scholarly journals A Novel Mechanism of Action of Histone Deacetylase Inhibitor Chidamide: Enhancing the Chemotaxis Function of Circulating PD-1(+) Cells From Patients With PTCL

2021 ◽  
Vol 11 ◽  
Author(s):  
Chong Wei ◽  
Shaoxuan Hu ◽  
Mingjie Luo ◽  
Chong Chen ◽  
Wei Wang ◽  
...  
Keyword(s):  
Signaling Pathways ◽  
Histone Deacetylase ◽  
Cellular Response ◽  
Kegg Pathway ◽  
Checkpoint Inhibitors ◽  
Interleukin 1 ◽  
Innate Immune ◽  
Receptor Interaction ◽  
Gene Concept ◽  
Concept Network

BackgroundPeripheral T‐cell lymphomas (PTCLs) are a heterogeneous group of neoplasms characterized by a poor prognosis. Histone deacetylase (HDAC) inhibitors have emerged as novel therapeutic agents for PTCLs. In this study, we aimed to explore the immunomodulatory effect of the HDAC inhibitor chidamide on circulating PD-1(+) cells from patients with PTCL, as well as its correlation with treatment response.MethodsWe enrolled newly diagnosed patients with PTCLs treated with a combination of chidamide and chemotherapy. Gene expression profile analysis was performed on peripheral blood PD-1(+) cells, both at baseline and at the end of treatment. A list of differentially expressed genes (DEGs) was identified. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to annotate the biological implications of the DEGs. A gene concept network was constructed to identify the key DEGs for further PCR verification.ResultsA total of 302 DEGs were identified in the complete remission (CR) group, including 162 upregulated and 140 downregulated genes. In contrast, only 12 DEGs were identified in the non-CR group. GO analysis revealed that these upregulated DEGs were mainly involved in chemokine activity, cell chemotaxis, and cellular response to interleukin-1 and interferon-γ. Furthermore, KEGG pathway analysis showed that these DEGs were enriched in cytokine-cytokine receptor interaction and chemokine signaling pathways. The innate immune signaling pathways, including the Toll-like and NOD-like receptor signaling pathways, were also influenced. The gene concept network revealed that the key upregulated genes belonged to the C-C chemokine family.ConclusionOur results showed that chidamide treatment notably enhanced the expression of genes associated with chemokine activity and chemotaxis function of circulating PD-1(+) cells. By recruiting immune cells and improving the innate immune function of PD-1(+) cells, chidamide may reshape the tumor microenvironment to an anti-tumor phenotype and synergize with checkpoint inhibitors.

Transient membrane recruitment of IRAK-1 in response to LPS and IL-1β requires TNF R1

2008 ◽  
Vol 295 (2) ◽  
pp. C313-C323 ◽  
Author(s):  
Angelia Lockett ◽  
Mark G. Goebl ◽  
Maureen A. Harrington
Keyword(s):  
Gene Expression ◽  
Immune Response ◽  
Plasma Membrane ◽  
Innate Immune Response ◽  
Cellular Response ◽  
Interleukin 1 ◽  
Innate Immune ◽  
Variable Response ◽  
Membrane Recruitment ◽  
Tnf Α

The transcription factor NF-κB is an essential regulator of the innate immune response that functions as the first line of defense against infections. Activation of the innate immune response by bacterial lipopolysaccharide (LPS) triggers production of tumor necrosis factor-α (TNF-α) followed by interleukin-1 (IL-1). The IL-1 receptor associated kinase-1 (IRAK-1) is an integral component of the LPS, TNF-α, and IL-1 signaling pathways that regulate NF-κB. Thus we hypothesized that IRAK-1 coordinates cellular NF-κB responses to LPS, TNF-α, and IL-1. In contrast to TNF-α where IRAK-1 subcellular localization does not change, treatment with LPS or IL-1 leads to a loss in cytoplasmic IRAK-1 with a coordinate increase in plasma membrane associated modified IRAK-1. In fibroblasts lacking the type 1 TNF-α receptor (TNF R1), IRAK-1 turnover is altered and modification of IRAK-1 in the plasma membrane is decreased in response to LPS and IL-1, respectively. When NF-κB controlled gene expression is measured, fibroblasts lacking TNF R1 are hyperresponsive to LPS, whereas a more variable response to IL-1 is seen. Further analysis of the LPS response revealed that plasma membrane-associated IRAK-1 is found in Toll 4, IL-1, and TNF R1-containing complexes. The data presented herein suggest a model whereby the TNF R1-IRAK-1 interaction integrates the cellular response to LPS, TNF-α, and IL-1, culminating in a cell poised to activate TNF-α-dependent NF-κB controlled gene expression. In the absence of TNF R1-dependent events, exposure to LPS or IL-1 leads to hyperactivation of the inflammatory response.

scholarly journals Construction and analysis of the abnormal lncRNA-miRNA-mRNA network in hypoxic pulmonary hypertension

2021 ◽  
Author(s):  
Jie Liu ◽  
Yishu Deng ◽  
Zeqin Fan ◽  
Shuanglan Xu ◽  
Li Wei ◽  
...  
Keyword(s):  
Pulmonary Hypertension ◽  
Cellular Response ◽  
High Throughput Sequencing ◽  
Interleukin 1 ◽  
Signalling Pathway ◽  
Receptor Interaction ◽  
Hypoxic Pulmonary Hypertension ◽  
Hypoxia Exposure ◽  
Receptor Signalling ◽  
Non Coding Rnas

The incidence of hypoxic pulmonary hypertension (HPH) is increasing. Accumulating evidence suggests that long non-coding RNAs (lncRNAs) play an important role in HPH, but the functions and mechanism have yet to be fully elucidated. In this study, we established an HPH rat model with 8 h of hypoxia exposure (10% O2) per day for 21 days. High-throughput sequencing identified 60 differently expressed (DE) lncRNAs, 20 DE miRNAs and 695 DE mRNAs in rat lung tissue. qRT-PCR verified the accuracy of the results. Immune response, inflammatory response, leukocyte migration, cell cycle, cellular response to interleukin-1, IL-17 signalling pathway, cytokine-cytokine receptor interaction and Toll-like receptor signalling pathway were significantly enriched in DE mRNAs. According to the theory of competing endogenous RNA (ceRNA) networks, lncRNA-miRNA-mRNA network was constructed by Cytoscape software, including 7 lncRNAs, 16 miRNAs and 144 mRNAs. The results suggested that seven DE lncRNAs (Ly6l, AABR07038849.2, AABR07069008.2, AABR07064873.1, AABR07001382.1, AABR07068161.1 and AABR07060341.2) could serve as molecular sponges of the corresponding miRNAs and play a major role in HPH.

scholarly journals Identification of differentially expressed genes and signaling pathways in rheumatoid arthritis by integrated bioinformatics analysis

2020 ◽  
Author(s):  
Yanzhi Ge ◽  
Li Zhou ◽  
Zuxiang Chen ◽  
Yingying Mao ◽  
Ting Li ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Signaling Pathways ◽  
Differentially Expressed Genes ◽  
Molecular Mechanisms ◽  
Bioinformatics Analysis ◽  
Kegg Pathway ◽  
Differentially Expressed ◽  
Receptor Interaction ◽  
Effective Prevention ◽  
Ppi Networks

Abstract Background The disability rate associated with rheumatoid arthritis (RA) ranks high among inflammatory joint diseases. However, the cause and potential molecular events are as yet not clear. Here, we aimed to identify key genes and pathways involved in RA utilizing integrated bioinformatics analysis and uncover underlying molecular mechanisms. Materials and methods The expression profiles of GSE55235, GSE55457, GSE55584 and GSE77298 were downloaded from the Gene Expression Omnibus database, which contained 76 synovial membrane samples, including 49 RA samples and 27 controls. The microarray datasets were consolidated and differentially expressed genes (DEGs) were acquired and further analyzed by bioinformatics techniques. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of DEGs were performed using R (version 3.6.1), respectively. The protein-protein interaction (PPI) networks of DEGs were developed utilizing the STRING database. Results A total of 828 DEGs were recognized, with 758 up-regulated and 70 down-regulated. GO and KEGG pathway analyses demonstrated that these DEGs focused primarily on multifactorial binding, transcription activity, cytokin-cytokin receptor interaction and relevant signaling pathways. The 30 most firmly related genes among DEGs were identified from the PPI network. Conclusion This study shows that screening for DEGs and pathways utilizing integrated bioinformatics analyses could aid in the comprehension of the molecular mechanisms involved in RA development. In addition, our study provides valuable data for the effective prevention, diagnosis, treatment and rehabilitation of RA patients as well as providing potential targets for the treatment of RA.

Comprehensive analysis of long noncoding RNAs and mRNAs expression profiles and functional networks during chondrogenic differentiation of murine ATDC5 cells

2019 ◽  
Vol 51 (8) ◽  
pp. 778-790
Author(s):  
Wei Wang ◽  
Yu Ding ◽  
Yanhua Xu ◽  
Hefeng Yang ◽  
Wenjing Liu ◽  
...  
Keyword(s):  
Signaling Pathways ◽  
Pathway Analysis ◽  
Chondrogenic Differentiation ◽  
Kegg Pathway ◽  
Expression Profiles ◽  
Noncoding Rnas ◽  
Long Noncoding Rnas ◽  
Receptor Interaction ◽  
Messenger Rnas ◽  
Kegg Pathway Analysis

AbstractChondrogenic differentiation is a coordinated biological process orchestrated by various cell signaling pathways, involving complex pathways regulated at both transcriptional and post-transcriptional levels. Long noncoding RNAs (lncRNAs) are emerging as important regulators in the modulation of multiple cell processes. However, the potential roles of lncRNAs and their regulatory mechanisms in chondrogenic differentiation remain largely unclear. In this study, microarray was performed to detect the expression profiles of lncRNAs and messenger RNAs (mRNAs) during chondrogenic differentiation of murine chondrogenic cell line ATDC5. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed to explore their functions. Coding-noncoding co-expression (CNC) and competing endogenous RNA (ceRNA) networks were also constructed with bioinformatics methods. The results revealed that 1009 lncRNAs and 1206 mRNAs were differentially regulated during chondrogenic differentiation. GO and KEGG pathway analysis indicated that the principal functions of the transcripts were associated with system development and extracellular matrix-receptor interaction, TGF-β signaling, and PI3K-Akt signaling pathways. The CNC network showed that lncRNA AK136902 was positively correlated with prostaglandin F receptor (FP). The ceRNA network covered 3 lncRNAs, 121 miRNAs and 241 edges. The upregulated lncRNA AK136902, AK016344, and ENSMUST00000180767 might promote chondrogenic differentiation by acting as ceRNAs. Knockdown of lncRNA AK136902 could inhibit the mRNA expression of FP and other chondrogenic related genes, including Aggrecan and Col2a1 during chondrogenic differentiation. Our results provide a new perspective on the modulation of lncRNAs during chondrogenic differentiation.

scholarly journals From Oncogenic Signaling Pathways to Single-Cell Sequencing of Immune Cells: Changing the Landscape of Cancer Immunotherapy

Molecules ◽  
2021 ◽  
Vol 26 (8) ◽  
pp. 2278
Author(s):  
Afshin Derakhshani ◽  
Zeinab Rostami ◽  
Hossein Safarpour ◽  
Mahdi Abdoli Shadbad ◽  
Niloufar Sadat Nourbakhsh ◽  
...  
Keyword(s):  
Single Cell ◽  
Signaling Pathways ◽  
Immune Cells ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Cancer Development ◽  
Immune Checkpoints ◽  
Single Cell Sequencing ◽  
Increased Risk

Over the past decade, there have been remarkable advances in understanding the signaling pathways involved in cancer development. It is well-established that cancer is caused by the dysregulation of cellular pathways involved in proliferation, cell cycle, apoptosis, cell metabolism, migration, cell polarity, and differentiation. Besides, growing evidence indicates that extracellular matrix signaling, cell surface proteoglycans, and angiogenesis can contribute to cancer development. Given the genetic instability and vast intra-tumoral heterogeneity revealed by the single-cell sequencing of tumoral cells, the current approaches cannot eliminate the mutating cancer cells. Besides, the polyclonal expansion of tumor-infiltrated lymphocytes in response to tumoral neoantigens cannot elicit anti-tumoral immune responses due to the immunosuppressive tumor microenvironment. Nevertheless, the data from the single-cell sequencing of immune cells can provide valuable insights regarding the expression of inhibitory immune checkpoints/related signaling factors in immune cells, which can be used to select immune checkpoint inhibitors and adjust their dosage. Indeed, the integration of the data obtained from the single-cell sequencing of immune cells with immune checkpoint inhibitors can increase the response rate of immune checkpoint inhibitors, decrease the immune-related adverse events, and facilitate tumoral cell elimination. This study aims to review key pathways involved in tumor development and shed light on single-cell sequencing. It also intends to address the shortcomings of immune checkpoint inhibitors, i.e., their varied response rates among cancer patients and increased risk of autoimmunity development, via applying the data from the single-cell sequencing of immune cells.

scholarly journals The Radiation-Induced Regenerative Response of Adult Tissue-Specific Stem Cells: Models and Signaling Pathways

Cancers ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 855
Author(s):  
Paola Serrano Martinez ◽  
Lorena Giuranno ◽  
Marc Vooijs ◽  
Robert P. Coppes
Keyword(s):  
Signaling Pathways ◽  
Progenitor Cells ◽  
Tissue Regeneration ◽  
Normal Tissue ◽  
Cellular Response ◽  
Adult Tissue ◽  
Tissue Specific ◽  
Radiation Induced

Radiotherapy is involved in the treatment of many cancers, but damage induced to the surrounding normal tissue is often inevitable. Evidence suggests that the maintenance of homeostasis and regeneration of the normal tissue is driven by specific adult tissue stem/progenitor cells. These tasks involve the input from several signaling pathways. Irradiation also targets these stem/progenitor cells, triggering a cellular response aimed at achieving tissue regeneration. Here we discuss the currently used in vitro and in vivo models and the involved specific tissue stem/progenitor cell signaling pathways to study the response to irradiation. The combination of the use of complex in vitro models that offer high in vivo resemblance and lineage tracing models, which address organ complexity constitute potential tools for the study of the stem/progenitor cellular response post-irradiation. The Notch, Wnt, Hippo, Hedgehog, and autophagy signaling pathways have been found as crucial for driving stem/progenitor radiation-induced tissue regeneration. We review how these signaling pathways drive the response of solid tissue-specific stem/progenitor cells to radiotherapy and the used models to address this.

scholarly journals AB0108 IRAK4 INHIBITION SUPPRESSES PROINFLAMMATORY CYTOKINE PRODUCTION FROM HUMAN MACROPHAGES STIMULATED WITH SYNOVIAL FLUID FROM RHEUMATOID ARTHRITIS PATIENTS

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 1353.2-1353
Author(s):  
A. Yadon ◽  
D. Ruelas ◽  
G. Min-Oo ◽  
J. Taylor ◽  
M. R. Warr
Keyword(s):  
Rheumatoid Arthritis ◽  
Synovial Fluid ◽  
Signaling Pathways ◽  
Proinflammatory Cytokines ◽  
Proinflammatory Cytokine ◽  
Cytokine Production ◽  
Interleukin 1 ◽  
Proinflammatory Cytokine Production ◽  
Human Macrophages ◽  
Percent Suppression

Background:Rheumatoid arthritis (RA) is characterized by chronic, uncontrolled joint inflammation and tissue destruction. Macrophages are thought to be key mediators in both the initiation and perpetuation of this pathology.1,2The RA synovium contains a complex inflammatory milieu that can stimulate macrophage-dependent production of proinflammatory cytokines through multiple signaling pathways.1,2Existing evidence indicates that toll-like receptors (TLRs) and interleukin-1 receptors (IL-1R) along with their agonists, damage-associated molecular patterns (DAMPs) and IL-1β, are highly expressed in RA joints and are important mediators of synovial macrophage activation and proinflammatory cytokine production.1-9IRAK4 (interleukin-1 receptor-associated kinase 4) is a serine/threonine kinase that facilitates TLR and IL-1R signaling in many cell types, including macrophages.10IRAK4 inhibition represents an opportunity to reduce proinflammatory cytokine production in the joints of patients with RA.Objectives:To investigate the effect of a highly selective IRAK4 inhibitor on proinflammatory cytokine production from human macrophages stimulated with synovial fluid from patients with RA.Methods:Primary human monocytes from 2 independent donors were differentiated for 6 days with granulocyte-macrophage colony-stimulating factor (GM-CSF) to generate human monocyte-derived macrophages (hMDMs). hMDMs were then pretreated with an IRAK4 inhibitor for 1 hour and subsequently stimulated for 24 hours with RA synovial fluid from 5 patients. Culture supernatants were then assessed for secretion of proinflammatory cytokines by MesoScale Discovery.Results:RA synovial fluid stimulation of hMDMs resulted in the production of several proinflammatory cytokines, including IL-6, IL-8, and TNFα. Pretreatment of hMDMs with an IRAK4 inhibitor resulted in the dose-dependent inhibition of IL-6, IL-8, and TNFα production, with an average EC50± SD of 27 ± 31, 26 ± 41, and 28 ± 22 nM, respectively. Maximal percent suppression ± SD of IL-6, IL-8, and TNFα were 76 ± 8.8, 73 ± 15, and 77 ± 13, respectively. To evaluate the specific IRAK4-dependent signaling pathways mediating this response, hMDMs were pretreated with inhibitors of TLR4 (TAK242) and IL-1R (IL-1RA) prior to stimulation with RA synovial fluid. Both TAK242 and IL-1RA inhibited proinflammatory cytokine production. For TAK242, maximal percent suppression ± SD of IL-6, IL-8, and TNFα were 39 ± 25, 48 ± 24, and 50 ± 21, respectively. For IL-1RA maximal percent suppression ± SD of IL-6, IL-8, and TNFα were 18 ± 18, 20 ± 23, and 16 ± 18, respectively. The broad range of inhibition across each stimulation highlights the complexity and variability in the signaling pathways mediating proinflammatory cytokine production from hMDMs stimulated with RA synovial fluid, but demonstrates that RA synovial fluid can stimulate proinflammatory cytokine production in hMDMs, at least partly, through IRAK4-dependent pathways.Conclusion:This work demonstrates that IRAK4 inhibition can suppress proinflammatory cytokine production from macrophages stimulated with synovial fluid from patients with RA and supports a potential pathophysiological role for IRAK4 in perpetuating chronic inflammation in RA.References:[1]Smolen JS, et al.Nat Rev Dis Primers.2018;4:18001.[2]Udalova IA, et al.Nat Rev Rheumatol.2016;12(8):472-485.[3]Joosten LAB, et al.Nat Rev Rheumatol.2016;12(6):344-357.[4]Huang QQ, Pope RM.Curr Rheumatol Rep.2009;11(5):357-364.[5]Roh JS, Sohn DH.Immune Netw.2018;18(4):e27.[6]Sacre SM, et al.Am J Pathol.2007;170(2):518-525.[7]Ultaigh SNA, et al.Arthritis Res Ther.2011;13(1):R33.[8]Bottini N, Firestein GS.Nat Rev Rheumatol.2013;9(1):24-33.[9]Firestein GS, McInnes IB.Immunity.2017;46(2):183-196.[10]Janssens S, Beyaert R.Mol Cell.2003;11(2):293-302.Disclosure of Interests:Adam Yadon Employee of: Gilead, Debbie Ruelas Employee of: Gilead, Gundula Min-Oo Employee of: Gilead, James Taylor Employee of: Gilead, Matthew R. Warr Employee of: Gilead

scholarly journals AB0005 IDENTIFICATION OF KEY GENES AND PATHWAYS FOR PSORIASIS BASED ON GEO DATABASES BY BIOINFORMATICS ANALYSIS

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 1037.2-1038
Author(s):  
X. Sun ◽  
S. X. Zhang ◽  
S. Song ◽  
T. Kong ◽  
C. Zheng ◽  
...  
Keyword(s):  
Gene Expression ◽  
Signaling Pathways ◽  
Differentially Expressed Genes ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Shanxi Province ◽  
Receptor Interaction ◽  
Term Therapy ◽  
Pathway Enrichment Analysis ◽  
Key Genes

Background:Psoriasis is an immune-mediated, genetic disease manifesting in the skin or joints or both, and also has a strong genetic predisposition and autoimmune pathogenic traits1. The hallmark of psoriasis is sustained inflammation that leads to uncontrolled keratinocyte proliferation and dysfunctional differentiation. And it’s also a chronic relapsing disease, which often necessitates a long-term therapy2.Objectives:To investigate the molecular mechanisms of psoriasis and find the potential gene targets for diagnosis and treating psoriasis.Methods:Total 334 gene expression data of patients with psoriasis research (GSE13355 GSE14905 and GSE30999) were obtained from the Gene Expression Omnibus database. After data preprocessing and screening of differentially expressed genes (DEGs) by R software. Online toll Metascape3 was used to analyze Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs. Interactions of proteins encoded by DEGs were discovered by Protein-protein interaction network (PPI) using STRING online software. Cytoscape software was utilized to visualize PPI and the degree of each DEGs was obtained by analyzing the topological structure of the PPI network.Results:A total of 611 DEGs were found to be differentially expressed in psoriasis. GO analysis revealed that up-regulated DEGs were mostly associated with defense and response to external stimulus while down-regulated DEGs were mostly associated with metabolism and synthesis of lipids. KEGG enrichment analysis suggested they were mainly enriched in IL-17 signaling, Toll-like receptor signaling and PPAR signaling pathways, Cytokine-cytokine receptor interaction and lipid metabolism. In addition, top 9 key genes (CXCL10, OASL, IFIT1, IFIT3, RSAD2, MX1, OAS1, IFI44 and OAS2) were identified through Cytoscape.Conclusion:DEGs of psoriasis may play an essential role in disease development and may be potential pathogeneses of psoriasis.References:[1]Boehncke WH, Schon MP. Psoriasis. Lancet 2015;386(9997):983-94. doi: 10.1016/S0140-6736(14)61909-7 [published Online First: 2015/05/31].[2]Zhang YJ, Sun YZ, Gao XH, et al. Integrated bioinformatic analysis of differentially expressed genes and signaling pathways in plaque psoriasis. Mol Med Rep 2019;20(1):225-35. doi: 10.3892/mmr.2019.10241 [published Online First: 2019/05/23].[3]Zhou Y, Zhou B, Pache L, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun 2019;10(1):1523. doi: 10.1038/s41467-019-09234-6 [published Online First: 2019/04/05].Acknowledgements:This project was supported by National Science Foundation of China (82001740), Open Fund from the Key Laboratory of Cellular Physiology (Shanxi Medical University) (KLCP2019) and Innovation Plan for Postgraduate Education in Shanxi Province (2020BY078).Disclosure of Interests:None declared

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