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Papadakos SP, Chatzikalil E, Arvanitakis K, Vakadaris G, Stergiou IE, Koutsompina ML, Argyrou A, Lekakis V, Konstantinidis I, Germanidis G, Theocharis S. Understanding the Role of Connexins in Hepatocellular Carcinoma: Molecular and Prognostic Implications. Cancers (Basel) 2024; 16:1533. [PMID: 38672615 PMCID: PMC11048329 DOI: 10.3390/cancers16081533] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2024] [Revised: 04/15/2024] [Accepted: 04/16/2024] [Indexed: 04/28/2024] Open
Abstract
Connexins, a family of tetraspan membrane proteins forming intercellular channels localized in gap junctions, play a pivotal role at the different stages of tumor progression presenting both pro- and anti-tumorigenic effects. Considering the potential role of connexins as tumor suppressors through multiple channel-independent mechanisms, their loss of expression may be associated with tumorigenic activity, while it is hypothesized that connexins favor the clonal expansion of tumor cells and promote cell migration, invasion, and proliferation, affecting metastasis and chemoresistance in some cases. Hepatocellular carcinoma (HCC), characterized by unfavorable prognosis and limited responsiveness to current therapeutic strategies, has been linked to gap junction proteins as tumorigenic factors with prognostic value. Notably, several members of connexins have emerged as promising markers for assessing the progression and aggressiveness of HCC, as well as the chemosensitivity and radiosensitivity of hepatocellular tumor cells. Our review sheds light on the multifaceted role of connexins in HCC pathogenesis, offering valuable insights on recent advances in determining their prognostic and therapeutic potential.
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Affiliation(s)
- Stavros P. Papadakos
- First Department of Pathology, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece; (S.P.P.); (E.C.)
| | - Elena Chatzikalil
- First Department of Pathology, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece; (S.P.P.); (E.C.)
| | - Konstantinos Arvanitakis
- Division of Gastroenterology and Hepatology, First Department of Internal Medicine, AHEPA University Hospital, Aristotle University of Thessaloniki, 54636 Thessaloniki, Greece; (K.A.); (G.V.)
- Basic and Translational Research Unit, Special Unit for Biomedical Research and Education, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 54636 Thessaloniki, Greece
| | - Georgios Vakadaris
- Division of Gastroenterology and Hepatology, First Department of Internal Medicine, AHEPA University Hospital, Aristotle University of Thessaloniki, 54636 Thessaloniki, Greece; (K.A.); (G.V.)
| | - Ioanna E. Stergiou
- Pathophysiology Department, School of Medicine, National and Kapodistrian University of Athens, 11527 Athens, Greece; (I.E.S.); (M.-L.K.)
| | - Maria-Loukia Koutsompina
- Pathophysiology Department, School of Medicine, National and Kapodistrian University of Athens, 11527 Athens, Greece; (I.E.S.); (M.-L.K.)
| | - Alexandra Argyrou
- Academic Department of Gastroenterology, Laikon General Hospital, Athens University Medical School, 11527 Athens, Greece; (A.A.); (V.L.)
| | - Vasileios Lekakis
- Academic Department of Gastroenterology, Laikon General Hospital, Athens University Medical School, 11527 Athens, Greece; (A.A.); (V.L.)
| | | | - Georgios Germanidis
- Division of Gastroenterology and Hepatology, First Department of Internal Medicine, AHEPA University Hospital, Aristotle University of Thessaloniki, 54636 Thessaloniki, Greece; (K.A.); (G.V.)
- Basic and Translational Research Unit, Special Unit for Biomedical Research and Education, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 54636 Thessaloniki, Greece
| | - Stamatios Theocharis
- First Department of Pathology, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece; (S.P.P.); (E.C.)
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Tian T, Lin S, Yang C. Beyond single cells: microfluidics empowering multiomics analysis. Anal Bioanal Chem 2024; 416:2203-2220. [PMID: 38008783 DOI: 10.1007/s00216-023-05028-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2023] [Revised: 10/26/2023] [Accepted: 10/30/2023] [Indexed: 11/28/2023]
Abstract
Single-cell multiomics technologies empower simultaneous measurement of multiple types of molecules within individual cells, providing a more profound comprehension compared with the analysis of discrete molecular layers from different cells. Microfluidic technology, on the other hand, has emerged as a pivotal facilitator for high-throughput single-cell analysis, offering precise control and manipulation of individual cells. The primary focus of this review encompasses an appraisal of cutting-edge microfluidic platforms employed in the realm of single-cell multiomics analysis. Furthermore, it discusses technological advancements in various single-cell omics such as genomics, transcriptomics, epigenomics, and proteomics, with their perspective applications. Finally, it provides future prospects of these integrated single-cell multiomics methodologies, shedding light on the possibilities for future biological research.
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Affiliation(s)
- Tian Tian
- Chemistry and Biomedicine Innovation Center (ChemBIC), School of Chemistry and Chemical Engineering, Nanjing University, Nanjing, 210023, China
| | - Shichao Lin
- Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province, Xiamen, 361005, China
| | - Chaoyong Yang
- Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province, Xiamen, 361005, China.
- The MOE Key Laboratory of Spectrochemical Analysis and Instrumentation, State Key Laboratory of Physical Chemistry of Solid Surfaces, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, 361005, China.
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Xiong K, Fang Y, Qiu B, Chen C, Huang N, Liang F, Huang C, Lu T, Zheng L, Zhao J, Zhu B. Investigation of cellular communication and signaling pathways in tumor microenvironment for high TP53-expressing osteosarcoma cells through single-cell RNA sequencing. Med Oncol 2024; 41:93. [PMID: 38526643 DOI: 10.1007/s12032-024-02318-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Accepted: 01/29/2024] [Indexed: 03/27/2024]
Abstract
Osteosarcoma (OS) stands as the most prevalent primary bone cancer in children and adolescents, and its limited treatment options often result in unsatisfactory outcomes, particularly for metastatic cases. The tumor microenvironment (TME) has been recognized as a crucial determinant in OS progression. However, the intercellular dynamics between high TP53-expressing OS cells and neighboring cell types within the TME are yet to be thoroughly understood. In our study, we harnessed the single-cell RNA sequencing (scRNA-seq) technology in combination with the computational tool-Cellchat, aiming to elucidate the intercellular communication networks present within OS. Through meticulous quantitative inference and subsequent analysis of these networks, we succeeded in identifying significant signaling pathways connecting high TP53-expressing OS cells with proximate cell types, namely Macrophages, Monocytes, Endothelial Cells, and PVLs. This research brings forth a nuanced understanding of the intricate patterns and coordination involved in the TME's intercellular communication signals. These findings not only provide profound insights into the molecular mechanisms underpinning OS but also indicate potential therapeutic targets that could revolutionize treatment strategies.
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Affiliation(s)
- Kai Xiong
- Guangxi Engineering Center in Biomedical Materials for Tissue and Organ Regeneration, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530021, China
- Collaborative Innovation Centre of Regenerative Medicine and Medical BioResource Development and Application Co-constructed by the Province and Ministry, Guangxi Medical University, Nanning, 530021, China
- Department of Orthopaedics Trauma and HandSurgery, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530021, China
- Department of Orthopaedics Trauma and HandSurgery, The Third Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530031, China
| | - Yuqi Fang
- Guangxi Engineering Center in Biomedical Materials for Tissue and Organ Regeneration, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530021, China
- Collaborative Innovation Centre of Regenerative Medicine and Medical BioResource Development and Application Co-constructed by the Province and Ministry, Guangxi Medical University, Nanning, 530021, China
| | - Boyuan Qiu
- Guangxi Engineering Center in Biomedical Materials for Tissue and Organ Regeneration, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530021, China
- Collaborative Innovation Centre of Regenerative Medicine and Medical BioResource Development and Application Co-constructed by the Province and Ministry, Guangxi Medical University, Nanning, 530021, China
| | - Chaotao Chen
- Guangxi Engineering Center in Biomedical Materials for Tissue and Organ Regeneration, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530021, China
- Collaborative Innovation Centre of Regenerative Medicine and Medical BioResource Development and Application Co-constructed by the Province and Ministry, Guangxi Medical University, Nanning, 530021, China
- Department of Orthopaedics Trauma and HandSurgery, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530021, China
| | - Nanchang Huang
- Guangxi Engineering Center in Biomedical Materials for Tissue and Organ Regeneration, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530021, China
- Collaborative Innovation Centre of Regenerative Medicine and Medical BioResource Development and Application Co-constructed by the Province and Ministry, Guangxi Medical University, Nanning, 530021, China
- Department of Orthopaedics Trauma and HandSurgery, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530021, China
| | - Feiyuan Liang
- Guangxi Engineering Center in Biomedical Materials for Tissue and Organ Regeneration, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530021, China
- Collaborative Innovation Centre of Regenerative Medicine and Medical BioResource Development and Application Co-constructed by the Province and Ministry, Guangxi Medical University, Nanning, 530021, China
- Department of Orthopaedics Trauma and HandSurgery, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530021, China
| | - Chuangming Huang
- Guangxi Engineering Center in Biomedical Materials for Tissue and Organ Regeneration, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530021, China
- Collaborative Innovation Centre of Regenerative Medicine and Medical BioResource Development and Application Co-constructed by the Province and Ministry, Guangxi Medical University, Nanning, 530021, China
- Department of Orthopaedics Trauma and HandSurgery, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530021, China
- Department of Bone and Soft Tissue Surgery, Guangxi Medical University Cancer Hospital, Guangxi Medical University, Nanning, 530021, China
| | - Tiantian Lu
- Guangxi Engineering Center in Biomedical Materials for Tissue and Organ Regeneration, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530021, China
- Collaborative Innovation Centre of Regenerative Medicine and Medical BioResource Development and Application Co-constructed by the Province and Ministry, Guangxi Medical University, Nanning, 530021, China
| | - Li Zheng
- Guangxi Engineering Center in Biomedical Materials for Tissue and Organ Regeneration, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530021, China.
- Collaborative Innovation Centre of Regenerative Medicine and Medical BioResource Development and Application Co-constructed by the Province and Ministry, Guangxi Medical University, Nanning, 530021, China.
- International Joint Laboratory of Ministry of Education for Regeneration of Bone and Soft Tissues, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530021, China.
| | - Jinmin Zhao
- Guangxi Engineering Center in Biomedical Materials for Tissue and Organ Regeneration, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530021, China.
- Collaborative Innovation Centre of Regenerative Medicine and Medical BioResource Development and Application Co-constructed by the Province and Ministry, Guangxi Medical University, Nanning, 530021, China.
- Department of Orthopaedics Trauma and HandSurgery, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530021, China.
- International Joint Laboratory of Ministry of Education for Regeneration of Bone and Soft Tissues, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530021, China.
- Guangxi Key Laboratory of Regenerative Medicine, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530021, China.
| | - Bo Zhu
- Guangxi Engineering Center in Biomedical Materials for Tissue and Organ Regeneration, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530021, China.
- Collaborative Innovation Centre of Regenerative Medicine and Medical BioResource Development and Application Co-constructed by the Province and Ministry, Guangxi Medical University, Nanning, 530021, China.
- Guangxi Key Laboratory of Regenerative Medicine, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530021, China.
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Schäfer PSL, Dimitrov D, Villablanca EJ, Saez-Rodriguez J. Integrating single-cell multi-omics and prior biological knowledge for a functional characterization of the immune system. Nat Immunol 2024; 25:405-417. [PMID: 38413722 DOI: 10.1038/s41590-024-01768-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Accepted: 01/16/2024] [Indexed: 02/29/2024]
Abstract
The immune system comprises diverse specialized cell types that cooperate to defend the host against a wide range of pathogenic threats. Recent advancements in single-cell and spatial multi-omics technologies provide rich information about the molecular state of immune cells. Here, we review how the integration of single-cell and spatial multi-omics data with prior knowledge-gathered from decades of detailed biochemical studies-allows us to obtain functional insights, focusing on gene regulatory processes and cell-cell interactions. We present diverse applications in immunology and critically assess underlying assumptions and limitations. Finally, we offer a perspective on the ongoing technological and algorithmic developments that promise to get us closer to a systemic mechanistic understanding of the immune system.
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Affiliation(s)
- Philipp Sven Lars Schäfer
- Institute for Computational Bioscience, Faculty of Medicine and Heidelberg University Hospital, Heidelberg University, Heidelberg, Germany
| | - Daniel Dimitrov
- Institute for Computational Bioscience, Faculty of Medicine and Heidelberg University Hospital, Heidelberg University, Heidelberg, Germany
| | - Eduardo J Villablanca
- Division of Immunology and Allergy, Department of Medicine Solna, Karolinska Institute and Karolinska University Hospital, Stockholm, Sweden
- Center of Molecular Medicine, Stockholm, Sweden
| | - Julio Saez-Rodriguez
- Institute for Computational Bioscience, Faculty of Medicine and Heidelberg University Hospital, Heidelberg University, Heidelberg, Germany.
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Wilk AJ, Marceau JO, Kazer SW, Fleming I, Miao VN, Galvez-Reyes J, Kimata JT, Shalek AK, Holmes S, Overbaugh J, Blish CA. Pro-inflammatory feedback loops define immune responses to pathogenic Lentivirus infection. Genome Med 2024; 16:24. [PMID: 38317183 PMCID: PMC10840164 DOI: 10.1186/s13073-024-01290-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Accepted: 01/19/2024] [Indexed: 02/07/2024] Open
Abstract
BACKGROUND The Lentivirus human immunodeficiency virus (HIV) causes chronic inflammation and AIDS in humans, with variable rates of disease progression between individuals driven by both host and viral factors. Similarly, simian lentiviruses vary in their pathogenicity based on characteristics of both the host species and the virus strain, yet the immune underpinnings that drive differential Lentivirus pathogenicity remain incompletely understood. METHODS We profile immune responses in a unique model of differential lentiviral pathogenicity where pig-tailed macaques are infected with highly genetically similar variants of SIV that differ in virulence. We apply longitudinal single-cell transcriptomics to this cohort, along with single-cell resolution cell-cell communication techniques, to understand the immune mechanisms underlying lentiviral pathogenicity. RESULTS Compared to a minimally pathogenic lentiviral variant, infection with a highly pathogenic variant results in a more delayed, broad, and sustained activation of inflammatory pathways, including an extensive global interferon signature. Conversely, individual cells infected with highly pathogenic Lentivirus upregulated fewer interferon-stimulated genes at a lower magnitude, indicating that highly pathogenic Lentivirus has evolved to partially escape from interferon responses. Further, we identify CXCL10 and CXCL16 as important molecular drivers of inflammatory pathways specifically in response to highly pathogenic Lentivirus infection. Immune responses to highly pathogenic Lentivirus infection are characterized by amplifying regulatory circuits of pro-inflammatory cytokines with dense longitudinal connectivity. CONCLUSIONS Our work presents a model of lentiviral pathogenicity where failures in early viral control mechanisms lead to delayed, sustained, and amplifying pro-inflammatory circuits, which in turn drives disease progression.
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Affiliation(s)
- Aaron J Wilk
- Stanford Immunology Program, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Medical Scientist Training Program, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Joshua O Marceau
- Division of Human Biology, Fred Hutchinson Cancer Research Center, Seattle, WA, 98109, USA
| | - Samuel W Kazer
- Institute for Medical Engineering & Science, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, 02139, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Ira Fleming
- Institute for Medical Engineering & Science, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, 02139, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Vincent N Miao
- Institute for Medical Engineering & Science, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, 02139, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
- Program in Health Sciences & Technology, Harvard Medical School & MIT, Boston, MA, 02115, USA
| | - Jennyfer Galvez-Reyes
- Institute for Medical Engineering & Science, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, 02139, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Jason T Kimata
- Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, USA
| | - Alex K Shalek
- Institute for Medical Engineering & Science, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, 02139, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Susan Holmes
- Department of Statistics, Stanford University, Stanford, CA, 94305, USA
| | - Julie Overbaugh
- Division of Human Biology, Fred Hutchinson Cancer Research Center, Seattle, WA, 98109, USA
| | - Catherine A Blish
- Stanford Immunology Program, Stanford University School of Medicine, Stanford, CA, 94305, USA.
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA.
- Medical Scientist Training Program, Stanford University School of Medicine, Stanford, CA, 94305, USA.
- Chan Zuckerberg Biohub, San Francisco, CA, 94158, USA.
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Liu A, Fernandes BS, Citu C, Zhao Z. Unraveling the intercellular communication disruption and key pathways in Alzheimer's disease: an integrative study of single-nucleus transcriptomes and genetic association. Alzheimers Res Ther 2024; 16:3. [PMID: 38167548 PMCID: PMC10762817 DOI: 10.1186/s13195-023-01372-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Accepted: 12/17/2023] [Indexed: 01/05/2024]
Abstract
BACKGROUND Recently, single-nucleus RNA-seq (snRNA-seq) analyses have revealed important cellular and functional features of Alzheimer's disease (AD), a prevalent neurodegenerative disease. However, our knowledge regarding intercellular communication mediated by dysregulated ligand-receptor (LR) interactions remains very limited in AD brains. METHODS We systematically assessed the intercellular communication networks by using a discovery snRNA-seq dataset comprising 69,499 nuclei from 48 human postmortem prefrontal cortex (PFC) samples. We replicated the findings using an independent snRNA-seq dataset of 56,440 nuclei from 18 PFC samples. By integrating genetic signals from AD genome-wide association studies (GWAS) summary statistics and whole genome sequencing (WGS) data, we prioritized AD-associated Gene Ontology (GO) terms containing dysregulated LR interactions. We further explored drug repurposing for the prioritized LR pairs using the Therapeutic Targets Database. RESULTS We identified 190 dysregulated LR interactions across six major cell types in AD PFC, of which 107 pairs were replicated. Among the replicated LR signals, we found globally downregulated communications in the astrocytes-to-neurons signaling axis, characterized, for instance, by the downregulation of APOE-related and Calmodulin (CALM)-related LR interactions and their potential regulatory connections to target genes. Pathway analyses revealed 44 GO terms significantly linked to AD, highlighting Biological Processes such as 'amyloid precursor protein processing' and 'ion transmembrane transport,' among others. We prioritized several drug repurposing candidates, such as cromoglicate, targeting the identified dysregulated LR pairs. CONCLUSIONS Our integrative analysis identified key dysregulated LR interactions in a cell type-specific manner and the associated GO terms in AD, offering novel insights into potential therapeutic targets involved in disrupted cell-cell communication in AD.
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Affiliation(s)
- Andi Liu
- Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
- Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, 7000 Fannin St., Suite 600, Houston, TX, 77030, USA
| | - Brisa S Fernandes
- Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, 7000 Fannin St., Suite 600, Houston, TX, 77030, USA
| | - Citu Citu
- Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, 7000 Fannin St., Suite 600, Houston, TX, 77030, USA
| | - Zhongming Zhao
- Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA.
- Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, 7000 Fannin St., Suite 600, Houston, TX, 77030, USA.
- Faillace Department of Psychiatry and Behavioral Sciences, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA.
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, 37203, USA.
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Zhu L, Tang Q, Mao Z, Chen H, Wu L, Qin Y. Microfluidic-based platforms for cell-to-cell communication studies. Biofabrication 2023; 16:012005. [PMID: 38035370 DOI: 10.1088/1758-5090/ad1116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2023] [Accepted: 11/30/2023] [Indexed: 12/02/2023]
Abstract
Intercellular communication is critical to the understanding of human health and disease progression. However, compared to traditional methods with inefficient analysis, microfluidic co-culture technologies developed for cell-cell communication research can reliably analyze crucial biological processes, such as cell signaling, and monitor dynamic intercellular interactions under reproducible physiological cell co-culture conditions. Moreover, microfluidic-based technologies can achieve precise spatial control of two cell types at the single-cell level with high throughput. Herein, this review focuses on recent advances in microfluidic-based 2D and 3D devices developed to confine two or more heterogeneous cells in the study of intercellular communication and decipher the advantages and limitations of these models in specific cellular research scenarios. This review will stimulate the development of more functionalized microfluidic platforms for biomedical research, inspiring broader interests across various disciplines to better comprehend cell-cell communication and other fields, such as tumor heterogeneity and drug screening.
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Affiliation(s)
- Lvyang Zhu
- Nantong Key Laboratory of Public Health and Medical Analysis, School of Public Health, Nantong University, No. 9, Seyuan Road, Nantong 226019, Jiangsu, People's Republic of China
| | - Qu Tang
- Nantong Key Laboratory of Public Health and Medical Analysis, School of Public Health, Nantong University, No. 9, Seyuan Road, Nantong 226019, Jiangsu, People's Republic of China
| | - Zhenzhen Mao
- Nantong Key Laboratory of Public Health and Medical Analysis, School of Public Health, Nantong University, No. 9, Seyuan Road, Nantong 226019, Jiangsu, People's Republic of China
| | - Huanhuan Chen
- Nantong Key Laboratory of Public Health and Medical Analysis, School of Public Health, Nantong University, No. 9, Seyuan Road, Nantong 226019, Jiangsu, People's Republic of China
| | - Li Wu
- Nantong Key Laboratory of Public Health and Medical Analysis, School of Public Health, Nantong University, No. 9, Seyuan Road, Nantong 226019, Jiangsu, People's Republic of China
| | - Yuling Qin
- Nantong Key Laboratory of Public Health and Medical Analysis, School of Public Health, Nantong University, No. 9, Seyuan Road, Nantong 226019, Jiangsu, People's Republic of China
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Peng R, Deng M. Mapping the protein-protein interactome in the tumor immune microenvironment. Antib Ther 2023; 6:311-321. [PMID: 38098892 PMCID: PMC10720949 DOI: 10.1093/abt/tbad026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Revised: 10/01/2023] [Accepted: 11/02/2023] [Indexed: 12/17/2023] Open
Abstract
The cell-to-cell communication primarily occurs through cell-surface and secreted proteins, which form a sophisticated network that coordinates systemic immune function. Uncovering these protein-protein interactions (PPIs) is indispensable for understanding the molecular mechanism and elucidating immune system aberrances under diseases. Traditional biological studies typically focus on a limited number of PPI pairs due to the relative low throughput of commonly used techniques. Encouragingly, classical methods have advanced, and many new systems tailored for large-scale protein-protein screening have been developed and successfully utilized. These high-throughput PPI investigation techniques have already made considerable achievements in mapping the immune cell interactome, enriching PPI databases and analysis tools, and discovering therapeutic targets for cancer and other diseases, which will definitely bring unprecedented insight into this field.
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Affiliation(s)
- Rui Peng
- Peking University International Cancer Institute, Health Science Center, Peking University, Beijing 100191, PR China
- School of Basic Medical Sciences, Health Science Center, Peking University, Beijing 100191, PR China
| | - Mi Deng
- Peking University International Cancer Institute, Health Science Center, Peking University, Beijing 100191, PR China
- School of Basic Medical Sciences, Health Science Center, Peking University, Beijing 100191, PR China
- Peking University Cancer Hospital and Institute, Peking University, Beijing 100142, PR China
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Luo J, Deng M, Zhang X, Sun X. ESICCC as a systematic computational framework for evaluation, selection, and integration of cell-cell communication inference methods. Genome Res 2023; 33:1788-1805. [PMID: 37827697 PMCID: PMC10691505 DOI: 10.1101/gr.278001.123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2023] [Accepted: 09/21/2023] [Indexed: 10/14/2023]
Abstract
Cell-cell communication (CCC) is critical for determining cell fates and functions in multicellular organisms. With the advent of single-cell RNA-sequencing (scRNA-seq) and spatial transcriptomics (ST), an increasing number of CCC inference methods have been developed. Nevertheless, a thorough comparison of their performances is yet to be conducted. To fill this gap, we developed a systematic benchmark framework called ESICCC to evaluate 18 ligand-receptor (LR) inference methods and five ligand/receptor-target inference methods using a total of 116 data sets, including 15 ST data sets, 15 sets of cell line perturbation data, two sets of cell type-specific expression/proteomics data, and 84 sets of sampled or unsampled scRNA-seq data. We evaluated and compared the agreement, accuracy, robustness, and usability of these methods. Regarding accuracy evaluation, RNAMagnet, CellChat, and scSeqComm emerge as the three best-performing methods for intercellular ligand-receptor inference based on scRNA-seq data, whereas stMLnet and HoloNet are the best methods for predicting ligand/receptor-target regulation using ST data. To facilitate the practical applications, we provide a decision-tree-style guideline for users to easily choose best tools for their specific research concerns in CCC inference, and develop an ensemble pipeline CCCbank that enables versatile combinations of methods and databases. Moreover, our comparative results also uncover several critical influential factors for CCC inference, such as prior interaction information, ligand-receptor scoring algorithm, intracellular signaling complexity, and spatial relationship, which may be considered in the future studies to advance the development of new methodologies.
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Affiliation(s)
- Jiaxin Luo
- Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China
- School of Mathematics, Sun Yat-sen University, Guangzhou 510275, China
| | - Minghua Deng
- School of Mathematical Sciences, Peking University, Beijing, 100871, China
| | - Xuegong Zhang
- Bioinformatics Division of BNRIST and Department of Automation, MOE Key Lab of Bioinformatics, Tsinghua University, Beijing, 100084, China
| | - Xiaoqiang Sun
- School of Mathematics, Sun Yat-sen University, Guangzhou 510275, China;
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Cheng D, Zhang Z, Mi Z, Tao W, Liu D, Fu J, Fan H. Deciphering the heterogeneity and immunosuppressive function of regulatory T cells in osteosarcoma using single-cell RNA transcriptome. Comput Biol Med 2023; 165:107417. [PMID: 37669584 DOI: 10.1016/j.compbiomed.2023.107417] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2023] [Revised: 08/03/2023] [Accepted: 08/28/2023] [Indexed: 09/07/2023]
Abstract
Osteosarcoma (OS) is a highly invasive malignant neoplasm with poor prognosis. The tumor microenvironment (TME) plays an essential role in the occurrence and development of OS. Regulatory T cells (Tregs) are known to facilitate immunosuppression, tumor progression, invasion, and metastasis. However, the effect of Tregs in the TME of OS remains unclear. In this study, single-cell RNA sequencing (scRNA-seq) data was used to identify Tregs and various other cell clusters in the TME of OS. Gene set variation analysis (GSVA) was used to investigate the signaling pathways in Tregs from OS and adjacent tissues. The CellChat and iTALK packages were used to analyze cellular communication. In addition, a prognostic model was established based on the Tregs-specific genes using bulk RNA-seq from the TARGET database, and it was verified using a Gene Expression Omnibus dataset. The pRRophetic package was used to predict drug sensitivity. Immunohistochemistry was used to verify the expression of candidate genes in OS. Based on the above methods, we showed that the OS samples were highly infiltrated with Tregs. GSVA revealed that oxidative phosphorylation, angiogenesis and mammalian target of rapamycin complex 1 (mTORC1) were highly activated in Tregs from OS compared with those from adjacent tissues. Using cellular communication analysis, we found that Tregs interacted with osteoblastic, endothelial, and myeloid cells via C-X-C motif chemokine ligand (CXCL) signaling; particularly, they strongly affected the expression of C-X-C motif chemokine receptor 4 (CXCR4) and interacted with other cell clusters through CXCL12/transforming growth factor β1 (TGFB1) to collectively enable tumor growth and progression. Subsequently, two Tregs-specific genes-CD320 and MAF-were screened through univariate, least absolute shrinkage and selection operator regression (LASSO) and multivariate analysis to construct a prognostic model, which showed excellent prognostic accuracy in two independent cohorts. In addition, drug sensitivity analysis demonstrated that OS patients at high Tregs risk were sensitive to sunitinib, sorafenib, and axitinib. We also used immunohistochemistry to validate that CD320 and MAF were significantly upregulated in OS tissues compared with adjacent tissues. Overall, this study reveals the heterogeneity of Tregs in the OS TME, providing new insights into the invasion and treatment of this cancer.
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Affiliation(s)
- Debin Cheng
- Department of Orthopaedic Surgery, Xi Jing Hospital, The Fourth Military Medical University, Xi'an, China
| | - Zhao Zhang
- Department of Orthopaedic Surgery, Xi Jing Hospital, The Fourth Military Medical University, Xi'an, China
| | - Zhenzhou Mi
- Department of Orthopaedic Surgery, Xi Jing Hospital, The Fourth Military Medical University, Xi'an, China
| | - Weidong Tao
- Department of Orthopaedic Surgery, Xi Jing Hospital, The Fourth Military Medical University, Xi'an, China
| | - Dong Liu
- Department of Orthopaedic Surgery, Xi Jing Hospital, The Fourth Military Medical University, Xi'an, China
| | - Jun Fu
- Department of Orthopaedic Surgery, Xi Jing Hospital, The Fourth Military Medical University, Xi'an, China
| | - Hongbin Fan
- Department of Orthopaedic Surgery, Xi Jing Hospital, The Fourth Military Medical University, Xi'an, China.
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Cheng C, Chen W, Jin H, Chen X. A Review of Single-Cell RNA-Seq Annotation, Integration, and Cell-Cell Communication. Cells 2023; 12:1970. [PMID: 37566049 PMCID: PMC10417635 DOI: 10.3390/cells12151970] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 07/10/2023] [Accepted: 07/21/2023] [Indexed: 08/12/2023] Open
Abstract
Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool for investigating cellular biology at an unprecedented resolution, enabling the characterization of cellular heterogeneity, identification of rare but significant cell types, and exploration of cell-cell communications and interactions. Its broad applications span both basic and clinical research domains. In this comprehensive review, we survey the current landscape of scRNA-seq analysis methods and tools, focusing on count modeling, cell-type annotation, data integration, including spatial transcriptomics, and the inference of cell-cell communication. We review the challenges encountered in scRNA-seq analysis, including issues of sparsity or low expression, reliability of cell annotation, and assumptions in data integration, and discuss the potential impact of suboptimal clustering and differential expression analysis tools on downstream analyses, particularly in identifying cell subpopulations. Finally, we discuss recent advancements and future directions for enhancing scRNA-seq analysis. Specifically, we highlight the development of novel tools for annotating single-cell data, integrating and interpreting multimodal datasets covering transcriptomics, epigenomics, and proteomics, and inferring cellular communication networks. By elucidating the latest progress and innovation, we provide a comprehensive overview of the rapidly advancing field of scRNA-seq analysis.
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Affiliation(s)
- Changde Cheng
- Department of Computational Biology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA;
| | - Wenan Chen
- Center for Applied Bioinformatics, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA; (W.C.); (H.J.)
| | - Hongjian Jin
- Center for Applied Bioinformatics, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA; (W.C.); (H.J.)
| | - Xiang Chen
- Department of Computational Biology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA;
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Clyde D. Single cell-cell communication. Nat Rev Genet 2023:10.1038/s41576-023-00631-8. [PMID: 37353568 DOI: 10.1038/s41576-023-00631-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/25/2023]
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