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Gottschalk RA, Germain RN. Linking signal input, cell state, and spatial context to inflammatory responses. Curr Opin Immunol 2024; 91:102462. [PMID: 39265520 DOI: 10.1016/j.coi.2024.102462] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2024] [Revised: 08/21/2024] [Accepted: 08/24/2024] [Indexed: 09/14/2024]
Abstract
Signal integration is central to a causal understanding of appropriately scaled inflammatory responses. Here, we discuss recent progress in our understanding of the stimulus-response linkages downstream of pro-inflammatory inputs, with special attention to (1) the impact of cell state on the specificity of evoked gene expression and (2) the critical role of the spatial context of stimulus exposure. Advances in these directions are emerging from new tools for inferring cell-cell interactions and the activities of cytokines and transcription factors in complex microenvironments, enabling analysis of signal integration in tissue settings. Building on data-driven elucidation of factors driving inflammatory outcomes, mechanistic modeling can then contribute to a quantitative understanding of regulatory events that balance protective versus pathological inflammation.
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Affiliation(s)
- Rachel A Gottschalk
- Department of Immunology, University of Pittsburgh School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA; Center for Systems Immunology, University of Pittsburgh, Pittsburgh, PA, USA.
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Lin S, Zhang S, Zhan A, Feng J, Yang Q, Li T, Liu Z, Mo Q, Fan H, Wang K, Wang L. Palmatine alleviates cardiac fibrosis by inhibiting fibroblast activation through the STAT3 pathway. Eur J Pharmacol 2024; 967:176395. [PMID: 38350592 DOI: 10.1016/j.ejphar.2024.176395] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Revised: 02/04/2024] [Accepted: 02/05/2024] [Indexed: 02/15/2024]
Abstract
Cardiac fibrosis, the hallmark of cardiovascular disease, is characterized by excessive deposition of extracellular matrix in the heart. Emerging evidence indicates that cardiac fibroblasts (CFs) play pivotal roles in driving cardiac fibrosis. However, due to incomplete insights into CFs, there are limited effective approaches to prevent or reverse cardiac fibrosis currently. Palmatine, a protoberberine alkaloid extracted from traditional Chinese botanical remedies, possesses diverse biological effects. This study investigated the potential therapeutic value and mechanism of palmatine against cardiac fibrosis. Adult male C57BL/6 mice were treated with vehicle, isoproterenol (ISO), or ISO plus palmatine for one week. After echocardiography assessment, mice hearts were collected for histopathology, real-time polymerase chain reaction, and Western blot analyses. Primary rat CFs were utilized in vitro. Compared to control, ISO-treated mice exhibited cardiac hypertrophy and structural abnormalities; however, treatment with palmatine ameliorated these effects of ISO. Moreover, palmatine treatment mitigated ISO-induced cardiac fibrosis. Network pharmacology and molecular docking analysis showed that palmatine strongly binds the regulators of cardiac fibrosis including signal transducer and activator of transcription 3 (STAT3) and mammalian target of rapamycin. Furthermore, palmatine reduced the elevated fibrotic factor expressions and overactivated STAT3 induced by ISO, Transformed growth factor β1 (TGF-β1), or interleukin-6 both in vivo and in vitro. Additionally, blocking STAT3 suppressed the TGF-β1-induced CF activation. Collectively, these data demonstrated that palmatine attenuated cardiac fibrosis partly by inhibiting fibroblast activation through the STAT3 pathway. This provides an experimental basis for the clinical treatment of cardiac fibrosis with palmatine.
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Affiliation(s)
- Shaoling Lin
- Guangdong Metabolic Diseases Research Center of Integrated Chinese and Western Medicine, Key Laboratory of Glycolipid Metabolic Disorder, Ministry of Education of China, Guangdong TCM Key Laboratory for Metabolic Diseases, Key Unit of Modulating Liver to Treat Hyperlipemia, State Administration of Traditional Chinese Medicine, Institute of Chinese Medicine, Guangdong Pharmaceutical University, Guangzhou, 510006, China
| | - Shengxi Zhang
- Guangdong Metabolic Diseases Research Center of Integrated Chinese and Western Medicine, Key Laboratory of Glycolipid Metabolic Disorder, Ministry of Education of China, Guangdong TCM Key Laboratory for Metabolic Diseases, Key Unit of Modulating Liver to Treat Hyperlipemia, State Administration of Traditional Chinese Medicine, Institute of Chinese Medicine, Guangdong Pharmaceutical University, Guangzhou, 510006, China; Guangdong Hydropower Group Hospital, Guangzhou, 511340, China
| | - Angyu Zhan
- Guangdong Metabolic Diseases Research Center of Integrated Chinese and Western Medicine, Key Laboratory of Glycolipid Metabolic Disorder, Ministry of Education of China, Guangdong TCM Key Laboratory for Metabolic Diseases, Key Unit of Modulating Liver to Treat Hyperlipemia, State Administration of Traditional Chinese Medicine, Institute of Chinese Medicine, Guangdong Pharmaceutical University, Guangzhou, 510006, China
| | - Jiaojiao Feng
- Guangdong Metabolic Diseases Research Center of Integrated Chinese and Western Medicine, Key Laboratory of Glycolipid Metabolic Disorder, Ministry of Education of China, Guangdong TCM Key Laboratory for Metabolic Diseases, Key Unit of Modulating Liver to Treat Hyperlipemia, State Administration of Traditional Chinese Medicine, Institute of Chinese Medicine, Guangdong Pharmaceutical University, Guangzhou, 510006, China
| | - Qianqian Yang
- Guangdong Metabolic Diseases Research Center of Integrated Chinese and Western Medicine, Key Laboratory of Glycolipid Metabolic Disorder, Ministry of Education of China, Guangdong TCM Key Laboratory for Metabolic Diseases, Key Unit of Modulating Liver to Treat Hyperlipemia, State Administration of Traditional Chinese Medicine, Institute of Chinese Medicine, Guangdong Pharmaceutical University, Guangzhou, 510006, China
| | - Tongjun Li
- Guangdong Metabolic Diseases Research Center of Integrated Chinese and Western Medicine, Key Laboratory of Glycolipid Metabolic Disorder, Ministry of Education of China, Guangdong TCM Key Laboratory for Metabolic Diseases, Key Unit of Modulating Liver to Treat Hyperlipemia, State Administration of Traditional Chinese Medicine, Institute of Chinese Medicine, Guangdong Pharmaceutical University, Guangzhou, 510006, China
| | - Zijian Liu
- Department of Emergency, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510080, China; NHC Key Laboratory of Assisted Circulation and Vascular Diseases (Sun Yat-sen University), Guangzhou, 510080, China
| | - Quqian Mo
- Guangdong Metabolic Diseases Research Center of Integrated Chinese and Western Medicine, Key Laboratory of Glycolipid Metabolic Disorder, Ministry of Education of China, Guangdong TCM Key Laboratory for Metabolic Diseases, Key Unit of Modulating Liver to Treat Hyperlipemia, State Administration of Traditional Chinese Medicine, Institute of Chinese Medicine, Guangdong Pharmaceutical University, Guangzhou, 510006, China
| | - Hui Fan
- Guangdong Metabolic Diseases Research Center of Integrated Chinese and Western Medicine, Key Laboratory of Glycolipid Metabolic Disorder, Ministry of Education of China, Guangdong TCM Key Laboratory for Metabolic Diseases, Key Unit of Modulating Liver to Treat Hyperlipemia, State Administration of Traditional Chinese Medicine, Institute of Chinese Medicine, Guangdong Pharmaceutical University, Guangzhou, 510006, China
| | - Keke Wang
- Department of Emergency, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510080, China; NHC Key Laboratory of Assisted Circulation and Vascular Diseases (Sun Yat-sen University), Guangzhou, 510080, China.
| | - Lexun Wang
- Guangdong Metabolic Diseases Research Center of Integrated Chinese and Western Medicine, Key Laboratory of Glycolipid Metabolic Disorder, Ministry of Education of China, Guangdong TCM Key Laboratory for Metabolic Diseases, Key Unit of Modulating Liver to Treat Hyperlipemia, State Administration of Traditional Chinese Medicine, Institute of Chinese Medicine, Guangdong Pharmaceutical University, Guangzhou, 510006, China.
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Cheemalavagu N, Shoger KE, Cao YM, Michalides BA, Botta SA, Faeder JR, Gottschalk RA. Predicting gene-level sensitivity to JAK-STAT signaling perturbation using a mechanistic-to-machine learning framework. Cell Syst 2024; 15:37-48.e4. [PMID: 38198893 PMCID: PMC10812086 DOI: 10.1016/j.cels.2023.12.006] [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: 05/01/2023] [Revised: 09/30/2023] [Accepted: 12/15/2023] [Indexed: 01/12/2024]
Abstract
The Janus kinase (JAK)-signal transducer and activator of transcription (STAT) pathway integrates complex cytokine signals via a limited number of molecular components, inspiring numerous efforts to clarify the diversity and specificity of STAT transcription factor function. We developed a computational framework to make global cytokine-induced gene predictions from STAT phosphorylation dynamics, modeling macrophage responses to interleukin (IL)-6 and IL-10, which signal through common STATs, but with distinct temporal dynamics and contrasting functions. Our mechanistic-to-machine learning model identified cytokine-specific genes associated with late pSTAT3 time frames and a preferential pSTAT1 reduction upon JAK2 inhibition. We predicted and validated the impact of JAK2 inhibition on gene expression, identifying genes that were sensitive or insensitive to JAK2 variation. Thus, we successfully linked STAT signaling dynamics to gene expression to support future efforts targeting pathology-associated STAT-driven gene sets. This serves as a first step in developing multi-level prediction models to understand and perturb gene expression outputs from signaling systems. A record of this paper's transparent peer review process is included in the supplemental information.
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Affiliation(s)
- Neha Cheemalavagu
- Department of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Department of Immunology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Center for Systems Immunology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Karsen E Shoger
- Department of Immunology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Center for Systems Immunology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Yuqi M Cao
- Department of Immunology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Center for Systems Immunology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Brandon A Michalides
- Department of Immunology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Center for Systems Immunology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Samuel A Botta
- Department of Immunology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Center for Systems Immunology, University of Pittsburgh, Pittsburgh, PA, USA
| | - James R Faeder
- Department of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Center for Systems Immunology, University of Pittsburgh, Pittsburgh, PA, USA.
| | - Rachel A Gottschalk
- Department of Immunology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Center for Systems Immunology, University of Pittsburgh, Pittsburgh, PA, USA.
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Duan J, Zhao Q, He Z, Tang S, Duan J, Xing W. Current understanding of macrophages in intracranial aneurysm: relevant etiological manifestations, signaling modulation and therapeutic strategies. Front Immunol 2024; 14:1320098. [PMID: 38259443 PMCID: PMC10800944 DOI: 10.3389/fimmu.2023.1320098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Accepted: 12/18/2023] [Indexed: 01/24/2024] Open
Abstract
Macrophages activation and inflammatory response play crucial roles in intracranial aneurysm (IA) formation and progression. The outcome of ruptured IA is considerably poor, and the mechanisms that trigger IA progression and rupture remain to be clarified, thereby developing effective therapy to prevent subarachnoid hemorrhage (SAH) become difficult. Recently, climbing evidences have been expanding our understanding of the macrophages relevant IA pathogenesis, such as immune cells population, inflammatory activation, intra-/inter-cellular signaling transductions and drug administration responses. Crosstalk between macrophages disorder, inflammation and cellular signaling transduction aggravates the devastating consequences of IA. Illustrating the pros and cons mechanisms of macrophages in IA progression are expected to achieve more efficient treatment interventions. In this review, we summarized the current advanced knowledge of macrophages activation, infiltration, polarization and inflammatory responses in IA occurrence and development, as well as the most relevant NF-κB, signal transducer and activator of transcription 1 (STAT1) and Toll-Like Receptor 4 (TLR4) regulatory signaling modulation. The understanding of macrophages regulatory mechanisms is important for IA patients' clinical outcomes. Gaining insight into the macrophages regulation potentially contributes to more precise IA interventions and will also greatly facilitate the development of novel medical therapy.
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Affiliation(s)
- Jian Duan
- Department of Cerebrovascular Disease, Suining Central Hospital, Suining, Sichuan, China
| | - Qijie Zhao
- Department of Cerebrovascular Disease, Suining Central Hospital, Suining, Sichuan, China
- Department of Pharmacy, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Zeyuan He
- Department of Cerebrovascular Disease, Suining Central Hospital, Suining, Sichuan, China
| | - Shuang Tang
- Department of Cerebrovascular Disease, Suining Central Hospital, Suining, Sichuan, China
| | - Jia Duan
- Department of Cerebrovascular Disease, Suining Central Hospital, Suining, Sichuan, China
| | - Wenli Xing
- Department of Cerebrovascular Disease, Suining Central Hospital, Suining, Sichuan, China
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Dong Y, Chen J, Chen Y, Liu S. Targeting the STAT3 oncogenic pathway: Cancer immunotherapy and drug repurposing. Biomed Pharmacother 2023; 167:115513. [PMID: 37741251 DOI: 10.1016/j.biopha.2023.115513] [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: 07/05/2023] [Revised: 09/09/2023] [Accepted: 09/12/2023] [Indexed: 09/25/2023] Open
Abstract
Immune effector cells in the microenvironment tend to be depleted or remodeled, unable to perform normal functions, and even promote the malignant characterization of tumors, resulting in the formation of immunosuppressive microenvironments. The strategy of reversing immunosuppressive microenvironment has been widely used to enhance the tumor immunotherapy effect. Signal transducer and activator of transcription 3 (STAT3) was found to be a crucial regulator of immunosuppressive microenvironment formation and activation as well as a factor, stimulating tumor cell proliferation, survival, invasiveness and metastasis. Therefore, regulating the immune microenvironment by targeting the STAT3 oncogenic pathway might be a new cancer therapy strategy. This review discusses the pleiotropic effects of STAT3 on immune cell populations that are critical for tumorigenesis, and introduces the novel strategies targeting STAT3 oncogenic pathway for cancer immunotherapy. Lastly, we summarize the conventional drugs used in new STAT3-targeting anti-tumor applications.
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Affiliation(s)
- Yushan Dong
- Graduate School of Heilongjiang University of Chinese Medicine, No. 24, Heping Road, Xiangfang District, Harbin, Heilongjiang, China
| | - Jingyu Chen
- Department of Chinese Medicine Internal Medicine, Xiyuan Hospital, China Academy of Chinese Medical Sciences, No. 1 Xiyuan Playground, Haidian District, Beijing, China
| | - Yuhan Chen
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Songjiang Liu
- The First Affiliated Hospital of Heilongjiang University of Chinese Medicine, No.26, Heping Road, Xiangfang District, Harbin, Heilongjiang Province, China.
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Cheemalavagu N, Shoger KE, Cao YM, Michalides BA, Botta SA, Faeder JR, Gottschalk RA. Predicting gene level sensitivity to JAK-STAT signaling perturbation using a mechanistic-to-machine learning framework. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.19.541151. [PMID: 37292918 PMCID: PMC10245690 DOI: 10.1101/2023.05.19.541151] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
The JAK-STAT pathway integrates complex cytokine signals via a limited number of molecular components, inspiring numerous efforts to clarify the diversity and specificity of STAT transcription factor function. We developed a computational workflow to make global cytokine-induced gene predictions from STAT phosphorylation dynamics, modeling macrophage responses to IL-6 and IL-10, which signal through common STATs, but with distinct temporal dynamics and contrasting functions. Our mechanistic-to-machine learning model identified select cytokine-induced gene sets associated with late pSTAT3 timeframes and a preferential pSTAT1 reduction upon JAK2 inhibition. We predicted and validated the impact of JAK2 inhibition on gene expression, identifying dynamically regulated genes that were sensitive or insensitive to JAK2 variation. Thus, we successfully linked STAT signaling dynamics to gene expression to support future efforts targeting pathology-associated STAT-driven gene sets. This serves as a first step in developing multi-level prediction models to understand and perturb gene expression outputs from signaling systems.
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Affiliation(s)
- Neha Cheemalavagu
- University of Pittsburgh, Department of Computational and Systems Biology, University of Pittsburgh School of Medicine, University of Pittsburgh, Pittsburgh, PA USA
- University of Pittsburgh, Department of Immunology, University of Pittsburgh School of Medicine, University of Pittsburgh, Pittsburgh, PA USA
- Center for Systems Immunology, University of Pittsburgh, Pittsburgh, PA USA
| | - Karsen E. Shoger
- University of Pittsburgh, Department of Immunology, University of Pittsburgh School of Medicine, University of Pittsburgh, Pittsburgh, PA USA
- Center for Systems Immunology, University of Pittsburgh, Pittsburgh, PA USA
| | - Yuqi M. Cao
- University of Pittsburgh, Department of Immunology, University of Pittsburgh School of Medicine, University of Pittsburgh, Pittsburgh, PA USA
- Center for Systems Immunology, University of Pittsburgh, Pittsburgh, PA USA
| | - Brandon A. Michalides
- University of Pittsburgh, Department of Immunology, University of Pittsburgh School of Medicine, University of Pittsburgh, Pittsburgh, PA USA
- Center for Systems Immunology, University of Pittsburgh, Pittsburgh, PA USA
| | - Samuel A. Botta
- University of Pittsburgh, Department of Immunology, University of Pittsburgh School of Medicine, University of Pittsburgh, Pittsburgh, PA USA
- Center for Systems Immunology, University of Pittsburgh, Pittsburgh, PA USA
| | - James R. Faeder
- University of Pittsburgh, Department of Computational and Systems Biology, University of Pittsburgh School of Medicine, University of Pittsburgh, Pittsburgh, PA USA
- Center for Systems Immunology, University of Pittsburgh, Pittsburgh, PA USA
| | - Rachel A. Gottschalk
- University of Pittsburgh, Department of Immunology, University of Pittsburgh School of Medicine, University of Pittsburgh, Pittsburgh, PA USA
- Center for Systems Immunology, University of Pittsburgh, Pittsburgh, PA USA
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Londoño AF, Scorpio DG, Dumler JS. Innate immunity in rickettsial infections. Front Cell Infect Microbiol 2023; 13:1187267. [PMID: 37228668 PMCID: PMC10203653 DOI: 10.3389/fcimb.2023.1187267] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Accepted: 04/19/2023] [Indexed: 05/27/2023] Open
Abstract
Rickettsial agents are a diverse group of alpha-proteobacteria within the order Rickettsiales, which possesses two families with human pathogens, Rickettsiaceae and Anaplasmataceae. These obligate intracellular bacteria are most frequently transmitted by arthropod vectors, a first step in the pathogens' avoidance of host cell defenses. Considerable study of the immune responses to infection and those that result in protective immunity have been conducted. Less study has focused on the initial events and mechanism by which these bacteria avoid the innate immune responses of the hosts to survive within and propagate from host cells. By evaluating the major mechanisms of evading innate immunity, a range of similarities among these bacteria become apparent, including mechanisms to escape initial destruction in phagolysosomes of professional phagocytes, those that dampen the responses of innate immune cells or subvert signaling and recognition pathways related to apoptosis, autophagy, proinflammatory responses, and mechanisms by which these microbes attach to and enter cells or those molecules that trigger the host responses. To illustrate these principles, this review will focus on two common rickettsial agents that occur globally, Rickettsia species and Anaplasma phagocytophilum.
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Affiliation(s)
- Andrés F. Londoño
- The Henry M. Jackson Foundation for Advancement in Military Medicine, Bethesda, MD, United States
- Department of Pathology, School of Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD, United States
| | - Diana G. Scorpio
- Host-Pathogen Interactions Program, Texas Biomedical Research Institute, San Antonio, TX, United States
| | - J. Stephen Dumler
- Department of Pathology, School of Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD, United States
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Xia T, Zhang M, Lei W, Yang R, Fu S, Fan Z, Yang Y, Zhang T. Advances in the role of STAT3 in macrophage polarization. Front Immunol 2023; 14:1160719. [PMID: 37081874 PMCID: PMC10110879 DOI: 10.3389/fimmu.2023.1160719] [Citation(s) in RCA: 37] [Impact Index Per Article: 37.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Accepted: 03/27/2023] [Indexed: 04/22/2023] Open
Abstract
The physiological processes of cell growth, proliferation, differentiation, and apoptosis are closely related to STAT3, and it has been demonstrated that aberrant STAT3 expression has an impact on the onset and progression of a number of inflammatory immunological disorders, fibrotic diseases, and malignancies. In order to produce the necessary biological effects, macrophages (M0) can be polarized into pro-inflammatory (M1) and anti-inflammatory (M2) types in response to various microenvironmental stimuli. STAT3 signaling is involved in macrophage polarization, and the research of the effect of STAT3 on macrophage polarization has gained attention in recent years. In order to provide references for the treatment and investigation of disorders related to macrophage polarization, this review compiles the pertinent signaling pathways associated with STAT3 and macrophage polarization from many fundamental studies.
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Affiliation(s)
- Tingting Xia
- Key Laboratory of Cell Engineering of Guizhou Province, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou, China
- Department of Dermatology, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou, China
| | - Meng Zhang
- Key Laboratory of Cell Engineering of Guizhou Province, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou, China
| | - Wei Lei
- Department of Dermatology, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou, China
| | - Ruilin Yang
- Key Laboratory of Cell Engineering of Guizhou Province, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou, China
| | - Shengping Fu
- Key Laboratory of Cell Engineering of Guizhou Province, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou, China
| | - Zhenhai Fan
- Key Laboratory of Cell Engineering of Guizhou Province, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou, China
- The Clinical Stem Cell Research Institute, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou, China
| | - Ying Yang
- Department of Dermatology, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou, China
| | - Tao Zhang
- Key Laboratory of Cell Engineering of Guizhou Province, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou, China
- Department of Dermatology, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou, China
- The Clinical Stem Cell Research Institute, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou, China
- *Correspondence: Tao Zhang,
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The JAK-STAT pathway at 30: Much learned, much more to do. Cell 2022; 185:3857-3876. [PMID: 36240739 PMCID: PMC9815833 DOI: 10.1016/j.cell.2022.09.023] [Citation(s) in RCA: 219] [Impact Index Per Article: 109.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Revised: 09/01/2022] [Accepted: 09/14/2022] [Indexed: 11/24/2022]
Abstract
The discovery of the Janus kinase (JAK)-signal transducer and activator of transcription (STAT) pathway arose from investigations of how cells respond to interferons (IFNs), revealing a paradigm in cell signaling conserved from slime molds to mammals. These discoveries revealed mechanisms underlying rapid gene expression mediated by a wide variety of extracellular polypeptides including cytokines, interleukins, and related factors. This knowledge has provided numerous insights into human disease, from immune deficiencies to cancer, and was rapidly translated to new drugs for autoimmune, allergic, and infectious diseases, including COVID-19. Despite these advances, major challenges and opportunities remain.
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