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Wang J, Zhou R, Zhong L, Chen Y, Wu X, Huang L, Tian Y, Mo W, Wang S, Liu Y. High-dimensional immune profiling using mass cytometry reveals IL-17A-producing γδ T cells as biomarkers in patients with T-cell-activated idiopathic severe aplastic anemia. Int Immunopharmacol 2023; 125:111163. [PMID: 37976596 DOI: 10.1016/j.intimp.2023.111163] [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: 09/04/2023] [Revised: 10/19/2023] [Accepted: 10/31/2023] [Indexed: 11/19/2023]
Abstract
Severe aplastic anemia (SAA) is a bone marrow failure syndrome characterized by activated T cells. Features of T-cell activation in the pathophysiology of SAA remain unknown. To understand T cell activation states, we investigated the atlas of peripheral immune cells and the secreted cytokine network with single cell mass cytometry analysis. We found decreased γδ T-cell frequencies in all patients with SAA, together with a significantly increased proportion of interleukin (IL)-17A-producing cell subsets. Cytokine network analysis of immune cells showed significant positive relationship between IL and 17A production from immune cells and disease severity of severe aplastic anemia. On separating SAA into two distinct subgroups based on T-cell activation stage, the proportion of γδ T cells tended to decrease in the T-cell-activated SAA group compared with non-T-cell-activated group. And the proportion of IL-17A-producing γδ T cells (γδT17) within γδ T cells was newly found to be significantly higher in the T-cell-activated SAA group, implying that IL-17A production by γδ T cells was associated with T-cell activation. Overall, our study revealed a role of γδT17 cells in mediating autoreactive T-cell activation in SAA and provided a novel diagnostic indicator for monitoring autoreactive T-cell activation status during the progression of aplastic anemia in the clinic.
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Affiliation(s)
- Jianwei Wang
- Department of Hematology, Guangzhou First People's Hospital, the Second Affiliated Hospital of South China University of Technology, Guangzhou, Guangdong 510180, China; Center for Medical Research on Innovation and Translation, Guangzhou First People's Hospital, the Second Affiliated Hospital of South China University of Technology, Guangzhou, Guangdong 510005, China
| | - Ruiqing Zhou
- Department of Hematology, Guangzhou First People's Hospital, the Second Affiliated Hospital of South China University of Technology, Guangzhou, Guangdong 510180, China
| | - Limei Zhong
- Department of Laboratory Medicine, Guangdong Second Provincial General Hospital, Guangzhou, Guangdong 510317, China
| | - Yinchun Chen
- Department of Hematology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong 510006, China
| | - Xiaojun Wu
- Department of Hematology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong 510006, China
| | - Liping Huang
- Department of Obstetrics and Gynecology, Southern Medical University Nanfang Hospital, Guangzhou, Guangdong 510515, China
| | - Yan Tian
- Department of Anesthesiology, Jiangxi Provincial Children's Hospital, Nanchang, Jiangxi 330000, China
| | - Wenjian Mo
- Department of Hematology, Guangzhou First People's Hospital, the Second Affiliated Hospital of South China University of Technology, Guangzhou, Guangdong 510180, China
| | - Shunqing Wang
- Department of Hematology, Guangzhou First People's Hospital, the Second Affiliated Hospital of South China University of Technology, Guangzhou, Guangdong 510180, China
| | - Yufeng Liu
- Department of Hematology, Guangzhou First People's Hospital, the Second Affiliated Hospital of South China University of Technology, Guangzhou, Guangdong 510180, China; Center for Medical Research on Innovation and Translation, Guangzhou First People's Hospital, the Second Affiliated Hospital of South China University of Technology, Guangzhou, Guangdong 510005, China.
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Zhao J, Ma L, Zheng M, Su L, Guo X. Meta-analysis of the results of haploidentical transplantation in the treatment of aplastic anemia. Ann Hematol 2023; 102:2565-2587. [PMID: 37442821 DOI: 10.1007/s00277-023-05339-7] [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: 12/01/2022] [Accepted: 06/24/2023] [Indexed: 07/15/2023]
Abstract
This meta-analysis was to evaluate the outcome of haploidentical hematopoietic stem cell transplantation (Haplo-HSCT) for aplastic anemia (AA) compared with matched related donor (MRD)-HSCT, matched unrelated donor (MUD)-HSCT, and immunosuppressive therapy (IST). Pubmed, Embase, Cochrane Library, Web of Science, CNKI, WanFang, and VIP databases were searched for relevant studies from inception to 22 June 2022. Relative risk (RR) was used to indicate the effect indicator, with a 95% confidence interval (CI) being applied to express the effect size. A subgroup analysis based on the literature quality (low, fair, and high) was applied. Totally, 25 studies were included in this study, comprising 2252 patients. Our findings demonstrated no difference between Haplo-HSCT and MRD-HSCT in 1-, 2-, and 3-year overall survival (OS), failure-free survival (FFS), and engraftment. However, Haplo-HSCT had higher incidences of II-IV acute graft-versus-host disease (aGVHD), chronic GVHD (cGVHD), and cytomegalovirus infection. There were no differences in 3- and 5-year OS, 3-year FFS, platelet engraftment, graft failure (GF), II-IV grade of aGVHD, and complication between Haplo-HSCT and MUD-HSCT; however, Haplo-HSCT had a lower incidence of cGVHD. Compared with IST, Haplo-HSCT had a higher 3-year FFS and 3- and 6-month response rate. However, there were no differences in 3- and 5-year OS, and 12-month response rate between Haplo-HSCT and IST. This study suggests that Haplo-HSCT may be a realistic therapeutic option for AA, which may provide a reference for decision-making.
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Affiliation(s)
- Jin Zhao
- Department of Hematology, Shanxi Province Cancer Hospital/Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, 3 Zhigongxinjie Street, Taiyuan, 030013, People's Republic of China
| | - Li Ma
- Department of Hematology, Shanxi Province Cancer Hospital/Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, 3 Zhigongxinjie Street, Taiyuan, 030013, People's Republic of China
| | - Meijing Zheng
- Department of Hematology, Shanxi Province Cancer Hospital/Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, 3 Zhigongxinjie Street, Taiyuan, 030013, People's Republic of China
| | - Liping Su
- Department of Hematology, Shanxi Province Cancer Hospital/Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, 3 Zhigongxinjie Street, Taiyuan, 030013, People's Republic of China.
| | - Xiaojing Guo
- Department of Hematology, Shanxi Province Cancer Hospital/Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, 3 Zhigongxinjie Street, Taiyuan, 030013, People's Republic of China.
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Zhang N, Zhang H, Liu Z, Dai Z, Wu W, Zhou R, Li S, Wang Z, Liang X, Wen J, Zhang X, Zhang B, Ouyang S, Zhang J, Luo P, Li X, Cheng Q. An artificial intelligence network-guided signature for predicting outcome and immunotherapy response in lung adenocarcinoma patients based on 26 machine learning algorithms. Cell Prolif 2023; 56:e13409. [PMID: 36822595 PMCID: PMC10068958 DOI: 10.1111/cpr.13409] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Revised: 12/27/2022] [Accepted: 01/12/2023] [Indexed: 02/25/2023] Open
Abstract
The immune cells play an increasingly vital role in influencing the proliferation, progression, and metastasis of lung adenocarcinoma (LUAD) cells. However, the potential of immune cells' specific genes-based model remains largely unknown. In the current study, by analysing single-cell RNA sequencing (scRNA-seq) data and bulk RNA sequencing data, the tumour-infiltrating immune cell (TIIC) associated signature was developed based on a total of 26 machine learning (ML) algorithms. As a result, the TIIC signature score could predict survival outcomes of LUAD patients across five independent datasets. The TIIC signature score showed superior performance to 168 previously established signatures in LUAD. Moreover, the TIIC signature score developed by the immunofluorescence staining of the tissue array of LUAD patients showed a prognostic value. Our research revealed a solid connection between TIIC signature score and tumour immunity as well as metabolism. Additionally, it has been discovered that the TIIC signature score can forecast genomic change, chemotherapeutic drug susceptibility, and-most significantly-immunotherapeutic response. As a newly demonstrated biomarker, the TIIC signature score facilitated the selection of the LUAD population who would benefit from future clinical stratification.
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Affiliation(s)
- Nan Zhang
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China.,College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Hao Zhang
- Department of Neurosurgery, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China
| | - Zaoqu Liu
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Ziyu Dai
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Wantao Wu
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China.,Department of Oncology, Xiangya Hospital, Central South University, Changsha, China
| | - Ran Zhou
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Shuyu Li
- Department of Thyroid and Breast Surgery, Tongji Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, China
| | - Zeyu Wang
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Xisong Liang
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Jie Wen
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Xun Zhang
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Bo Zhang
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Sirui Ouyang
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Jian Zhang
- Department of Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Peng Luo
- Department of Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Xizhe Li
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China.,Department of Thoracic Surgery, Xiangya Hospital, Central South University, Changsha, China.,Hunan Engineering Research Center for Pulmonary Nodules Precise Diagnosis & Treatment, Changsha, China
| | - Quan Cheng
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
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Sun Y, Zhang Y, Yu H, Wang H, Shao Z, Liu C. Cofilin-1 participates in the hyperfunction of myeloid dendritic cells in patients with severe aplastic anaemia. J Cell Mol Med 2022; 26:3460-3470. [PMID: 35579089 PMCID: PMC9189344 DOI: 10.1111/jcmm.17359] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2021] [Revised: 04/16/2022] [Accepted: 04/26/2022] [Indexed: 11/28/2022] Open
Abstract
Cofilin‐1 interacts with actin to regulate cell movement. The importance of cofilin‐1 in immunity has been established, and its involvement in a number of autoimmune diseases has been confirmed. However, its role in severe aplastic anaemia (SAA) remains elusive. Thus, the aim of the current study was to investigate the role of cofilin‐1 in patients with SAA. Flow cytometry, Western blotting and real‐time quantitative reverse transcription‐polymerase chain reaction were performed to detect the mRNA and protein expression of cofilin‐1 in myeloid dendritic cells (mDCs) from patients with SAA. The expression of cofilin‐1 was then suppressed via siRNA, and its effects on mDCs and downstream effector T‐cell function were evaluated. Cofilin‐1 expression was higher in mDCs from patients with SAA and correlated with routine blood and immune indexes. Moreover, cofilin‐1 knockdown in mDCs from patients with SAA reduced their phagocytic capacity, migration capacity, and CD86 expression through F‐actin remodelling, downregulating the stimulatory capacity of mDCs on CD4+ and CD8+ T lymphocytes. Collectively, these findings indicate that cofilin‐1 participates in the hyperfunction of mDCs in patients with SAA and that the downregulation of cofilin‐1 in mDCs from patients with SAA could be a novel treatment approach for SAA.
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Affiliation(s)
- Yingying Sun
- Department of Hematology, Tianjin Medical University General Hospital, Tianjin, China
| | - Yu Zhang
- Department of Hematology, Tianjin Medical University General Hospital, Tianjin, China
| | - Hong Yu
- Department of Hematology, Tianjin Medical University General Hospital, Tianjin, China
| | - Huaquan Wang
- Department of Hematology, Tianjin Medical University General Hospital, Tianjin, China
| | - Zonghong Shao
- Department of Hematology, Tianjin Medical University General Hospital, Tianjin, China
| | - Chunyan Liu
- Department of Hematology, Tianjin Medical University General Hospital, Tianjin, China
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