Tumor necrosis factor α–induced proteins: Natural brakes on inflammation

Jacques, Peggy; Elewaut, Dirk

doi:10.1002/art.34664

Cited by 12 publications

(10 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Accumulating evidence supports PGRN’s anti-inflammatory role in various disease conditions[10, 11, 56–59], but its exact mechanisms need to be better elucidated. Our findings suggest that PGRN recruits A20, which providing a natural brake on inflammation[60], and blocks the production of type I IFNs and proinflammatory cytokines. This represents a novel mechanism of the anti-inflammatory function of PGRN.…”

Section: Discussionmentioning

confidence: 99%

Induction of PGRN by influenza virus inhibits the antiviral immune responses through downregulation of type I interferons signaling

Wei¹,

Jiang²,

Sun³

et al. 2019

PLoS Pathog

View full text Add to dashboard Cite

Type I interferons (IFNs) play a critical role in host defense against influenza virus infection, and the mechanism of influenza virus to evade type I IFNs responses remains to be fully understood. Here, we found that progranulin (PGRN) was significantly increased both in vitro and in vivo during influenza virus infection. Using a PGRN knockdown assay and PGRN-deficient mice model, we demonstrated that influenza virus-inducing PGRN negatively regulated type I IFNs production by inhibiting the activation of NF-κB and IRF3 signaling. Furthermore, we showed that PGRN directly interacted with NF-κB essential modulator (NEMO) via its Grn CDE domains. We also verified that PGRN recruited A20 to deubiquitinate K63-linked polyubiquitin chains on NEMO at K264. In addition, we found that macrophage played a major source of PGRN during influenza virus infection, and PGRN neutralizing antibodies could protect against influenza virus-induced lethality in mice. Our data identify a PGRN-mediated IFN evasion pathway exploited by influenza virus with implication in antiviral applications. These findings also provide insights into the functions and crosstalk of PGRN in innate immunity.

show abstract

Section: Discussionmentioning

confidence: 99%

Induction of PGRN by influenza virus inhibits the antiviral immune responses through downregulation of type I interferons signaling

Wei¹,

Jiang²,

Sun³

et al. 2019

PLoS Pathog

View full text Add to dashboard Cite

show abstract

“…The identified DEGs not only confirmed some previous research findings, but also provided new findings. For example, TNFAIP, a well-known tumor α-induced protein that acts as a natural brake on inflammation, was found to be upregulated in this KIRC research [26]. Another DEG, SLC6A3, which has already been implicated in lung and breast cancer, was here found to be involved in KIRC for the first time [27, 28].…”

Section: Discussionmentioning

confidence: 78%

Identifying prognostic biomarkers based on aberrant DNA methylation in kidney renal clear cell carcinoma

Chen

Wang

et al. 2016

Oncotarget

View full text Add to dashboard Cite

The outcome of kidney renal clear cell carcinoma (KIRC) differs even among individuals with similar clinical characteristics. DNA methylation is regarded as a regulator of gene expression in cancers, which may be a molecular marker of prognosis. In this study, we aimed to mine novel methylation markers of the prognosis of KIRC. We revealed a total of 2793 genes differentially methylated in their promoter regions (DMGs) and 2979 differentially expressed genes (DEGs) in KIRC tissues compared with normal tissues using The Cancer Genome Atlas datasets. Then, we detected 57 and 34 subpathways enriched among the DMGs and DEGs, respectively, using the R package iSubpathwayMiner. We retained 56 subpathways related to both aberrant methylation and expression based on a hypergeometric test for further analysis. An integrated gene regulatory network was constructed using the regulatory relationships between genes in the subpathways. Using the top 15% of the nodes from the network ranked by degree, survival analysis was performed. We validated four DNA methylation signatures (RAC2, PLCB2, VAV1, and PARVG) as being highly correlated with prognosis in KIRC. These findings suggest that DNA methylation might become a prognostic predictor in KIRC and could supplement histological prognostic prediction.

show abstract

“…These differentially expressed genes not only confirmed some previous research findings but also provided new findings. For example, TNFAIP , a known tumour α -induced protein that acts as a natural brake on inflammation [ 10 ], was up-regulated in KIRC in the analysis. Another differentially expressed gene, SLC6A3 , which is implicated in lung and breast cancer [ 11 , 12 ], has not yet been well known in KIRC.…”

Section: Resultsmentioning

confidence: 99%

Identification of genes and pathways involved in kidney renal clear cell carcinoma

et al. 2014

View full text Add to dashboard Cite

BackgroundKidney Renal Clear Cell Carcinoma (KIRC) is one of fatal genitourinary diseases and accounts for most malignant kidney tumours. KIRC has been shown resistance to radiotherapy and chemotherapy. Like many types of cancers, there is no curative treatment for metastatic KIRC. Using advanced sequencing technologies, The Cancer Genome Atlas (TCGA) project of NIH/NCI-NHGRI has produced large-scale sequencing data, which provide unprecedented opportunities to reveal new molecular mechanisms of cancer. We combined differentially expressed genes, pathways and network analyses to gain new insights into the underlying molecular mechanisms of the disease development.ResultsFollowed by the experimental design for obtaining significant genes and pathways, comprehensive analysis of 537 KIRC patients' sequencing data provided by TCGA was performed. Differentially expressed genes were obtained from the RNA-Seq data. Pathway and network analyses were performed. We identified 186 differentially expressed genes with significant p-value and large fold changes (P < 0.01, |log(FC)| > 5). The study not only confirmed a number of identified differentially expressed genes in literature reports, but also provided new findings. We performed hierarchical clustering analysis utilizing the whole genome-wide gene expressions and differentially expressed genes that were identified in this study. We revealed distinct groups of differentially expressed genes that can aid to the identification of subtypes of the cancer. The hierarchical clustering analysis based on gene expression profile and differentially expressed genes suggested four subtypes of the cancer. We found enriched distinct Gene Ontology (GO) terms associated with these groups of genes. Based on these findings, we built a support vector machine based supervised-learning classifier to predict unknown samples, and the classifier achieved high accuracy and robust classification results. In addition, we identified a number of pathways (P < 0.04) that were significantly influenced by the disease. We found that some of the identified pathways have been implicated in cancers from literatures, while others have not been reported in the cancer before. The network analysis leads to the identification of significantly disrupted pathways and associated genes involved in the disease development. Furthermore, this study can provide a viable alternative in identifying effective drug targets.ConclusionsOur study identified a set of differentially expressed genes and pathways in kidney renal clear cell carcinoma, and represents a comprehensive computational approach to analysis large-scale next-generation sequencing data. The pathway and network analyses suggested that information from distinctly expressed genes can be utilized in the identification of aberrant upstream regulators. Identification of distinctly expressed genes and altered pathways are important in effective biomarker identification for early cancer diagnosis and treatment planning. Combining differentially expressed genes with...

show abstract

Tumor necrosis factor α–induced proteins: Natural brakes on inflammation

Cited by 12 publications

References 18 publications

Induction of PGRN by influenza virus inhibits the antiviral immune responses through downregulation of type I interferons signaling

Induction of PGRN by influenza virus inhibits the antiviral immune responses through downregulation of type I interferons signaling

Identifying prognostic biomarkers based on aberrant DNA methylation in kidney renal clear cell carcinoma

Identification of genes and pathways involved in kidney renal clear cell carcinoma

Contact Info

Product

Resources

About