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Chung SD, Yong CC, Kee KM, Lu SN, Hu TH, Wang JH, Hung CH, Chen CH, Liu YW, Li WF, Wang CC, Yen YH, Lin CY. Overall survival is comparable between percutaneous radiofrequency ablation and liver resection as first-line therapies for solitary 3-5 cm hepatocellular carcinoma. Langenbecks Arch Surg 2025; 410:66. [PMID: 39937293 PMCID: PMC11821760 DOI: 10.1007/s00423-025-03632-9] [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: 11/20/2024] [Accepted: 02/01/2025] [Indexed: 02/13/2025]
Abstract
PURPOSE Few studies have compared survival outcomes between liver resection (LR) and percutaneous radiofrequency ablation (RFA) for treating solitary 3-5 cm hepatocellular carcinoma (HCC). We aimed to clarify this issue. METHODS Patients with Child-Pugh class A liver disease and a solitary HCC of 3-5 cm without macrovascular invasion or extrahepatic metastasis who underwent LR or percutaneous RFA between 2011 and 2021 were enrolled in this retrospective study; 310 patients underwent LR and 114 patients underwent percutaneous RFA. Propensity score matching (PSM) was used to balance baseline variables, including age, sex, alpha-fetoprotein level, and Model for End-Stage Liver Disease score, between the two groups. RESULTS Before PSM, 5-year overall survival (OS) and recurrence-free survival (RFS) were significantly lower in the percutaneous RFA group than in the LR group (both p < 0.001). After PSM, 5-year OS was comparable between the two modalities (p = 0.367); however, 5-year RFS was significantly lower in the RFA group than in the LR group (p = 0.001). The two modalities did not differ in severe post-treatment complications (p = 1.000). CONCLUSIONS Five-year OS did not differ between treatment modalities for patients with a solitary HCC of 3-5 cm; however, the LR group's 5-year RFS was superior. LR should be recommended as the first-line treatment for these patients.
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Affiliation(s)
- Shih-Da Chung
- Division of Hepatogastroenterology, Department of Internal Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, 123 Ta Pei Road, Kaohsiung, Taiwan
| | - Chee-Chien Yong
- Liver Transplantation Center and Department of Surgery, Kaohsiung Chang Gung Memorial Hospital, 123 Ta Pei Road, Kaohsiung, Taiwan
| | - Kwong-Ming Kee
- Division of Hepatogastroenterology, Department of Internal Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, 123 Ta Pei Road, Kaohsiung, Taiwan
| | - Sheng-Nan Lu
- Division of Hepatogastroenterology, Department of Internal Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, 123 Ta Pei Road, Kaohsiung, Taiwan
| | - Tsung-Hui Hu
- Division of Hepatogastroenterology, Department of Internal Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, 123 Ta Pei Road, Kaohsiung, Taiwan
| | - Jing-Houng Wang
- Division of Hepatogastroenterology, Department of Internal Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, 123 Ta Pei Road, Kaohsiung, Taiwan
| | - Chao-Hung Hung
- Division of Hepatogastroenterology, Department of Internal Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, 123 Ta Pei Road, Kaohsiung, Taiwan
| | - Chien-Hung Chen
- Division of Hepatogastroenterology, Department of Internal Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, 123 Ta Pei Road, Kaohsiung, Taiwan
| | - Yueh-Wei Liu
- Liver Transplantation Center and Department of Surgery, Kaohsiung Chang Gung Memorial Hospital, 123 Ta Pei Road, Kaohsiung, Taiwan
| | - Wei-Feng Li
- Liver Transplantation Center and Department of Surgery, Kaohsiung Chang Gung Memorial Hospital, 123 Ta Pei Road, Kaohsiung, Taiwan
| | - Chih-Chi Wang
- Liver Transplantation Center and Department of Surgery, Kaohsiung Chang Gung Memorial Hospital, 123 Ta Pei Road, Kaohsiung, Taiwan.
| | - Yi-Hao Yen
- Division of Hepatogastroenterology, Department of Internal Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, 123 Ta Pei Road, Kaohsiung, Taiwan.
| | - Chih-Yun Lin
- Biostatistics Center of Kaohsiung Chang, Gung Memorial Hospital, Kaohsiung, Taiwan
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Stulpinas R, Zilenaite-Petrulaitiene D, Rasmusson A, Gulla A, Grigonyte A, Strupas K, Laurinavicius A. Prognostic Value of CD8+ Lymphocytes in Hepatocellular Carcinoma and Perineoplastic Parenchyma Assessed by Interface Density Profiles in Liver Resection Samples. Cancers (Basel) 2023; 15:cancers15020366. [PMID: 36672317 PMCID: PMC9857181 DOI: 10.3390/cancers15020366] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2022] [Revised: 12/28/2022] [Accepted: 01/04/2023] [Indexed: 01/08/2023] Open
Abstract
Hepatocellular carcinoma (HCC) often emerges in the setting of long-standing inflammatory liver disease. CD8 lymphocytes are involved in both the antitumoral response and hepatocyte damage in the remaining parenchyma. We investigated the dual role of CD8 lymphocytes by assessing density profiles at the interfaces of both HCC and perineoplastic liver parenchyma with surrounding stroma in whole-slide immunohistochemistry images of surgical resection samples. We applied a hexagonal grid-based digital image analysis method to sample the interface zones and compute the CD8 density profiles within them. The prognostic value of the indicators was explored in the context of clinicopathological, peripheral blood testing, and surgery data. Independent predictors of worse OS were a low standard deviation of CD8+ density along the tumor edge, high mean CD8+ density within the epithelial aspect of the perineoplastic liver-stroma interface, longer duration of surgery, a higher level of aspartate transaminase (AST), and a higher basophil count in the peripheral blood. A combined score, derived from these five independent predictors, enabled risk stratification of the patients into three prognostic categories with a 5-year OS probability of 76%, 40%, and 8%. Independent predictors of longer RFS were stage pT1, shorter duration of surgery, larger tumor size, wider tumor-free margin, and higher mean CD8+ density in the epithelial aspect of the tumor-stroma interface. We conclude that (1) our computational models reveal independent and opposite prognostic impacts of CD8+ cell densities at the interfaces of the malignant and non-malignant epithelium interfaces with the surrounding stroma; and (2) together with pathology, surgery, and laboratory data, comprehensive prognostic models can be constructed to predict patient outcomes after liver resection due to HCC.
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Affiliation(s)
- Rokas Stulpinas
- Faculty of Medicine, Institute of Biomedical Sciences, Department of Pathology, Forensic Medicine and Pharmacology, Vilnius University, 03101 Vilnius, Lithuania
- National Center of Pathology, Affiliate of Vilnius University Hospital Santaros Clinics, 08406 Vilnius, Lithuania
- Correspondence:
| | - Dovile Zilenaite-Petrulaitiene
- Faculty of Medicine, Institute of Biomedical Sciences, Department of Pathology, Forensic Medicine and Pharmacology, Vilnius University, 03101 Vilnius, Lithuania
- National Center of Pathology, Affiliate of Vilnius University Hospital Santaros Clinics, 08406 Vilnius, Lithuania
| | - Allan Rasmusson
- Faculty of Medicine, Institute of Biomedical Sciences, Department of Pathology, Forensic Medicine and Pharmacology, Vilnius University, 03101 Vilnius, Lithuania
- National Center of Pathology, Affiliate of Vilnius University Hospital Santaros Clinics, 08406 Vilnius, Lithuania
| | - Aiste Gulla
- Faculty of Medicine, Institute of Clinical Medicine, Vilnius University, 03101 Vilnius, Lithuania
- Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Agne Grigonyte
- Faculty of Medicine, Vilnius University, 03101 Vilnius, Lithuania
| | - Kestutis Strupas
- Faculty of Medicine, Institute of Clinical Medicine, Vilnius University, 03101 Vilnius, Lithuania
| | - Arvydas Laurinavicius
- Faculty of Medicine, Institute of Biomedical Sciences, Department of Pathology, Forensic Medicine and Pharmacology, Vilnius University, 03101 Vilnius, Lithuania
- National Center of Pathology, Affiliate of Vilnius University Hospital Santaros Clinics, 08406 Vilnius, Lithuania
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3
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Kudo M. Atezolizumab plus Bevacizumab Followed by Curative Conversion (ABC Conversion) in Patients with Unresectable, TACE-Unsuitable Intermediate-Stage Hepatocellular Carcinoma. Liver Cancer 2022; 11:399-406. [PMID: 36158590 PMCID: PMC9485978 DOI: 10.1159/000526163] [Citation(s) in RCA: 54] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Accepted: 07/21/2022] [Indexed: 02/04/2023] Open
Affiliation(s)
- Masatoshi Kudo
- Department of Gastroenterology and Hepatology, Kindai University Faculty of Medicine, Osaka-Sayama, Japan
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4
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Beumer BR, Buettner S, Galjart B, van Vugt JLA, de Man RA, IJzermans JNM, Koerkamp BG. Systematic review and meta-analysis of validated prognostic models for resected hepatocellular carcinoma patients. Eur J Surg Oncol 2021; 48:492-499. [PMID: 34602315 DOI: 10.1016/j.ejso.2021.09.012] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Revised: 09/13/2021] [Accepted: 09/15/2021] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND Many prognostic models for Hepatocellular Carcinoma (HCC) have been developed to inform patients and doctors about individual prognosis. Previous reviews of these models were qualitative and did not assess performance at external validation. We assessed the performance of prognostic models for HCC and set a benchmark for biomarker studies. METHODS All externally validated models predicting survival for patients with resected HCC were systematically reviewed. After selection, we extracted descriptive statistics and aggregated c-indices using meta-analysis. RESULTS Thirty-eight validated prognostic models were included. Models used on average 7 (IQR:4-9) prognostic factors. Tumor size, tumor number, and vascular invasion were almost always included. Alpha-fetoprotein (AFP) was commonly incorporated since 2007. Recently, the more subjective items ascites and encephalopathy have been dropped. Eight established models performed poor to moderate at external validation, with a pooled C-index below 0.7; including the Barcelona Clinic Liver Cancer (BCLC) system, the American Joint Committee on Cancer (AJCC) 7th edition, the Cancer of the Liver Italian (CLIP) Program, and the Japan Integrated Staging (JIS) score. Out of 24 prognostic models predicting OS, only 6 (25%) had good performance at external validation with pooled C-indices above 0.7; the Li-post (0.77), Li-OS (0.74), Yang-pre (0.74), Yang-post (0.76), Shanghai-score (0.70), and Wang-nomogram (0.71). Models improved over time, but overall performance and study quality remained low. CONCLUSIONS Six validated prognostic models demonstrated good performance for predicting survival after resection of HCC. These models can guide patients and doctors and are a benchmark for future models incorporating novel biomarkers.
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Affiliation(s)
- Berend R Beumer
- Erasmus MC Transplant Institute, Department of Surgery Division of HPB & Transplant Surgery, Erasmus MC, University Medical Centre Rotterdam, Rotterdam, the Netherlands
| | - Stefan Buettner
- Erasmus MC Transplant Institute, Department of Surgery Division of HPB & Transplant Surgery, Erasmus MC, University Medical Centre Rotterdam, Rotterdam, the Netherlands
| | - Boris Galjart
- Erasmus MC Transplant Institute, Department of Surgery Division of HPB & Transplant Surgery, Erasmus MC, University Medical Centre Rotterdam, Rotterdam, the Netherlands
| | - Jeroen L A van Vugt
- Erasmus MC Transplant Institute, Department of Surgery Division of HPB & Transplant Surgery, Erasmus MC, University Medical Centre Rotterdam, Rotterdam, the Netherlands
| | - Robert A de Man
- Erasmus MC Transplant Institute, Department of Gastroenterology and Hepatology, Erasmus MC, University Medical Centre Rotterdam, Rotterdam, the Netherlands
| | - Jan N M IJzermans
- Erasmus MC Transplant Institute, Department of Surgery Division of HPB & Transplant Surgery, Erasmus MC, University Medical Centre Rotterdam, Rotterdam, the Netherlands
| | - Bas Groot Koerkamp
- Erasmus MC Transplant Institute, Department of Surgery Division of HPB & Transplant Surgery, Erasmus MC, University Medical Centre Rotterdam, Rotterdam, the Netherlands.
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5
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Imaging HCC treated with radioembolization: review of the literature and clinical examples of choline PET utility. Clin Transl Imaging 2020. [DOI: 10.1007/s40336-020-00384-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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6
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Preoperative predictors of liver decompensation after mini-invasive liver resection. Surg Endosc 2020; 35:718-727. [PMID: 32124061 DOI: 10.1007/s00464-020-07438-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2019] [Accepted: 02/10/2020] [Indexed: 02/06/2023]
Abstract
BACKGROUND Post-hepatectomy liver failure (PHLF) represents the most frequent complication after liver surgery, and the most common cause of morbidity and mortality. Aim of the study is to identify the predictors of PHLF after mini-invasive liver surgery in cirrhosis and chronic liver disease, and to develop a model for risk prediction. METHODS The present study is a multicentric prospective cohort study on 490 consecutive patients who underwent mini-invasive liver resection from the Italian Registry of Mini-invasive Liver Surgery (I go MILS). Retrospective additional biochemical and clinical data were collected. RESULTS On 490 patients (26.5% females), PHLF occurred in 89 patients (18.2%). The only independent predictors of PHLF were Albumin-Bilirubin (ALBI) score (OR 3.213; 95% CI 1.661-6.215; p < .0.0001) and presence of ascites (OR 3.320; 95% CI 1.468-7.508; p = 0.004). Classification and regression tree (CART) modeling led to the identification of three risk groups: PHLF occurred in 23/217 patients with ALBI grade 1 (10.6%, low risk group), in 54/254 patients with ALBI score 2 or 3 and absence of ascites (21.3%, intermediate risk group) and in 12/19 patients with ALBI score 2 or 3 and evidence of ascites (63.2%, high risk group), p < 0.0001. The three groups showed a corresponding increase in postoperative complications (20.0%, 27.5% and 66.7%), Comprehensive Complication Index (5.1 ± 11.1, 6.0 ± 10.9 and 18.8 ± 18.9) and hospital stay (6.0 ± 4.0, 6.0 ± 6.0 and 8.0 ± 5.0 days). CONCLUSION The risk of PHLF can be stratified by determining two easily available preoperative factors: ALBI and ascites. This model of risk prediction offers an objective instrument for a correct clinical decision-making.
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7
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Lu RC, She B, Gao WT, Ji YH, Xu DD, Wang QS, Wang SB. Positron-emission tomography for hepatocellular carcinoma: Current status and future prospects. World J Gastroenterol 2019; 25:4682-4695. [PMID: 31528094 PMCID: PMC6718031 DOI: 10.3748/wjg.v25.i32.4682] [Citation(s) in RCA: 53] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/11/2019] [Revised: 06/30/2019] [Accepted: 07/19/2019] [Indexed: 02/06/2023] Open
Abstract
Hepatocellular carcinoma (HCC) is one of the leading causes of cancer mortality worldwide. Various imaging modalities provide important information about HCC for its clinical management. Since positron-emission tomography (PET) or PET-computed tomography was introduced to the oncologic setting, it has played crucial roles in detecting, distinguishing, accurately staging, and evaluating local, residual, and recurrent HCC. PET imaging visualizes tissue metabolic information that is closely associated with treatment. Dynamic PET imaging and dual-tracer have emerged as complementary techniques that aid in various aspects of HCC diagnosis. The advent of new radiotracers and the development of immuno-PET and PET-magnetic resonance imaging have improved the ability to detect lesions and have made great progress in treatment surveillance. The current PET diagnostic capabilities for HCC and the supplementary techniques are reviewed herein.
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Affiliation(s)
- Ren-Cai Lu
- PET-CT Center, the First People’s Hospital of Yunnan Province, Kunming 650032, Yunnan Province, China
| | - Bo She
- PET-CT Center, the First People’s Hospital of Yunnan Province, Kunming 650032, Yunnan Province, China
| | - Wen-Tao Gao
- PET-CT Center, the First People’s Hospital of Yunnan Province, Kunming 650032, Yunnan Province, China
| | - Yun-Hai Ji
- PET-CT Center, the First People’s Hospital of Yunnan Province, Kunming 650032, Yunnan Province, China
| | - Dong-Dong Xu
- PET-CT Center, the First People’s Hospital of Yunnan Province, Kunming 650032, Yunnan Province, China
| | - Quan-Shi Wang
- Nanfang PET Center, Nanfang Hospital, Southern Medical University, Guangzhou 510515, Guangdong Province, China
| | - Shao-Bo Wang
- PET-CT Center, the First People’s Hospital of Yunnan Province, Kunming 650032, Yunnan Province, China
- Yunnan Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650093, Yunnan Province, China
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8
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Sun HC, Xie L, Yang XR, Li W, Yu J, Zhu XD, Xia Y, Zhang T, Xu Y, Hu B, Du LP, Zeng LY, Ouyang J, Zhang W, Song TQ, Li Q, Shi YH, Zhou J, Qiu SJ, Liu Q, Li YX, Tang ZY, Shyr Y, Shen F, Fan J. Shanghai Score: A Prognostic and Adjuvant Treatment-evaluating System Constructed for Chinese Patients with Hepatocellular Carcinoma after Curative Resection. Chin Med J (Engl) 2017; 130:2650-2660. [PMID: 29133751 PMCID: PMC5695048 DOI: 10.4103/0366-6999.218019] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2017] [Indexed: 01/27/2023] Open
Abstract
BACKGROUND For Chinese patients with hepatocellular carcinoma (HCC), surgical resection is the most important treatment to achieve long-term survival for patients with an early-stage tumor, and yet the prognosis after surgery is diverse. We aimed to construct a scoring system (Shanghai Score) for individualized prognosis estimation and adjuvant treatment evaluation. METHODS A multivariate Cox proportional hazards model was constructed based on 4166 HCC patients undergoing resection during 2001-2008 at Zhongshan Hospital. Age, hepatitis B surface antigen, hepatitis B e antigen, partial thromboplastin time, total bilirubin, alkaline phosphatase, γ-glutamyltransferase, α-fetoprotein, tumor size, cirrhosis, vascular invasion, differentiation, encapsulation, and tumor number were finally retained by a backward step-down selection process with the Akaike information criterion. The Harrell's concordance index (C-index) was used to measure model performance. Shanghai Score is calculated by summing the products of the 14 variable values times each variable's corresponding regression coefficient. Totally 1978 patients from Zhongshan Hospital undergoing resection during 2009-2012, 808 patients from Eastern Hepatobiliary Surgery Hospital during 2008-2010, and 244 patients from Tianjin Medical University Cancer Hospital during 2010-2011 were enrolled as external validation cohorts. Shanghai Score was also implied in evaluating adjuvant treatment choices based on propensity score matching analysis. RESULTS Shanghai Score showed good calibration and discrimination in postsurgical HCC patients. The bootstrap-corrected C-index (confidence interval [CI]) was 0.74 for overall survival (OS) and 0.68 for recurrence-free survival (RFS) in derivation cohort (4166 patients), and in the three independent validation cohorts, the CI s for OS ranged 0.70-0.72 and that for RFS ranged 0.63-0.68. Furthermore, Shanghai Score provided evaluation for adjuvant treatment choices (transcatheter arterial chemoembolization or interferon-α). The identified subset of patients at low risk could be ideal candidates for curative surgery, and subsets of patients at moderate or high risk could be recommended with possible adjuvant therapies after surgery. Finally, a web server with individualized outcome prediction and treatment recommendation was constructed. CONCLUSIONS Based on the largest cohort up to date, we established Shanghai Score - an individualized outcome prediction system specifically designed for Chinese HCC patients after surgery. The Shanghai Score web server provides an easily accessible tool to stratify the prognosis of patients undergoing liver resection for HCC.
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Affiliation(s)
- Hui-Chuan Sun
- Department of Liver Surgery, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai 200032, China
| | - Lu Xie
- Shanghai Center for Bioinformation Technology, Shanghai Academy of Science and Technology, Shanghai 201203, China
| | - Xin-Rong Yang
- Department of Liver Surgery, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai 200032, China
| | - Wei Li
- Shanghai Center for Bioinformation Technology, Shanghai Academy of Science and Technology, Shanghai 201203, China
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Jian Yu
- Shanghai Center for Bioinformation Technology, Shanghai Academy of Science and Technology, Shanghai 201203, China
| | - Xiao-Dong Zhu
- Department of Liver Surgery, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai 200032, China
| | - Yong Xia
- Department of Hepatic Surgery, Eastern Hepatobiliary Surgery Hospital, The Second Military Medical University, Shanghai 200438, China
| | - Ti Zhang
- Department of Hepatobiliary Surgery, Tianjin Medical University Cancer Institute and Hospital, Tianjin 300040, China
| | - Yang Xu
- Department of Liver Surgery, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai 200032, China
| | - Bo Hu
- Department of Liver Surgery, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai 200032, China
| | - Li-Ping Du
- Center for Quantitative Sciences, Vanderbilt University School of Medicine, Nashville, TN 37232, USA
| | - Ling-Yao Zeng
- Shanghai Center for Bioinformation Technology, Shanghai Academy of Science and Technology, Shanghai 201203, China
| | - Jian Ouyang
- Shanghai Center for Bioinformation Technology, Shanghai Academy of Science and Technology, Shanghai 201203, China
| | - Wei Zhang
- Department of Hepatobiliary Surgery, Tianjin Medical University Cancer Institute and Hospital, Tianjin 300040, China
| | - Tian-Qiang Song
- Department of Hepatobiliary Surgery, Tianjin Medical University Cancer Institute and Hospital, Tianjin 300040, China
| | - Qiang Li
- Department of Hepatobiliary Surgery, Tianjin Medical University Cancer Institute and Hospital, Tianjin 300040, China
| | - Ying-Hong Shi
- Department of Liver Surgery, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai 200032, China
| | - Jian Zhou
- Department of Liver Surgery, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai 200032, China
| | - Shuang-Jian Qiu
- Department of Liver Surgery, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai 200032, China
| | - Qian Liu
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Yi-Xue Li
- Shanghai Center for Bioinformation Technology, Shanghai Academy of Science and Technology, Shanghai 201203, China
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Zhao-You Tang
- Department of Liver Surgery, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai 200032, China
| | - Yu Shyr
- Center for Quantitative Sciences, Vanderbilt University School of Medicine, Nashville, TN 37232, USA
| | - Feng Shen
- Department of Hepatic Surgery, Eastern Hepatobiliary Surgery Hospital, The Second Military Medical University, Shanghai 200438, China
| | - Jia Fan
- Department of Liver Surgery, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai 200032, China
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