Multi-omics segregate different transcriptomic impacts of anti-IL-17A blockade on type 17 T-cells and regulatory immune cells in psoriasis skin.

Durable psoriasis improvement has been reported in a subset of psoriasis patients after treatment withdrawal of biologics blocking IL-23/Type 17 T-cell (T17) autoimmune axis. However, it is not well understood if systemic blockade of the IL-23/T17 axis promotes immune tolerance in psoriasis skin. The purpose of the study was to find translational evidence that systemic IL-17A blockade promotes regulatory transcriptome modification in human psoriasis skin immune cell subsets. We analyzed human psoriasis lesional skin 6 mm punch biopsy tissues before and after systemic IL-17A blockade using the muti-genomics approach integrating immune cell-enriched scRNA-seq (n = 18), microarray (n = 61), and immunohistochemistry (n = 61) with repository normal control skin immune cell-enriched scRNA-seq (n = 10) and microarray (n = 8) data. For the T17 axis transcriptome, systemic IL-17A blockade depleted 100% of IL17A + T-cells and 95% of IL17F + T-cells in psoriasis skin. The expression of IL23A in DC subsets was also downregulated by IL-17A blockade. The expression of IL-17-driven inflammatory mediators (IL36G, S100A8, DEFB4A, and DEFB4B) in suprabasal keratinocytes was correlated with psoriasis severity and was downregulated by IL-17A blockade. For the regulatory DC transcriptome, the proportion of regulatory semimature DCs expressing regulatory DC markers of BDCA-3 (THBD) and DCIR (CLEC4A) was increased in posttreatment psoriasis lesional skin compared to pretreatment psoriasis lesional skin. In addition, IL-17A blockade induced higher expression of CD1C and CD14, which are markers of CD1c+ CD14+ dendritic cell (DC) subset that suppresses antigen-specific T-cell responses, in posttreatment regulatory semimature DCs compared to pretreatment regulatory semimature DCs. In conclusion, systemic IL-17A inhibition not only blocks the entire IL-23/T17 cell axis but also promotes regulatory gene expression in regulatory DCs in human psoriasis skin.

PRID: Prediction Model Using RWR for Interactions between Drugs.

Drug-drug interactions (DDI) occur because of the unexpected pharmacological effects of drug pairs. Although drug efficacy can be improved by taking two or more drugs in the short term, this may cause inevitable side effects. Currently, multiple drugs are prescribed based on the experience or knowledge of the clinician, and there is no standard database that can be referred to as safe co-prescriptions. Thus, accurately identifying DDI is critical for patient safety and treatment modalities. Many computational methods have been developed to predict DDIs based on chemical structures or biological features, such as target genes or functional mechanisms. However, some features are only available for certain drugs, and their pathological mechanisms cannot be fully employed to predict DDIs by considering the direct overlap of target genes. In this study, we propose a novel deep learning model to predict DDIs by utilizing chemical structure similarity and protein-protein interaction (PPI) information among drug-binding proteins, such as carriers, transporters, enzymes, and targets (CTET) proteins. We applied the random walk with restart (RWR) algorithm to propagate drug CTET proteins across a PPI network derived from the STRING database, which will lead to the successful incorporation of the hidden biological mechanisms between CTET proteins and disease-associated genes. We confirmed that the RWR propagation of CTET proteins helps predict DDIs by utilizing indirectly co-regulated biological mechanisms. Our method identified the known DDIs between clinically proven epilepsy drugs. Our results demonstrated the effectiveness of PRID in predicting DDIs in known drug combinations as well as unknown drug pairs. PRID could be helpful in identifying novel DDIs and associated pharmacological mechanisms to cause the DDIs.

Reference-based read clustering improves the de novo genome assembly of microbial strains.

Constructing accurate microbial genome assemblies is necessary to understand genetic diversity in microbial genomes and its functional consequences. However, it still remains as a challenging task especially when only short-read sequencing technologies are used. Here, we present a new read-clustering algorithm, called RBRC, for improving de novo microbial genome assembly, by accurately estimating read proximity using multiple reference genomes. The performance of RBRC was confirmed by simulation-based evaluation in terms of assembly contiguity and the number of misassemblies, and was successfully applied to existing fungal and bacterial genomes by improving the quality of the assemblies without using additional sequencing data. RBRC is a very useful read-clustering algorithm that can be used (i) for generating high-quality genome assemblies of microbial strains when genome assemblies of related strains are available, and (ii) for upgrading existing microbial genome assemblies when the generation of additional sequencing data, such as long reads, is difficult.

Differential expression of MicroRNAs in Alzheimer's disease: a systematic review and meta-analysis.

Alzheimer's disease (AD) results in progressive cognitive decline owing to the accumulation of amyloid plaques and hyperphosphorylated tau. MicroRNAs (miRNAs) have attracted attention as a putative diagnostic and therapeutic target for neurodegenerative diseases. However, existing meta-analyses on AD and its association with miRNAs have produced inconsistent results. The primary objective of this study is to evaluate the magnitude and consistency of differences in miRNA levels between AD patients, mild cognitive impairment (MCI) patients and healthy controls (HC). Articles investigating miRNA levels in blood, brain tissue, or cerebrospinal fluid (CSF) of AD and MCI patients versus HC were systematically searched in PubMed/Medline from inception to February 16th, 2021. Fixed- and random-effects meta-analyses were complemented with the I2 statistic to measure the heterogeneity, assessment of publication bias, sensitivity subgroup analyses (AD severity, brain region, post-mortem versus ante-mortem specimen for CSF and type of analysis used to quantify miRNA) and functional enrichment pathway analysis. Of the 1512 miRNAs included in 61 articles, 425 meta-analyses were performed on 334 miRNAs. Fifty-six miRNAs were significantly upregulated (n = 40) or downregulated (n = 16) in AD versus HC and all five miRNAs were significantly upregulated in MCI versus HC. Functional enrichment analysis confirmed that pathways related to apoptosis, immune response and inflammation were statistically enriched with upregulated pathways in participants with AD relative to HC. This study confirms that miRNAs' expression is altered in AD and MCI compared to HC. These findings open new diagnostic and therapeutic perspectives for this disorder.

Transcriptional analysis of sweet corn hybrids in response to crowding stress.

Crop tolerance to crowding stress, specifically plant population density, is an important target to improve productivity in processing sweet corn. Due to limited knowledge of biological mechanisms involved in crowding stress in sweet corn, a study was conducted to 1) investigate phenotypic and transcriptional response of sweet corn hybrids under different plant densties, 2) compare the crowding stress response mechanisms between hybrids and 3) identify candidate biological mechanisms involved in crowding stress response. Yield per hectare of a tolerant hybrid (DMC21-84) increased with plant density. Yield per hectare of a sensitive hybrid (GSS2259P) declined with plant density. Transcriptional analysis found 694, 537, 359 and 483 crowding stress differentially expressed genes (DEGs) for GSS2259P at the Fruit Farm and Vegetable Farm and for DMC21-84 at the Fruit Farm and Vegetable Farm, respectively. Strong transcriptional change due to hybrid was observed. Functional analyses of DEGs involved in crowding stress also revealed that protein folding and photosynthetic processes were common response mechanisms for both hybrids. However, DEGs related to starch biosynthetic, carbohydrate metabolism, and ABA related processes were significant only for DMC21-84, suggesting the genes have closer relationship to plant productivity under stress than other processes. These results collectively provide initial insight into potential crowding stress response mechanisms in sweet corn.

The Effect of Interleukin-4 and Dexamethasone on RNA-Seq-Based Transcriptomic Profiling of Human Podocytes: A Potential Role in Minimal Change Nephrotic Syndrome.

Interleukin-4 (IL-4) expression is implicated in the pathogenesis of nephrotic syndrome (NS). This study aimed to investigate the changes in the transcriptomes of human podocytes induced by IL-4 treatment and to analyze whether these changes could be affected by simultaneous steroid treatment. Three groups of human podocytes were treated with control, IL-4, and IL-4 plus dexamethasone (DEX), respectively. We performed whole-transcriptome sequencing to identify differentially expressed genes (DEGs) between the groups. We investigated relevant biological pathways using Gene Ontology (GO) enrichment analyses. We also attempted to compare and validate the DEGs with the genes listed in PodNet, a literature-based database on mouse podocyte genes. A total of 176 genes were differentially expressed among the three groups. GO analyses showed that pathways related to cytoskeleton organization and cell signaling were significantly enriched. Among them, 24 genes were listed in PodNet, and 12 of them were previously reported to be associated with IL-4-induced changes in human podocytes. Of the 12 genes, the expression levels of BMP4, RARB, and PLCE1 were reversed when podocytes were simultaneously treated with DEX. In conclusion, this study explored changes in the transcriptome profiles of human podocytes treated with IL-4. Few genes were reported in previous studies and were previously validated in experiments with human podocytes. We speculate that IL-4 may exert pathogenic effects on the transcriptome of human podocytes, and a few genes may be involved in the pathogenesis.

Understanding the genetics of systemic lupus erythematosus using Bayesian statistics and gene network analysis.

The publication of genetic epidemiology meta-analyses has increased rapidly, but it has been suggested that many of the statistically significant results are false positive. In addition, most such meta-analyses have been redundant, duplicate, and erroneous, leading to research waste. In addition, since most claimed candidate gene associations were false-positives, correctly interpreting the published results is important. In this review, we emphasize the importance of interpreting the results of genetic epidemiology meta-analyses using Bayesian statistics and gene network analysis, which could be applied in other diseases.

Clinical application of a phenotype-based NGS panel for differential diagnosis of inherited kidney disease and beyond.

Understanding the genetic causes of kidney disease is essential for accurate diagnosis and could lead to improved therapeutic strategies and prognosis. To accurately and promptly identify the genetic background of kidney diseases, we applied a targeted next-generation sequencing gene panel including 203 genes associated with kidney disease, as well as diseases originating in other organs with mimicking symptoms of kidney disease, to analyze 51 patients with nonspecific nephrogenic symptoms, followed by validation of its efficacy as a diagnostic tool. We simultaneously screened for copy number variants (CNVs) in each patient to obtain a higher diagnostic yield (molecular diagnostic rate: 39.2%). Notably, one patient suspected of having Bartter syndrome presented with chloride-secreting diarrhea attributable to homozygous SLC26A3 variants. Additionally, in eight patients, NGS confirmed the genetic causes of undefined kidney diseases (8/20, 40%), and initial clinical impression and molecular diagnosis were matched in 11 patients (11/20, 55%). Moreover, we found seven novel pathogenic/likely pathogenic variants in PKD1, PKHD1, COL4A3, and SLC12A1 genes, with a possible pathogenic variant in COL4A3 (c.1229G>A) identified in two unrelated patients. These results suggest that targeted NGS-panel testing performed with CNV analysis might be advantageous for noninvasive and comprehensive diagnosis of suspected genetic kidney diseases.

Genetic Variation and Autism: A Field Synopsis and Systematic Meta-Analysis.

This study aimed to verify noteworthy findings between genetic risk factors and autism spectrum disorder (ASD) by employing the false positive report probability (FPRP) and the Bayesian false-discovery probability (BFDP). PubMed and the Genome-Wide Association Studies (GWAS) catalog were searched from inception to 1 August, 2019. We included meta-analyses on genetic factors of ASD of any study design. Overall, twenty-seven meta-analyses articles from literature searches, and four manually added articles from the GWAS catalog were re-analyzed. This showed that five of 31 comparisons for meta-analyses of observational studies, 40 out of 203 comparisons for the GWAS meta-analyses, and 18 out of 20 comparisons for the GWAS catalog, respectively, had noteworthy estimations under both Bayesian approaches. In this study, we found noteworthy genetic comparisons highly related to an increased risk of ASD. Multiple genetic comparisons were shown to be associated with ASD risk; however, genuine associations should be carefully verified and understood.

ID1-Mediated BMP Signaling Pathway Potentiates Glucagon-Like Peptide-1 Secretion in Response to Nutrient Replenishment.

Glucagon-like peptide-1 (GLP-1) is a well-known incretin hormone secreted from enteroendocrinal L cells in response to nutrients, such as glucose and dietary fat, and controls glycemic homeostasis. However, the detailed intracellular mechanisms of how L cells control GLP-1 secretion in response to nutrients still remain unclear. Here, we report that bone morphogenetic protein (BMP) signaling pathway plays a pivotal role to control GLP-1 secretion in response to nutrient replenishment in well-established mouse enteroendocrinal L cells (GLUTag cells). Nutrient starvation dramatically reduced cellular respiration and GLP-1 secretion in GLUTag cells. Transcriptome analysis revealed that nutrient starvation remarkably reduced gene expressions involved in BMP signaling pathway, whereas nutrient replenishment rescued BMP signaling to potentiate GLP-1 secretion. Transient knockdown of inhibitor of DNA binding (ID)1, a well-known target gene of BMP signaling, remarkably reduced GLP-1 secretion. Consistently, LDN193189, an inhibitor of BMP signaling, markedly reduced GLP-1 secretion in L cells. In contrast, BMP4 treatment activated BMP signaling pathway and potentiated GLP-1 secretion in response to nutrient replenishment. Altogether, we demonstrated that BMP signaling pathway is a novel molecular mechanism to control GLP-1 secretion in response to cellular nutrient status. Selective activation of BMP signaling would be a potent therapeutic strategy to stimulate GLP-1 secretion in order to restore glycemic homeostasis.

TNF-α Pretreatment Improves the Survival and Function of Transplanted Human Neural Progenitor Cells Following Hypoxic-Ischemic Brain Injury.

Neural progenitor cells (NPCs) therapy offers great promise in hypoxic-ischemic (HI) brain injury. However, the poor survival of implanted NPCs in the HI host environment limits their therapeutic effects. Tumor necrosis factor-alpha (TNF-α) is a pleiotropic cytokine that is induced in response to a variety of pathological processes including inflammation and immunity. On the other hand, TNF-α has protective effects on cell apoptosis and death and affects the differentiation, proliferation, and survival of neural stem/progenitor cells in the brain. The present study investigated whether TNF-α pretreatment on human NPCs (hNPCs) enhances the effectiveness of cell transplantation therapy under ischemic brain. Fetal brain tissue-derived hNPCs were pretreated with TNF-α before being used in vitro experiments or transplantation. TNF-α significantly increased expression of cIAP2, and the use of short hairpin RNA-mediated knockdown of cIAP2 demonstrated that cIAP2 protected hNPCs against HI-induced cytotoxicity. In addition, pretreatment of hNPCs with TNF-α mediated neuroprotection by altering microglia polarization via increased expression of CX3CL1 and by enhancing expression of neurotrophic factors. Furthermore, transplantation of TNF-α-treated hNPCs reduced infarct volume and improved neurological functions in comparison with non-pretreated hNPCs or vehicle. These findings show that TNF-α pretreatment, which protects hNPCs from HI-injured brain-induced apoptosis and increases neuroprotection, is a simple and safe approach to improve the survival of transplanted hNPCs and the therapeutic efficacy of hNPCs in HI brain injury.

Immune dysregulation, polyendocrinopathy, enteropathy, X-linked (IPEX) syndrome: A systematic review.

BACKGROUND: Immune dysregulation, polyendocrinopathy, enteropathy, X-linked (IPEX) syndrome is a monogenic disorder characterized by early onset fatal multi-system autoimmunity due to loss-of-function mutations in the gene encoding the forkhead box P3 (FOXP3) transcription factor which is crucial for the development, maturation, and maintenance of CD4+ regulatory T (T-reg) cells. Various autoimmune phenomena such as enteropathy, endocrinopathies, cytopenias, renal disease, and skin manifestations are characteristic findings in patients affected by IPEX syndrome. OBJECTIVES: In this systematic review, we focus on both clinical and demographic characteristics of IPEX patients, highlighting possible genotype-phenotype correlations and address prognostic factors for disease outcome. METHODS: We performed a literature search to systematically investigate the case reports of IPEX which were published before August 7th, 2017. RESULTS: A total of 75 articles (195 patients) were identified. All IPEX patients included had FOXP3 mutations which were most frequently located in the forkhead domain (n = 68, 34.9%) followed by the leucine-zipper domain (n = 30, 15.4%) and repressor domain (n = 36, 18.4%). Clinical manifestations were as follows: enteropathy (n = 191, 97.9%), skin manifestations (n = 121, 62.1%), endocrinopathy (n = 104, 53.3%), hematologic abnormalities (n = 75, 38.5%), infections (n = 78, 40.0%), other immune-related complications (n = 43, 22.1%), and renal involvement (n = 32, 16.4%). Enteropathic presentations (P = 0.017), eczema (P = 0.030), autoimmune hemolytic anemia (P = 0.022) and food allergy (P = 0.009) were associated with better survival, while thrombocytopenia (P = 0.034), septic shock (P = 0.045) and mutations affecting the repressor domain (P = 0.021), intron 7 (P = 0.033) or poly A sequence (P = 0.025) were associated with increased risk of death. Immunosuppressive therapy alone was significantly associated with increased cumulative survival compared to patients who received no treatment (P = 0.041). CONCLUSIONS: We report the most comprehensive summary of demographic and clinical profiles derived from a total of 195 IPEX patients with deleterious mutations in FOXP3. Analysis of our findings provides new insights into genotype/phenotype correlations, and clinical and genetic factors associated with increased risk of death and response to treatment strategies.

Systematic Approach for Drug Repositioning of Anti-Epileptic Drugs.

Epilepsy is a central neurological disorder affecting individuals of all ages and causing unpredictable seizures. In spite of the improved efficacy of new antiepileptic drugs and novel therapy, there are still approximately 20%~30% of patients, who have either intractable or uncontrolled seizures. The epilepsy drug-target network (EDT) is constructed and successfully demonstrates the characteristics and efficacy of popularly used AEDs through the identification of causative genes for 60 epilepsy patients. We discovered that the causative genes of most intractable patients were not the targets of existing AEDs, as well as being very far from the etiological mechanisms of existing AEDs in the functional networks. We show that the existence of new drugs that target the causative genes of intractable epilepsy patients, which will be potential candidates for refractory epilepsy patients. Our systematic approach demonstrates a new possibility for drug repositioning through the combination of the drug-target and functional networks.

RORα is crucial for attenuated inflammatory response to maintain intestinal homeostasis.

Retinoic acid-related orphan receptor α (RORα) functions as a transcription factor for various biological processes, including circadian rhythm, cancer, and metabolism. Here, we generate intestinal epithelial cell (IEC)-specific RORα-deficient (RORαΔIEC) mice and find that RORα is crucial for maintaining intestinal homeostasis by attenuating nuclear factor κB (NF-κB) transcriptional activity. RORαΔIEC mice exhibit excessive intestinal inflammation and highly activated inflammatory responses in the dextran sulfate sodium (DSS) mouse colitis model. Transcriptome analysis reveals that deletion of RORα leads to up-regulation of NF-κB target genes in IECs. Chromatin immunoprecipitation analysis reveals corecruitment of RORα and histone deacetylase 3 (HDAC3) on NF-κB target promoters and subsequent dismissal of CREB binding protein (CBP) and bromodomain-containing protein 4 (BRD4) for transcriptional repression. Together, we demonstrate that RORα/HDAC3-mediated attenuation of NF-κB signaling controls the balance of inflammatory responses, and therapeutic strategies targeting this epigenetic regulation could be beneficial to the treatment of chronic inflammatory diseases, including inflammatory bowel disease (IBD).

Combination treatment with n-3 polyunsaturated fatty acids and ursodeoxycholic acid dissolves cholesterol gallstones in mice.

The increasing prevalence of cholesterol gallstone disease places an economic burden on the healthcare system. To identify novel therapeutics, we assessed the effects of n-3 polyunsaturated fatty acids (PUFA) in combination with UDCA in a mouse model of cholesterol gallstones. Gallstone dissolution, gallbladder wall thickness, mucin gene expression in the gallbladder, and levels of phospholipids, cholesterol, and bile acids in bile and serum were analysed. RNA was extracted from the liver for mRNA sequencing and gene expression profiling. Combination treatment resulted in greater gallstone dissolution compared with the control group, and PUFA and combination treatments reduced the thickness of the gallbladder wall. Expression levels of mucin genes were significantly lower in the UDCA, PUFA, and combination groups. Transcriptome analyses revealed that combination treatment modulated hepatic lipid metabolism. The PUFA and combination groups showed elevated bile phospholipid and bile acid levels and a lower cholesterol saturation index. Combination treatment with PUFA and UDCA dissolves cholesterol gallstones in mice by decreasing mucin production, increasing levels of phospholipids and bile acids in bile, and decreasing cholesterol saturation. Further studies of the therapeutic effects of combination PUFA and UDCA treatment in patients with cholesterol gallstones are warranted.

Genetic Variants in Antineutrophil Cytoplasmic Antibody-Associated Vasculitis: A Bayesian Approach and Systematic Review.

A number of genome-wide association studies (GWASs) and meta-analyses of genetic variants have been performed in antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis. We reinterpreted previous studies using false-positive report probability (FPRP) and Bayesian false discovery probability (BFDP). This study searched publications in PubMed and Excerpta Medica Database (EMBASE) up to February 2018. Identification of noteworthy associations were analyzed using FPRP and BFDP, and data (i.e., odds ratio (OR), 95% confidence interval (CI), p-value) related to significant associations were separately extracted. Using filtered gene variants, gene ontology (GO) enrichment analysis and protein⁻protein interaction (PPI) networks were performed. Overall, 241 articles were identified, and 7 were selected for analysis. Single nucleotide polymorphisms (SNPs) discovered by GWASs were shown to be noteworthy, whereas only 27% of significant results from meta-analyses of observational studies were noteworthy. Eighty-five percent of SNPs with borderline p-values (5.0 × 10-8 < p < 0.05) in GWASs were found to be noteworthy. No overlapping SNPs were found between PR3-ANCA and MPO-ANCA vasculitis. GO analysis revealed immune-related GO terms, including "antigen processing and presentation of peptide or polysaccharide antigen via major histocompatibility complex (MHC) class II", "interferon-gamma-mediated (IFN-γ) signaling pathway". By using FPRP and BFDP, network analysis of noteworthy genetic variants discovered genetic risk factors associated with the IFN-γ pathway as novel mechanisms potentially implicated in the complex pathogenesis of ANCA-associated vasculitis.

Markov chain Monte Carlo simulation of a Bayesian mixture model for gene network inference.

BACKGROUND: Simultaneous measurement of gene expression level for thousands of genes contains the rich information about many different aspects of biological mechanisms. A major computational challenge is to find methods to extract new biological insights from this wealth of data. Complex biological processes are often regulated under the various conditions or circumstances and associated gene interactions are dynamically changed depending on different biological contexts. Thus, inference of such dynamic relationships between genes with consideration of biological conditions is very challenging. METHOD: In this study, we propose a comprehensive and integrated approach to infer the dynamic relationships between genes and evaluate this approach on three distinct gene networks. RESULTS: This study demonstrates the advantage of integrating Markov chain Monte Carlo (MCMC) simulation into a Bayesian mixture model to overcome the high-dimension, low sample size (HDLSS) problem as well as to identify context-specific biological modules. Such biological modules were identified through the summarization of sampled network structures obtained from MCMC simulation. CONCLUSION: This novel approach gives a comprehensive understanding of the dynamically regulated biological modules.

mySyntenyPortal: an application package to construct websites for synteny block analysis.

BACKGROUND: Advances in sequencing technologies have facilitated large-scale comparative genomics based on whole genome sequencing. Constructing and investigating conserved genomic regions among multiple species (called synteny blocks) are essential in the comparative genomics. However, they require significant amounts of computational resources and time in addition to bioinformatics skills. Many web interfaces have been developed to make such tasks easier. However, these web interfaces cannot be customized for users who want to use their own set of genome sequences or definition of synteny blocks. RESULTS: To resolve this limitation, we present mySyntenyPortal, a stand-alone application package to construct websites for synteny block analyses by using users' own genome data. mySyntenyPortal provides both command line and web-based interfaces to build and manage websites for large-scale comparative genomic analyses. The websites can be also easily published and accessed by other users. To demonstrate the usability of mySyntenyPortal, we present an example study for building websites to compare genomes of three mammalian species (human, mouse, and cow) and show how they can be easily utilized to identify potential genes affected by genome rearrangements. CONCLUSIONS: mySyntenyPortal will contribute for extended comparative genomic analyses based on large-scale whole genome sequences by providing unique functionality to support the easy creation of interactive websites for synteny block analyses from user's own genome data.

TNF-α induces human neural progenitor cell survival after oxygen-glucose deprivation by activating the NF-κB pathway.

Neural progenitor cell (NPC) transplantation has been shown to be beneficial in the ischemic brain. However, the low survival rate of transplanted NPCs in an ischemic microenvironment limits their therapeutic effects. Tumor necrosis factor-alpha (TNF-α) is one of the proinflammatory cytokines involved in the pathogenesis of various injuries. On the other hand, several studies have shown that TNF-α influences the proliferation, survival, and differentiation of NPCs. Our study investigated the effect of TNF-α pretreatment on human NPCs (hNPCs) under ischemia-related conditions in vitro. hNPCs harvested from fetal brain tissue were pretreated with TNF-α before being subjected to oxygen-glucose deprivation (OGD) to mimic ischemia in vitro. TNF-α pretreatment improved the viability and reduced the apoptosis of hNPCs after OGD. At the molecular level, TNF-α markedly increased the level of NF-κB signaling in hNPCs, and an NF-κB pathway inhibitor, BAY11-7082, completely reversed the protective effects of TNF-α on hNPCs. These results suggest that TNF-α improves hNPC survival by activating the NF-κB pathway. In addition, TNF-α significantly enhanced the expression of cellular inhibitor of apoptosis 2 (cIAP2). Use of a lentivirus-mediated short hairpin RNA targeting cIAP2 mRNA demonstrated that cIAP2 protected against OGD-induced cytotoxicity in hNPCs. Our study of intracellular NF-κB signaling revealed that inhibition of NF-κB activity abolished the TNF-α-mediated upregulation of cIAP2 in hNPCs and blocked TNF-α-induced cytoprotection against OGD. Therefore, this study suggests that TNF-α pretreatment, which protects hNPCs from OGD-induced apoptosis by activating the NF-κB pathway, provides a safe and simple approach to improve the viability of transplanted hNPCs in cerebral ischemia.