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Chan YT, Zhang C, Wu J, Lu P, Xu L, Yuan H, Feng Y, Chen ZS, Wang N. Biomarkers for diagnosis and therapeutic options in hepatocellular carcinoma. Mol Cancer 2024; 23:189. [PMID: 39242496 PMCID: PMC11378508 DOI: 10.1186/s12943-024-02101-z] [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: 07/30/2024] [Accepted: 08/23/2024] [Indexed: 09/09/2024] Open
Abstract
Liver cancer is a global health challenge, causing a significant social-economic burden. Hepatocellular carcinoma (HCC) is the predominant type of primary liver cancer, which is highly heterogeneous in terms of molecular and cellular signatures. Early-stage or small tumors are typically treated with surgery or ablation. Currently, chemotherapies and immunotherapies are the best treatments for unresectable tumors or advanced HCC. However, drug response and acquired resistance are not predictable with the existing systematic guidelines regarding mutation patterns and molecular biomarkers, resulting in sub-optimal treatment outcomes for many patients with atypical molecular profiles. With advanced technological platforms, valuable information such as tumor genetic alterations, epigenetic data, and tumor microenvironments can be obtained from liquid biopsy. The inter- and intra-tumoral heterogeneity of HCC are illustrated, and these collective data provide solid evidence in the decision-making process of treatment regimens. This article reviews the current understanding of HCC detection methods and aims to update the development of HCC surveillance using liquid biopsy. Recent critical findings on the molecular basis, epigenetic profiles, circulating tumor cells, circulating DNAs, and omics studies are elaborated for HCC diagnosis. Besides, biomarkers related to the choice of therapeutic options are discussed. Some notable recent clinical trials working on targeted therapies are also highlighted. Insights are provided to translate the knowledge into potential biomarkers for detection and diagnosis, prognosis, treatment response, and drug resistance indicators in clinical practice.
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Affiliation(s)
- Yau-Tuen Chan
- School of Chinese Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong
| | - Cheng Zhang
- School of Chinese Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong
| | - Junyu Wu
- School of Chinese Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong
| | - Pengde Lu
- School of Chinese Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong
| | - Lin Xu
- School of Chinese Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong
| | - Hongchao Yuan
- School of Chinese Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong
| | - Yibin Feng
- School of Chinese Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong
| | - Zhe-Sheng Chen
- School of Chinese Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong.
- Department of Pharmaceutical Sciences, College of Pharmacy and Health Sciences, St. John's University, 8000 Utopia Parkway, Queens, NY, 11439, USA.
| | - Ning Wang
- School of Chinese Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong.
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Deng T, Chen G. Single-cell-based molecular classification in systematic treatment of hepatocellular carcinoma: From in silico to bedside. Hepatology 2024; 80:505-507. [PMID: 38546296 DOI: 10.1097/hep.0000000000000874] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/13/2024] [Accepted: 03/18/2024] [Indexed: 04/30/2024]
Affiliation(s)
- Tuo Deng
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China
- Zhejiang-Germany Interdisciplinary Joint Laboratory of Hepatobiliary-Pancreatic Tumor and Bioengineering
- Zhejiang Key Laboratory of Intelligent Cancer Biomarker Discovery and Translation, are department of The First Affiliated Hospital of Wenzhou Medical University
| | - Gang Chen
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China
- Zhejiang-Germany Interdisciplinary Joint Laboratory of Hepatobiliary-Pancreatic Tumor and Bioengineering
- Zhejiang Key Laboratory of Intelligent Cancer Biomarker Discovery and Translation, are department of The First Affiliated Hospital of Wenzhou Medical University
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Dong M, Li C, Zhang L, Zhou J, Xiao Y, Zhang T, Jin X, Fang Z, Zhang L, Han Y, Guan J, Weng Z, Cheng N, Wang J. Intertumoral Heterogeneity Based on MRI Radiomic Features Estimates Recurrence in Hepatocellular Carcinoma. J Magn Reson Imaging 2024. [PMID: 38712652 DOI: 10.1002/jmri.29428] [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: 02/17/2024] [Revised: 04/16/2024] [Accepted: 04/16/2024] [Indexed: 05/08/2024] Open
Abstract
BACKGROUND Hepatocellular carcinoma (HCC) heterogeneity impacts prognosis, and imaging is a potential indicator. PURPOSE To characterize HCC image subtypes in MRI and correlate subtypes with recurrence. STUDY TYPE Retrospective. POPULATION A total of 440 patients (training cohort = 213, internal test cohort = 140, external test cohort = 87) from three centers. FIELD STRENGTH/SEQUENCE 1.5-T/3.0-T, fast/turbo spin-echo T2-weighted, spin-echo echo-planar diffusion-weighted, contrast-enhanced three-dimensional gradient-recalled-echo T1-weighted with extracellular agents (Gd-DTPA, Gd-DTPA-BMA, and Gd-BOPTA). ASSESSMENT Three-dimensional volume-of-interest of HCC was contoured on portal venous phase, then coregistered with precontrast and late arterial phases. Subtypes were identified using non-negative matrix factorization by analyzing radiomics features from volume-of-interests, and correlated with recurrence. Clinical (demographic and laboratory data), pathological, and radiologic features were compared across subtypes. Among clinical, radiologic features and subtypes, variables with variance inflation factor above 10 were excluded. Variables (P < 0.10) in univariate Cox regression were included in stepwise multivariate analysis. Three recurrence estimation models were built: clinical-radiologic model, subtype model, hybrid model integrating clinical-radiologic characteristics, and subtypes. STATISTICAL TESTS Mann-Whitney U test, Kruskal-Wallis H test, chi-square test, Fisher's exact test, Kaplan-Meier curves, log-rank test, concordance index (C-index). Significance level: P < 0.05. RESULTS Two subtypes were identified across three cohorts (subtype 1:subtype 2 of 86:127, 60:80, and 36:51, respectively). Subtype 1 showed higher microvascular invasion (MVI)-positive rates (53%-57% vs. 26%-31%), and worse recurrence-free survival. Hazard ratio (HR) for the subtype is 6.10 in subtype model. Clinical-radiologic model included alpha-fetoprotein (HR: 3.01), macrovascular invasion (HR: 2.32), nonsmooth tumor margin (HR: 1.81), rim enhancement (HR: 3.13), and intratumoral artery (HR: 2.21). Hybrid model included alpha-fetoprotein (HR: 2.70), nonsmooth tumor margin (HR: 1.51), rim enhancement (HR: 3.25), and subtypes (HR: 5.34). Subtype model was comparable to clinical-radiologic model (C-index: 0.71-0.73 vs. 0.71-0.73), but hybrid model outperformed both (C-index: 0.77-0.79). CONCLUSION MRI radiomics-based clustering identified two HCC subtypes with distinct MVI status and recurrence-free survival. Hybrid model showed superior capability to estimate recurrence. LEVEL OF EVIDENCE 3 TECHNICAL EFFICACY STAGE: 2.
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Affiliation(s)
- Mengshi Dong
- Department of Radiology, The Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Chao Li
- Department of Radiology, The Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Lina Zhang
- Department of Radiology, The Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Jinhui Zhou
- Department of Radiology, The Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Yuanqiang Xiao
- Department of Radiology, The Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Tianhui Zhang
- Department of Radiology, Meizhou People's Hospital, Meizhou, China
| | - Xin Jin
- Department of Radiology, The Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Zebin Fang
- Department of Radiology, The Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Linqi Zhang
- Department of Radiology, Affiliated Cancer Hospital and Institute of Guangzhou Medical University, Guangzhou, China
| | - Yu Han
- Department of Radiology, The Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Jiexia Guan
- Department of Pathology, The Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Zijin Weng
- Department of Pathology, The Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Na Cheng
- Department of Pathology, The Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Jin Wang
- Department of Radiology, The Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
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Yang YH, Wei YL, She ZY. Kinesin-7 CENP-E in tumorigenesis: Chromosome instability, spindle assembly checkpoint, and applications. Front Mol Biosci 2024; 11:1366113. [PMID: 38560520 PMCID: PMC10978661 DOI: 10.3389/fmolb.2024.1366113] [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: 01/05/2024] [Accepted: 03/04/2024] [Indexed: 04/04/2024] Open
Abstract
Kinesin motors are a large family of molecular motors that walk along microtubules to fulfill many roles in intracellular transport, microtubule organization, and chromosome alignment. Kinesin-7 CENP-E (Centromere protein E) is a chromosome scaffold-associated protein that is located in the corona layer of centromeres, which participates in kinetochore-microtubule attachment, chromosome alignment, and spindle assembly checkpoint. Over the past 3 decades, CENP-E has attracted great interest as a promising new mitotic target for cancer therapy and drug development. In this review, we describe expression patterns of CENP-E in multiple tumors and highlight the functions of CENP-E in cancer cell proliferation. We summarize recent advances in structural domains, roles, and functions of CENP-E in cell division. Notably, we describe the dual functions of CENP-E in inhibiting and promoting tumorigenesis. We summarize the mechanisms by which CENP-E affects tumorigenesis through chromosome instability and spindle assembly checkpoints. Finally, we overview and summarize the CENP-E-specific inhibitors, mechanisms of drug resistances and their applications.
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Affiliation(s)
- Yu-Hao Yang
- Department of Cell Biology and Genetics, The School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China
- Key Laboratory of Stem Cell Engineering and Regenerative Medicine, Fujian Province University, Fuzhou, China
| | - Ya-Lan Wei
- Medical Research Center, Fujian Maternity and Child Health Hospital, Fuzhou, China
- College of Clinical Medicine for Obstetrics and Gynecology and Pediatrics, Fujian Medical University, Fuzhou, China
| | - Zhen-Yu She
- Department of Cell Biology and Genetics, The School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China
- Key Laboratory of Stem Cell Engineering and Regenerative Medicine, Fujian Province University, Fuzhou, China
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Sun Z, Li X, Liang H, Shi Z, Ren H. A Deep Learning Model Combining Multimodal Factors to Predict the Overall Survival of Transarterial Chemoembolization. J Hepatocell Carcinoma 2024; 11:385-397. [PMID: 38435683 PMCID: PMC10906280 DOI: 10.2147/jhc.s443660] [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: 10/11/2023] [Accepted: 01/30/2024] [Indexed: 03/05/2024] Open
Abstract
Background To develop and validate an overall survival (OS) prediction model for transarterial chemoembolization (TACE). Methods In this retrospective study, 301 patients with hepatocellular carcinoma (HCC) who received TACE from 2012 to 2015 were collected. The residual network was used to extract prognostic information from CT images, which was then combined with the clinical factors adjusted by COX regression to predict survival using a modified deep learning model (DLOPCombin). The DLOPCombin model was compared with the residual network model (DLOPCTR), multiple COX regression model (DLOPCox), Radiomic model (Radiomic), and clinical model. Results In the validation cohort, DLOPCombin shows the highest TD AUC of all cohorts, which compared with Radiomic (TD AUC: 0.96vs 0.63) and clinical model (TD AUC: 0.96 vs 0.62) model. DLOPCombin showed significant difference in C index compared with DLOPCTR and DLOPCox models (P < 0.05). Moreover, the DLOPCombin showed good calibration and overall net benefit. Patients with DLOPCombin model score ≤ 0.902 had better OS (33 months vs 15.5 months, P < 0.0001). Conclusion The deep learning model can effectively predict the patients' overall survival of TACE.
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Affiliation(s)
- Zhongqi Sun
- Department of Radiology, the Second Affiliated Hospital of Harbin Medical University, Harbin, 150086, People’s Republic of China
| | - Xin Li
- Department of Radiology, the Second Affiliated Hospital of Harbin Medical University, Harbin, 150086, People’s Republic of China
| | - Hongwei Liang
- Department of Radiology, the Second Affiliated Hospital of Harbin Medical University, Harbin, 150086, People’s Republic of China
| | - Zhongxing Shi
- Department of Interventional Radiology, the Second Affiliated Hospital of Harbin Medical University, Harbin, 150086, People’s Republic of China
| | - Hongjia Ren
- School of Information Science and Engineering, Yanshan University, Qinhuangdao, 066004, People’s Republic of China
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Li B, Li Y, Zhou H, Xu Y, Cao Y, Cheng C, Peng J, Li H, Zhang L, Su K, Xu Z, Hu Y, Lu J, Lu Y, Qian L, Wang Y, Zhang Y, Liu Q, Xie Y, Guo S, Mehal WZ, Yu D. Multiomics identifies metabolic subtypes based on fatty acid degradation allocating personalized treatment in hepatocellular carcinoma. Hepatology 2024; 79:289-306. [PMID: 37540187 PMCID: PMC10789383 DOI: 10.1097/hep.0000000000000553] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Accepted: 06/26/2023] [Indexed: 08/05/2023]
Abstract
BACKGROUND AND AIMS Molecular classification is a promising tool for prognosis prediction and optimizing precision therapy for HCC. Here, we aimed to develop a molecular classification of HCC based on the fatty acid degradation (FAD) pathway, fully characterize it, and evaluate its ability in guiding personalized therapy. APPROACH AND RESULTS We performed RNA sequencing (RNA-seq), PCR-array, lipidomics, metabolomics, and proteomics analysis of 41 patients with HCC, in which 17 patients received anti-programmed cell death-1 (PD-1) therapy. Single-cell RNA sequencing (scRNA-seq) was performed to explore the tumor microenvironment. Nearly, 60 publicly available multiomics data sets were analyzed. The associations between FAD subtypes and response to sorafenib, transarterial chemoembolization (TACE), immune checkpoint inhibitor (ICI) were assessed in patient cohorts, patient-derived xenograft (PDX), and spontaneous mouse model ls. A novel molecular classification named F subtype (F1, F2, and F3) was identified based on the FAD pathway, distinguished by clinical, mutational, epigenetic, metabolic, and immunological characteristics. F1 subtypes exhibited high infiltration with immunosuppressive microenvironment. Subtype-specific therapeutic strategies were identified, in which F1 subtypes with the lowest FAD activities represent responders to compounds YM-155 and Alisertib, sorafenib, anti-PD1, anti-PD-L1, and atezolizumab plus bevacizumab (T + A) treatment, while F3 subtypes with the highest FAD activities are responders to TACE. F2 subtypes, the intermediate status between F1 and F3, are potential responders to T + A combinations. We provide preliminary evidence that the FAD subtypes can be diagnosed based on liquid biopsies. CONCLUSIONS We identified 3 FAD subtypes with unique clinical and biological characteristics, which could optimize individual cancer patient therapy and help clinical decision-making.
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Affiliation(s)
- Binghua Li
- State Key Laboratory of Pharmaceutical Biotechnology, Division of Hepatobiliary and Transplantation Surgery, Department of General Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
- Department of Internal Medicine, Section of Digestive Diseases, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Yunzheng Li
- State Key Laboratory of Pharmaceutical Biotechnology, Division of Hepatobiliary and Transplantation Surgery, Department of General Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
| | - Huajun Zhou
- Department of Data Science & Bioinformatics, Crown Bioscience Inc., Suzhou, Jiangsu, China
| | - Yanchao Xu
- Division of Hepatobiliary and Transplantation Surgery, Department of General Surgery, Nanjing Drum Tower Hospital Clinical College of Jiangsu University, Nanjing, China
| | - Yajuan Cao
- State Key Laboratory of Pharmaceutical Biotechnology, Division of Hepatobiliary and Transplantation Surgery, Department of General Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
| | - Chunxiao Cheng
- Division of Hepatobiliary and Transplantation Surgery, Department of General Surgery, Affiliated Drum Tower Hospital, Nanjing University of Chinese Medicine, Nanjing, China
| | - Jin Peng
- State Key Laboratory of Pharmaceutical Biotechnology, Division of Hepatobiliary and Transplantation Surgery, Department of General Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
| | - Huan Li
- State Key Laboratory of Pharmaceutical Biotechnology, Division of Hepatobiliary and Transplantation Surgery, Department of General Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
| | - Laizhu Zhang
- State Key Laboratory of Pharmaceutical Biotechnology, Division of Hepatobiliary and Transplantation Surgery, Department of General Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
| | - Ke Su
- State Key Laboratory of Pharmaceutical Biotechnology, Division of Hepatobiliary and Transplantation Surgery, Department of General Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
| | - Zhu Xu
- State Key Laboratory of Pharmaceutical Biotechnology, Division of Hepatobiliary and Transplantation Surgery, Department of General Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
| | - Yue Hu
- Biobank of Nanjing Drum Tower Hospital, Department of Pathology, The Affiliated Hospital of Nanjing University Medical School, Nanjing, Nanjing, China
| | - Jiaming Lu
- Department of Radiology, The Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China
| | - Yijun Lu
- State Key Laboratory of Pharmaceutical Biotechnology, Division of Hepatobiliary and Transplantation Surgery, Department of General Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
| | - Liyuan Qian
- Department of Hepatobiliary and Pancreatic Surgery, The First People’s Hospital of Changzhou, The Third Affiliated Hospital of Soochow University, Changzhou, China
| | - Ye Wang
- State Key Laboratory of Pharmaceutical Biotechnology, Division of Hepatobiliary and Transplantation Surgery, Department of General Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
| | - Yuchen Zhang
- State Key Laboratory of Pharmaceutical Biotechnology, Division of Hepatobiliary and Transplantation Surgery, Department of General Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
| | - Qi Liu
- State Key Laboratory of Pharmaceutical Biotechnology, Division of Hepatobiliary and Transplantation Surgery, Department of General Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
| | - Yuanyuan Xie
- State Key Laboratory of Pharmaceutical Biotechnology, Division of Hepatobiliary and Transplantation Surgery, Department of General Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
| | - Sheng Guo
- Department of Data Science & Bioinformatics, Crown Bioscience Inc., Suzhou, Jiangsu, China
| | - Wajahat Z. Mehal
- Department of Internal Medicine, Section of Digestive Diseases, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Decai Yu
- State Key Laboratory of Pharmaceutical Biotechnology, Division of Hepatobiliary and Transplantation Surgery, Department of General Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
- Division of Hepatobiliary and Transplantation Surgery, Department of General Surgery, Nanjing Drum Tower Hospital Clinical College of Jiangsu University, Nanjing, China
- Division of Hepatobiliary and Transplantation Surgery, Department of General Surgery, Affiliated Drum Tower Hospital, Nanjing University of Chinese Medicine, Nanjing, China
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Wu R, Gao Y, Zhao X, Guo S, Zhou H, Zhang Y, Hou Y, Mei L, Zhi H, Wang P, Li X, Ning S, Zhang Y. Tumor biology, immune infiltration and liver function define seven hepatocellular carcinoma subtypes linked to distinct drivers, survival and drug response. Comput Biol Med 2023; 167:107593. [PMID: 37883849 DOI: 10.1016/j.compbiomed.2023.107593] [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: 07/26/2023] [Revised: 09/25/2023] [Accepted: 10/17/2023] [Indexed: 10/28/2023]
Abstract
BACKGROUND & AIMS Tumor heterogeneity is jointly determined by the components of the tumor ecosystem (TES) including tumor cells, immune cells, stromal cells, and non-cellular components. We aimed to identify subtypes using TES-related genes and determine subtype specific drivers and treatments for hepatocellular carcinoma (HCC). METHODS We collected 68 genesets depicting tumor biology, immune infiltration, and liver function, totaling 2831 genes, and collected mRNA profiles and clinical data for over 6000 tumors from 65 datasets in the GEO, TCGA, ICGC, and several other databases. We designed a three-step clustering pipeline to identify subtypes. The microenvironment, genomic alteration, and drug response differences were systematically compared among subtypes. RESULTS Seven subtypes (TES-1/2/3/4/5/6/7) were revealed in 159 tumors from the CHCC-HBV cohort. We constructed a single sample classifier using paired genes (sscpgsTES). TES subtypes were significantly associated with multiple clinical variables including etiology, and survival in 14 of 17 cohorts and the meta-cohort. TES-1 had the poorest prognosis and highest proliferation level. Both TES-2 and TES-7 were immune-enriched, however, TES-2 had a significantly worse prognosis, and hypoxic and immunosuppressive microenvironment. TES-4 had activated Wnt pathway, driven by CTNNB1 mutation. Good prognosis TES-6 exhibited the best differentiation. TES-5 and TES-3 were considered as novel subclasses by comparing with ten previous subtyping systems. TES-5 tumors had high AFP but good overall survival, and ∼45% of them harbored AXIN1 mutation. TES-3 was immune and stromal desert, may be driven by high copy number alteration burden, and had the poorest response to immune checkpoint inhibitor. TES-1 and TES-2 had significantly lower response to transarterial chemoembolization, but they showed significantly higher sensitivity to compound YM-155. CONCLUSIONS Tumor ecosystem subtypes expand existing HCC subtyping systems, have distinct drivers, prognosis, and treatment vulnerabilities.
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Affiliation(s)
- Ruihong Wu
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China; Phase I Clinical Research Center, First Hospital of Jilin University, Chang chun, Jilin, China
| | - Yue Gao
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China
| | - Xiaoxi Zhao
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China
| | - Shuang Guo
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China
| | - Hanxiao Zhou
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China
| | - Yakun Zhang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China
| | - Yaopan Hou
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China
| | - Lan Mei
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China
| | - Hui Zhi
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China
| | - Peng Wang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China
| | - Xia Li
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China.
| | - Shangwei Ning
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China.
| | - Yunpeng Zhang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China.
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8
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Chong ML, Knight J, Peng G, Ji W, Chai H, Lu Y, Wu S, Li P, Hu Q. Integrated exome sequencing and microarray analyses detected genetic defects and underlying pathways of hepatocellular carcinoma. Cancer Genet 2023; 276-277:30-35. [PMID: 37418972 DOI: 10.1016/j.cancergen.2023.06.002] [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: 02/23/2023] [Revised: 05/25/2023] [Accepted: 06/26/2023] [Indexed: 07/09/2023]
Abstract
We performed whole exome sequencing (WES) and microarray analysis to detect somatic variants and copy number alterations (CNAs) for underlying mechanisms in a case series of hepatocellular carcinoma (HCC) with paired DNA samples from tumor and adjacent nontumor tissues. Clinicopathologic findings based on Edmondson-Steiner (E-S) grading, Barcelona-Clinic Liver Cancer (BCLC) stages, recurrence, and survival status and their associations with tumor mutation burden (TMB) and CNA burden (CNAB) were evaluated. WES from 36 cases detected variants in the TP53, AXIN1, CTNNB1, and SMARCA4 genes, amplifications of the AKT3, MYC, and TERT genes, and deletions of the CDH1, TP53, IRF2, RB1, RPL5, and PTEN genes. These genetic defects affecting the p53/cell cycle control, PI3K/Ras, and β-catenin pathways were observed in approximately 80% of cases. A germline variant in the ALDH2 gene was detected in 52% of the cases. Significantly higher CNAB in patients with poor prognosis by E-S grade III, BCLC stage C, and recurrence than patients with good prognosis by grade III, stage A, grade III and nonrecurrence was noted. Further analysis on a large case series to correlate genomic profiling with clinicopathologic classifications could provide evidence for diagnostic interpretation, prognostic prediction, and target intervention on involved genes and pathways.
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Affiliation(s)
- Mei Ling Chong
- Department of Genetics, School of Medicine, Yale University, New Haven, CT, USA
| | - James Knight
- Department of Genetics, School of Medicine, Yale University, New Haven, CT, USA; Yale Center for Genome Analysis, School of Medicine, Yale University, New Haven, CT, USA
| | - Gang Peng
- Department of Genetics, School of Medicine, Yale University, New Haven, CT, USA; Department of Medical and Molecular Genomics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Weizhen Ji
- Department of Genetics, School of Medicine, Yale University, New Haven, CT, USA
| | - Hongyan Chai
- Department of Genetics, School of Medicine, Yale University, New Haven, CT, USA
| | - Yufei Lu
- Department of Cell Biology and Genetics, School of Pre-Clinical Medicine, Guangxi Medical University, Nanning, Guangxi, China
| | - Shengming Wu
- Department of Pathology, Affiliated Tumor Hospital of Guangxi Medical University, Nanning, Guangxi, China
| | - Peining Li
- Department of Genetics, School of Medicine, Yale University, New Haven, CT, USA; Yale Center for Genome Analysis, School of Medicine, Yale University, New Haven, CT, USA
| | - Qiping Hu
- Department of Cell Biology and Genetics, School of Pre-Clinical Medicine, Guangxi Medical University, Nanning, Guangxi, China.
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Wang Y, Chai S, Cai W, Yu J, Liang P. Prognostic and pathological implications of contrast-enhanced ultrasound features in hepatocellular carcinoma. J Cancer Res Ther 2023; 19:1040-1047. [PMID: 37675734 DOI: 10.4103/jcrt.jcrt_1155_23] [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: 09/08/2023]
Abstract
Background Contrast-enhanced ultrasound (CEUS) plays a vital role in diagnosing hepatocellular carcinoma (HCC) and, to some extent, reflects tumor prognosis. This suggests that some pathological features of HCC may be associated with CEUS features. Aim This study aimed to verify the prognostic significance of four CEUS features and further explore their pathological significance. Materials and Methods This study included 243 HCC patients who underwent a preoperative CEUS examination. All pathological diagnoses and immunohistochemical information were obtained from the pathological report. The prognostic significance of four CEUS features, including nodule-in-nodule architecture, mosaic architecture, intratumoral feeding arteries, and peritumoral arterial phase (AP) hyperenhancement, was analyzed. The correlation between prognostic-related features and immunohistochemical information was further analyzed. Results The disease-free survival (DFS) of HCC was significantly affected by mosaic architecture or intratumoral feeding arteries (HR = 1.79; 95% confidence interval (95% CI), 1.09-2.95; P = 0.004; HR = 1.70; 95% CI, 1.07-2.71; P = 0.025, respectively). Intratumoral feeding arteries were positively correlated with the expression of serum alpha-fetoprotein (AFP), microvascular invasion (MVI), differentiation, size, and Ki-67, among which the correlation with size was the strongest, followed by Ki-67 and MVI. The mosaic architecture was positively correlated with serum AFP, MVI, differentiation, and size, among which the correlation with size was strongest, followed by MVI. Conclusion The mosaic architecture and intratumoral feeding arteries of CEUS were closely related to the postoperative progression of HCC. Mosaic architecture had a good correlation with tumor size and MVI, whereas intratumoral feeding arteries were closely associated with tumor size and Ki-67 expression.
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Affiliation(s)
- Yuling Wang
- Department of Interventional Ultrasound, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Suwan Chai
- Department of Interventional Ultrasound, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Wenjia Cai
- Department of Interventional Ultrasound, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Jie Yu
- Department of Interventional Ultrasound, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Ping Liang
- Department of Interventional Ultrasound, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
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Yim SY, Lee JS. Reply: Consensus subtypes of HCC associated with clinical outcomes and genomic phenotypes. Hepatology 2023; 78:E44. [PMID: 37264702 DOI: 10.1097/hep.0000000000000501] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Accepted: 05/04/2023] [Indexed: 06/03/2023]
Affiliation(s)
- Sun Young Yim
- Department of Internal Medicine, Korea University College of Medicine, Seoul, Korea
| | - Ju-Seog Lee
- Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
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11
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Dhanasekaran R, Suzuki H, Lemaitre L, Kubota N, Hoshida Y. Molecular and immune landscape of hepatocellular carcinoma to guide therapeutic decision-making. Hepatology 2023:01515467-990000000-00480. [PMID: 37300379 PMCID: PMC10713867 DOI: 10.1097/hep.0000000000000513] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Accepted: 05/12/2023] [Indexed: 06/12/2023]
Abstract
Liver cancer, primarily HCC, exhibits highly heterogeneous histological and molecular aberrations across tumors and within individual tumor nodules. Such intertumor and intratumor heterogeneities may lead to diversity in the natural history of disease progression and various clinical disparities across the patients. Recently developed multimodality, single-cell, and spatial omics profiling technologies have enabled interrogation of the intertumor/intratumor heterogeneity in the cancer cells and the tumor immune microenvironment. These features may influence the natural history and efficacy of emerging therapies targeting novel molecular and immune pathways, some of which had been deemed undruggable. Thus, comprehensive characterization of the heterogeneities at various levels may facilitate the discovery of biomarkers that enable personalized and rational treatment decisions, and optimize treatment efficacy while minimizing the risk of adverse effects. Such companion biomarkers will also refine HCC treatment algorithms across disease stages for cost-effective patient management by optimizing the allocation of limited medical resources. Despite this promise, the complexity of the intertumor/intratumor heterogeneity and ever-expanding inventory of therapeutic agents and regimens have made clinical evaluation and translation of biomarkers increasingly challenging. To address this issue, novel clinical trial designs have been proposed and incorporated into recent studies. In this review, we discuss the latest findings in the molecular and immune landscape of HCC for their potential and utility as biomarkers, the framework of evaluation and clinical application of predictive/prognostic biomarkers, and ongoing biomarker-guided therapeutic clinical trials. These new developments may revolutionize patient care and substantially impact the still dismal HCC mortality.
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Affiliation(s)
| | - Hiroyuki Suzuki
- Division of Gastroenterology, Department of Medicine, Kurume University School of Medicine, Kurume, Fukuoka
| | - Lea Lemaitre
- Division of Gastroenterology and Hepatology, Stanford University, Stanford, California
| | - Naoto Kubota
- Liver Tumor Translational Research Program, Simmons Comprehensive Cancer Center, Division of Digestive and Liver Diseases, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Yujin Hoshida
- Liver Tumor Translational Research Program, Simmons Comprehensive Cancer Center, Division of Digestive and Liver Diseases, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas
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12
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Jung J, Park S, Jang Y, Lee SH, Jeong YS, Yim SY, Lee JS. Clinical Significance of Glycolytic Metabolic Activity in Hepatocellular Carcinoma. Cancers (Basel) 2022; 15:186. [PMID: 36612182 PMCID: PMC9818850 DOI: 10.3390/cancers15010186] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 12/17/2022] [Accepted: 12/23/2022] [Indexed: 12/31/2022] Open
Abstract
High metabolic activity is a hallmark of cancers, including hepatocellular carcinoma (HCC). However, the molecular features of HCC with high metabolic activity contributing to clinical outcomes and the therapeutic implications of these characteristics are poorly understood. We aimed to define the features of HCC with high metabolic activity and uncover its association with response to current therapies. By integrating gene expression data from mouse liver tissues and tumor tissues from HCC patients (n = 1038), we uncovered three metabolically distinct HCC subtypes that differ in clinical outcomes and underlying molecular biology. The high metabolic subtype is characterized by poor survival, the strongest stem cell signature, high genomic instability, activation of EPCAM and SALL4, and low potential for benefitting from immunotherapy. Interestingly, immune cell analysis showed that regulatory T cells (Tregs) are highly enriched in high metabolic HCC tumors, suggesting that high metabolic activity of cancer cells may trigger activation or infiltration of Tregs, leading to cancer cells' evasion of anti-cancer immune cells. In summary, we identified clinically and metabolically distinct subtypes of HCC, potential biomarkers associated with these subtypes, and a potential mechanism of metabolism-mediated immune evasion by HCC cells.
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Affiliation(s)
- Joann Jung
- Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Sowon Park
- Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Yeonwoo Jang
- Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Sung-Hwan Lee
- Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, Yonsei University College of Medicine, Yonsei 03722, Republic of Korea
- Division of Hepatobiliary and Pancreas, Department of Surgery, CHA Bundang Medical Center, CHA University, Seongnam 46371, Republic of Korea
| | - Yun Seong Jeong
- Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Sun Young Yim
- Division of Hepatobiliary and Pancreas, Department of Surgery, CHA Bundang Medical Center, CHA University, Seongnam 46371, Republic of Korea
- Department of Internal Medicine, Korea University College of Medicine, Seoul 02841, Republic of Korea
| | - Ju-Seog Lee
- Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
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