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Maestri E, Kedei N, Khatib S, Forgues M, Ylaya K, Hewitt SM, Wang L, Chaisaingmongkol J, Ruchirawat M, Ma L, Wang XW. Spatial proximity of tumor-immune interactions predicts patient outcome in hepatocellular carcinoma. Hepatology 2024; 79:768-779. [PMID: 37725716 PMCID: PMC10948323 DOI: 10.1097/hep.0000000000000600] [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: 02/09/2023] [Accepted: 08/30/2023] [Indexed: 09/21/2023]
Abstract
BACKGROUND AND AIMS The fitness and viability of a tumor ecosystem are influenced by the spatial organization of its cells. We aimed to study the structure, architecture, and cell-cell dynamics of the heterogeneous liver cancer tumor microenvironment using spatially resolved multiplexed imaging. APPROACH AND RESULTS We performed co-detection by indexing multiplexed immunofluorescence imaging on 68 HCC biopsies from Thai patients [(Thailand Initiative in Genomics and Expression Research for Liver Cancer (TIGER-LC)] as a discovery cohort, and then validated the results in an additional 190 HCC biopsies from Chinese patients [Liver Cancer Institute (LCI)]. We segmented and annotated 117,270 and 465,632 cells from the TIGER-LC and LCI cohorts, respectively. We observed 4 patient groups of TIGER-LC (IC1, IC2, IC3, and IC4) with distinct tumor-immune cellular interaction patterns. In addition, patients from IC2 and IC4 had much better overall survival than those from IC1 and IC3. Noticeably, tumor and CD8 + T-cell interactions were strongly enriched in IC2, the group with the best patient outcomes. The close proximity between the tumor and CD8 + T cells was a strong predictor of patient outcome in both the TIGER-LC and the LCI cohorts. Bulk transcriptomic data from 51 of the 68 HCC cases were used to determine tumor-specific gene expression features of our classified subtypes. Moreover, we observed that the presence of immune spatial neighborhoods in HCC as a measure of overall immune infiltration is linked to better patient prognosis. CONCLUSIONS Highly multiplexed imaging analysis of liver cancer reveals tumor-immune cellular heterogeneity within spatial contexts, such as tumor and CD8 + T-cell interactions, which may predict patient survival.
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Affiliation(s)
- Evan Maestri
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland, USA
| | - Noemi Kedei
- Collaborative Protein Technology Resource, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland, USA
| | - Subreen Khatib
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland, USA
| | - Marshonna Forgues
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland, USA
| | - Kris Ylaya
- Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland, USA
| | - Stephen M. Hewitt
- Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland, USA
| | - Limin Wang
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland, USA
| | - Jittiporn Chaisaingmongkol
- Laboratory of Chemical Carcinogenesis, Chulabhorn Research Institute, Bangkok 10210, Thailand
- Center of Excellence on Environmental Health and Toxicology (EHT), OPS, MHESI, Thailand
| | - Mathuros Ruchirawat
- Laboratory of Chemical Carcinogenesis, Chulabhorn Research Institute, Bangkok 10210, Thailand
- Center of Excellence on Environmental Health and Toxicology (EHT), OPS, MHESI, Thailand
| | - Lichun Ma
- Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA
- Liver Cancer Program, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland, USA
| | - Xin Wei Wang
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland, USA
- Liver Cancer Program, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland, USA
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Deng Y, Chen P, Xiao J, Li M, Shen J, Qin S, Jia T, Li C, Chang A, Zhang W, Liu H, Xue R, Zhang N, Wang X, Huang L, Chen D. SCAR: Single-cell and Spatially-resolved Cancer Resources. Nucleic Acids Res 2024; 52:D1407-D1417. [PMID: 37739405 PMCID: PMC10767865 DOI: 10.1093/nar/gkad753] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Revised: 08/16/2023] [Accepted: 09/05/2023] [Indexed: 09/24/2023] Open
Abstract
Advances in sequencing and imaging technologies offer a unique opportunity to unravel cell heterogeneity and develop new immunotherapy strategies for cancer research. There is an urgent need for a resource that effectively integrates a vast amount of transcriptomic profiling data to comprehensively explore cancer tissue heterogeneity and the tumor microenvironment. In this context, we developed the Single-cell and Spatially-resolved Cancer Resources (SCAR) database, a combined tumor spatial and single-cell transcriptomic platform, which is freely accessible at http://8.142.154.29/SCAR2023 or http://scaratlas.com. SCAR contains spatial transcriptomic data from 21 tumor tissues and single-cell transcriptomic data from 11 301 352 cells encompassing 395 cancer subtypes and covering a wide variety of tissues, organoids, and cell lines. This resource offers diverse functional modules to address key cancer research questions at multiple levels, including the screening of tumor cell types, metabolic features, cell communication and gene expression patterns within the tumor microenvironment. Moreover, SCAR enables the analysis of biomarker expression patterns and cell developmental trajectories. SCAR also provides a comprehensive analysis of multi-dimensional datasets based on 34 state-of-the-art omics techniques, serving as an essential tool for in-depth mining and understanding of cell heterogeneity and spatial location. The implications of this resource extend to both cancer biology research and cancer immunotherapy development.
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Affiliation(s)
- Yushan Deng
- State Key Laboratory of Common Mechanism Research for Major Diseases, Suzhou Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Suzhou 215123, China
| | - Peixin Chen
- State Key Laboratory of Common Mechanism Research for Major Diseases, Suzhou Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Suzhou 215123, China
- Cam-Su Genomic Resource Center, Medical College of Soochow University, Suzhou 215123, China
| | - Jiedan Xiao
- State Key Laboratory of Common Mechanism Research for Major Diseases, Suzhou Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Suzhou 215123, China
| | - Mengrou Li
- State Key Laboratory of Common Mechanism Research for Major Diseases, Suzhou Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Suzhou 215123, China
- Institutes of Biology and Medical Sciences (IBMS), Soochow University, Suzhou 215123, China
| | - Jiayi Shen
- State Key Laboratory of Common Mechanism Research for Major Diseases, Suzhou Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Suzhou 215123, China
- Peninsula Cancer Research Center, School of Basic Medical Sciences, Binzhou Medical University, Yantai 264003, China
| | - Siying Qin
- State Key Laboratory of Common Mechanism Research for Major Diseases, Suzhou Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Suzhou 215123, China
| | - Tengfei Jia
- State Key Laboratory of Common Mechanism Research for Major Diseases, Suzhou Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Suzhou 215123, China
- Institutes of Biology and Medical Sciences (IBMS), Soochow University, Suzhou 215123, China
| | - Changxiao Li
- State Key Laboratory of Common Mechanism Research for Major Diseases, Suzhou Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Suzhou 215123, China
| | - Ashley Chang
- State Key Laboratory of Common Mechanism Research for Major Diseases, Suzhou Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Suzhou 215123, China
| | - Wensheng Zhang
- Cam-Su Genomic Resource Center, Medical College of Soochow University, Suzhou 215123, China
- Peninsula Cancer Research Center, School of Basic Medical Sciences, Binzhou Medical University, Yantai 264003, China
| | - Hebin Liu
- Institutes of Biology and Medical Sciences (IBMS), Soochow University, Suzhou 215123, China
| | - Ruidong Xue
- Peking University-Yunnan Baiyao International Medical Research Center, Peking University Health Science Center & Translational Cancer Research Center, Peking University First Hospital, Beijing 100191, China
| | - Ning Zhang
- Peking University-Yunnan Baiyao International Medical Research Center, Peking University Health Science Center & Translational Cancer Research Center, Peking University First Hospital, Beijing 100191, China
| | - Xiangdong Wang
- Zhongshan Hospital, Department of Pulmonary and Critical Care Medicine, Institute for Clinical Science, Shanghai Institute of Clinical Bioinformatics, Shanghai 200000, China
| | - Li Huang
- The Future Laboratory, Tsinghua University, Beijing 100084, China
| | - Dongsheng Chen
- State Key Laboratory of Common Mechanism Research for Major Diseases, Suzhou Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Suzhou 215123, China
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Liu Y, Tang Y, Jiang H, Zhang X, Chen X, Guo J, Jin C, Wu M. Exosome-Related FTCD Facilitates M1 Macrophage Polarization and Impacts the Prognosis of Hepatocellular Carcinoma. Biomolecules 2023; 14:41. [PMID: 38254641 PMCID: PMC10813691 DOI: 10.3390/biom14010041] [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: 11/21/2023] [Revised: 12/21/2023] [Accepted: 12/25/2023] [Indexed: 01/24/2024] Open
Abstract
BACKGROUND Exosomes are essential for hepatocellular carcinoma (HCC) progression and have garnered significant interest as novel targets for diagnostic, prognostic, and therapeutic approaches. This study aims to identify potential exosome-related biomarkers for the development of useful strategies for HCC diagnosis and therapy. METHODS Three datasets obtained from the Gene Expression Omnibus (GEO) were utilized to identify differentially expressed genes (DEGs) in HCC. Through Gene Ontology (GO) analysis and protein-protein interaction (PPI) network, overall survival (OS) analysis, Cox analyses, and diethylnitrosamine (DEN)-induced HCC mouse model detection, exosome-related hub gene was screened out, followed by a prognostic value assessment and immune-correlates analysis based on the Cancer Genome Atlas (TCGA) dataset. The hub gene-containing exosomes derived from Hepa1-6 cells were isolated and characterized using differential ultracentrifugation, transmission electron microscopy scanning, and Western blot. Ultrasound-guided intrahepatic injection, cell co-culture, CCK-8, and flow cytometry were performed to investigate the effects of the hub gene on macrophage infiltration and polarization in HCC. RESULTS A total of 83 DEGs enriched in the extracellular exosome term, among which, FTCD, HRA, and C8B showed the strongest association with the progression of HCC. FTCD was independently associated with a protective effect in HCC and selected as the hub gene. The presence of FTCD in exosomes was confirmed. FTCD-stimulated macrophages were polarized towards the M1 type and suppressed HCC cells proliferation. CONCLUSIONS FTCD is a potential exosome-related biomarker for HCC diagnosis, prognosis, and treatment. The crosstalk between FTCD-containing exosomes and macrophages in HCC progression deserves further investigation.
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Affiliation(s)
- Youyi Liu
- Wuxi School of Medicine, Jiangnan University, Wuxi 214122, China; (Y.L.); (Y.T.); (H.J.); (X.C.); (J.G.)
| | - Yifei Tang
- Wuxi School of Medicine, Jiangnan University, Wuxi 214122, China; (Y.L.); (Y.T.); (H.J.); (X.C.); (J.G.)
| | - Hongliang Jiang
- Wuxi School of Medicine, Jiangnan University, Wuxi 214122, China; (Y.L.); (Y.T.); (H.J.); (X.C.); (J.G.)
| | - Xiading Zhang
- Wuxi Higher Health Vocational Technology School, Wuxi 214000, China;
| | - Xingyi Chen
- Wuxi School of Medicine, Jiangnan University, Wuxi 214122, China; (Y.L.); (Y.T.); (H.J.); (X.C.); (J.G.)
| | - Jingrou Guo
- Wuxi School of Medicine, Jiangnan University, Wuxi 214122, China; (Y.L.); (Y.T.); (H.J.); (X.C.); (J.G.)
| | - Cheng Jin
- Department of Hepatobiliary Surgery, Affiliated Hospital of Jiangnan University, Jiangnan University, Wuxi 214041, China
| | - Minchen Wu
- Wuxi School of Medicine, Jiangnan University, Wuxi 214122, China; (Y.L.); (Y.T.); (H.J.); (X.C.); (J.G.)
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Qi W, Zhang Q. Insights on epithelial cells at the single-cell level in hepatocellular carcinoma prognosis and response to chemotherapy. Front Pharmacol 2023; 14:1292831. [PMID: 38044951 PMCID: PMC10690771 DOI: 10.3389/fphar.2023.1292831] [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: 09/12/2023] [Accepted: 11/06/2023] [Indexed: 12/05/2023] Open
Abstract
Background: Hepatocellular carcinoma (HCC) originates from Epithelial cells, and epithelial lineage plasticity has become a promising research direction for advancing HCC treatment. This study aims to focus on Epithelial cells to provide target insights for detecting HCC prognosis and response to drug therapy. Methods: Single-cell RNA sequencing (scRNA-seq) data from GSE149614 were clustered using Seurat, and the differentiation and evolution of epithelial cells were analyzed by Monocle 2. Scissor+ and Scissor- Epithelial cells associated with the prognostic phenotypes of bulk RNA-seq of HCC were screened using the Scissor algorithm for differential analysis to screen candidate genes. Candidate genes were overlapped with prognostic related genes screened by univariate Cox regression, and the Least Absolute Shrinkage and Selection Operator (LASSO) sparse penalty was imposed on the intersection genes to construct a risk assessment system. Results: Eight major cell subpopulations of HCC were identified, among which the proportion of epithelial cells in non-tumor liver tissues and HCC tissues was significantly different, and its proportion increased with advanced clinical stage. During the progression of HCC, the whole direction of epithelial cells differentiation trajectory was towards enhanced cell proliferation. Differential analysis between Scissor+ and Scissor- epithelial cells screened 1,265 upregulated and 191 downregulated prognostic candidate genes. Wherein, the upregulated genes were enriched in Cell processes, Genetic information processing, Metabolism and Human disease with Infection. Nevertheless, immune system related pathways took the main proportions in downregulated genes enriched pathways. There were 17 common genes between upregulated candidate genes and prognostic risk genes, of which CDC20, G6PD and PLOD2 were selected as components for constructing the risk assessment system. Risk score showed a significant correlation with tumor stage, epithelial-mesenchymal transition (EMT) related pathways and 22 therapeutic drugs, and was an independent prognostic factor for HCC. Conclusion: This study revealed the cellular composition of HCC, the differentiation evolution and functional landscape of epithelial cells in the further deterioration of HCC, and established a 3-gene risk model, which was closely related to clinical features, EMT, and drug sensitivity prediction. These findings provided insights in patient prognosis and drug therapy detection for HCC.
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Affiliation(s)
| | - Qian Zhang
- Department of digestive, China-Japan Union Hospital of Jilin University, Changchun, China
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Abstract
The human liver is a complex organ made up of multiple specialized cell types that carry out key physiological functions. An incomplete understanding of liver biology limits our ability to develop therapeutics to prevent chronic liver diseases, liver cancers, and death as a result of organ failure. Recently, single-cell modalities have expanded our understanding of the cellular phenotypic heterogeneity and intercellular cross-talk in liver health and disease. This review summarizes these findings and looks forward to highlighting new avenues for the application of single-cell genomics to unravel unknown pathogenic pathways and disease mechanisms for the development of new therapeutics targeting liver pathology. As these technologies mature, their integration into clinical data analysis will aid in patient stratification and in developing treatment plans for patients suffering from liver disease.
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Affiliation(s)
- Jawairia Atif
- Ajmera Transplant Centre, Schwartz Reisman Liver Research Centre, Toronto General Research Institute, University Health Network, Toronto, Ontario, Canada
- Department of Immunology, University of Toronto, Medical Sciences Building, Toronto, Ontario, Canada
| | - Cornelia Thoeni
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada
| | - Gary D. Bader
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
- The Donnelly Centre, University of Toronto, Toronto, Ontario, Canada
| | - Ian D. McGilvray
- Ajmera Transplant Centre, Schwartz Reisman Liver Research Centre, Toronto General Research Institute, University Health Network, Toronto, Ontario, Canada
| | - Sonya A. MacParland
- Ajmera Transplant Centre, Schwartz Reisman Liver Research Centre, Toronto General Research Institute, University Health Network, Toronto, Ontario, Canada
- Department of Immunology, University of Toronto, Medical Sciences Building, Toronto, Ontario, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada
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Chen X, Lin L, Chen G, Yan H, Li Z, Xiao M, He X, Zhang F, Zhang Y. High Levels of DEAH-Box Helicases Relate to Poor Prognosis and Reduction of DHX9 Improves Radiosensitivity of Hepatocellular Carcinoma. Front Oncol 2022; 12:900671. [PMID: 35814441 PMCID: PMC9256992 DOI: 10.3389/fonc.2022.900671] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2022] [Accepted: 05/17/2022] [Indexed: 11/13/2022] Open
Abstract
BackgroundLiver hepatocellular carcinoma (LIHC), one of the most common primary malignancies, exhibits high levels of molecular and clinical heterogeneity. Increasing evidence has confirmed the important roles of some RNA helicase families in tumor development, but the function of the DEAH-box RNA helicase family in LIHC therapeutic strategies has not yet been clarified.MethodsThe LIHC dataset was downloaded from The Cancer Genome Atlas (TCGA). Consensus clustering was applied to group the patients. Least absolute shrinkage and selection operator Cox regression and univariate and multivariate Cox regression were used to develop and validate a prognostic risk model. The Tumor Immune Estimation Resource and Tumor Immune Single Cell Hub databases were used to explore the role of DEAH-box RNA helicases in LIHC immunotherapy. In vitro experiments were performed to investigate the role of DHX9 in LIHC radiosensitivity.ResultsTwelve survival-related DEAH-box RNA helicases were identified. High helicase expression levels were associated with a poor prognosis and clinical features. A prognostic model comprising six DEAH-box RNA helicases (DHX8, DHX9, DHX34, DHX35, DHX38, and DHX57) was constructed. The risk score of this model was found to be an independent prognostic indicator, and LIHC patients with different prognosis were distinguished by the model in the training and test cohorts. DNA damage repair pathways were also enriched in patients with high-risk scores. The six DEAH-box RNA helicases in the risk model were substantially related to innate immune cell infiltration and immune inhibitors. In vitro experiments showed that DHX9 knockdown improved radiosensitivity by increasing DNA damage.ConclusionThe DEAH-box RNA helicase signature can be used as a reliable prognostic biomarker for LIHC. In addition, DHX9 may be a definitive indicator and therapeutic target in radiotherapy and immunotherapy for LIHC.
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Affiliation(s)
- Xi Chen
- Department of Minimally Invasive Interventional Therapy, Sun Yat-sen University Cancer Center, Guangzhou, China
- State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center (SYSUCC), Guangzhou, China
- Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China
| | - Letao Lin
- Department of Minimally Invasive Interventional Therapy, Sun Yat-sen University Cancer Center, Guangzhou, China
- State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center (SYSUCC), Guangzhou, China
- Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China
| | - Guanyu Chen
- Department of Minimally Invasive Interventional Therapy, Sun Yat-sen University Cancer Center, Guangzhou, China
- State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center (SYSUCC), Guangzhou, China
- Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China
| | - Huzheng Yan
- Department of Interventional Radiology, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Zhenyu Li
- State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center (SYSUCC), Guangzhou, China
- Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China
| | - Meigui Xiao
- Department of Minimally Invasive Interventional Therapy, Sun Yat-sen University Cancer Center, Guangzhou, China
- State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center (SYSUCC), Guangzhou, China
- Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China
| | - Xu He
- Interventional Medical Center, Zhuhai People’s Hospital, Zhuhai, China
| | - Fujun Zhang
- Department of Minimally Invasive Interventional Therapy, Sun Yat-sen University Cancer Center, Guangzhou, China
- State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center (SYSUCC), Guangzhou, China
- Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China
- *Correspondence: Fujun Zhang, ; Yanling Zhang,
| | - Yanling Zhang
- Department of Minimally Invasive Interventional Therapy, Sun Yat-sen University Cancer Center, Guangzhou, China
- State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center (SYSUCC), Guangzhou, China
- Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China
- School of Laboratory Medicine and Biotechnology, Southern Medical University, Guangzhou, China
- *Correspondence: Fujun Zhang, ; Yanling Zhang,
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