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Xie H, Guo W, Jiang H, Zhang T, Zhao L, Hu J, Gao S, Song S, Xu J, Xu L, Sun X, Ding Y, Jiang L, Ding X. Photosensitive Hydrogel with Temperature-Controlled Reversible Nano-Apertures for Single-Cell Protein Analysis. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2308569. [PMID: 38483955 PMCID: PMC11109651 DOI: 10.1002/advs.202308569] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Revised: 02/15/2024] [Indexed: 05/23/2024]
Abstract
Single cell western blot (scWB) is one of the most important methods for cellular heterogeneity profiling. However, current scWB based on conventional photoactive polyacrylamide hydrogel material suffers from the tradeoff between in-gel probing and separation resolution. Here, a highly sensitive temperature-controlled single-cell western blotting (tc-scWB) method is introduced, which is based on a thermo/photo-dualistic-sensitive polyacrylamide hydrogel, namely acrylic acid-functionalized graphene oxide (AFGO) assisted, N-isopropylacrylamide modified polyacrylamide (ANP) hydrogel. The ANP hydrogel is contracted at high-temperature to constrain protein band diffusion during microchip electrophoretic separation, while the gel aperture is expanded under low-temperature for better antibody penetration into the hydrogel. The tc-scWB method enables the separation and profiling of small-molecule-weight proteins with highly crosslinked gel (12% T) in SDS-PAGE. The tc-scWB is demonstrated on three metabolic and ER stress-specific proteins (CHOP, MDH2 and FH) in four pancreatic cell subtypes, revealing the expression of key enzymes in the Krebs cycle is upregulated with enhanced ER stress. It is found that ER stress can regulate crucial enzyme (MDH2 and FH) activities of metabolic cascade in cancer cells, boosting aerobic respiration to attenuate the Warburg effect and promote cell apoptosis. The tc-scWB is a general toolbox for the analysis of low-abundance small-molecular functional proteins at the single-cell level.
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Affiliation(s)
- Haiyang Xie
- Department of Anesthesiology and Surgical Intensive Care UnitXinhua HospitalSchool of Medicine and School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200092China
- State Key Laboratory of Oncogenes and Related GenesInstitute for Personalized MedicineSchool of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200030China
| | - Wenke Guo
- Department of Anesthesiology and Surgical Intensive Care UnitXinhua HospitalSchool of Medicine and School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200092China
- State Key Laboratory of Oncogenes and Related GenesInstitute for Personalized MedicineSchool of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200030China
| | - Hui Jiang
- Department of Anesthesiology and Surgical Intensive Care UnitXinhua HospitalSchool of Medicine and School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200092China
- State Key Laboratory of Oncogenes and Related GenesInstitute for Personalized MedicineSchool of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200030China
| | - Ting Zhang
- Department of Anesthesiology and Surgical Intensive Care UnitXinhua HospitalSchool of Medicine and School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200092China
- State Key Laboratory of Oncogenes and Related GenesInstitute for Personalized MedicineSchool of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200030China
| | - Lei Zhao
- Department of Anesthesiology and Surgical Intensive Care UnitXinhua HospitalSchool of Medicine and School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200092China
- State Key Laboratory of Oncogenes and Related GenesInstitute for Personalized MedicineSchool of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200030China
| | - Jinjuan Hu
- Department of Anesthesiology and Surgical Intensive Care UnitXinhua HospitalSchool of Medicine and School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200092China
- State Key Laboratory of Oncogenes and Related GenesInstitute for Personalized MedicineSchool of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200030China
| | - Shuxin Gao
- Department of Anesthesiology and Surgical Intensive Care UnitXinhua HospitalSchool of Medicine and School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200092China
- State Key Laboratory of Oncogenes and Related GenesInstitute for Personalized MedicineSchool of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200030China
| | - Sunfengda Song
- Department of Anesthesiology and Surgical Intensive Care UnitXinhua HospitalSchool of Medicine and School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200092China
- State Key Laboratory of Oncogenes and Related GenesInstitute for Personalized MedicineSchool of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200030China
| | - Jiasu Xu
- Department of Anesthesiology and Surgical Intensive Care UnitXinhua HospitalSchool of Medicine and School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200092China
- State Key Laboratory of Oncogenes and Related GenesInstitute for Personalized MedicineSchool of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200030China
| | - Li Xu
- Department of Anesthesiology and Surgical Intensive Care UnitXinhua HospitalSchool of Medicine and School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200092China
- State Key Laboratory of Oncogenes and Related GenesInstitute for Personalized MedicineSchool of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200030China
| | - Xinyi Sun
- Department of Anesthesiology and Surgical Intensive Care UnitXinhua HospitalSchool of Medicine and School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200092China
- State Key Laboratory of Oncogenes and Related GenesInstitute for Personalized MedicineSchool of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200030China
| | - Yi Ding
- Department of Anesthesiology and Surgical Intensive Care UnitXinhua HospitalSchool of Medicine and School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200092China
- State Key Laboratory of Oncogenes and Related GenesInstitute for Personalized MedicineSchool of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200030China
| | - Lai Jiang
- Department of Anesthesiology and Surgical Intensive Care UnitXinhua HospitalSchool of Medicine and School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200092China
- State Key Laboratory of Oncogenes and Related GenesInstitute for Personalized MedicineSchool of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200030China
| | - Xianting Ding
- Department of Anesthesiology and Surgical Intensive Care UnitXinhua HospitalSchool of Medicine and School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200092China
- State Key Laboratory of Oncogenes and Related GenesInstitute for Personalized MedicineSchool of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200030China
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2
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Balog JÁ, Zvara Á, Bukovinszki V, Puskás LG, Balog A, Szebeni GJ. Comparative single-cell multiplex immunophenotyping of therapy-naive patients with rheumatoid arthritis, systemic sclerosis, and systemic lupus erythematosus shed light on disease-specific composition of the peripheral immune system. Front Immunol 2024; 15:1376933. [PMID: 38726007 PMCID: PMC11079270 DOI: 10.3389/fimmu.2024.1376933] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2024] [Accepted: 04/03/2024] [Indexed: 05/12/2024] Open
Abstract
Introduction Systemic autoimmune diseases (SADs) are a significant burden on the healthcare system. Understanding the complexity of the peripheral immunophenotype in SADs may facilitate the differential diagnosis and identification of potential therapeutic targets. Methods Single-cell mass cytometric immunophenotyping was performed on peripheral blood mononuclear cells (PBMCs) from healthy controls (HCs) and therapy-naive patients with rheumatoid arthritis (RA), progressive systemic sclerosis (SSc), and systemic lupus erythematosus (SLE). Immunophenotyping was performed on 15,387,165 CD45+ live single cells from 52 participants (13 cases/group), using an antibody panel to detect 34 markers. Results Using the t-SNE (t-distributed stochastic neighbor embedding) algorithm, the following 17 main immune cell types were determined: CD4+/CD57- T cells, CD4+/CD57+ T cells, CD8+/CD161- T cells, CD8+/CD161+/CD28+ T cells, CD8dim T cells, CD3+/CD4-/CD8- T cells, TCRγ/δ T cells, CD4+ NKT cells, CD8+ NKT cells, classic NK cells, CD56dim/CD98dim cells, B cells, plasmablasts, monocytes, CD11cdim/CD172dim cells, myeloid dendritic cells (mDCs), and plasmacytoid dendritic cells (pDCs). Seven of the 17 main cell types exhibited statistically significant frequencies in the investigated groups. The expression levels of the 34 markers in the main populations were compared between HCs and SADs. In summary, 59 scatter plots showed significant differences in the expression intensities between at least two groups. Next, each immune cell population was divided into subpopulations (metaclusters) using the FlowSOM (self-organizing map) algorithm. Finally, 121 metaclusters (MCs) of the 10 main immune cell populations were found to have significant differences to classify diseases. The single-cell T-cell heterogeneity represented 64MCs based on the expression of 34 markers, and the frequency of 23 MCs differed significantly between at least twoconditions. The CD3- non-T-cell compartment contained 57 MCs with 17 MCs differentiating at least two investigated groups. In summary, we are the first to demonstrate the complexity of the immunophenotype of 34 markers over 15 million single cells in HCs vs. therapy-naive patients with RA, SSc, and SLE. Disease specific population frequencies or expression patterns of peripheral immune cells provide a single-cell data resource to the scientific community.
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Affiliation(s)
- József Á. Balog
- Laboratory of Functional Genomics, Institute of Genetics, HUN-REN Biological Research Centre, Szeged, Hungary
- Core Facility, HUN-REN Biological Research Centre, Szeged, Hungary
| | - Ágnes Zvara
- Laboratory of Functional Genomics, Institute of Genetics, HUN-REN Biological Research Centre, Szeged, Hungary
- Core Facility, HUN-REN Biological Research Centre, Szeged, Hungary
| | - Vivien Bukovinszki
- Department of Rheumatology and Immunology, Faculty of Medicine, Albert Szent-Gyorgyi Health Centre, University of Szeged, Szeged, Hungary
| | - László G. Puskás
- Laboratory of Functional Genomics, Institute of Genetics, HUN-REN Biological Research Centre, Szeged, Hungary
- Core Facility, HUN-REN Biological Research Centre, Szeged, Hungary
| | - Attila Balog
- Department of Rheumatology and Immunology, Faculty of Medicine, Albert Szent-Gyorgyi Health Centre, University of Szeged, Szeged, Hungary
| | - Gábor J. Szebeni
- Laboratory of Functional Genomics, Institute of Genetics, HUN-REN Biological Research Centre, Szeged, Hungary
- Core Facility, HUN-REN Biological Research Centre, Szeged, Hungary
- Department of Internal Medicine, Hematology Centre, Faculty of Medicine University of Szeged, Szeged, Hungary
- Astridbio Technologies Ltd., Szeged, Hungary
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3
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Shao W, Yao Y, Yang L, Li X, Ge T, Zheng Y, Zhu Q, Ge S, Gu X, Jia R, Song X, Zhuang A. Novel insights into TCR-T cell therapy in solid neoplasms: optimizing adoptive immunotherapy. Exp Hematol Oncol 2024; 13:37. [PMID: 38570883 PMCID: PMC10988985 DOI: 10.1186/s40164-024-00504-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Accepted: 03/21/2024] [Indexed: 04/05/2024] Open
Abstract
Adoptive immunotherapy in the T cell landscape exhibits efficacy in cancer treatment. Over the past few decades, genetically modified T cells, particularly chimeric antigen receptor T cells, have enabled remarkable strides in the treatment of hematological malignancies. Besides, extensive exploration of multiple antigens for the treatment of solid tumors has led to clinical interest in the potential of T cells expressing the engineered T cell receptor (TCR). TCR-T cells possess the capacity to recognize intracellular antigen families and maintain the intrinsic properties of TCRs in terms of affinity to target epitopes and signal transduction. Recent research has provided critical insight into their capability and therapeutic targets for multiple refractory solid tumors, but also exposes some challenges for durable efficacy. In this review, we describe the screening and identification of available tumor antigens, and the acquisition and optimization of TCRs for TCR-T cell therapy. Furthermore, we summarize the complete flow from laboratory to clinical applications of TCR-T cells. Last, we emerge future prospects for improving therapeutic efficacy in cancer world with combination therapies or TCR-T derived products. In conclusion, this review depicts our current understanding of TCR-T cell therapy in solid neoplasms, and provides new perspectives for expanding its clinical applications and improving therapeutic efficacy.
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Affiliation(s)
- Weihuan Shao
- Department of Ophthalmology, Ninth People's Hospital, Shanghai JiaoTong University School of Medicine, 639 Zhi Zao Ju Road, Shanghai Ninth People's Hospital, Shanghai, 200011, People's Republic of China
- Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, Shanghai, 200011, People's Republic of China
| | - Yiran Yao
- Department of Ophthalmology, Ninth People's Hospital, Shanghai JiaoTong University School of Medicine, 639 Zhi Zao Ju Road, Shanghai Ninth People's Hospital, Shanghai, 200011, People's Republic of China
- Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, Shanghai, 200011, People's Republic of China
| | - Ludi Yang
- Department of Ophthalmology, Ninth People's Hospital, Shanghai JiaoTong University School of Medicine, 639 Zhi Zao Ju Road, Shanghai Ninth People's Hospital, Shanghai, 200011, People's Republic of China
- Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, Shanghai, 200011, People's Republic of China
| | - Xiaoran Li
- Department of Ophthalmology, Ninth People's Hospital, Shanghai JiaoTong University School of Medicine, 639 Zhi Zao Ju Road, Shanghai Ninth People's Hospital, Shanghai, 200011, People's Republic of China
- Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, Shanghai, 200011, People's Republic of China
| | - Tongxin Ge
- Department of Ophthalmology, Ninth People's Hospital, Shanghai JiaoTong University School of Medicine, 639 Zhi Zao Ju Road, Shanghai Ninth People's Hospital, Shanghai, 200011, People's Republic of China
- Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, Shanghai, 200011, People's Republic of China
| | - Yue Zheng
- Department of Ophthalmology, Ninth People's Hospital, Shanghai JiaoTong University School of Medicine, 639 Zhi Zao Ju Road, Shanghai Ninth People's Hospital, Shanghai, 200011, People's Republic of China
- Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, Shanghai, 200011, People's Republic of China
| | - Qiuyi Zhu
- Department of Ophthalmology, Ninth People's Hospital, Shanghai JiaoTong University School of Medicine, 639 Zhi Zao Ju Road, Shanghai Ninth People's Hospital, Shanghai, 200011, People's Republic of China
- Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, Shanghai, 200011, People's Republic of China
| | - Shengfang Ge
- Department of Ophthalmology, Ninth People's Hospital, Shanghai JiaoTong University School of Medicine, 639 Zhi Zao Ju Road, Shanghai Ninth People's Hospital, Shanghai, 200011, People's Republic of China
- Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, Shanghai, 200011, People's Republic of China
| | - Xiang Gu
- Department of Ophthalmology, Ninth People's Hospital, Shanghai JiaoTong University School of Medicine, 639 Zhi Zao Ju Road, Shanghai Ninth People's Hospital, Shanghai, 200011, People's Republic of China
- Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, Shanghai, 200011, People's Republic of China
| | - Renbing Jia
- Department of Ophthalmology, Ninth People's Hospital, Shanghai JiaoTong University School of Medicine, 639 Zhi Zao Ju Road, Shanghai Ninth People's Hospital, Shanghai, 200011, People's Republic of China.
- Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, Shanghai, 200011, People's Republic of China.
| | - Xin Song
- Department of Ophthalmology, Ninth People's Hospital, Shanghai JiaoTong University School of Medicine, 639 Zhi Zao Ju Road, Shanghai Ninth People's Hospital, Shanghai, 200011, People's Republic of China.
- Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, Shanghai, 200011, People's Republic of China.
| | - Ai Zhuang
- Department of Ophthalmology, Ninth People's Hospital, Shanghai JiaoTong University School of Medicine, 639 Zhi Zao Ju Road, Shanghai Ninth People's Hospital, Shanghai, 200011, People's Republic of China.
- Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, Shanghai, 200011, People's Republic of China.
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4
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Huang L, Li H, Zhang C, Chen Q, Liu Z, Zhang J, Luo P, Wei T. Unlocking the potential of T-cell metabolism reprogramming: Advancing single-cell approaches for precision immunotherapy in tumour immunity. Clin Transl Med 2024; 14:e1620. [PMID: 38468489 PMCID: PMC10928360 DOI: 10.1002/ctm2.1620] [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: 11/22/2023] [Revised: 02/20/2024] [Accepted: 02/22/2024] [Indexed: 03/13/2024] Open
Abstract
As single-cell RNA sequencing enables the detailed clustering of T-cell subpopulations and facilitates the analysis of T-cell metabolic states and metabolite dynamics, it has gained prominence as the preferred tool for understanding heterogeneous cellular metabolism. Furthermore, the synergistic or inhibitory effects of various metabolic pathways within T cells in the tumour microenvironment are coordinated, and increased activity of specific metabolic pathways generally corresponds to increased functional activity, leading to diverse T-cell behaviours related to the effects of tumour immune cells, which shows the potential of tumour-specific T cells to induce persistent immune responses. A holistic understanding of how metabolic heterogeneity governs the immune function of specific T-cell subsets is key to obtaining field-level insights into immunometabolism. Therefore, exploring the mechanisms underlying the interplay between T-cell metabolism and immune functions will pave the way for precise immunotherapy approaches in the future, which will empower us to explore new methods for combating tumours with enhanced efficacy.
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Affiliation(s)
- Lihaoyun Huang
- Department of OncologyZhujiang HospitalSouthern Medical UniversityGuangzhouChina
- The First Clinical Medical SchoolSouthern Medical UniversityGuangzhouChina
| | - Haitao Li
- Department of OncologyTaishan People's HospitalGuangzhouChina
| | - Cangang Zhang
- Department of Pathogenic Microbiology and ImmunologySchool of Basic Medical SciencesXi'an Jiaotong UniversityXi'anShaanxiChina
| | - Quan Chen
- Department of NeurosurgeryXiangya HospitalCentral South UniversityChangshaHunanChina
| | - Zaoqu Liu
- Key Laboratory of ProteomicsBeijing Proteome Research CenterNational Center for Protein Sciences (Beijing)Beijing Institute of LifeomicsBeijingChina
- Key Laboratory of Medical Molecular BiologyChinese Academy of Medical SciencesDepartment of PathophysiologyPeking Union Medical CollegeInstitute of Basic Medical SciencesBeijingChina
| | - Jian Zhang
- Department of OncologyZhujiang HospitalSouthern Medical UniversityGuangzhouChina
- The First Clinical Medical SchoolSouthern Medical UniversityGuangzhouChina
| | - Peng Luo
- Department of OncologyZhujiang HospitalSouthern Medical UniversityGuangzhouChina
- The First Clinical Medical SchoolSouthern Medical UniversityGuangzhouChina
| | - Ting Wei
- Department of OncologyZhujiang HospitalSouthern Medical UniversityGuangzhouChina
- The First Clinical Medical SchoolSouthern Medical UniversityGuangzhouChina
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5
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Na S, Choo Y, Yoon TH, Paek E. CyGate Provides a Robust Solution for Automatic Gating of Single Cell Cytometry Data. Anal Chem 2023; 95:16918-16926. [PMID: 37946317 PMCID: PMC10666088 DOI: 10.1021/acs.analchem.3c03006] [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: 07/10/2023] [Revised: 10/12/2023] [Accepted: 10/23/2023] [Indexed: 11/12/2023]
Abstract
To gain a better understanding of the complex human immune system, it is necessary to measure and interpret numerous cellular protein expressions at the single cell level. Mass cytometry is a relatively new technology that offers unprecedented information about the protein expression of a single cell. Conversely, the analysis of high-dimensional and multiparametric mass cytometric data sets presents a new computational challenge. For instance, conventional "manual gating" analysis was inefficient and unreliable for multiparametric phenotyping of the heterogeneous immune cellular system; consequently, automated methods have been developed to address the high dimensionality of mass cytometry data and enhance the reproducibility of the analysis. Here, we present CyGate, a semiautomated method for classifying single cells into their respective cell types. CyGate learns a gating strategy from a reference data set, trains a model for cell classification, and then automatically analyzes additional data sets using the trained model. CyGate also supports the machine learning framework for the classification of "ungated" cells, which are typically disregarded by automated methods. CyGate's utility was demonstrated by its high performance in cell type classification and the lowest generalization error on various public data sets when compared to the state-of-the-art semiautomated methods. Notably, CyGate had the shortest execution time, allowing it to scale with a growing number of samples. CyGate is available at https://github.com/seungjinna/cygate.
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Affiliation(s)
- Seungjin Na
- Institute
for Artificial Intelligence Research, Hanyang
University, Seoul 04763, Republic
of Korea
- Department
of Computer Science, Hanyang University, Seoul 04763, Republic of Korea
| | - Yujin Choo
- Department
of Artificial Intelligence, Hanyang University, Seoul 04763, Republic of Korea
| | - Tae Hyun Yoon
- Department
of Chemistry, College of Natural Sciences, Hanyang University, Seoul 04763, Republic
of Korea
- Institute
of Next Generation Material Design, Hanyang
University, Seoul 04763, Republic of Korea
- Yoon
Idea
Lab Co., Ltd., Seoul 04763, Republic of Korea
| | - Eunok Paek
- Institute
for Artificial Intelligence Research, Hanyang
University, Seoul 04763, Republic
of Korea
- Department
of Computer Science, Hanyang University, Seoul 04763, Republic of Korea
- Department
of Artificial Intelligence, Hanyang University, Seoul 04763, Republic of Korea
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6
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Zhang Z, Duan Z, Cui Y. CD8 + T cells in brain injury and neurodegeneration. Front Cell Neurosci 2023; 17:1281763. [PMID: 38077952 PMCID: PMC10702747 DOI: 10.3389/fncel.2023.1281763] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Accepted: 10/30/2023] [Indexed: 02/19/2024] Open
Abstract
The interaction between the peripheral immune system and the brain is increasingly being recognized as an important layer of neuroimmune regulation and plays vital roles in brain homeostasis as well as neurological disorders. As an important population of T-cell lymphocytes, the roles of CD8+ T cells in infectious diseases and tumor immunity have been well established. Recently, increasing number of complex functions of CD8+ T cells in brain disorders have been revealed. However, an advanced summary and discussion of the functions and mechanisms of CD8+ T cells in brain injury and neurodegeneration are still lacking. Here, we described the differentiation and function of CD8+ T cells, reviewed the involvement of CD8+ T cells in the regulation of brain injury including stroke and traumatic brain injury and neurodegenerative diseases, such as Alzheimer's disease (AD) and Parkinson's disease (PD), and discussed therapeutic prospects and future study goals. Understanding these processes will promote the investigation of T-cell immunity in brain disorders and provide new intervention strategies for the treatment of brain injury and neurodegeneration.
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Affiliation(s)
- Zhaolong Zhang
- Department of Interventional Radiology, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, China
| | - Zhongying Duan
- Institute of Neuroregeneration and Neurorehabilitation, Qingdao University, Qingdao, Shandong, China
- Qingdao Medical College, Qingdao University, Qingdao, China
| | - Yu Cui
- Institute of Neuroregeneration and Neurorehabilitation, Qingdao University, Qingdao, Shandong, China
- Qingdao Medical College, Qingdao University, Qingdao, China
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7
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Wu C, Men X, Liu M, Wei Y, Wei X, Yu YL, Xu ZR, Chen ML, Wang JH. Two-Dimensional Multi-parameter Cytometry Platform for Single-Cell Analysis. Anal Chem 2023; 95:13297-13304. [PMID: 37610312 DOI: 10.1021/acs.analchem.3c02457] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/24/2023]
Abstract
A 2D flow cytometry platform, known as CytoLM Plus, was developed for multi-parameter single-cell analysis. Single particles or cells after hydrodynamic alignment in a microfluidic unit undergo first-dimension fluorescence and side scattering dual-channel optical detection. They were thereafter immediately directed to ICP-MS by connecting the microfluidic unit with a high-efficiency nebulizer to facilitate the second-dimension ICP-MS detection. Flow cytometry measurements of fluorescent microspheres evaluated the performance of CytoLM Plus for optical detection. 6434 fluorescence bursts were observed with a valid signal proportion as high as 99.7%. After signal unification and gating analysis, 6067 sets of single-particle signals were obtained with 6.6 and 6.2% deviations for fluorescence burst area and height, respectively. This is fairly comparable with that achieved by a commercial flow cytometer. Afterward, CytoLM Plus was evaluated by 2D flow cytometry measurement of Ag+-incubated and AO-stained MCF-7 cells. A program for 2D single-cell signal unification was developed based on the algorithm of screening in lag time window. In the present case, a lag time window of -4.2 ± 0.09 s was determined by cross-correlation analysis and two-parameter optimization, which efficiently unified the concurrent single-cell signals from fluorescence, side scattering, and ICP-MS. A total of 495 sets of concurrent 2D signals were screened out, and the statistical analysis of these single-cell signals ensured 2D multi-parameter single-cell analysis and data elucidation.
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Affiliation(s)
- Chengxin Wu
- Research Center for Analytical Sciences, Department of Chemistry, College of Sciences, Northeastern University, Shenyang 110819, China
| | - Xue Men
- School of Chemistry and Environment, Yunnan Minzu University, Kunming 650504, China
| | - Meijun Liu
- Research Center for Analytical Sciences, Department of Chemistry, College of Sciences, Northeastern University, Shenyang 110819, China
| | - Yujia Wei
- Research Center for Analytical Sciences, Department of Chemistry, College of Sciences, Northeastern University, Shenyang 110819, China
| | - Xing Wei
- Research Center for Analytical Sciences, Department of Chemistry, College of Sciences, Northeastern University, Shenyang 110819, China
| | - Yong-Liang Yu
- Research Center for Analytical Sciences, Department of Chemistry, College of Sciences, Northeastern University, Shenyang 110819, China
| | - Zhang-Run Xu
- Research Center for Analytical Sciences, Department of Chemistry, College of Sciences, Northeastern University, Shenyang 110819, China
| | - Ming-Li Chen
- Research Center for Analytical Sciences, Department of Chemistry, College of Sciences, Northeastern University, Shenyang 110819, China
| | - Jian-Hua Wang
- Research Center for Analytical Sciences, Department of Chemistry, College of Sciences, Northeastern University, Shenyang 110819, China
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8
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Lin Y, Cao Y, Willie E, Patrick E, Yang JYH. Atlas-scale single-cell multi-sample multi-condition data integration using scMerge2. Nat Commun 2023; 14:4272. [PMID: 37460600 DOI: 10.1038/s41467-023-39923-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Accepted: 07/04/2023] [Indexed: 07/20/2023] Open
Abstract
The recent emergence of multi-sample multi-condition single-cell multi-cohort studies allows researchers to investigate different cell states. The effective integration of multiple large-cohort studies promises biological insights into cells under different conditions that individual studies cannot provide. Here, we present scMerge2, a scalable algorithm that allows data integration of atlas-scale multi-sample multi-condition single-cell studies. We have generalized scMerge2 to enable the merging of millions of cells from single-cell studies generated by various single-cell technologies. Using a large COVID-19 data collection with over five million cells from 1000+ individuals, we demonstrate that scMerge2 enables multi-sample multi-condition scRNA-seq data integration from multiple cohorts and reveals signatures derived from cell-type expression that are more accurate in discriminating disease progression. Further, we demonstrate that scMerge2 can remove dataset variability in CyTOF, imaging mass cytometry and CITE-seq experiments, demonstrating its applicability to a broad spectrum of single-cell profiling technologies.
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Affiliation(s)
- Yingxin Lin
- Sydney Precision Data Science Centre, The University of Sydney, Sydney, NSW, Australia
- Charles Perkins Centre, The University of Sydney, Sydney, NSW, Australia
- School of Mathematics and Statistics, The University of Sydney, Sydney, NSW, Australia
- Laboratory of Data Discovery for Health Limited (D24H), Science Park, Hong Kong SAR, China
| | - Yue Cao
- Sydney Precision Data Science Centre, The University of Sydney, Sydney, NSW, Australia
- Charles Perkins Centre, The University of Sydney, Sydney, NSW, Australia
- School of Mathematics and Statistics, The University of Sydney, Sydney, NSW, Australia
- Laboratory of Data Discovery for Health Limited (D24H), Science Park, Hong Kong SAR, China
| | - Elijah Willie
- Sydney Precision Data Science Centre, The University of Sydney, Sydney, NSW, Australia
| | - Ellis Patrick
- Sydney Precision Data Science Centre, The University of Sydney, Sydney, NSW, Australia
- School of Mathematics and Statistics, The University of Sydney, Sydney, NSW, Australia
- Laboratory of Data Discovery for Health Limited (D24H), Science Park, Hong Kong SAR, China
- The Westmead Institute for Medical Research, The University of Sydney, Sydney, NSW, 2006, Australia
| | - Jean Y H Yang
- Sydney Precision Data Science Centre, The University of Sydney, Sydney, NSW, Australia.
- Charles Perkins Centre, The University of Sydney, Sydney, NSW, Australia.
- School of Mathematics and Statistics, The University of Sydney, Sydney, NSW, Australia.
- Laboratory of Data Discovery for Health Limited (D24H), Science Park, Hong Kong SAR, China.
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9
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Kim CH, Kim HJ, Park JE, Lee YH, Choi SH, Seo H, Yoo SS, Lee SY, Cha SI, Park JY, Lee J. CyTOF analysis for differential immune cellular profiling between latent tuberculosis infection and active tuberculosis. Tuberculosis (Edinb) 2023; 140:102344. [PMID: 37084568 DOI: 10.1016/j.tube.2023.102344] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Revised: 04/08/2023] [Accepted: 04/13/2023] [Indexed: 04/23/2023]
Abstract
Limited data exist about the comparative immune cell population profile determined by cytometry by time-of-flight (CyTOF) analysis between active tuberculosis (TB) and latent TB infection (LTBI). In this study, we performed CyTOF analysis using peripheral blood mononuclear cells (PBMCs) to compare the differential immune cellular profile between active TB and LTBI. A total of 51 subjects (active TB [n = 34] and LTBI [n = 17]) were included. CyTOF analysis of 16 subjects (active TB [n = 8] and LTBI [n = 8]) identified a significantly higher Th17-like cell population in active TB than in LTBI. This finding was validated in the remaining 35 subjects (active TB [n = 26] and LTBI [n = 9]) using flow cytometry analysis, which consistently reveals a higher percentage of Th17 cell population in active TB (p = 0.032). The Th1/Th17 ratio represented good ability to discriminate between active TB and LTBI (AUC = 0.812). Among patients with active TB, the Th17 cell percentage was found to be lower in more advanced forms of the disease. Additionally, Th17 cell percentage positively correlated with the levels of IL-6 and neutrophil-lymphocyte ratio, respectively. In conclusion, CyTOF analysis of PBMCs showed a significantly higher percentage of Th17 cells in active TB although fairly similar immune cell populations between active TB and LTBI were observed.
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Affiliation(s)
- Chang Ho Kim
- Department of Internal Medicine, Kyungpook National University, School of Medicine, Daegu, Republic of Korea
| | - Ha-Jeong Kim
- Department of Physiology, Cell and Matrix Research Institute, BK21 Plus KNU Biomedical Convergence Program, Tumor Heterogeneity and Network (THEN) Research Center, Kyungpook National University, School of Medicine, Daegu, Republic of Korea
| | - Ji Eun Park
- Department of Internal Medicine, Kyungpook National University, School of Medicine, Daegu, Republic of Korea
| | - Yong Hoon Lee
- Department of Internal Medicine, Kyungpook National University, School of Medicine, Daegu, Republic of Korea
| | - Sun Ha Choi
- Department of Internal Medicine, Kyungpook National University, School of Medicine, Daegu, Republic of Korea
| | - Hyewon Seo
- Department of Internal Medicine, Kyungpook National University, School of Medicine, Daegu, Republic of Korea
| | - Seung Soo Yoo
- Department of Internal Medicine, Kyungpook National University, School of Medicine, Daegu, Republic of Korea
| | - Shin Yup Lee
- Department of Internal Medicine, Kyungpook National University, School of Medicine, Daegu, Republic of Korea
| | - Seung Ick Cha
- Department of Internal Medicine, Kyungpook National University, School of Medicine, Daegu, Republic of Korea
| | - Jae Yong Park
- Department of Internal Medicine, Kyungpook National University, School of Medicine, Daegu, Republic of Korea
| | - Jaehee Lee
- Department of Internal Medicine, Kyungpook National University, School of Medicine, Daegu, Republic of Korea.
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10
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de Jong E, Kocer A. Current Methods for Identifying Plasma Membrane Proteins as Cancer Biomarkers. MEMBRANES 2023; 13:409. [PMID: 37103836 PMCID: PMC10142483 DOI: 10.3390/membranes13040409] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Revised: 03/31/2023] [Accepted: 04/01/2023] [Indexed: 06/19/2023]
Abstract
Plasma membrane proteins are a special class of biomolecules present on the cellular membrane. They provide the transport of ions, small molecules, and water in response to internal and external signals, define a cell's immunological identity, and facilitate intra- and intercellular communication. Since they are vital to almost all cellular functions, their mutants, or aberrant expression is linked to many diseases, including cancer, where they are a part of cancer cell-specific molecular signatures and phenotypes. In addition, their surface-exposed domains make them exciting biomarkers for targeting by imaging agents and drugs. This review looks at the challenges in identifying cancer-related cell membrane proteins and the current methodologies that solve most of the challenges. We classified the methodologies as biased, i.e., search cells for the presence of already known membrane proteins. Second, we discuss the unbiased methods that can identify proteins without prior knowledge of what they are. Finally, we discuss the potential impact of membrane proteins on the early detection and treatment of cancer.
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11
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Arnett LP, Rana R, Chung WWY, Li X, Abtahi M, Majonis D, Bassan J, Nitz M, Winnik MA. Reagents for Mass Cytometry. Chem Rev 2023; 123:1166-1205. [PMID: 36696538 DOI: 10.1021/acs.chemrev.2c00350] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
Mass cytometry (cytometry by time-of-flight detection [CyTOF]) is a bioanalytical technique that enables the identification and quantification of diverse features of cellular systems with single-cell resolution. In suspension mass cytometry, cells are stained with stable heavy-atom isotope-tagged reagents, and then the cells are nebulized into an inductively coupled plasma time-of-flight mass spectrometry (ICP-TOF-MS) instrument. In imaging mass cytometry, a pulsed laser is used to ablate ca. 1 μm2 spots of a tissue section. The plume is then transferred to the CyTOF, generating an image of biomarker expression. Similar measurements are possible with multiplexed ion bean imaging (MIBI). The unit mass resolution of the ICP-TOF-MS detector allows for multiparametric analysis of (in principle) up to 130 different parameters. Currently available reagents, however, allow simultaneous measurement of up to 50 biomarkers. As new reagents are developed, the scope of information that can be obtained by mass cytometry continues to increase, particularly due to the development of new small molecule reagents which enable monitoring of active biochemistry at the cellular level. This review summarizes the history and current state of mass cytometry reagent development and elaborates on areas where there is a need for new reagents. Additionally, this review provides guidelines on how new reagents should be tested and how the data should be presented to make them most meaningful to the mass cytometry user community.
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Affiliation(s)
- Loryn P Arnett
- Department of Chemistry, University of Toronto, 80 St. George Street, Toronto, OntarioM5S 3H6, Canada
| | - Rahul Rana
- Department of Chemistry, University of Toronto, 80 St. George Street, Toronto, OntarioM5S 3H6, Canada
| | - Wilson Wai-Yip Chung
- Department of Chemistry, University of Toronto, 80 St. George Street, Toronto, OntarioM5S 3H6, Canada
| | - Xiaochong Li
- Department of Chemistry, University of Toronto, 80 St. George Street, Toronto, OntarioM5S 3H6, Canada
| | - Mahtab Abtahi
- Department of Chemistry, University of Toronto, 80 St. George Street, Toronto, OntarioM5S 3H6, Canada
| | - Daniel Majonis
- Standard BioTools Canada Inc. (formerly Fluidigm Canada Inc.), 1380 Rodick Road, Suite 400, Markham, OntarioL3R 4G5, Canada
| | - Jay Bassan
- Department of Chemistry, University of Toronto, 80 St. George Street, Toronto, OntarioM5S 3H6, Canada
| | - Mark Nitz
- Department of Chemistry, University of Toronto, 80 St. George Street, Toronto, OntarioM5S 3H6, Canada
| | - Mitchell A Winnik
- Department of Chemistry, University of Toronto, 80 St. George Street, Toronto, OntarioM5S 3H6, Canada.,Department of Chemical Engineering and Applied Chemistry, 200 College Street, Toronto, OntarioM5S 3E5, Canada
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12
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Li H, Li J, Wang M, Feng W, Gao F, Han Y, Shi Y, Du Z, Yuan Q, Cao P, Wang X, Gao X, Cao K, Gao L. Clusterbody Enables Flow Sorting-Assisted Single-Cell Mass Spectrometry Analysis for Identifying Reversal Agent of Chemoresistance. Anal Chem 2023; 95:560-564. [PMID: 36563048 DOI: 10.1021/acs.analchem.2c04070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Identifying effective reversal agents overcoming multidrug resistance with causal mechanisms from an efflux pump protein is of vital importance for enhanced tumor chemotherapy in clinic. To achieve this end, we construct a metal cluster-based probe, named clusterbody, to develop flow sorting-assisted single-cell mass spectrometry analysis. This clusterbody synthesized by biomimetic mineralization possesses an antibody-like property to selectively recognize an efflux pump protein. The intrinsic red fluorescence emission of the clusterbody facilitates fluorescence-activated high-throughput cell sorting of subpopulations with different multidrug resistance levels. Furthermore, based on the accurate formula of the clusterbody, the corresponding protein abundance at the single-cell level is determined through detecting gold content via precise signal amplification by laser ablation inductively coupled plasma mass spectrometry. Therefore, the effect of reversal agent treatment overcoming multidrug resistance is evaluated in a quantitative manner. This work opens a new avenue to identify reversal agents, shedding light on developing combined or synergetic tumor therapy.
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Affiliation(s)
- Han Li
- Department of Chemistry, Faculty of Environment and Life Science, Center of Excellence for Environmental Safety and Biological Effects, Beijing University of Technology, Beijing 100124, China
| | - Jiaojiao Li
- Department of Chemistry, Faculty of Environment and Life Science, Center of Excellence for Environmental Safety and Biological Effects, Beijing University of Technology, Beijing 100124, China
| | - Meng Wang
- CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - Weiyue Feng
- CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - Fuping Gao
- CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - Ying Han
- Department of Chemistry, Faculty of Environment and Life Science, Center of Excellence for Environmental Safety and Biological Effects, Beijing University of Technology, Beijing 100124, China
| | - Yijie Shi
- Department of Chemistry, Faculty of Environment and Life Science, Center of Excellence for Environmental Safety and Biological Effects, Beijing University of Technology, Beijing 100124, China
| | - Zhongying Du
- Department of Chemistry, Faculty of Environment and Life Science, Center of Excellence for Environmental Safety and Biological Effects, Beijing University of Technology, Beijing 100124, China
| | - Qing Yuan
- Department of Chemistry, Faculty of Environment and Life Science, Center of Excellence for Environmental Safety and Biological Effects, Beijing University of Technology, Beijing 100124, China
| | - Peng Cao
- Department of Chemistry, Faculty of Environment and Life Science, Center of Excellence for Environmental Safety and Biological Effects, Beijing University of Technology, Beijing 100124, China
| | - Xiayan Wang
- Department of Chemistry, Faculty of Environment and Life Science, Center of Excellence for Environmental Safety and Biological Effects, Beijing University of Technology, Beijing 100124, China
| | - Xueyun Gao
- Department of Chemistry, Faculty of Environment and Life Science, Center of Excellence for Environmental Safety and Biological Effects, Beijing University of Technology, Beijing 100124, China
| | - Kai Cao
- Department of Chemistry, Faculty of Environment and Life Science, Center of Excellence for Environmental Safety and Biological Effects, Beijing University of Technology, Beijing 100124, China
| | - Liang Gao
- Department of Chemistry, Faculty of Environment and Life Science, Center of Excellence for Environmental Safety and Biological Effects, Beijing University of Technology, Beijing 100124, China
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13
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Lin W, Liu S, Huang Z, Li H, Lu T, Luo Y, Zhong J, Xu Z, Liu Y, Li Y, Li P, Xu Q, Cai J, Li H, Chen XL. Mass cytometry and single-cell RNA sequencing reveal immune cell characteristics of active and inactive phases of Crohn's disease. Front Med (Lausanne) 2023; 9:1064106. [PMID: 36714133 PMCID: PMC9878392 DOI: 10.3389/fmed.2022.1064106] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Accepted: 12/14/2022] [Indexed: 01/13/2023] Open
Abstract
Objectives For Crohn's disease (CD), the alternation of the active phase and inactive phase may be related to humoral immunity and cellular immunity. This study aims to understand the characteristics of immune cells in patients with active CD (CDa) and inactive CD (CDin). Methods Mass cytometry (CyTOF) and single-cell RNA sequencing (scRNA-seq) data about CDa, CDin, and healthy control (HC) were included. CyTOF analysis was performed to capture gated subsets, including T cells, T regulatory (Treg) cells, B cells, innate immune cells, and natural killer (NK) cells. Differential analysis was used to identify different immune cell subsets among CDa, CDin, and HC. ScRNA-seq analysis was used to verify the results of CyTOF. CD-related signaling pathways were obtained using KEGG pathway enrichment analysis. CellChat analysis was used to infer the cell communication network among immune cell subsets. Results Compared to patients with CDin, patients with CDa had higher abundances of CD16+CD38+CD4+CXCR3+CCR6+ naive T cells, HLA-DR+CD38+IFNγ+TNF+ effector memory (EM) T cells, HLA-DR+IFNγ+ naive B cells, and CD14++CD11C+IFNγ+IL1B+ monocytes. KEGG analysis showed the similarity of pathway enrichment for the earlier four subsets, such as thermogenesis, oxidative phosphorylation, and metabolic pathways. The patients with CDin were characterized by an increased number of CD16+CD56dimCD44+HLA-DR+IL22+ NK cells. Compared to HC, patients with CDa demonstrated a low abundance of HLA-DR+CCR6+ NK cells and a high abundance of FOXP3+CD44+ EM Tregs. CellChat analysis revealed the interaction network of cell subsets amplifying in CDa compared with CDin. Conclusion Some immune subsets cells were identified for CDa and CDin. These cells may be related to the occurrence and development of CD and may provide assistance in disease diagnosis and treatment.
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Affiliation(s)
- Wenjia Lin
- School of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Shiying Liu
- School of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Zhuojian Huang
- School of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Haiwen Li
- Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, China
| | - Tianyu Lu
- School of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Yongxin Luo
- School of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Jiamin Zhong
- School of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Zewen Xu
- School of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Yu Liu
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Yanwu Li
- Science and Technology Innovation Center, Guangzhou University of Chinese Medicine, Guangzhou, China,Pi-Wei Institute, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Peiwu Li
- The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Qian Xu
- School of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Jiazhong Cai
- Science and Technology Innovation Center, Guangzhou University of Chinese Medicine, Guangzhou, China,Pi-Wei Institute, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Huibiao Li
- The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Xin-lin Chen
- School of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, China,*Correspondence: Xin-lin Chen,
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14
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Deckers J, Anbergen T, Hokke AM, de Dreu A, Schrijver DP, de Bruin K, Toner YC, Beldman TJ, Spangler JB, de Greef TFA, Grisoni F, van der Meel R, Joosten LAB, Merkx M, Netea MG, Mulder WJM. Engineering cytokine therapeutics. NATURE REVIEWS BIOENGINEERING 2023; 1:286-303. [PMID: 37064653 PMCID: PMC9933837 DOI: 10.1038/s44222-023-00030-y] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/18/2023]
Abstract
Cytokines have pivotal roles in immunity, making them attractive as therapeutics for a variety of immune-related disorders. However, the widespread clinical use of cytokines has been limited by their short blood half-lives and severe side effects caused by low specificity and unfavourable biodistribution. Innovations in bioengineering have aided in advancing our knowledge of cytokine biology and yielded new technologies for cytokine engineering. In this Review, we discuss how the development of bioanalytical methods, such as sequencing and high-resolution imaging combined with genetic techniques, have facilitated a better understanding of cytokine biology. We then present an overview of therapeutics arising from cytokine re-engineering, targeting and delivery, mRNA therapeutics and cell therapy. We also highlight the application of these strategies to adjust the immunological imbalance in different immune-mediated disorders, including cancer, infection and autoimmune diseases. Finally, we look ahead to the hurdles that must be overcome before cytokine therapeutics can live up to their full potential.
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Affiliation(s)
- Jeroen Deckers
- Department of Internal Medicine and Radboud Center for Infectious diseases (RCI), Radboud University Medical Centre, Nijmegen, Netherlands
| | - Tom Anbergen
- Department of Internal Medicine and Radboud Center for Infectious diseases (RCI), Radboud University Medical Centre, Nijmegen, Netherlands
| | - Ayla M. Hokke
- Laboratory of Chemical Biology, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands
| | - Anne de Dreu
- Laboratory of Chemical Biology, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands
| | - David P. Schrijver
- Laboratory of Chemical Biology, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands
| | - Koen de Bruin
- Laboratory of Chemical Biology, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands
| | - Yohana C. Toner
- Department of Internal Medicine and Radboud Center for Infectious diseases (RCI), Radboud University Medical Centre, Nijmegen, Netherlands
| | - Thijs J. Beldman
- Department of Internal Medicine and Radboud Center for Infectious diseases (RCI), Radboud University Medical Centre, Nijmegen, Netherlands
| | - Jamie B. Spangler
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD USA
- Department of Chemical and Biomolecular Engineering, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD USA
- Translational Tissue Engineering Center, Johns Hopkins University School of Medicine, Baltimore, MD USA
| | - Tom F. A. de Greef
- Laboratory of Chemical Biology, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands
- Department of Biomedical Engineering, Institute for Complex Molecular Systems, Eindhoven University of Technology, Eindhoven, Netherlands
- Institute for Molecules and Materials, Radboud University, Nijmegen, The Netherlands
- Centre for Living Technologies, Alliance Eindhoven University of Technology, Wageningen University & Research, Utrecht University and University Medical Center Utrecht (EWUU), Utrecht, Netherlands
| | - Francesca Grisoni
- Department of Biomedical Engineering, Institute for Complex Molecular Systems, Eindhoven University of Technology, Eindhoven, Netherlands
- Centre for Living Technologies, Alliance Eindhoven University of Technology, Wageningen University & Research, Utrecht University and University Medical Center Utrecht (EWUU), Utrecht, Netherlands
| | - Roy van der Meel
- Laboratory of Chemical Biology, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands
- Present Address: Department of Biomedical Engineering, Institute for Complex Molecular Systems, Eindhoven University of Technology, Eindhoven, Netherlands
| | - Leo A. B. Joosten
- Department of Internal Medicine and Radboud Center for Infectious diseases (RCI), Radboud University Medical Centre, Nijmegen, Netherlands
- Radboud Institute for Molecular Life Sciences (RIMLS), Radboud University Medical Centre, Nijmegen, Netherlands
- Department of Medical Genetics, Iuliu Hațieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania
| | - Maarten Merkx
- Laboratory of Chemical Biology, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands
- Present Address: Department of Biomedical Engineering, Institute for Complex Molecular Systems, Eindhoven University of Technology, Eindhoven, Netherlands
| | - Mihai G. Netea
- Department of Internal Medicine and Radboud Center for Infectious diseases (RCI), Radboud University Medical Centre, Nijmegen, Netherlands
- Radboud Institute for Molecular Life Sciences (RIMLS), Radboud University Medical Centre, Nijmegen, Netherlands
- Department for Genomics and Immunoregulation, Life and Medical Sciences Institute (LIMES), University of Bonn, Bonn, Germany
| | - Willem J. M. Mulder
- Department of Internal Medicine and Radboud Center for Infectious diseases (RCI), Radboud University Medical Centre, Nijmegen, Netherlands
- Laboratory of Chemical Biology, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands
- Present Address: Department of Biomedical Engineering, Institute for Complex Molecular Systems, Eindhoven University of Technology, Eindhoven, Netherlands
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15
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Rocha-Hasler M, Müller L, Wagner A, Tu A, Stanek V, Campion NJ, Bartosik T, Zghaebi M, Stoshikj S, Gompelmann D, Zech A, Mei H, Kratochwill K, Spittler A, Idzko M, Schneider S, Eckl-Dorna J. Using mass cytometry for the analysis of samples of the human airways. Front Immunol 2022; 13:1004583. [PMID: 36578479 PMCID: PMC9791368 DOI: 10.3389/fimmu.2022.1004583] [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: 08/18/2022] [Accepted: 11/16/2022] [Indexed: 12/14/2022] Open
Abstract
Mass cytometry (MC) is a powerful method for mapping complex cellular systems at single-cell levels, based on the detection of cellular proteins. Numerous studies have been performed using human blood, but there is a lack of protocols describing the processing and labeling of bronchoalveolar lavage fluid (BALF) and nasal polyps (NP) for acquisition by MC. These specimens are essential in the investigation of immune cell characteristics in airway diseases such as asthma and chronic rhinosinusitis with NP (CRSwNP). Here we optimized a workflow for processing, labeling, and acquisition of BALF and NP cells by MC. Among three methods tested for NP digestion, combined enzymatic/mechanical processing yielded maximum cell recovery, viability and labeling patterns compared to the other methods. Treatment with DNAse improved sample acquisition by MC. In a final step, we performed a comparison of blood, BALF and NP cell composition using a 31-marker MC antibody panel, revealing expected differences between the different tissue but also heterogeneity among the BALF and NP samples. We here introduce an optimized workflow for the MC analysis of human NP and BALF, which enables comparative analysis of different samples in larger cohorts. A deeper understanding of immune cell characteristics in these samples may guide future researchers and clinicians to a better disease management.
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Affiliation(s)
- Marianne Rocha-Hasler
- Allergology and Sinusitis Research Lab, Department of Otorhinolaryngology, Medical University of Vienna, Vienna, Austria
| | - Lena Müller
- Core Facility Flow Cytometry & Department of Surgery, Research Lab, Medical University of Vienna, Vienna, Austria
| | - Anja Wagner
- Core Facility Proteomics, Medical University of Vienna, Vienna, Austria,Division of Pediatric Nephrology and Gastroenterology, Department of Pediatrics and Adolescent Medicine, Comprehensive Center for Pediatrics, Medical University of Vienna, Vienna, Austria
| | - Aldine Tu
- Allergology and Sinusitis Research Lab, Department of Otorhinolaryngology, Medical University of Vienna, Vienna, Austria
| | - Victoria Stanek
- Allergology and Sinusitis Research Lab, Department of Otorhinolaryngology, Medical University of Vienna, Vienna, Austria
| | - Nicholas James Campion
- Allergology and Sinusitis Research Lab, Department of Otorhinolaryngology, Medical University of Vienna, Vienna, Austria
| | - Tina Bartosik
- Allergology and Sinusitis Research Lab, Department of Otorhinolaryngology, Medical University of Vienna, Vienna, Austria
| | - Mohammed Zghaebi
- Allergology and Sinusitis Research Lab, Department of Otorhinolaryngology, Medical University of Vienna, Vienna, Austria
| | - Slagjana Stoshikj
- Division of Pulmonology, Department of Internal Medicine II, Medical University Vienna, Vienna, Austria
| | - Daniela Gompelmann
- Division of Pulmonology, Department of Internal Medicine II, Medical University Vienna, Vienna, Austria
| | - Andreas Zech
- Division of Pulmonology, Department of Internal Medicine II, Medical University Vienna, Vienna, Austria
| | - Henrik Mei
- German Rheumatism Research Center Berlin, Berlin, Germany
| | - Klaus Kratochwill
- Core Facility Proteomics, Medical University of Vienna, Vienna, Austria,Division of Pediatric Nephrology and Gastroenterology, Department of Pediatrics and Adolescent Medicine, Comprehensive Center for Pediatrics, Medical University of Vienna, Vienna, Austria
| | - Andreas Spittler
- Core Facility Flow Cytometry & Department of Surgery, Research Lab, Medical University of Vienna, Vienna, Austria
| | - Marco Idzko
- Division of Pulmonology, Department of Internal Medicine II, Medical University Vienna, Vienna, Austria
| | - Sven Schneider
- Allergology and Sinusitis Research Lab, Department of Otorhinolaryngology, Medical University of Vienna, Vienna, Austria,*Correspondence: Sven Schneider,
| | - Julia Eckl-Dorna
- Allergology and Sinusitis Research Lab, Department of Otorhinolaryngology, Medical University of Vienna, Vienna, Austria
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16
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Zeng L, Yang K, Zhang T, Zhu X, Hao W, Chen H, Ge J. Research progress of single-cell transcriptome sequencing in autoimmune diseases and autoinflammatory disease: A review. J Autoimmun 2022; 133:102919. [PMID: 36242821 DOI: 10.1016/j.jaut.2022.102919] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Revised: 09/16/2022] [Accepted: 09/19/2022] [Indexed: 12/07/2022]
Abstract
Autoimmunity refers to the phenomenon that the body's immune system produces antibodies or sensitized lymphocytes to its own tissues to cause an immune response. Immune disorders caused by autoimmunity can mediate autoimmune diseases. Autoimmune diseases have complicated pathogenesis due to the many types of cells involved, and the mechanism is still unclear. The emergence of single-cell research technology can solve the problem that ordinary transcriptome technology cannot be accurate to cell type. It provides unbiased results through independent analysis of cells in tissues and provides more mRNA information for identifying cell subpopulations, which provides a novel approach to study disruption of immune tolerance and disturbance of pro-inflammatory pathways on a cellular basis. It may fundamentally change the understanding of molecular pathways in the pathogenesis of autoimmune diseases and develop targeted drugs. Single-cell transcriptome sequencing (scRNA-seq) has been widely applied in autoimmune diseases, which provides a powerful tool for demonstrating the cellular heterogeneity of tissues involved in various immune inflammations, identifying pathogenic cell populations, and revealing the mechanism of disease occurrence and development. This review describes the principles of scRNA-seq, introduces common sequencing platforms and practical procedures, and focuses on the progress of scRNA-seq in 41 autoimmune diseases, which include 9 systemic autoimmune diseases and autoinflammatory diseases (rheumatoid arthritis, systemic lupus erythematosus, etc.) and 32 organ-specific autoimmune diseases (5 Skin diseases, 3 Nervous system diseases, 4 Eye diseases, 2 Respiratory system diseases, 2 Circulatory system diseases, 6 Liver, Gallbladder and Pancreas diseases, 2 Gastrointestinal system diseases, 3 Muscle, Bones and joint diseases, 3 Urinary system diseases, 2 Reproductive system diseases). This review also prospects the molecular mechanism targets of autoimmune diseases from the multi-molecular level and multi-dimensional analysis combined with single-cell multi-omics sequencing technology (such as scRNA-seq, Single cell ATAC-seq and single cell immune group library sequencing), which provides a reference for further exploring the pathogenesis and marker screening of autoimmune diseases and autoimmune inflammatory diseases in the future.
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Affiliation(s)
- Liuting Zeng
- Department of Rheumatology, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, National Clinical Research Center for Dermatologic and Immunologic Diseases, State Key Laboratory of Complex Severe and Rare Diseases, Beijing, China.
| | - Kailin Yang
- Key Laboratory of Hunan Province for Integrated Traditional Chinese and Western Medicine on Prevention and Treatment of Cardio-Cerebral Diseases, Hunan University of Chinese Medicine, Changsha, China.
| | - Tianqing Zhang
- Key Laboratory of Hunan Province for Integrated Traditional Chinese and Western Medicine on Prevention and Treatment of Cardio-Cerebral Diseases, Hunan University of Chinese Medicine, Changsha, China
| | - Xiaofei Zhu
- Key Laboratory of Hunan Province for Integrated Traditional Chinese and Western Medicine on Prevention and Treatment of Cardio-Cerebral Diseases, Hunan University of Chinese Medicine, Changsha, China.
| | - Wensa Hao
- Institute of Materia Medica, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Hua Chen
- Department of Rheumatology, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, National Clinical Research Center for Dermatologic and Immunologic Diseases, State Key Laboratory of Complex Severe and Rare Diseases, Beijing, China.
| | - Jinwen Ge
- Key Laboratory of Hunan Province for Integrated Traditional Chinese and Western Medicine on Prevention and Treatment of Cardio-Cerebral Diseases, Hunan University of Chinese Medicine, Changsha, China; Hunan Academy of Chinese Medicine, Changsha, China.
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Wang SSY, Chng WJ, Liu H, de Mel S. Tumor-Associated Macrophages and Related Myelomonocytic Cells in the Tumor Microenvironment of Multiple Myeloma. Cancers (Basel) 2022; 14:5654. [PMID: 36428745 PMCID: PMC9688291 DOI: 10.3390/cancers14225654] [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: 10/08/2022] [Revised: 11/05/2022] [Accepted: 11/11/2022] [Indexed: 11/19/2022] Open
Abstract
Multiple myeloma (MM) is the second-most common hematologic malignancy and remains incurable despite potent plasma cell directed therapeutics. The tumor microenvironment (TME) is a key player in the pathogenesis and progression of MM and is an active focus of research with a view to targeting immune dysregulation. Tumor-associated macrophages (TAM), myeloid derived suppressor cells (MDSC), and dendritic cells (DC) are known to drive progression and treatment resistance in many cancers. They have also been shown to promote MM progression and immune suppression in vitro, and there is growing evidence of their impact on clinical outcomes. The heterogeneity and functional characteristics of myelomonocytic cells in MM are being unraveled through high-dimensional immune profiling techniques. We are also beginning to understand how they may affect and be modulated by current and future MM therapeutics. In this review, we provide an overview of the biology and clinical relevance of TAMs, MDSCs, and DCs in the MM TME. We also highlight key areas to be addressed in future research as well as our perspectives on how the myelomonocytic compartment of the TME may influence therapeutic strategies of the future.
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Affiliation(s)
- Samuel S. Y. Wang
- Department of Rheumatology, Allergy and Immunology, Tan Tock Seng Hospital, Singapore 308433, Singapore
| | - Wee Joo Chng
- Department of Haematology-Oncology, National University Cancer Institute Singapore, National University Health System, Singapore 119228, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Dr, Singapore 117597, Singapore
- Cancer Science Institute, National University of Singapore, 14 Medical Dr, #12-01 Centre for Translational Medicine, Singapore 117599, Singapore
| | - Haiyan Liu
- Immunology Programme, Life Sciences Institute, National University of Singapore, Singapore 117456, Singapore
- Immunology Translational Research Program, Department of Microbiology and Immunology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117456, Singapore
| | - Sanjay de Mel
- Department of Haematology-Oncology, National University Cancer Institute Singapore, National University Health System, Singapore 119228, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Dr, Singapore 117597, Singapore
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18
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Dastmalchi F, Xu K, Jones H, Lemas DJ. Assessment of human milk in the era of precision health. Curr Opin Clin Nutr Metab Care 2022; 25:292-297. [PMID: 35838294 PMCID: PMC9710510 DOI: 10.1097/mco.0000000000000860] [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] [Indexed: 11/25/2022]
Abstract
PURPOSE OF REVIEW Precision health provides an unprecedented opportunity to improve the assessment of infant nutrition and health outcomes. Breastfeeding is positively associated with infant health outcomes, yet only 58.3% of children born in 2017 were still breastfeeding at 6 months. There is an urgent need to examine the application of precision health tools that support the development of public health interventions focused on improving breastfeeding outcomes. RECENT FINDINGS In this review, we discussed the novel and highly sensitive techniques that can provide a vast amount of omics data and clinical information just by evaluating small volumes of milk samples, such as RNA sequencing, cytometry by time-of-flight, and human milk analyzer for clinical implementation. These advanced techniques can run multiple samples in a short period of time making them ideal for the routine clinical evaluation of milk samples. SUMMARY Precision health tools are increasingly used in clinical research studies focused on infant nutrition. The integration of routinely collected multiomics human milk data within the electronic health records has the potential to identify molecular biomarkers associated with infant health outcomes.
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Affiliation(s)
- Farhad Dastmalchi
- Department of Health Outcomes and Biomedical Informatics, University of Florida College of Medicine, Gainesville, FL, United States of America
| | - Ke Xu
- Department of Health Outcomes and Biomedical Informatics, University of Florida College of Medicine, Gainesville, FL, United States of America
| | - Helen Jones
- Department of Physiology and Functional Genomics, University of Florida, Gainesville, FL, United States of America
- Center for Research in Perinatal Outcomes, University of Florida, Gainesville, FL, United States of America
- Department of Obstetrics & Gynecology, University of Florida College of Medicine, Gainesville, Florida
| | - Dominick J Lemas
- Department of Health Outcomes and Biomedical Informatics, University of Florida College of Medicine, Gainesville, FL, United States of America
- Center for Research in Perinatal Outcomes, University of Florida, Gainesville, FL, United States of America
- Department of Obstetrics & Gynecology, University of Florida College of Medicine, Gainesville, Florida
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19
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2021 White Paper on Recent Issues in Bioanalysis: ISR for Biomarkers, Liquid Biopsies, Spectral Cytometry, Inhalation/Oral & Multispecific Biotherapeutics, Accuracy/LLOQ for Flow Cytometry ( Part 2 - Recommendations on Biomarkers/CDx Assays Development & Validation, Cytometry Validation & Innovation, Biotherapeutics PK LBA Regulated Bioanalysis, Critical Reagents & Positive Controls Generation). Bioanalysis 2022; 14:627-692. [PMID: 35578974 DOI: 10.4155/bio-2022-0080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
The 15th edition of the Workshop on Recent Issues in Bioanalysis (15th WRIB) was held on 27 September to 1 October 2021. Even with a last-minute move from in-person to virtual, an overwhelmingly high number of nearly 900 professionals representing pharma and biotech companies, contract research organizations (CROs), and multiple regulatory agencies still eagerly convened to actively discuss the most current topics of interest in bioanalysis. The 15th WRIB included three Main Workshops and seven Specialized Workshops that together spanned 1 week in order to allow exhaustive and thorough coverage of all major issues in bioanalysis, biomarkers, immunogenicity, gene therapy, cell therapy and vaccines. Moreover, in-depth workshops on biomarker assay development and validation (BAV) (focused on clarifying the confusion created by the increased use of the term "context of use" [COU]); mass spectrometry of proteins (therapeutic, biomarker and transgene); state-of-the-art cytometry innovation and validation; and critical reagent and positive control generation were the special features of the 15th edition. This 2021 White Paper encompasses recommendations emerging from the extensive discussions held during the workshop, and is aimed to provide the bioanalytical community with key information and practical solutions on topics and issues addressed, in an effort to enable advances in scientific excellence, improved quality and better regulatory compliance. Due to its length, the 2021 edition of this comprehensive White Paper has been divided into three parts for editorial reasons. This publication (Part 2) covers the recommendations on ISR for Biomarkers, Liquid Biopsies, Spectral Cytometry, Inhalation/Oral & Multispecific Biotherapeutics, Accuracy/LLOQ for Flow Cytometry. Part 1A (Endogenous Compounds, Small Molecules, Complex Methods, Regulated Mass Spec of Large Molecules, Small Molecule, PoC), Part 1B (Regulatory Agencies' Inputs on Bioanalysis, Biomarkers, Immunogenicity, Gene & Cell Therapy and Vaccine) and Part 3 (TAb/NAb, Viral Vector CDx, Shedding Assays; CRISPR/Cas9 & CAR-T Immunogenicity; PCR & Vaccine Assay Performance; ADA Assay Comparability & Cut Point Appropriateness) are published in volume 14 of Bioanalysis, issues 9 and 11 (2022), respectively.
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20
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Xie H, Ding X. The Intriguing Landscape of Single-Cell Protein Analysis. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2022; 9:e2105932. [PMID: 35199955 PMCID: PMC9036017 DOI: 10.1002/advs.202105932] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Revised: 01/27/2022] [Indexed: 05/15/2023]
Abstract
Profiling protein expression at single-cell resolution is essential for fundamental biological research (such as cell differentiation and tumor microenvironmental examination) and clinical precision medicine where only a limited number of primary cells are permitted. With the recent advances in engineering, chemistry, and biology, single-cell protein analysis methods are developed rapidly, which enable high-throughput and multiplexed protein measurements in thousands of individual cells. In combination with single cell RNA sequencing and mass spectrometry, single-cell multi-omics analysis can simultaneously measure multiple modalities including mRNAs, proteins, and metabolites in single cells, and obtain a more comprehensive exploration of cellular signaling processes, such as DNA modifications, chromatin accessibility, protein abundance, and gene perturbation. Here, the recent progress and applications of single-cell protein analysis technologies in the last decade are summarized. Current limitations, challenges, and possible future directions in this field are also discussed.
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Affiliation(s)
- Haiyang Xie
- State Key Laboratory of Oncogenes and Related GenesInstitute for Personalized MedicineSchool of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200030China
| | - Xianting Ding
- State Key Laboratory of Oncogenes and Related GenesInstitute for Personalized MedicineSchool of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200030China
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21
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Baskar R, Kimmey SC, Bendall SC. Revealing new biology from multiplexed, metal-isotope-tagged, single-cell readouts. Trends Cell Biol 2022; 32:501-512. [PMID: 35181197 DOI: 10.1016/j.tcb.2022.01.012] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 01/19/2022] [Accepted: 01/20/2022] [Indexed: 11/26/2022]
Abstract
Mass cytometry (MC) is a recent technology that pairs plasma-based ionization of cells in suspension with time-of-flight (TOF) mass spectrometry to sensitively quantify the single-cell abundance of metal-isotope-tagged affinity reagents to key proteins, RNA, and peptides. Given the ability to multiplex readouts (~50 per cell) and capture millions of cells per experiment, MC offers a robust way to assay rare, transitional cell states that are pertinent to human development and disease. Here, we review MC approaches that let us probe the dynamics of cellular regulation across multiple conditions and sample types in a single experiment. Additionally, we discuss current limitations and future extensions of MC as well as computational tools commonly used to extract biological insight from single-cell proteomic datasets.
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Affiliation(s)
- Reema Baskar
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA, USA
| | - Sam C Kimmey
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA, USA
| | - Sean C Bendall
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA, USA.
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22
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Analysis of the Single-Cell Heterogeneity of Adenocarcinoma Cell Lines and the Investigation of Intratumor Heterogeneity Reveals the Expression of Transmembrane Protein 45A (TMEM45A) in Lung Adenocarcinoma Cancer Patients. Cancers (Basel) 2021; 14:cancers14010144. [PMID: 35008313 PMCID: PMC8750076 DOI: 10.3390/cancers14010144] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Revised: 12/14/2021] [Accepted: 12/24/2021] [Indexed: 11/25/2022] Open
Abstract
Simple Summary Non-small cell lung cancer (NSCLC) is one of the main causes of cancer-related deaths worldwide. Intratumoral heterogeneity (ITH) is responsible for the majority of difficulties encountered in the treatment of lung-cancer patients. Therefore, the heterogeneity of NSCLC cell lines and primary lung adenocarcinoma was investigated by single-cell mass cytometry (CyTOF). Human NSCLC adenocarcinoma cells A549, H1975, and H1650 were studied at single-cell resolution for the expression pattern of 13 markers: GLUT1, MCT4, CA9, TMEM45A, CD66, CD274, CD24, CD326, pan-keratin, TRA-1-60, galectin-3, galectin-1, and EGFR. The intra- and inter-cell-line heterogeneity of A549, H1975, and H1650 cells were demonstrated through hypoxic modeling. Additionally, human primary lung adenocarcinoma, and non-involved healthy lung tissue were homogenized to prepare a single-cell suspension for CyTOF analysis. The single-cell heterogeneity was confirmed using unsupervised viSNE and FlowSOM analysis. Our results also show, for the first time, that TMEM45A is expressed in lung adenocarcinoma. Abstract Intratumoral heterogeneity (ITH) is responsible for the majority of difficulties encountered in the treatment of lung-cancer patients. Therefore, the heterogeneity of NSCLC cell lines and primary lung adenocarcinoma was investigated by single-cell mass cytometry (CyTOF). First, we studied the single-cell heterogeneity of frequent NSCLC adenocarcinoma models, such as A549, H1975, and H1650. The intra- and inter-cell-line single-cell heterogeneity is represented in the expression patterns of 13 markers—namely GLUT1, MCT4, CA9, TMEM45A, CD66, CD274 (PD-L1), CD24, CD326 (EpCAM), pan-keratin, TRA-1-60, galectin-3, galectin-1, and EGFR. The qRT-PCR and CyTOF analyses revealed that a hypoxic microenvironment and altered metabolism may influence cell-line heterogeneity. Additionally, human primary lung adenocarcinoma and non-involved healthy lung tissue biopsies were homogenized to prepare a single-cell suspension for CyTOF analysis. The CyTOF showed the ITH of human primary lung adenocarcinoma for 14 markers; particularly, the higher expressions of GLUT1, MCT4, CA9, TMEM45A, and CD66 were associated with the lung-tumor tissue. Our single-cell results are the first to demonstrate TMEM45A expression in human lung adenocarcinoma, which was verified by immunohistochemistry.
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Varrone F, Mandrich L, Caputo E. Melanoma Immunotherapy and Precision Medicine in the Era of Tumor Micro-Tissue Engineering: Where Are We Now and Where Are We Going? Cancers (Basel) 2021; 13:5788. [PMID: 34830940 PMCID: PMC8616100 DOI: 10.3390/cancers13225788] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Revised: 11/05/2021] [Accepted: 11/12/2021] [Indexed: 11/16/2022] Open
Abstract
Malignant melanoma still remains a cancer with very poor survival rates, although it is at the forefront of personalized medicine. Most patients show partial responses and disease progressed due to adaptative resistance mechanisms, preventing long-lasting clinical benefits to the current treatments. The response to therapies can be shaped by not only taking into account cancer cell heterogeneity and plasticity, but also by its structural context as well as the cellular component of the tumor microenvironment (TME). Here, we review the recent development in the field of immunotherapy and target-based therapy and how, in the era of tumor micro-tissue engineering, ex-vivo assays could help to enhance our melanoma biology knowledge in its complexity, translating it in the development of successful therapeutic strategies, as well as in the prediction of therapeutic benefits.
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Affiliation(s)
| | - Luigi Mandrich
- Research Institute on Terrestrial Ecosystem—IRET-CNR Via Pietro Castellino 111, I-80131 Naples, Italy;
| | - Emilia Caputo
- Institute of Genetics and Biophysics—IGB-CNR, “A. Buzzati-Traverso”, Via Pietro Castellino 111, I-80131 Naples, Italy
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24
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Li Y, An H, Shen C, Wang B, Zhang T, Hong Y, Jiang H, Zhou P, Ding X. Deep phenotyping of T cell populations under long-term treatment of tacrolimus and rapamycin in patients receiving renal transplantations by mass cytometry. Clin Transl Med 2021; 11:e629. [PMID: 34841735 PMCID: PMC8574956 DOI: 10.1002/ctm2.629] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Revised: 10/04/2021] [Accepted: 10/08/2021] [Indexed: 12/14/2022] Open
Abstract
Tacrolimus (FK506) and rapamycin (RAPA) are widely used to maintain long-term immunosuppression after organ transplantation. However, the impact of accumulative drug administration on the recipients' immune systems remains unclear. We investigated the impact of 3-year FK506 or RAPA treatment after renal transplantation on the human immune systems. A discovery cohort of 30 patients was first recruited, and we discovered two distinctive T lineage suppressive regulatory patterns induced by chronic treatment of FK506 and RAPA. The increased percentage of senescent CD8+ CD57+ T lineages and less responsive T cell receptor (TCR) pathway in the FK506 group indicate better graft acceptance. Meanwhile, percentages of regulatory T cells (Tregs) and expression of CTLA-4 were both up to two-fold higher in the RAPA group, suggesting the inconsistent reactivation potential of the FK506 and RAPA groups when an anti-tumour or anti-infection immune response is concerned. Additionally, up-regulation of phosphorylated signaling proteins in T lineages after in vitro CD3/CD28 stimulation suggested more sensitive TCR-signaling pathways reserved in the RAPA group. An independent validation cohort of 100 renal transplantation patients was further investigated for the hypothesis that long-term RAPA administration mitigates the development of tumours and infections during long-term intake of immunosuppressants. Our results indicate that RAPA administration indeed results in less clinical oncogenesis and infection. The deep phenotyping of T-cell lineages, as educated by the long-term treatment of different immunosuppressants, provides new evidence for personalized precision medicine after renal transplantations.
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Affiliation(s)
- Yiyang Li
- State Key Laboratory of Oncogenes and Related GenesSchool of Biomedical EngineeringInstitute for Personalized MedicineShanghai Jiao Tong UniversityShanghaiPeople's Republic of China
| | - Huimin An
- Division of Kidney TransplantDepartment of UrologyRuijin HospitalShanghai Jiao Tong University School of MedicineShanghaiPeople's Republic of China
| | - Chuan Shen
- Department of Liver SurgeryRenji HospitalShanghai Jiao Tong University School of MedicineShanghaiPeople's Republic of China
| | - Boqian Wang
- State Key Laboratory of Oncogenes and Related GenesSchool of Biomedical EngineeringInstitute for Personalized MedicineShanghai Jiao Tong UniversityShanghaiPeople's Republic of China
| | - Ting Zhang
- State Key Laboratory of Oncogenes and Related GenesSchool of Biomedical EngineeringInstitute for Personalized MedicineShanghai Jiao Tong UniversityShanghaiPeople's Republic of China
| | - Yifan Hong
- State Key Laboratory of Oncogenes and Related GenesSchool of Biomedical EngineeringInstitute for Personalized MedicineShanghai Jiao Tong UniversityShanghaiPeople's Republic of China
| | - Hui Jiang
- State Key Laboratory of Oncogenes and Related GenesSchool of Biomedical EngineeringInstitute for Personalized MedicineShanghai Jiao Tong UniversityShanghaiPeople's Republic of China
| | - Peijun Zhou
- Division of Kidney TransplantDepartment of UrologyRuijin HospitalShanghai Jiao Tong University School of MedicineShanghaiPeople's Republic of China
| | - Xianting Ding
- State Key Laboratory of Oncogenes and Related GenesSchool of Biomedical EngineeringInstitute for Personalized MedicineShanghai Jiao Tong UniversityShanghaiPeople's Republic of China
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25
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Couloume L, Michel L. New concepts on immunology of Multiple Sclerosis. Presse Med 2021; 50:104072. [PMID: 34547375 DOI: 10.1016/j.lpm.2021.104072] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 08/15/2021] [Accepted: 09/14/2021] [Indexed: 12/27/2022] Open
Abstract
Multiple sclerosis (MS) is a chronic inflammatory and immune-driven demyelinating disease of the central nervous system (CNS). During the past decade, major advances have been made to understand the development of MS as well as its progressive stage. Here, we discuss some emerging concepts on immunology of MS, including the growing interest in the involvement of gut microbiota and the recent pathological concepts on the progression phase. Finally, we present some immuno-tools recently available that contribute to better understand diversity and function of the immune system.
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Affiliation(s)
| | - Laure Michel
- Univ Rennes, CHU Rennes, Neurology, Inserm, CIC 1414 (Centre d'Investigation Clinique de Rennes), F-35000 Rennes, France; Unité Mixte de Recherche (UMR) S1236, INSERM, University of Rennes, Etablissement Français du Sang, Rennes, France; Suivi Immunologique des Thérapeutiques Innovantes, Centre Hospitalier Universitaire de Rennes, Etablissement Français du Sang, Rennes, France.
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Pereiro I, Aubert J, Kaigala GV. Micro-scale technologies propel biology and medicine. BIOMICROFLUIDICS 2021; 15:021302. [PMID: 33948133 PMCID: PMC8081554 DOI: 10.1063/5.0047196] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/11/2021] [Accepted: 04/05/2021] [Indexed: 05/05/2023]
Abstract
Historically, technology has been central to new discoveries in biology and progress in medicine. Among various technologies, microtechnologies, in particular, have had a prominent role in the revolution experienced by the life sciences in the last few decades, which will surely continue in the years to come. In this Perspective, we illustrate how microtechnologies, with a focus on microfluidics, have evolved in trends/waves to tackle the boundary of knowledge in the life sciences. We provide illustrative examples of technology-enabled biological breakthroughs and their current and future use in clinics. Finally, we take a closer look at the translational process to understand why the incorporation of new micro-scale technologies in medicine has been comparatively slow so far.
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