SEARCH · Search PubMed

Results for “Interferon signaling pathway”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 recordsLinked to original sources

PubMed2026

Transcriptomic signatures of mind-body transformations therapy in breast cancer: Downregulation of the interferon signaling pathway.

BACKGROUND: Growing evidence has shown that Mind-Body Transformations-Therapies (MBT-T) are able to modulate chronic inflammation, a well-known driver of cancer progression and drug resistance. In our previous work, we showed that a specific MBT-T protocol was able to reduce the release of various pro-inflammatory cytokines and chemokines in the sera of patients with breast cancer that completed adjuvant chemotherapy. Despite these clinical observations, the underlying molecular pathways through which this therapy exerts its effects remain unclear. This study aims to address this gap by characterizing genome-wide transcriptional profiles in patients undergoing a novel MBT-T protocol. METHODS: In this proof-of-concept study, patients with breast cancer were randomized into two groups: Group 1 (CTL), receiving standard follow-up care, and Group 2 (MBT-T), receiving standard follow-up plus biweekly MBT-T for 4 months. Blood samples were collected at different timepoints during the treatment. After RNA extraction from whole blood, gene expression was analyzed on twenty-one patients (CTL, n = 7; MBT-T, n = 14) using the nCounter® Human Inflammation Panel (249 genes). RESULTS: Patients undergoing MBT-T showed a significant global downregulation of inflammatory gene expression compared to the control group. The analysis revealed that the Interferon (IFN) signaling pathway was the most significantly suppressed, by downregulation of key genes such as IFIT1, IFIT3, IFI44, MX1 and OASL in the MBT-T group. CONCLUSIONS: MBT-T acts as a biological modulator capable of downregulating key inflammatory pathways at the transcriptional level. These findings provide a genomic basis for the clinical benefits of mind-body interventions in oncology.

Breast cancer↗

PubMed2026

Variants in the interferon regulatory factor 5 gene confer genetic risk for systemic lupus erythematosus in a Han Chinese population.

BACKGROUND: Interferon regulatory factor 5 (IRF5), integral to interferon signaling pathways, has been identified as a susceptibility locus for systemic lupus erythematosus (SLE). Nevertheless, the relationship between IRF5 variants and SLE risk within the Han Chinese demographic remains inadequately characterized. MATERIALS AND METHODS: Genotyping of two functional single nucleotide variants (SNVs) in IRF5 was conducted in 167 individuals with SLE and 246 healthy controls utilizing sequence-specific primer polymerase chain reaction (PCR-SSP). Chi-square and Fisher's exact tests were employed to assess associations. RESULTS: The rs10954213 variant demonstrated a significant association with SLE susceptibility under the recessive model (GG vs. AG+AA, OR = 2.20, 95% CI: 1.30-3.75, p = 0.003, adjusted p [pc] = 0.030) and homozygous model (GG vs. AA, OR = 2.43, 95% CI: 1.36-4.42, p = 0.003, pc = 0.032). Similarly, the rs2004640 variant was associated with an increased risk of SLE across allelic (T vs. G, OR = 1.66, 95% CI: 1.22-2.26, p = 0.001, pc = 0.011), dominant (TG+TT vs. GG, OR = 1.77, 95% CI: 1.19-2.63, p = 0.005, pc = 0.047), and homozygous models (TT vs. GG, OR = 3.72, 95% CI: 1.58-8.78, p = 0.002, pc = 0.016). Haplotype analysis identified protective haplotype HT1 (A/G, OR = 0.54, 95% CI: 0.41-0.73, p < 0.001) and risk haplotype HT4 (G/T, OR = 2.51, 95% CI: 1.42-4.42, p = 0.001). CONCLUSIONS: These findings indicate that IRF5 gene variants substantially modulate susceptibility to SLE in the Han Chinese population. They hold potential as biomarkers for evaluating SLE risk and offer valuable perspectives into disease pathogenesis.

Adult↗

PubMed2026

Structural biology of the dengue virus NS2B-NS3 protease as a target for antiviral drug development.

Dengue is the most common global problem in recent times, particularly in tropical and subtropical areas, yet antivirals for therapy or prophylaxis are lacking. Millions of people are affected by this dengue virus, but no proper medication is available yet to cure this disease. One polyprotein that is encoded by the DENV genome is converted into structural and non-structural proteins that are necessary for viral pathogenesis and replication. Among these, the non-structural protein complex NS2B-NS3 is essential for viral polyprotein processing, replication, and host innate immune response control. It acts as a trypsin-like serine protease. The NS2B/NS3 protease is a key enzyme involved in viral replication and serves as a major target for drug development against the dengue virus. The NS3 protease has a conserved catalytic triad (His-Asp-Ser), whereas NS2B serves as an essential cofactor that stabilizes the active conformation of the enzyme and aids in substrate recognition. By disrupting interferon signalling pathways, the NS2B-NS3 protease not only aids in viral replication but also makes immune evasion easier. The compound that inhibits the action of this enzyme could be pioneering in the antiviral drug discovery process. This article provides a comprehensive overview of the detailed structural information of the viral protease (NS2B/NS3) enzyme with the mechanistic role of this enzyme, and highlights various inhibitors related to the NS2B/NS3 protease. A more thorough comprehension of this protease could facilitate the logical development of potent antiviral medications to prevent dengue infection.

Dengue↗

PubMed2026

Integrated multi-omics profiling identifies aging-related molecular signatures and convergent interferon signaling in systemic lupus erythematosus.

BACKGROUND: Systemic lupus erythematosus (SLE) is characterized by chronic immune activation and molecular alterations that overlap with aging-related biological processes. However, how these alterations are organized across molecular layers and whether they converge on shared regulatory networks remain incompletely understood. METHODS: We performed an integrative multi-omics analysis combining in-house proteomic and phosphoproteomic data from 130 patients with SLE and 90 healthy controls (HCs) and publicly available transcriptomic datasets comprising 1,461 SLE patients. Proteins and phosphorylation sites were annotated using established aging-related gene resources. Differential protein abundance and phosphorylation changes were analyzed across disease-status and disease-activity comparisons. Nominal P-value thresholds were used for exploratory feature selection, whereas FDR-adjusted P values were used to assess robustness after multiple-testing correction. Kinase-substrate enrichment, transcription factor annotation, and cell-type-resolved transcriptomic comparison were used to explore potential regulatory programs. RESULTS: We identified 128 nominally altered proteins annotated to aging-related biological processes, including genomic instability, mitochondrial dysfunction, and epigenetic alterations. Phosphoproteomic analysis revealed 36 nominally altered phosphorylation sites, including previously unreported sites in IFI16 (S153, S780) and PKCδ (S507, S664). Clustering analysis demonstrated heterogeneous protein co-regulation patterns across disease states. Kinase activity inference suggested altered activity of TBK1 and IKKβ. TF analysis further highlighted STAT1, RELA, and PML as potential central nodes within the inferred regulatory network. Notably, these multi-omic alterations were not randomly distributed but showed convergence toward shared signaling pathways, particularly those related to interferon responses. CONCLUSIONS: This integrative multi-omics study identifies inflammatory and interferon-dominated molecular alterations in SLE PBMCs that overlap with aging-related biological processes and converge on shared regulatory networks. These findings provide a hypothesis-generating framework for investigating the intersection between chronic immune activation and aging-related molecular remodeling in SLE.

Humans↗

PubMed2026

NAT10 is critical to block RNA sensing-induced IFN-β transactivation in viral infection.

UNLABELLED: Cells detect invading viruses and produce type I interferons (IFNs) to stimulate an innate antiviral effector response. However, IFN levels must be fine-tuned to achieve antiviral efficacy while limiting hyperinflammatory and tissue-damaging effects. Here, we report that NAT10, a histone and cytidine acetyltransferase, regulates the production of type I IFNs and RNA virus infections. Depletion of NAT10 increased the expression of IFN-β and IFN-stimulated genes, and correspondingly impaired viral replication. Mechanistically, NAT10 dynamically associated with the IFN-β promoter and also negatively regulated IRF3's chromatin associations through modulation of long noncoding RNAs that inhibit IRF3. Treatment of cells with Remodelin, a NAT10 inhibitor, similarly increased IFN-β expression and inhibited viral infections. Overall, our findings reveal NAT10 is a potential host-directed target for antiviral treatment via regulation of type I IFN. IMPORTANCE: Type I interferons (IFNs) signaling pathway is critical to cellular defense and innate immunity against evading pathogens, including viruses. However, induction of type I IFNs is fine-tuned to achieve the antiviral consequence while maintaining host cellular homeostasis. This paper presents a novel mechanism for the NAT10 protein to silence IFN-β induction through modulation of IRF3 activity at the promoter of IFN-β, and further demonstrates the therapeutic potential of the NAT10 inhibitor Remodelin to restrict viral infection while inducing IFN-β.

Interferon-beta↗

PubMed2025

Dissecting Sex-Specific Pathology in K18-hACE2 Transgenic Mice Infected With Different SARS-CoV-2 Variants.

Sex-biased differences in COVID-19 outcomes in relation to individual SARS-CoV-2 variants are not well understood. In this study, lungs and nasal cavities of age-matched female and male K18-hACE2 transgenic mice were collected for dissecting sex-specific differences in pathology after infection of SARS-CoV-2 614 G, Delta, or Omicron variant. Overall, Delta infection induced the most severe inflammation and pathology in nasal cavity and lung followed by the 614 G, then Omicron variant. Sex differences in host responses to SARS-CoV-2 infection were variant-specific. Delta-infected males showed increased pulmonary infiltration of CD163+ "M2" macrophages, Ly6G+ neutrophils, and NKR-P1C + NK cells during early onset of infection, and elevated lung inflammatory cytokines such as IL-10, IL-6, and IP-10 than Delta-infected females. Conversely, females had increased lung CD4 + T cell recruitment after Omicron infection and significantly elevated lung MCP-1 secretion after Delta infection than males. Lung spatial transcriptomics data revealed that Delta-infected females had enriched gene pathways related to humoral immune response and interferon signaling, while males had enriched pathways associated with extracellular matrix production, chemokine signaling, and cell chemotaxis. Taken together, this study highlights the complex infection dynamics with respect to individual SARS-CoV-2 variants and underscores the importance of sex as a confounding factor for COVID-19 pathology.

Animals↗

PubMed2025

Verification of biological markers of subacute cutaneous lupus erythematosus via TMT labelling proteomics combined with transcriptome data.

OBJECTIVE: This study aimed to investigate biological markers in subacute cutaneous lupus erythematosus (SCLE). METHODS: The tandem mass tag (TMT)-labelling proteomics method was used to explore differentially expressed proteins between SCLE lesions and normal skin tissues. The differences in transcriptomic data between SCLE tissues and normal skin tissues were analysed from the GEO database (GSE81071, GSE109248 and GSE112943). The differences in transcriptomic data from peripheral blood mononuclear cells (PBMCs) of patients with systemic lupus erythematosus (SLE) and normal controls were analysed (GSE81622 and GSE154851). The 35 healthy controls, 30 SCLE patients, 35 SLE patients and 30 lupus nephritis (LN) patients were diagnosed and enrolled. The serum expression levels of IFI44 and EPSTI1 were detected. Data were presented as the mean ± standard deviation or frequency and were analysed using Student's t-test, Chi-square test and one-way ANOVA between the groups. Receiver operating characteristic (ROC) curves were used to analyse the clinical efficacy of IFI44 and EPSTI1 in distinguishing SCLE from SLE. RESULTS: In a comparative analysis of SCLE lesions and normal skin tissues, proteomics studies identified 376 proteins that exhibited significant differential expression. In GO and KEGG analyses, the enriched terms mainly included the interferon-gamma-mediated signalling pathway (p < .001), immune receptor activity (p < .001) and cell adhesion molecules (p < .001). The top 10 hub genes were screened in SCLE as follows: CD8A, CXCL10, IFI44, CD7, CCL5, TLR4, EPSTI1, ISG15, KLRD1 and SELL using Cytoscape (3.10.1) software. The 15 common proteins/genes between proteomics and three datasets results were found, including CXCL10, OAS1, DDX60L, CFB, IFI6, HERC6, IFI44L, GBP1, EPSTI1, OAS2, CXCL11, TYMP, IFI44, ISG15 and IFIT3. The 61 differentially expressed genes in GSE81622 and the top 100 differentially expressed genes in GSE154851, alongside the 15 identified genes described above through Venn diagram analysis. Four common genes, IFI44L, IFI44, EPSTI1 and OAS1, were identified. Two common genes, IFI44 and EPSTI1, were found in hub genes from the proteomics results. The serum levels of IFI44 and EPSTI1 in LN were significantly higher than those in SLE patients (p < .05). ROC curve analysis demonstrated that serum levels of IFI44 and EPSTI1 could differentiate SCLE from SLE with an area under the curve (AUC) of 0.898 and 0.847, respectively. CONCLUSIONS: The IFI44 and EPSTI1 proved to be closely involved in the progression from SCLE to SLE, and can represent new candidate diagnostic molecular markers of occurrence and progression of SCLE.

Humans↗

PubMed2026

The establishment of prostate-specific, SKP2 humanized mice by CRISPR knock-in method reveals neoplastic initiation and microenvironmental reprogramming.

Genetic inactivation of SKP2 has been shown to effectively prevent cancer initiation and block tumorigenesis. However, direct in vivo evidence for SKP2 on cancer initiation and prostatic microenvironment is still lacking and a SKP2 humanized mouse model is critical for developing prostate cancer immunoprevention approaches through targeting SKP2. We therefore have established a prostate-specific human SKP2 knock-in mouse model driven by an endogenous mouse probasin promoter. Overexpression of hSKP2 induces PIN and low-grade carcinoma. RNA-sequencing analysis revealed significant gene expression alterations in EMT, extracellular matrix, and interferon signaling. Single-cell deconvolution showed an increase of fibroblast population and a decrease of CD8+ T cell and B cell populations. Consistent with these results from the SKP2 humanized mouse, SKP2 protein is overexpressed in human prostatic hyperplasia, PIN and prostate adenocarcinoma compared to normal prostate tissues. Overexpression of SKP2 markedly increased cell migration and invasion and induced the gene expression of EMT and interferon pathways. Inhibition of SKP2 signaling by Flavokawain A and C1 reverses EMT and affects EMT and interferon-related gene expression. In addition, paired prostate organoids were derived from SKP2 humanized and wild-type mice for drug screening and validated by known SKP2 inhibitors, Flavokawain A and C1. Both of which selectively decreased viability and altered the morphologies of organoids of hSKP2 knock-in rather than wild-type mice. Our studies provide a well-characterized prostate-specific hSKP2 knock-in mouse model and offer new mechanistic insights for understanding the oncogenic role of SKP2 in shaping the prostatic microenvironment during early carcinogenesis.

Animals↗

PubMed2025

African Swine Fever Virus MGF 360-2L Disrupts Host Antiviral Immunity Based on Transcriptomic Analysis.

Background/Objectives: The African swine fever virus (ASFV) multi-gene family (MGF) 360 proteins play critical roles in immune evasion, replication regulation, and virulence determination. Despite substantial advances in this field, the functional roles of many members within this gene family remain to be fully characterized. Methods: In this study, Transcriptional kinetics analysis indicated that the expression profile of MGF 360-2L was consistent with that of the late marker gene B646L (p72). Transcriptomic profiling identified 13 and 171 differentially expressed genes (DEGs) at 12 and 24 h post-infection (hpi) with ΔMGF 360-2L, respectively. Results: Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses indicated that these DEGs were predominantly enriched in Type I interferon (IFN-I) signaling pathways. It is noteworthy that transcriptome analysis further demonstrates that the absence of MGF 360-2L specifically results in the dysregulation of expression of the replication-essential genes E199L and E301R. These findings indicate that MG F360-2L is essential for maintaining the stable expression of these proteins. Conclusions:MGF 360-2L is a late gene that contributes to the precise regulation of viral protein expression and modulates the host immune response during infection.

African swine fever virus↗

PubMed2026

Integrative post-GWAS analysis prioritizes immune regulatory pathways and candidate effector signals in systemic lupus erythematosus.

BACKGROUND: Systemic lupus erythematosus (SLE) has a complex polygenic architecture, but translating genome-wide association signals into biologically interpretable candidates remains challenging. We applied an integrative post-GWAS framework to refine SLE-associated loci and prioritize candidate regulatory mechanisms. METHODS: European-ancestry SLE GWAS summary statistics from FinnGen and Bentham et al. were meta-analysed, comprising 8417 cases and 354,277 controls. After quality filtering, 6,782,131 SNPs were retained. Downstream analyses included LAVA regional prioritization, Bayesian colocalization with GTEx v8 whole-blood and spleen eQTLs, independent replication in the Julià et al. Spanish cohort, pathway enrichment, bivariate LAVA cross-trait local genetic correlation, and therapeutic annotation. RESULTS: The discovery meta-analysis identified 46 genome-wide significant SLE-associated loci, including putative novel signals requiring database/literature qualification. LAVA identified 14 candidate index variants across 12 high-confidence regions, of which nine index variants were retained as the primary prioritized set based on LAVA support and/or convergent regulatory evidence. The strongest association mapped to the chr6p21.3/MHC region (rs389884), where four genes showed colocalization support, including CLIC1 in whole blood and C4A in spleen. Because the chr6p21.3/MHC rs389884 region lead variant was unavailable for replication and no suitable proxy was identified, this signal was interpreted as an emerging candidate for functional validation rather than a replicated causal signal. Seven available variants replicated with concordant effects. An exploratory Roadmap immune chromatin-state overlap analysis placed 15 of 45 non-MHC lead variants (33.3%) directly, and 34 of 45 (75.6%) within ±10 kb, in active immune enhancer/promoter states. Pathway analyses highlighted type I interferon, JAK-STAT signaling, cytokine regulation, and antigen presentation, while bivariate LAVA analyses supported shared local genetic architecture with rheumatoid arthritis, systemic sclerosis, and Sjögren syndrome. CONCLUSIONS: This integrative post-GWAS analysis refines SLE association signals into biologically interpretable candidate regions and supports interferon and JAK-STAT signaling as central genetically supported pathways in SLE.

CLIC1↗

PubMed2026

Beyond genes: EpiSwitch® and Orion platform-powered 3D genome architecture biomarkers reveal shared biology across ME/CFS, long COVID, PTSD, rheumatoid arthritis, and multiple sclerosis.

BACKGROUND: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), Long COVID (LC19), post-traumatic stress disorder (PTSD), rheumatoid arthritis (RA), and multiple sclerosis (MS) are clinically distinct disorders that share substantial symptom overlap, including persistent fatigue, cognitive impairment, autonomic dysfunction, and immune dysregulation. Although these conditions differ in diagnosis and clinical presentation, their underlying biological mechanisms remain poorly understood and may involve convergent regulatory pathways. METHODS: The EpiSwitch® 3D genomics platform and Orion knowledgebase were used to integrate chromosome conformation signatures with genome-wide association study (GWAS)-derived datasets across ME/CFS, LC19, PTSD, RA, and MS. Three-dimensional genomic anchors were mapped to coding genes and analysed using STRING protein-protein interaction networks and Cytoscape-based systems biology approaches. Disease-specific anchor datasets were generated and compared at both gene and network levels to identify shared biological processes and regulatory mechanisms. RESULTS: Analysis of the ME/CFS dataset identified 552 unique 3D genomic anchors mapped to 567 genes, with analogous disease-specific anchor sets generated for LC19, PTSD, RA, and MS. Direct overlap between disease-associated genes was limited; however, higher-order network analyses revealed substantial interconnectivity and convergence across conditions. Shared biological pathways included immune and cytokine signalling, interferon responses, mitochondrial function, metabolic regulation, and neuroendocrine processes. Highly connected hub genes included immune regulatory nodes such as LAG3 and components of the mTOR signalling pathway, implicating T-cell exhaustion, chronic immune activation, and immunometabolic dysregulation as common mechanisms underlying these disorders. CONCLUSIONS: These findings support a systems-level model in which clinically overlapping fatigue-associated syndromes arise from perturbations of interconnected regulatory networks rather than discrete disease-specific pathways. Despite limited genetic overlap, substantial convergence at the network level suggests shared biological architecture across ME/CFS, LC19, PTSD, RA, and MS. The identification of common regulatory pathways provides a mechanistic framework for the development of cross-disease diagnostic and therapeutic strategies. By capturing dynamic regulatory states, 3D genomic biomarkers offer significant potential for objective blood-based diagnostics, patient stratification, and the identification of shared therapeutic targets across complex chronic disorders. These findings support the application of precision medicine approaches and may accelerate the development of novel interventions for fatigue-associated multisystem diseases.

Humans↗

PubMed2026

Retrotransposable element derepression distinguishes DNMT3A-mutant from TET2-mutant clonal haematopoiesis.

Clonal haematopoiesis (CH) is driven by somatic mutations in haematopoietic stem cells that generate clonal populations detectable in peripheral blood and is present in 10-20% of individuals over the age of 65. Mutations in DNMT3A and TET2 are the most common drivers and have been linked to inflammatory phenotypes and increased risk of haematologic and cardiovascular disease. However, the cell-intrinsic mechanisms connecting these mutations to inflammatory signalling remain incompletely understood. Because retrotransposable elements (RTEs) are epigenetically regulated and can activate innate immune pathways when derepressed, we hypothesised that RTE reactivation may represent a mutation-specific mechanism linking clonal haematopoiesis driver mutations to inflammatory pathways. We analysed RTE expression and clonal burden in peripheral blood mononuclear cell (PBMC) samples from 56 individuals with CH and 12 non-CH controls using integrated genomic and transcriptomic approaches, with complementary validation by TARGET-seq across haematopoietic lineages. High variant allele frequency (VAF; > 10%) DNMT3A-mutant clones exhibited widespread derepression of RTEs, particularly LINE and LTR families, whereas TET2-mutant clones showed a trend towards reduced RTE expression relative to controls. Transcriptomic analyses revealed that DNMT3A high-variant allele frequency clones with elevated RTE expression were enriched for inflammatory signalling pathways, including TNF-α/NF-κB signalling, interferon responses, and senescence-associated signatures. In contrast, TET2-mutant clones lacked these RTE-associated inflammatory signatures and instead showed enrichment of oxidative phosphorylation, reactive oxygen species signalling, and a mechanistic target of rapamycin complex 1 pathway. These findings were reproduced in an independent cohort. Collectively, our results highlight mutation-specific inflammatory mechanisms in clonal haematopoiesis and provide a foundation for future functional and preclinical studies to determine whether modulation of RTE activity can influence the inflammatory phenotype of DNMT3A-mutant CH and represent a potential therapeutic strategy.

DNMT3A↗

PubMed2026

Cellular transcriptomic signatures underpinning the heterogeneity of depression in Alzheimer's disease.

INTRODUCTION: Late-onset Alzheimer's disease (LOAD) and major depressive disorder (MDD) share genetic etiologies. Here, we investigated brain transcriptomic landscapes to gain insights into shared and divergent molecular and biological etiologies across LOAD and MDD. METHODS: Brain single-nucleus RNA sequencing (snRNA-seq) datasets from cognitively normal older and young individuals and LOAD patients stratified by comorbid MDD were analyzed to identify differential expressed genes (DEGs). Using cell type-specific DEGs we performed biological pathway and intercellular-communication networks analyses. We investigated shared DEGs across MDD and LOAD cohorts and sex-specific DEGs. Results were validated by comparison with four transcriptomic and proteomic studies of MDD and depression. RESULTS: MDD-associated dysregulated genes and pathways were shared between LOAD and cognitive-normal individuals, including JUNB and DUSP1 in glutamatergic neurons, and PRAM1 and SNX9 in microglia. DEGs shared between the MDD and LOAD cohorts included HSPA1A and NDUFB7 in glutamatergic neurons. Sex interaction analysis identified numerous new DEGs in the MDD cohorts, whereas there were ≈5 to 10 times more DEGs in female than in male individuals. LOAD and MDD common microglial pathways included neuronal injury, stress, peroxisome proliferator-activated receptor (PPAR) signaling and interferon alpha/beta signaling. DISCUSSION: LOAD and MDD exhibited common molecular profiles, dysregulated pathways, and cellular communication changes. MDD develops earlier in life, thus, our findings provide a window into early molecular and biological processes preceding LOAD-onset.

Humans↗

PubMed2025

Automating candidate gene prioritization with large language models: from naive scoring to literature-grounded validation.

MOTIVATION: Identifying promising therapeutic targets from thousands of genes in transcriptomic studies remains a major bottleneck in biomedical research. While large language models (LLMs) show potential for gene prioritization, they suffer from hallucination and lack systematic validation against expert knowledge. RESULTS: The framework identified 609 sepsis-relevant genes with >94% filtering efficiency, demonstrating strong enrichment for inflammatory pathways including TNF-α signaling, complement activation, and interferon responses. Literature validation yielded 30 ultra-high confidence therapeutic candidates, including both established sepsis genes (IL10, TREM1, S100A9, NLRP3) and novel targets warranting investigation. Benchmark validation against expert-curated databases achieved 71.2% recall, with systematic correlation between computational confidence and evidence quality. The final candidate set balanced discovery (11 novel genes) with validation (19 known genes), maintaining biological coherence throughout the filtering process. This framework demonstrates that rigorous methodology can transform unreliable LLM outputs into systematically validated biological insights. By combining computational efficiency with literature grounding, the approach provides a practical tool for prioritizing experimental validation efforts. The modular design enables adaptation to other diseases through knowledge base substitution, offering a systematic approach to literature-guided biomarker discovery. AVAILABILITY AND IMPLEMENTATION: We developed a two-stage computational framework that combines LLM-based screening with literature validation for systematic gene prioritization. Starting with 10 824 genes from the BloodGen3 repertoire, we applied multi-criteria evaluation for sepsis relevance, followed by retrieval-augmented generation using 6346 curated sepsis publications. A novel faithfulness evaluation system verified that LLM predictions aligned with retrieved literature evidence. Source code and implementation details are available at https://github.com/taushifkhan/llm-geneprioritization-framework, vector database at https://doi.org/10.5281/zenodo.15802241, and Interactive demonstration at https://llm-geneprioritization.streamlit.app/.

Humans↗

PubMed2025

Genetic and transcriptional insights into immune checkpoint blockade response and survival: lessons from melanoma and beyond.

BACKGROUND: Integration of immune checkpoint inhibitors (ICIs) with non-immune therapies relies on identifying combinatorial biomarkers, which are essential for patient stratification and personalized treatment. METHODS: We analyzed genomic and transcriptomic data from pretreatment tumor samples of 342 melanoma patients treated with ICIs to identify mutations and expression signatures associated with ICI response and survival. External validation and mechanistic exploratory analyses were conducted in two additional datasets to assess generalizability. RESULTS: Responders were more likely to have received anti-PD-1 therapy rather than anti-CTLA-4 and exhibited a higher tumor mutation burden (both P < 0.001). Mutations in the dynein axonemal heavy chain (DNAH) family genes, specifically DNAH2 (P = 0.03), DNAH6 (P < 0.001), and DNAH9 (P < 0.01), were enriched in responders. The combined mutational status of DNAH 2/6/9 effectively stratified patients by progression-free survival (hazard ratio [HR]: 0.69; 95% confidence interval [CI] 0.51-0.92; P = 0.013) and overall survival (HR: 0.58; 95% CI 0.43-0.78; P < 0.001), with consistent association observed in the validation cohort (HR: 0.28; 95% CI 0.12-0.61; P < 0.001). DNAH-altered melanomas exhibited upregulation of chemokine signaling, cytokine-cytokine receptor interaction, and cell cycle-related pathways, along with elevated expression of immune-related signatures in interferon signaling, cytolytic activity, T cell function, and immune checkpoints. Using LASSO logistic regression, we identified a 26-gene composite signature predictive of clinical response, achieving an area under the curve (AUC) of 0.880 (95% CI 0.825-0.936) in the training dataset and 0.725 (95% CI 0.595-0.856) in the testing dataset. High-risk patients, stratified by the expression levels of a 13-gene signature, demonstrated significantly shorter overall survival in both datasets (HR: 3.35; P < 0.001; HR: 2.93; P = 0.002). CONCLUSIONS: This analysis identified potential molecular determinants of response and survival to ICI treatment. Insights from melanoma biomarker research hold significant promise for translation into other malignancies, guiding individualized anti-tumor immunotherapy.

Humans↗

PubMed2025

Setdb2 Regulates Inflammatory Trigger-Induced Trained Immunity of Macrophages Through Two Different Epigenetic Mechanisms.

"Trained immunity" of innate immune cells occurs through a sequential two-step process where an initial pathogenic or sterile inflammatory trigger is followed by an amplified response to a later un-related secondary pathogen challenge. The memory effect is mediated at least in part through epigenetic modifications of the chromatin landscape. Here, we investigated the role of the epigenetic modifier Setdb2 in microbial (β-glucan) or sterile trigger (Western-diet-WD/oxidized-LDL-oxLDL)-induced trained immunity of macrophages. Using genetic mouse models and genomic analysis, we uncovered a critical role of Setdb2 in regulating proinflammatory and metabolic pathway reprogramming. We further show that Setdb2 regulates trained immunity through two different complementary mechanisms: one where it positively regulates glycolytic and inflammatory pathway genes via enhancer-promoter looping, and is independent of its enzymatic activity; while the second mechanism is associated with both increased promoter associated H3K9 methylation and repression of interferon response pathway genes. Interestingly, while both mechanisms occur in response to pathogenic training, only the chromatin-looping mechanism operates in response to the sterile inflammatory stimulus. These results reveal a previously unknown bifurcation in the downstream pathways that distinguishes between pathogenic and sterile inflammatory signaling responses associated with the innate immune memory response and may provide potential therapeutic opportunities to target cytokine vs. interferon pathways to limit complications of chronic inflammation.

Setdb2↗

PubMed2026

Attribution of PM2.5-Induced Transcriptomic Perturbation to Toxic Components.

Ambient fine particulate matter (PM2.5) is a chemically complex mixture whose health impacts are not fully captured by particle mass. Here, we developed an interpretable chemotranscriptomic framework to attribute PM2.5-induced molecular perturbations to toxicity-relevant components. PM2.5 collected from urban roadside and coastal environments was separated into whole, extractable, and unextractable fractions, characterized by LC/GC × GC-HRMS-based nontarget analysis and inductively coupled plasma mass spectrometry (ICP-MS), and evaluated using cytotoxicity testing and transcriptomic profiling in human bronchial epithelial cells. Urban PM2.5 exhibited greater cytotoxic potency per unit mass than coastal PM2.5, with extractable fractions accounting for most cytotoxic and pathway-level responses. Transcriptomics revealed distinct site-specific modes of action: urban PM2.5 preferentially induced oxidative stress, xenobiotic metabolism, and cell cycle suppression, consistent with acute, nonapoptotic injury, whereas coastal PM2.5 elicited weaker cytotoxicity but stronger interferon-mediated immune and apoptosis-related signaling. Integrating chemical abundance with pathway activity using random forest regression, SHAP interpretation, and mechanistic corroboration reduced 5,033 detected features to 444 pathway-linked candidate drivers. Fewer than 5% of features explained ∼95% of cumulative model contribution. Standard-confirmed contributors included plasticizer-related compounds, aromatic and heteroaromatic combustion products, and copper for urban PM2.5 and secondary/aged organics and nickel for coastal PM2.5. These findings support mechanism-informed prioritization of hazardous PM2.5 components beyond mass-based assessment.

Particulate Matter↗

PubMed2026

Exploring shared biomarkers and their mechanisms in thyroid cancer and systemic lupus erythematosus via bioinformatics analysis.

BACKGROUND: Systemic lupus erythematosus (SLE), an autoimmune disorder, is linked to a heightened risk of multiple malignancies, including thyroid cancer. Thyroid cancer is the most prevalent malignancy of the endocrine system, and its autoimmune-related pathological features render it an optimal subject for investigating the mechanisms of their comorbidity. The molecular mechanisms underlying this comorbidity are still ambiguous. The accurate diagnosis and treatment of thyroid cancer urgently necessitate innovative molecular targets that extend beyond conventional pathological characteristics. This study seeks to employ integrated bioinformatics approaches to elucidate potential shared molecular mechanisms and immunological features between thyroid cancer and systemic lupus erythematosus (SLE), aiming to enhance understanding of their comorbidity and identify novel intervention targets. METHODS: This study initially acquired gene expression data for TC and SLE from the GEO database and subsequently screened and identified differentially expressed genes (DEGs) shared by both diseases. Subsequently, we conducted Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Reactome functional enrichment analyses on these 46 shared differentially expressed genes (DEGs) and further assessed the activation status of pertinent pathways using Gene Set Enrichment Analysis (GSEA). Subsequently, we employed CIBERSORTx to examine immune infiltration patterns and developed protein-protein interaction networks utilising the STRING database. We identified hub genes utilising the MCODE and cytoHubba plugins and visualised the findings with Cytoscape software. We additionally assessed the diagnostic efficacy of these core hub genes in an independent dataset utilising ROC curves and investigated their prognostic relevance in thyroid cancer through Kaplan-Meier survival analysis and multivariate Cox proportional hazards regression. Ultimately, we employed the Network Analyst platform to forecast transcription factor-gene and miRNA-gene regulatory networks and identified potential targeted therapeutic compounds utilising the DSigDB database. RESULTS: This study identified 46 differentially expressed genes (DEGs) commonly linked to thyroid cancer and systemic lupus erythematosus (SLE), which were significantly enriched in signalling pathways associated with immune-inflammatory activation, type I interferon responses, and complement pathway activation. Moreover, GSEA findings validated that immune-inflammatory and autoimmune-related pathways are markedly activated in both conditions. Twelve hub genes were discerned through protein-protein interaction networks. Analysis of immune infiltration indicated that thyroid cancer and systemic lupus erythematosus exhibit a shared characteristic of innate immune dysregulation, marked by the infiltration of myeloid cells (neutrophils, M0/M2 macrophages). Receiver operating characteristic (ROC) curve analysis identified six significant core hub genes with substantial diagnostic value: C1QB, LCN2, C1QC, LTF, VSIG4, and C3AR1. Univariate survival analysis indicated that elevated expression of C1QC and C3AR1 significantly enhances overall survival in thyroid cancer patients; however, multivariate COX regression analysis revealed that their independent prognostic significance necessitates further validation. This study predicted the interaction networks of transcription factors and miRNAs regulating key genes, with LCN2 demonstrating the highest connectivity to miRNAs, and identified candidate therapeutic compounds linked to it. CONCLUSION: This study employed bioinformatics analysis to identify critical shared hub genes and molecular pathways connecting thyroid cancer and systemic lupus erythematosus, offering novel insights into their shared pathogenesis and the advancement of targeted biomarkers and therapeutic strategies.

Bioinformatics analysis↗