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PubMed2026

IL1B-centered immune dysregulation involving IL7R, CCR7, ITGB2 and IRF1 across insomnia and inflammatory bowel disease.

BACKGROUND: Insomnia is a prevalent sleep disorder that strongly affects one's quality of life and physical well-being. Inflammatory bowel disease (IBD) is a chronic inflammatory condition of the intestines, and a majority of IBD patients suffer from comorbid insomnia. However, the shared molecular features linking insomnia and IBD remain poorly characterized. METHODS: Common differentially expressed genes (DEGs) were identified in datasets of insomnia (GSE208668) and IBD (GSE179285) using the Limma package. Functional enrichment was performed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Protein-protein interaction (PPI) network construction and hub gene identification was subsequently performed. Furthermore, we validated the reliability of the hub genes using qRT-PCR and Enzyme-linked immunosorbent assay (ELISA). In addition, we constructed a TF-miRNA regulatory network of hub genes and assessed the abundance of immune cell infiltration in insomnia and IBD using CIBERSORT, EPIC, and xCell algorithms. Finally, we utilized the DsigDB to predict potential therapeutic candidates. RESULTS: The analysis revealed 75 upregulated and 32 downregulated common DEGs. Functional enrichment analysis revealed the inflammatory response and immune activation as pivotal drivers underlying the pathogenesis of both insomnia and IBD. Five hub DEGs, namely, IL1B, IL7R, CCR7, ITGB2, and IRF1, were subsequently screened and validated. The TF-miRNA-mRNA regulatory network consisted of 5 TFs, 14 miRNA nodes and 5 core mRNA nodes. Immune cell infiltration analysis revealed several patterns shared between insomnia and IBD. Additionally, 10 potential therapeutic drugs for insomnia and IBD were proposed. CONCLUSION: Integrative coexpression network analysis reveals convergent dysregulation of an IL1B-centered immune module (comprising IL7R, CCR7, ITGB2, and IRF1) across insomnia and IBD, a shared immune disturbance and candidate targets for simultaneous intervention upon further mechanistic validation.

Humans↗

PubMed2025

Bioinformatics identification and validation of pyroptosis-related gene for ischemic stroke.

BACKGROUND: Ischemic stroke (IS) is one of the common and frequent diseases with extremely high lethality and disability in the world, and there is no effective treatment at present. This study aimed to screen hub genes involved in cerebral ischemia/reperfusion injury (CIRI) and pyroptosis, and explore promising intervention targets. METHODS: CIRI-related genes (GSE202659 and GSE131193) and pyroptosis-related genes (PRGs) in mice were obtained from the Gene Expression Omnibus (GEO) and GeneCards database. We screened for LASSO regression to construct a prognostic model of GSE131193 and PRGs and examined by GSE137482. The functional enrichment analysis of Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) were performed on pyroptosis-related differentially expressed genes (PRDEGs) of GSE202659.The key modules for CIRI and pyroptosis were identified by Weight Gene Co-expression Network Analysis (WGCNA). Subsequently, Protein-protein Interaction (PPI) network and the Cytoscape was constructed to screen out hub genes. Used the starBase to predict miRNA interacting with hub genes and constructed mRNA-miRNA-lncRNA interaction networks. CIRI-related Molecular Subtypes were constructed for hub genes. The relationship between immune cells and hub genes was verified via CIBERSORT. Finally, we selected C57BL/6 mice to construct models to confirm hub genes by enzyme linked immunosorbent assay (ELISA), reverse transcription-polymerase chain reaction (RT-PCR), western blot, and Immunofluorescence. RESULTS: A total of 272 PRGs and 35 PRDEGs were screened. An eight-gene risk prediction models were established (AUC = 0.868). GO, KEGG, GSEA and GSVA analyses revealed that PRDEGs were mainly involved in positive regulation of cytokine production, and NOD-like receptor signaling pathway. And then, seven hub genes (Irf1, Icam1, Tlr2, Tnf, Cebpb, Il1rn, and Casp8) were identified by PPI. Icam1, Tnf, Cebpb, Il1rn, and Casp8 had high expression profiles in Cluster2 by hierarchical clustering. The immune infiltration analysis results showed that among the hub genes, Cebpb, Il1rn, and Casp8, showed a significant positive correlation with the degree of NK.Actived, and Icam1 showed a significant negative correlation with B.Cells.Memory. The results of animal experiments significantly demonstrated an upregulation of Irf1, Icam1, Tlr2, Cebpb, and Il1rn. CONCLUSION: Our finding indicated that Irf1, Icam1, Tlr2, Cebpb, and Il1rn are hub genes associated with pyroptosis, and these genes are all associated with different immune cells, so as to provide new targets for the prevention and treatment of IS from the perspective of pyroptosis.

Pyroptosis↗

PubMed2025

Rare epigenetic alterations are conserved across hematopoietic differentiation stages after mycobacterial infection.

Infection leads to durable cell-autonomous changes in hematopoietic stem and progenitor cells (HSPCs), resulting in production of innate immune cells with heightened immunity. The mechanisms underlying this phenomenon, termed central trained immunity, remain poorly understood. We hypothesized that infection induces histone modifications leading to changes in chromatin accessibility that are conserved during differentiation from HSPCs to myeloid progenitors and monocytes. We conducted genome-wide surveillance of histone marks H3K27ac and H3K4me3 and chromatin accessibility in hematopoietic stem cells, multipotent progenitor 3, granulocyte-monocyte progenitors, and monocytes and macrophages of naive and Mycobacterium avium-infected mice. IFN signaling pathways and related transcription factor binding motifs including IRFs, NF-κB, and CEBP showed increased activating histone marks and chromatin accessibility across cell types. However, histone marks and increased chromatin accessibility were conserved at only a few loci, notably Irf1 and Gbp6. Knock out of IRF1 disrupted enhanced mitochondrial respiration and bacterial killing in human monocyte cell lines, while GBP6-KO monocyte cell lines showed dysregulated mitochondrial respiration. In summary, this study identifies IRF1 and GBP6 as 2 key loci at which infection-induced systemic inflammation leads to epigenetic changes that are conserved from HSPCs to downstream monocytes, providing a mechanistic avenue for central trained immunity.

Animals↗

PubMed2026

Hope is linked with more favorable tumor molecular signatures in serous ovarian cancer.

INTRODUCTION: Hope has been associated with improved quality of life and lower mortality in cancer, but the underlying biological mechanisms are poorly characterized. We previously reported that hope was associated with less inflammation and more normalized diurnal cortisol pre-treatment among women with ovarian cancer. We also reported associations of socio-environmental factors with pro-metastatic processes. Here, we used genome-wide transcriptional profiling to quantify associations between hope and tumor molecular signatures reflecting invasiveness, inflammation, and cellular immunity. METHOD: Participants were 74 women with serous ovarian cancer who provided demographic information and completed surveys pre-surgery. Hope was assessed using a face-valid item from the Center for Epidemiological Studies Depression Scale (CES-D). Depression was assessed using the full CES-D without the hope item. Illumina HT12 microarrays were used to assay tumor RNA, and associations between hope and tumor gene expression were quantified, adjusting for depression, age, BMI, grade, and stage. RESULTS: Adjusting for covariates, hope was associated with multiple favorable differences in RNA expression, including lower levels of mesenchymal differentiation (p = 0.008) and pro-inflammatory gene regulation (NF-κB: p < 0.001; IRF1: p = 0.024; STAT: p = 0.018), elevated epithelial differentiation (p = 0.011), and elevated activity of the IRF7 transcription factor which promotes cellular immunity (p = 0.016). CONCLUSIONS: These data suggest that hope is associated with an ovarian tumor gene expression profile characterized by reduced epithelial-mesenchymal transition (EMT) and inflammatory activity, and increased activity of a transcription factor promoting cellular immunity. These findings highlight potential biological implications of a resilience factor such as hope, but need replication with more robust assessments of hope.

Epithelial mesenchymal transition↗

PubMed2026

Antibody-Mediated Targeting of Secretory Protein SCUBE3 Suppresses Cancer Progression by Inhibiting Oncogenic Signaling and Inducing Antitumor Immunity.

UNLABELLED: Approaches targeting factors that simultaneously promote tumor growth and progression, induce therapy resistance, and inhibit antitumor immunity offer clear benefits over therapies targeting only one of these tumor-promoting processes. Through comprehensive loss-of-function genomic screening, we identified SCUBE3 as a pivotal factor that supports survival and therapy resistance and also orchestrates an immunosuppressive tumor microenvironment. Secretory SCUBE3 supported oncogenic activity through interactions with key oncogenic cell surface receptor proteins, including EGFR, mutant CALR, and TGFβRI/II. These interactions activated the transcription factors FOXR2 and c-Myc, promoting cancer cell proliferation and therapy resistance by enhancing DNA damage repair. Additionally, the SCUBE3-FOXR2 axis created an immunosuppressive tumor microenvironment by facilitating recruitment of the DNMT1 epigenetic repressor complex to the transcription regulator IRF1, thereby inhibiting the expression of MHC-I and MHC-II genes. A first-in-class neutralizing antibody targeting SCUBE3, which was developed using a sophisticated antibody discovery platform and engineered with specific mutations in the heavy chain for enhanced specificity and efficacy, demonstrated profound therapeutic potential across various cancer types in preclinical models, including patient-derived breast and ovarian cancer xenografts. This discovery marks an advancement toward developing a targeted therapy for cancers characterized by hyperactive SCUBE3-associated signaling pathways. SIGNIFICANCE: Targeting SCUBE3 with a neutralizing antibody inhibits tumor growth and metastasis by blocking oncogenic signaling through FOXR2 and c-Myc and by circumventing immunosuppression, providing a promising pan-cancer treatment approach.

Humans↗

PubMed2026

NLCD: A method to discover nonlinear causal relations among genes.

Distinguishing correlation from causation is a fundamental challenge in many scientific fields, including biology, especially when interventions like randomized controlled trials are infeasible and only observational data are available. Methods based on statistical tests of conditional independence within the Mendelian Randomization framework can detect causality between two observed variables that are each associated with a third instrumental variable. However, these methods for detecting causal relationships between traits (e.g., two gene expression or clinical traits associated with a genetic variant, all observed in the same population) often assume a linear relationship, thereby hindering the discovery of causal gene networks from genomics data. We have developed NLCD, a method for NonLinear Causal Discovery from genomics data based on nonlinear regression modeling and conditional feature importance scoring. NLCD uses these techniques to extend the statistical tests in an existing linear causal discovery method called the Causal Inference Test (CIT). We benchmarked NLCD against current state-of-the-art methods: CIT, Findr, and MRPC. On simulated datasets, NLCD performs comparably to most methods in detecting linear relations (Average AUPRC (Area Under the Precision-Recall Curve) of NLCD = 0.94, CIT = 0.94, Findr = 0.94, and MRPC = 0.99), and outperforms them in detecting nonlinear (sine and sawtooth type) relations between two genes (Average AUPRC of NLCD = 0.76, CIT = 0.60, Findr = 0.56, and MRPC = 0.73). When tested on a nonlinear subset of a yeast genomic dataset to recover known causal relations involving transcription factors, NLCD and CIT performed comparable to each other and slightly better than Findr and MRPC (Average AUPRC of NLCD = 0.82, CIT = 0.81, Findr = 0.71, and MRPC = 0.54). On application to a human genomic dataset, NLCD revealed active causal gene pairs (IRF1 → PSME1 and HLA-C → HLA-T) in the muscle tissue, and clarified the promises and challenges in discovering causal gene networks in tissues under in vivo human settings.

Humans↗