/2023]
Abstract
OBJECTIVE To investigate the diagnostic value of early dynamic 18F-FDG PET/CT(ED 18F-FDG PET/CT) combined with conventional whole-body 18F-FDG PET/CT(WB 18F-FDG PET/CT) in hepatocellular carcinoma (HCC), as well as the difference of early dynamic blood flow parameters and maximum standardized uptake value (SUVmax) in HCC patients with/without liver cirrhosis or microvascular invasion (MVI). METHODS Twenty-two consecutive patients (mean age 57.8 years) with 28 established HCC lesions (mean size 4.5 cm) underwent a blood flow study with an 18F-FDG dynamic scan divided into 24 sequences of 5 s each and a standard PET/CT scan. On the ED PET/CT study, an experienced PET/CT physician obtained volumes of interest (VOIs) where three blood flow estimates (time to peak [TTP], blood flow [BF], and hepatic perfusion index [HPI]) were calculated. On the WB PET/CT study, a VOI was placed on the fused scan for each HCC and maximum standardized uptake value (SUVmax) was obtained. Comparison of blood flow estimates, SUVmax, and tumor/background ratio (TNR) was performed among HCCs with and without angioinvasion, as well as HCCs in cirrhotic and non-cirrhotic liver. RESULTS Compared with WB 18F-FDG PET/CT alone, ED combined with WB 18F-FDG PET/CT can significantly increase the detection rate of moderately differentiated and poorly differentiated HCCs (both P < 0.05). HPI was higher in HCCs in patients with liver cirrhosis than those without liver cirrhosis (P = 0.044). There was no significant difference in TTP, BF, SUVmax, or TNR between HCCs in patients with liver cirrhosis and those without liver cirrhosis. There was no significant difference in blood flow estimates or SUVmax in background liver parenchyma between patients with and those without cirrhosis. TTP was shorter in HCCs with MVI than without MVI (P = 0.046). There was no significant difference in BF, HPI, SUVmax, or TNR between HCCs with MVI and without MVI. There was no significant difference in blood flow estimates or SUVmax in background liver parenchyma between patients with and those without MVI. CONCLUSION ED combined with WB 18F-FDG PET/CT can significantly increase the detection rate of moderately differentiated and poorly differentiated HCCs. HPI was significantly higher in HCCs in patients with liver cirrhosis than those without liver cirrhosis. TTP was significantly shorter in HCCs with MVI than without MVI.
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Affiliation(s)
- Yiqiu Zhang
- Department of Nuclear Medicine, Zhongshan Hospital, Fudan University, Shanghai, China
- Department of Nuclear Medicine, Zhongshan Hospital(Xiamen), Fudan University, Xiamen, Fujian, China
- Nuclear Medicine Institute of Fudan University, Shanghai, China
- Shanghai Institute of Medical Imaging, Shanghai, China
| | - Yun Dong
- Shanghai United Imaging Healthcare Co., Ltd., Shanghai, China
| | - Wenjun Yu
- Shanghai United Imaging Healthcare Co., Ltd., Shanghai, China
| | - Shuguang Chen
- Department of Nuclear Medicine, Zhongshan Hospital, Fudan University, Shanghai, China
- Nuclear Medicine Institute of Fudan University, Shanghai, China
- Shanghai Institute of Medical Imaging, Shanghai, China
| | - Haojun Yu
- Department of Nuclear Medicine, Zhongshan Hospital, Fudan University, Shanghai, China
- Nuclear Medicine Institute of Fudan University, Shanghai, China
- Shanghai Institute of Medical Imaging, Shanghai, China
| | - Beilei Li
- Department of Nuclear Medicine, Zhongshan Hospital(Xiamen), Fudan University, Xiamen, Fujian, China.
- Nuclear Medicine Institute of Fudan University, Shanghai, China.
- Shanghai Institute of Medical Imaging, Shanghai, China.
| | - Hongcheng Shi
- Department of Nuclear Medicine, Zhongshan Hospital, Fudan University, Shanghai, China.
- Department of Nuclear Medicine, Zhongshan Hospital(Xiamen), Fudan University, Xiamen, Fujian, China.
- Nuclear Medicine Institute of Fudan University, Shanghai, China.
- Shanghai Institute of Medical Imaging, Shanghai, China.
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Yao J, Li K, Yang H, Lu S, Ding H, Luo Y, Li K, Xie X, Wu W, Jing X, Liu F, Yu J, Cheng Z, Tan S, Dou J, Dong X, Wang S, Zhang Y, Li Y, Qi E, Han Z, Liang P, Yu X. Analysis of Sonazoid contrast-enhanced ultrasound for predicting the risk of microvascular invasion in hepatocellular carcinoma: a prospective multicenter study. Eur Radiol 2023; 33:7066-7076. [PMID: 37115213 DOI: 10.1007/s00330-023-09656-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 02/23/2023] [Accepted: 03/07/2023] [Indexed: 04/29/2023]
Abstract
OBJECTIVES The aim of this study was to evaluate the potential of Sonazoid contrast-enhanced ultrasound (SNZ-CEUS) as an imaging biomarker for preoperative prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC). METHODS From August 2020 to March 2021, we conducted a prospective multicenter study on the clinical application of Sonazoid in liver tumor; a MVI prediction model was developed and validated by integrating clinical and imaging variables. Multivariate logistic regression analysis was used to establish the MVI prediction model; three models were developed: a clinical model, a SNZ-CEUS model, and a combined model and conduct external validation. We conducted subgroup analysis to investigate the performance of the SNZ-CEUS model in non-invasive prediction of MVI. RESULTS Overall, 211 patients were evaluated. All patients were split into derivation (n = 170) and external validation (n = 41) cohorts. Patients who had MVI accounted for 89 of 211 (42.2%) patients. Multivariate analysis revealed that tumor size (> 49.2 mm), pathology differentiation, arterial phase heterogeneous enhancement pattern, non-single nodular gross morphology, washout time (< 90 s), and gray value ratio (≤ 0.50) were significantly associated with MVI. Combining these factors, the area under the receiver operating characteristic (AUROC) of the combined model in the derivation and external validation cohorts was 0.859 (95% confidence interval (CI): 0.803-0.914) and 0.812 (95% CI: 0.691-0.915), respectively. In subgroup analysis, the AUROC of the SNZ-CEUS model in diameter ≤ 30 mm and ˃ 30 mm cohorts were 0.819 (95% CI: 0.698-0.941) and 0.747 (95% CI: 0.670-0.824). CONCLUSIONS Our model predicted the risk of MVI in HCC patients with high accuracy preoperatively. CLINICAL RELEVANCE STATEMENT Sonazoid, a novel second-generation ultrasound contrast agent, can accumulate in the endothelial network and form a unique Kupffer phase in liver imaging. The preoperative non-invasive prediction model based on Sonazoid for MVI is helpful for clinicians to make individualized treatment decisions. KEY POINTS • This is the first prospective multicenter study to analyze the possibility of SNZ-CEUS preoperatively predicting MVI. • The model established by combining SNZ-CEUS image features and clinical features has high predictive performance in both derivation cohort and external validation cohort. • The findings can help clinicians predict MVI in HCC patients before surgery and provide a basis for optimizing surgical management and monitoring strategies for HCC patients.
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Affiliation(s)
- Jundong Yao
- Department of Interventional Ultrasound, First Medical Center of Chinese PLA General Hospital, No. 28 Fuxing Road, Beijing, 100853, China
- Chinese PLA Medical School, Beijing, 100853, China
| | - Kaiyan Li
- Department of Ultrasound Imaging, Affiliated Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Hong Yang
- Department of Ultrasound, the First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, China
| | - Shichun Lu
- Department of Hepatobiliary Surgery, First Medical Center of Chinese PLA General Hospital, Beijing, 100853, China
| | - Hong Ding
- Department of Ultrasound, Huashan Hospital, Fudan University, Shanghai, 200040, China
| | - Yan Luo
- Department of Ultrasound, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Kai Li
- Department of Ultrasound, the Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510630, China
| | - Xiaoyan Xie
- Department of Ultrasound, the First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510080, China
| | - Wei Wu
- Department of Ultrasound, Peking University Cancer Hospital & Institute, Beijing, 100142, China
| | - Xiang Jing
- Department of Ultrasound, the Third Central Hospital of Tianjin, Tianjin, 300170, China
| | - Fangyi Liu
- Department of Interventional Ultrasound, Fifth Medical Center of Chinese PLA General Hospital, No. 28 Fuxing Road, Beijing, 100853, China
| | - Jie Yu
- Department of Interventional Ultrasound, Fifth Medical Center of Chinese PLA General Hospital, No. 28 Fuxing Road, Beijing, 100853, China
| | - Zhigang Cheng
- Department of Interventional Ultrasound, Fifth Medical Center of Chinese PLA General Hospital, No. 28 Fuxing Road, Beijing, 100853, China
| | - Shuilian Tan
- Department of Interventional Ultrasound, Fifth Medical Center of Chinese PLA General Hospital, No. 28 Fuxing Road, Beijing, 100853, China
| | - Jianping Dou
- Department of Interventional Ultrasound, Fifth Medical Center of Chinese PLA General Hospital, No. 28 Fuxing Road, Beijing, 100853, China
| | - XueJuan Dong
- Department of Interventional Ultrasound, Fifth Medical Center of Chinese PLA General Hospital, No. 28 Fuxing Road, Beijing, 100853, China
| | - Shuo Wang
- Department of Interventional Ultrasound, First Medical Center of Chinese PLA General Hospital, No. 28 Fuxing Road, Beijing, 100853, China
| | - Yiqiong Zhang
- Department of Interventional Ultrasound, First Medical Center of Chinese PLA General Hospital, No. 28 Fuxing Road, Beijing, 100853, China
| | - Yunlin Li
- Department of Interventional Ultrasound, First Medical Center of Chinese PLA General Hospital, No. 28 Fuxing Road, Beijing, 100853, China
| | - Erpeng Qi
- Department of Interventional Ultrasound, First Medical Center of Chinese PLA General Hospital, No. 28 Fuxing Road, Beijing, 100853, China
| | - Zhiyu Han
- Department of Interventional Ultrasound, Fifth Medical Center of Chinese PLA General Hospital, No. 28 Fuxing Road, Beijing, 100853, China.
| | - Ping Liang
- Department of Interventional Ultrasound, Fifth Medical Center of Chinese PLA General Hospital, No. 28 Fuxing Road, Beijing, 100853, China.
| | - XiaoLing Yu
- Department of Interventional Ultrasound, First Medical Center of Chinese PLA General Hospital, No. 28 Fuxing Road, Beijing, 100853, China.
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Chen Z, Li X, Zhang Y, Yang Y, Zhang Y, Zhou D, Yang Y, Zhang S, Liu Y. MRI Features for Predicting Microvascular Invasion and Postoperative Recurrence in Hepatocellular Carcinoma Without Peritumoral Hypointensity. J Hepatocell Carcinoma 2023; 10:1595-1608. [PMID: 37786565 PMCID: PMC10541533 DOI: 10.2147/jhc.s422632] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2023] [Accepted: 09/08/2023] [Indexed: 10/04/2023] Open
Abstract
Purpose To identify MRI features of hepatocellular carcinoma (HCC) that predict microvascular invasion (MVI) and postoperative intrahepatic recurrence in patients without peritumoral hepatobiliary phase (HBP) hypointensity. Patients and Methods One hundred and thirty patients with HCC who underwent preoperative gadoxetate-enhanced MRI and curative hepatic resection were retrospectively reviewed. Two radiologists reviewed all preoperative MR images and assessed the radiological features of HCCs. The ability of peritumoral HBP hypointensity to identify MVI and intrahepatic recurrence was analyzed. We then assessed the MRI features of HCC that predicted the MVI and intrahepatic recurrence-free survival (RFS) in the subgroup without peritumoral HBP hypointensity. Finally, a two-step flowchart was constructed to assist in clinical decision-making. Results Peritumoral HBP hypointensity (odds ratio, 3.019; 95% confidence interval: 1.071-8.512; P=0.037) was an independent predictor of MVI. The sensitivity, specificity, positive predictive value, negative predictive value, and AUROC of peritumoral HBP hypointensity in predicting MVI were 23.80%, 91.04%, 71.23%, 55.96%, and 0.574, respectively. Intrahepatic RFS was significantly shorter in patients with peritumoral HBP hypointensity (P<0.001). In patients without peritumoral HBP hypointensity, the only significant difference between MVI-positive and MVI-negative HCCs was the presence of a radiological capsule (P=0.038). Satellite nodule was an independent risk factor for intrahepatic RFS (hazard ratio,3.324; 95% CI: 1.733-6.378; P<0.001). The high-risk HCC detection rate was significantly higher when using the two-step flowchart that incorporated peritumoral HBP hypointensity and satellite nodule than when using peritumoral HBP hypointensity alone (P<0.001). Conclusion In patients without peritumoral HBP hypointensity, a radiological capsule is useful for identifying MVI and satellite nodule is an independent risk factor for intrahepatic RFS.
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Affiliation(s)
- Zhiyuan Chen
- Department of Radiology, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, 510120, People’s Republic of China
| | - Xiaohuan Li
- The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, 510120, People’s Republic of China
| | - Yu Zhang
- The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, 510120, People’s Republic of China
| | - Yiming Yang
- Department of Radiology, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, 510120, People’s Republic of China
| | - Yan Zhang
- Integrated Department, the Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, 510120, People’s Republic of China
| | - Dongjing Zhou
- Department of Radiology, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, 510120, People’s Republic of China
| | - Yu Yang
- Department of Pathology, the Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, 510120, People’s Republic of China
| | - Shuping Zhang
- Department of Radiology, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, 510120, People’s Republic of China
| | - Yupin Liu
- Department of Radiology, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, 510120, People’s Republic of China
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