Tumor necrosis factor α-induced proteins: natural brakes on inflammation

Differences in expression of tumor suppressor, innate immune, inflammasome, and potassium/gap junction channel host genes significantly predict viral reservoir size during treated HIV infection

The major barrier to an HIV cure is the persistence of infected cells that evade host immune surveillance despite effective antiretroviral therapy (ART). Most prior host genetic HIV studies have focused on identifying DNA polymorphisms (e.g., CCR5Δ32 , MHC class I alleles) associated with viral load among untreated "elite controllers" (~1% of HIV+ individuals who are able to control virus without ART). However, there have been few studies evaluating host genetic predictors of viral control for the majority of people living with HIV (PLWH) on ART. We performed host RNA sequencing and HIV reservoir quantification (total DNA, unspliced RNA, intact DNA) from peripheral CD4+ T cells from 191 HIV+ ART-suppressed non-controllers. Multivariate models included covariates for timing of ART initiation, nadir CD4+ count, age, sex, and ancestry. Lower HIV total DNA (an estimate of the total reservoir) was associated with upregulation of tumor suppressor genes NBL1 (q=0.012) and P3H3 (q=0.012). Higher HIV unspliced RNA (an estimate of residual HIV transcription) was associated with downregulation of several host genes involving inflammasome ( IL1A, CSF3, TNFAIP5, TNFAIP6, TNFAIP9 , CXCL3, CXCL10 ) and innate immune ( TLR7 ) signaling, as well as novel associations with potassium ( KCNJ2 ) and gap junction ( GJB2 ) channels, all q<0.05. Gene set enrichment analyses identified significant associations with TLR4/microbial translocation (q=0.006), IL-1β/NRLP3 inflammasome (q=0.008), and IL-10 (q=0.037) signaling. HIV intact DNA (an estimate of the "replication-competent" reservoir) demonstrated trends with thrombin degradation ( PLGLB1 ) and glucose metabolism ( AGL ) genes, but data were (HIV intact DNA detected in only 42% of participants). Our findings demonstrate that among treated PLWH, that inflammation, innate immune responses, bacterial translocation, and tumor suppression/cell proliferation host signaling play a key role in the maintenance of the HIV reservoir during ART. Further data are needed to validate these findings, including functional genomic studies, and expanded epidemiologic studies in female, non-European cohorts.

Author Summary

Although lifelong HIV antiretroviral therapy (ART) suppresses virus, the major barrier to an HIV cure is the persistence of infected cells that evade host immune surveillance despite effective ART, "the HIV reservoir." HIV eradication strategies have focused on eliminating residual virus to allow for HIV remission, but HIV cure trials to date have thus far failed to show a clinically meaningful reduction in the HIV reservoir. There is an urgent need for a better understanding of the host-viral dynamics during ART suppression to identify potential novel therapeutic targets for HIV cure. This is the first epidemiologic host gene expression study to demonstrate a significant link between HIV reservoir size and several well-known immunologic pathways (e.g., IL-1β, TLR7, TNF-α signaling pathways), as well as novel associations with potassium and gap junction channels (Kir2.1, connexin 26). Further data are needed to validate these findings, including functional genomic studies and expanded epidemiologic studies in female, non-European cohorts.

Pan-cancer analysis of oncogenic TNFAIP2 identifying its prognostic value and immunological function in acute myeloid leukemia

BACKGROUND

Tumor necrosis factor alpha-induced protein 2 (TNFAIP2), a TNFα-inducible gene, appears to participate in inflammation, immune response, hematopoiesis, and carcinogenesis. However, the potential role of TNFAIP2 in the development of acute myeloid leukemia (AML) remains unknow yet. Therefore, we aimed to study the biological role of TNFAIP2 in leukemogenesis.

METHODS

TNFAIP2 mRNA level, prognostic value, co-expressed genes, differentially expressed genes, DNA methylation, and functional enrichment analysis in AML patients were explored via multiple public databases, including UALCAN, GTEx portal, Timer 2.0, LinkedOmics, SMART, MethSurv, Metascape, GSEA and String databases. Data from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and Beat AML database were used to determine the associations between TNFAIP2 expression and various clinical or genetic parameters of AML patients. Moreover, the biological functions of TNFAIP2 in AML were investigated through in vitro experiments.

RESULTS

By large-scale data mining, our study indicated that TNFAIP2 was differentially expressed across different normal and tumor tissues. TNFAIP2 expression was significantly increased in AML, particularly in French-American-British (FAB) classification M4/M5 patients, compared with corresponding control tissues. Overexpression of TNFAIP2 was an independent poor prognostic factor of overall survival (OS) and was associated with unfavorable cytogenetic risk and gene mutations in AML patients. DNA hypermethylation of TNFAIP2 at gene body linked to upregulation of TNFAIP2 and inferior OS in AML. Functional enrichment analysis indicated immunomodulation function and inflammation response of TNFAIP2 in leukemogenesis. Finally, the suppression of TNFAIP resulted in inhibition of proliferation by altering cell-cycle progression and increase of cell death by promoting early and late apoptosis in THP-1 and U937AML cells.

CONCLUSION

Collectively, the oncogenic TNFAIP2 can function as a novel biomarker and prognostic factor in AML patients. The immunoregulation function of TNFAIP2 warrants further validation in AML.

TNFAIP8 modulates the survival and immune activity of Th17 cells via p53/ p21/ MDM2 pathway after acute insult

Th17 cells induced immunosuppression plays a vital role in sepsis. As a member of the tumor necrosis factor α induced protein 8 (TNFAIP8) family, TNFAIP8 is associated with different physiopathological conditions with immunological responses. However, its potential roles in regulating Th17 cells after the acute insult have not been fully elucidated. In this study, sepsis was induced by cecal ligation and puncture (CLP) in the male adult C57BL/6 mice. The stable TNFAIP8 knockdown (KD) Th17 cells were established by infecting with lentivirus carrying TNFAIP8-specific shRNA. CCK-8 assay was conducted to evaluate Th17 cell proliferation, and Annexin V/7-AAD assay was applied for apoptosis measurement by flow cytometry. The alterations of p53/ p21/ MDM2 pathway were assessed by Western blot. We observed that a high TNFAIP8 expression level was related to acute injury in septic mice. TNFAIP8 silencing suppressed Th17 cell proliferation and cytokine production in vivo and in vitro. In addition, TNFAIP8 KD increased Th17 cell apoptosis in septic mice. Furthermore, TNFAIP8 seems to affect the immune function of Th17 cells by regulating p53/ p21/ MDM2 signaling processes. We found that TNFAIP8 KD caused the up-regulation of P21 and MDM2, and also elevated p53 protein level during sepsis. Pharmacological inhibition of p53 partially rescued cell proliferation and apoptotic effects of TNFAIP8 KD. In summary, our work suggests that TNFAIP8 modulates the survival and immune function of Th17 cells after acute insult, which was possibly mediated through the p53/ p21/ MDM2 pathway.

Preparation and characterization of a fully human monoclonal antibody specific for human tumor necrosis factor alpha

Tumor necrosis factor alpha (TNFα) is an important inflammatory factor. It plays a cardinal role in inflammatory synovitis and articular matrix degradation, and is, therefore, a prime target for directed immunotherapy in autoimmune diseases. In this study, we screened and isolated the B cells secreting anti-TNFα antibody from patients with rheumatoid arthritis. The heavy-chain and light-chain sequences of the antibody were cloned and used to generate a stable Chinese hamster ovary (CHO) cell line producing the antibody, which was named Haidalimumab. Haidalimumab showed a TNFα binding affinity comparable to that of the antibody Humira, which is the best TNF inhibitor on the market. Furthermore, Haidalimumab could effectively neutralize recombinant human tumor necrosis factor alpha (rhTNFα) toxicity in a C57BL/6 mouse model and showed significant therapeutic effect in a tumor necrosis factor transgenic (TNF-Tg) mouse arthritis model. In conclusion, we developed a high-affinity, fully human anti-TNFα antibody with low immunogenicity that could potentially have significant therapeutic applications in rheumatoid arthritis or other autoimmune diseases.Abbreviations: ELISAenzyme linked immunosorbent assayRArheumatoid arthritisSDS-PAGEsodium dodecyl sulfate polyacrylamide gel electrophoresisrhTNFαrecombinant human tumor necrosis factor-alphaEC50concentration for 50% of maximal effectTNF-Tg micetumor necrosis factor transgenic miceAMDactinomycin DMTTmethylthiazolyldiphenyl-tetrazolium bromidePBSphosphate-buffered saline.

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

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.

The innate immune system is the first line of host defense against microbial infection, while viruses develop several strategies to evade the host defense. It is of great significance to explore the mechanism by which viruses to evade the antiviral host defense. Previous studies have found that progranulin (PGRN) plays an important role in a variety of physiologic and disease processes. Here, we demonstrated that PGRN induced by influenza virus negatively regulated type I IFN production by inhibiting the activation of NF-κB and IRF3 signaling. We further showed that PGRN directly interacted with NEMO via its Grn CDE domains and recruited A20 to deubiquitinate K63-linked polyubiquitin chains on NEMO. 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 findings highlight a new strategy whereby influenza virus to evade type I IFN-mediated antiviral immune response and also provide insights into the functions and crosstalk of PGRN in innate immunity.

Effects of HLA-B27 on Gut Microbiota in Experimental Spondyloarthritis Implicate an Ecological Model of Dysbiosis

OBJECTIVE

To investigate whether HLA-B27-mediated experimental spondyloarthritis (SpA) is associated with a common gut microbial signature, in order to identify potential drivers of pathogenesis.

METHODS

The effects of HLA-B27 on 3 genetic backgrounds, dark agouti (DA), Lewis, and Fischer, were compared, using wild-type littermates and HLA-B7-transgenic Lewis rats as controls. Cecum and colon tissue specimens or contents were collected from the rats at 2, 3-4, and 6-8 months of age, and histologic analysis was performed to assess inflammation, RNA sequencing was used to determine gene expression differences, and 16S ribosomal RNA gene sequencing was used to determine microbiota differences.

RESULTS

Both HLA-B27-transgenic Lewis rats and HLA-B27-transgenic Fischer rats developed gut inflammation, while DA rats were resistant to the effects of HLA-B27, and HLA-B7-transgenic rats were not affected. Immune dysregulation was similar in affected Lewis and Fischer rats and was dominated by activation of interleukin-23 (IL-23)/IL-17, interferon, tumor necrosis factor, and IL-1 cytokines and pathways in the colon and cecum, while DA rats exhibited low-level cytokine dysregulation without inflammation. Gut microbial changes in HLA-B27-transgenic rats were strikingly divergent on the 3 different host genetic backgrounds, including different patterns of dysbiosis in HLA-B27-transgenic Lewis and HLA-B27-transgenic Fischer rat strains, with some overlap. Interestingly, DA rats lacked segmented filamentous bacteria that promote CD4+ Th17 cell development, which may explain their resistance to disease.

CONCLUSION

The effects of HLA-B27 on gut microbiota and dysbiosis in SpA are highly dependent on the host genetic background and/or environment, despite convergence of dysregulated immune pathways. These results implicate an ecological model of dysbiosis, with the effects of multiple microbes contributing to the aberrant immune response, rather than a single or small number of microbes driving pathogenesis.

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

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.

Di-(2-ethylhexyl) phthalate suppresses IL-12p40 production by GM-CSF-dependent macrophages via the PPARα/TNFAIP3/TRAF6 axis after lipopolysaccharide stimulation

Activation of peroxisome proliferator-activated receptor α (PPARα) by di-(2-ethylhexyl) phthalate (DEHP) has an anti-inflammatory effect. This study investigated the potential combined influence of PPARα, tumor necrosis factor α-induced protein 3 (TNFAIP3/A20), and tumor necrosis factor receptor-associated factor 6 (TRAF6) on interleukin (IL)-12p40 production by macrophages exposed to DEHP and stimulated with lipopolysaccharide (LPS). LPS upregulated IL-12p40 expression by granulocyte-macrophage colony-stimulating factor-dependent macrophages (on day 9 of culture), whereas adding DEHP to cultures significantly attenuated the response of IL-12p40 to LPS stimulation. PPARα protein was also reduced by DEHP. Interestingly, transfection of macrophages with small interfering RNA (siRNA) duplexes for PPARα, TNFAIP3/A20, or dual oxidase 2 restored the response of IL-12p40 protein to LPS stimulation in the presence of DEHP. siRNAs for various protein kinase Cs (PKCs) (α, β, γ, or δ) also restored IL-12p40 production by macrophages exposed to LPS and DEHP. While LPS upregulated both IL-12p40 and TNFAIP3/A20 production, adding DEHP to cultures dramatically reduced IL-12p40 and TNFAIP3/A20 levels. Silencing of PKCα reduced TNFAIP3/A20 production, whereas PKCγ siRNA (but not PKCβ or δ siRNA) significantly increased TNFAIP3/A20. TRAF6 was also attenuated by macrophages with DEHP. The PPARα/TNFAIP3/TRAF6 axis may have an important role in the mechanism through which DEHP reduces IL-12p40 production by LPS-stimulated macrophages.

Multi-label multi-instance transfer learning for simultaneous reconstruction and cross-talk modeling of multiple human signaling pathways

BACKGROUND

Signaling pathways play important roles in the life processes of cell growth, cell apoptosis and organism development. At present the signal transduction networks are far from complete. As an effective complement to experimental methods, computational modeling is suited to rapidly reconstruct the signaling pathways at low cost. To our knowledge, the existing computational methods seldom simultaneously exploit more than three signaling pathways into one predictive model for the discovery of novel signaling components and the cross-talk modeling between signaling pathways.

RESULTS

In this work, we propose a multi-label multi-instance transfer learning method to simultaneously reconstruct 27 human signaling pathways and model their cross-talks. Computational results show that the proposed method demonstrates satisfactory multi-label learning performance and rational proteome-wide predictions. Some predicted signaling components or pathway targeted proteins have been validated by recent literature. The predicted signaling components are further linked to pathways using the experimentally derived PPIs (protein-protein interactions) to reconstruct the human signaling pathways. Thus the map of the cross-talks via common signaling components and common signaling PPIs is conveniently inferred to provide valuable insights into the regulatory and cooperative relationships between signaling pathways. Lastly, gene ontology enrichment analysis is conducted to gain statistical knowledge about the reconstructed human signaling pathways.

CONCLUSIONS

Multi-label learning framework has been demonstrated effective in this work to model the phenomena that a signaling protein belongs to more than one signaling pathway. As results, novel signaling components and pathways targeted proteins are predicted to simultaneously reconstruct multiple human signaling pathways and the static map of their cross-talks for further biomedical research.

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

BACKGROUND

Kidney 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.

RESULTS

Followed 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.

CONCLUSIONS

Our 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 pathway and network analyses using intelligent computational approaches provide an unprecedented opportunity to identify upstream disease causal genes and effective drug targets.