Search Results (229)

Dengue virus (DENV) and chikungunya virus (CHIKV) co-circulate in many regions and present with overlapping clinical features, which complicate accurate diagnosis and disease management. This study develops an integrative transcriptomic framework to identify robust host gene signatures that distinguish between dengue, chikungunya, and healthy states. Publicly available RNA sequencing (RNA-seq) datasets derived from human blood samples were analyzed using a cross-validation design to ensure robustness and prevent information leakage. Differential expression analysis was performed independently within each dataset using the Generalized Linear Models with Quasi-Likelihood F-tests and Magnitude–Altitude Scoring (GLMQL-MAS) framework, followed by Cross-Magnitude–Altitude Scoring (Cross-MAS) integration to identify shared and virus-specific gene signatures. A strict consensus approach across folds was applied to derive reproducible gene sets. These signatures were used for dimensionality reduction and multinomial logistic regression to evaluate classification performance. A small subset of selected genes showed strong discriminative performance within the cross-validation framework, with test balanced accuracy reaching 0.97, which improved upon models using all genes. Biologically, both infections exhibited a shared antiviral response characterized by interferon signaling and innate immune activation. However, distinct virus-specific patterns were identified. Dengue infection was associated with cell-cycle and DNA replication pathways, while chikungunya infection showed stronger enrichment of inflammatory and immune signaling pathways, including NF-kappaB and Toll-like receptor signaling. Overall, this study provides a cross-validation-based framework for integrative transcriptomic analysis and identifies compact, reproducible host-response signatures with strong discriminative signals in the analyzed cohorts. These signatures require validation in larger independent cohorts before any clinical or diagnostic application. Full article

Type I interferons (IFN-I), including IFN-α, IFN-β, and IFN-ω, are central to antiviral defence and immune regulation. Autoantibodies targeting IFN-I (anti-IFN-I AAbs) have emerged as key pathogenic factors in severe coronavirus disease 2019 (COVID-19) and are detectable in systemic lupus erythematosus (SLE), a prototypic IFN-driven autoimmune disease. Here we compare the prevalence and clinical impact of anti-IFN-I autoantibodies (Aabs) in COVID-19 and SLE based on a structured review of 53 studies from 2014 to 2025 and highlight the clinical associations and therapeutic opportunities presented by these autoantibodies. In COVID-19, neutralising anti-IFN-α and/or anti-IFN-ω AAbs were consistently associated with severe disease and impaired antiviral responses, particularly in older male populations. In SLE, anti-IFN-α AAbs were variably detected; neutralising antibodies were associated with reduced interferon gene signatures in some cohorts but inconsistent correlations with disease activity. Therapeutically, anti-IFN-I AAbs in COVID-19 may inform risk stratification and early antiviral strategies, whereas in SLE, IFN-α blockade, including IFN-α kinoid vaccination, demonstrates modulation of IFN signatures but variable clinical benefit. Notably, these findings reveal an immunological paradox: the same neutralising mechanism that impairs antiviral defence in COVID-19 may attenuate chronic IFN-driven inflammation in SLE. Taken together, anti-IFN-I AAbs exert context-dependent effects: pathogenic in acute viral infection yet potentially modulatory in chronic IFN-driven autoimmunity. Prospective longitudinal studies are required to further clarify their translational utility and long-term clinical impact. Full article

Mitochondria are central hubs of antiviral immunity and cellular metabolism, yet the links between SARS-CoV-2–induced mitochondrial remodeling, antiviral gene regulation, and post-translational control remain incompletely understood. Here, we investigated mitochondrial–immune remodeling in SARS-CoV-2–infected lung-derived LC-HK2 cells at 48 and 96 h post-infection using confocal and high-content imaging, colocalization analysis, CellProfiler quantification, RT-qPCR, proteomics, cytokine profiling, and conditioned-medium analysis. Infection induced a time-dependent mitochondrial phenotype. At 48 hpi, cells displayed early mitochondrial stress and fission-associated signatures, including increased DRP1, transient upregulation of mitochondrial respiratory genes, and reduced MFN1/2. At 96 hpi, mitochondria shifted toward elongated perinuclear networks, accompanied by increased fusion/biogenesis markers and partial ISG15–MFN2 colocalization, indicating a spatial association between ISG15-related antiviral/stress responses and mitochondrial remodeling. Antiviral and ISG-related transcripts were consistently upregulated, but IFN-α2 secretion remained limited, suggesting partial uncoupling between antiviral transcriptional activation and downstream interferon output. SUMO2/3 was dynamically modulated and showed time-dependent colocalization with mitochondrial dynamics proteins and MAVS. Together, these data support a coordinated mitochondrial–immune regulatory axis involving mitochondrial remodeling, ISG15-associated responses, and SUMO-dependent regulation during SARS-CoV-2 infection. Full article

Neuroinflammation in multiple sclerosis (MS) is driven by the infiltration of myelin-reactive T cells into the central nervous system (CNS). Interferon-β (IFN-β) is one of the earliest disease-modifying treatments (DMTs) approved for MS and remains widely used in special populations (pregnant and elderly patients) owing to its favorable safety profile. However, the exact mechanism of action of this drug and reliable biomarkers of treatment response remain unclear. Transcriptomic profiling and data integration approaches offer powerful tools for investigating complex patterns of regulation and molecular mechanisms underlying therapeutic efficacy. In this study, we performed an integrative analysis of openly available transcriptomic datasets to characterize IFN-β-induced gene expression changes in MS patients. By combining data from large independent cohorts, we identified a 43-gene transcriptional signature consistently associated with IFN-β treatment across disease stages, including progressive MS. To explore the relevance of this signature, we cross-referenced the 43-gene signature with publicly available expression quantitative trait loci (eQTL) datasets to determine whether these genes could be influenced by known MS-associated risk variants highlighting Interferon-Induced Transmembrane Protein 3 (IFITM3) as a candidate molecular mediator of MS. This integrative approach provides new insights into IFN-β-driven immune modulation and supports the development of therapeutic strategies for MS. Full article

Background/Objectives: Chlamydia trachomatis (CT) is a prevalent sexually transmitted pathogen associated with pelvic inflammatory disease, infertility, and has been proposed as a potential contributor to carcinogenesis through chronic inflammation and tissue remodeling. The molecular mechanisms triggered by CT infection in fallopian tube cellular contexts and their relevance to ovarian cancer transcriptomes remain incompletely understood. Methods: We analyzed GSE109428, profiling primary human fallopian tube mesenchymal cells infected with CT, to identify differentially expressed genes and characterize affected pathways using g:Profiler and STRING protein–protein association networks (confidence ≥ 0.7). To provide translational context, we computed ssGSEA scores in TCGA-OV for four signatures capturing IFN/ISG, TNF/NF-κB, NOD/innate immunity, and ECM programs, and evaluated inter-signature correlations and exploratory associations with overall survival (OS) and progression-free interval (PFI). Results: CT infection induced sustained inflammatory and interferon-associated transcriptional programs, with STRING networks highlighting cytokine hubs and a densely connected ISG module. Genes downregulated at 48 h post-infection (48-hpi) showed coherent enrichment for ECM organization and adhesion pathways. In TCGA-OV (n = 307), inflammatory and innate immune signatures co-occurred across tumors, with moderate correlations between TNF/NF-κB and NOD/innate (ρ = 0.591) and IFN/ISG and NOD/innate (ρ = 0.534). Exploratory survival analyses showed no significant associations with OS or PFI in Kaplan–Meier analyses or multivariable Cox models, including clinically adjusted and tumor microenvironment-adjusted specifications. Conclusions: CT infection induces sustained inflammatory and interferon-linked programs and coordinated repression of ECM networks in fallopian tube mesenchymal cells. Analogous immune transcriptional states co-occur in ovarian tumors, though the signatures evaluated did not yield robust prognostic signals in TCGA-OV. As this is an entirely in silico study without experimental validation, these findings should be treated as hypothesis-generating; thus, further mechanistic and experimental studies are warranted to clarify how CT infection-associated pathways may intersect with female tumorigenesis. Full article

Osteoarthritis is a chronic degenerative joint disease characterized by inflammation and cartilage degradation, for which current treatments are mainly symptomatic and unable to halt disease progression. Adipose-derived mesenchymal stem cells (ASCs) represent a promising therapeutic option due to their regenerative and immunomodulatory properties, which may be further enhanced through specific priming strategies. In this study, primary human ASCs were exposed to interleukin-1 beta (IL1β), interferon-gamma (IFNγ), or hypoxic priming, and subsequently analyzed using a multi-omics approach integrating RNA sequencing, proteomics of secretome, and exosomal miRNA profiling. Differential gene expression, protein abundance, and miRNA signatures were assessed together with functional enrichment and network analyses. IL1β priming induced marked transcriptional reprogramming of ASCs, while hypoxia and IFNγ priming produced limited changes. IL1β also profoundly reshaped the ASC secretome and exosomal miRNA cargo, revealing coordinated regulation of pathways involved in immune modulation and cartilage remodeling. In contrast, the other priming conditions showed minimal and less integrated molecular effects. Overall, IL1β priming consistently generated a multi-layered molecular signature linking immunoregulatory and regenerative pathways. These findings suggest that IL1β priming enhances the functional properties of ASCs and provides mechanistic insight supporting their potential use in osteoarthritis therapy. Full article

The prioritization of biomarkers that inform molecular-targeted cancer research remains challenging because tumor vulnerabilities are context-dependent. The ubiquitin–proteasome system is essential for cancer cell survival; however, the functional and biomarker-level relevance of individual proteasome subunits has not been systematically defined across cancer types. In this study, we performed an integrative pan-cancer analysis to prioritize proteasome subunits that function as context-dependent vulnerability biomarkers. We analyzed proteasome subunits and proteasome-associated genes across 54 cancer types by integrating large-scale CRISPR (n = 1178 cell lines) and RNAi (n = 707 cell lines) dependency datasets with transcriptomic, survival, immune infiltration, and co-essentiality network analyses. PSMB5 and PSMB6 were prioritized as robust cross-platform and cross-lineage dependency biomarkers, exhibiting reproducible and selective vulnerability patterns across diverse malignancies. Their dependency strength was quantitatively associated with immune-related signaling pathways, including MHC and interferon responses, and inversely correlated with key immune regulatory genes such as NLRC5 and IRF1. Co-essentiality network analysis revealed modular functional organization of proteasome-associated genes, supporting context-dependent roles rather than uniform essentiality. Importantly, the association between proteasome subunits and tumor immune context was externally validated through meta-analysis across 24 independent hepatocellular carcinoma cohorts, demonstrating reproducible correlations with CD4-positive T cell, CD8 T cell, and macrophage infiltration signatures. Functional validation further confirmed that siRNA-mediated knockdown of PSMB5 and PSMB6 significantly impaired proliferation across multiple hepatocellular carcinoma cell lines. Collectively, this study prioritizes PSMB5 and PSMB6 as consistently associated functional biomarkers that integrate genetic dependency and immune context, providing a data-driven framework for stratifying proteasome-targeted therapeutic strategies across cancers. Full article

Background: Fibrolamellar carcinoma (FLC) is a rare liver malignancy affecting adolescents. FLCs harbor a DNAJB1–PRKACA gene fusion that combines heat shock protein DNAJB1 with the catalytic subunit of protein kinase A. Surgery with systemic therapy provides 5-year survivals of 30–50%, but advanced disease remains largely incurable. Three-dimensional explants from 41 FLC patients were interrogated for drug sensitivity, resistance, and synergy against cytotoxics, targeted agents, and signal transduction inhibitors. Methods: Sterile specimens from histologically confirmed FLC patients were analyzed by Ex Vivo Analysis of Programmed Cell Death (EVA/PCD™) in a CLIA-licensed laboratory. Following mechanical and enzymatic disaggregation, explants underwent 72 h drug exposure. LC₅₀ values were derived from five-point dose–response curves and compared with a database of over 10,000 human tumor analyses. Synergy was assessed by combination index. In parallel, targeted metabolomic profiling was performed in five FLC patients using tandem MS/MS. Results: Forty-one samples were analyzed. Of 24 drugs selected, tumor-cell yields were adequate for testing in 18 (75%). Single-agent activity favored vorinostat, followed by phenformin and 6-diazo-5-oxo-L-norleucine. Combinations favored gemcitabine plus oxaliplatin (GEMOX) and 5-FU plus interferon. Metabolomic analysis identified distinct signature consistent with mitochondrial dysfunction and altered polyamine metabolism. Conclusions: The present findings are exploratory, and hypothesis-generating and should not be interpreted as evidence of clinical efficacy. Prospective clinical validation and mechanistic studies will be required to further define the therapeutic relevance of these observations in fibrolamellar carcinoma. Full article

Background: Chemotherapy and radiation accelerate aging of multiple systems, including the immune and musculoskeletal systems. Resistance training may mitigate some of the late physiologic effects of cancer therapy. Methods: We developed a community-based pilot study of resistance training for long-term cancer survivors meeting criteria for pre-frailty or frailty (N = 8; 6 allogeneic hematopoietic cell transplant, 1 autologous hematopoietic transplant, 1 breast cancer survivor) and their caregivers (N = 8 healthy controls) consisting of a baseline assessment, 10 weeks of personalized resistance training at least once weekly as a group and as many additional times on an individual basis as their schedule allowed, and an end-of-study assessment to measure change in strength and body composition. Blood samples were collected at the start of the study and after the 10-week training program to assess changes in peripheral blood mononuclear cell DNA methylation patterns, gene expression measured by RNA sequencing, and stool microbiome analysis using metagenomics. The median number of resistance training sessions was 25 sessions. Results: Cancer survivors and controls both more than doubled their squat and press volume after 10 weeks. At baseline, cancer survivors exhibited a pro-inflammatory transcriptomic and epigenetic profile with elevated interferon signaling and reduced naïve T cell signatures compared to healthy controls, consistent with immune senescence. After 10 weeks of resistance training, these differences normalized, suggesting that exercise exerted anti-inflammatory and immune-restorative effects in cancer survivors at both gene expression and methylation levels. Ten fecal microbial pathways that were lower in relative abundance in patients compared with controls at baseline were no longer significantly different post-exercise. Conclusions: Our data suggest that in addition to beneficial changes in body composition, resistance training may exert an immune restorative effect in cancer survivors. Full article

Polycythemia vera (PV) is a JAK2V617F-driven myeloproliferative neoplasm characterized by erythroid expansion, increased thrombotic risk, and heterogeneous clinical outcomes. Although prior studies have described key transcriptional abnormalities—including Janus kinase–signal transducer and activator of transcription (JAK–STAT) hyperactivation and chronic myeloinflammation—most have examined single hematopoietic compartments. A multi-compartment approach may reveal conserved and lineage-specific disease-associated transcriptional programs. Here, an integrated, multi-compartment transcriptomic analysis of publicly available microarray datasets was performed, spanning bone marrow (BM) CD34+ progenitors, peripheral blood (PB) CD34+ progenitors, and whole blood from PV patients and healthy controls, with independent validation in neutrophils. Differential gene expression, pathway enrichment, and protein–protein interaction network analyses were used to delineate conserved versus compartment-specific transcriptional programs and to evaluate persistence of progenitor-derived signatures into mature myeloid cells. Across compartments, PV demonstrated consistent enrichment of inflammatory, interferon, and JAK–STAT-associated pathways despite limited overlap at the individual gene level, indicating that core disease processes are maintained through lineage- and differentiation-stage-specific transcriptional reprogramming. Network analysis identified highly connected hub genes, which were used to derive a single-sample gene set enrichment (ssGSEA) signature. This signature showed strong diagnostic performance across cohorts; remained enriched in PV neutrophils; and correlated with platelet count, indolent disease status, and reduced levels in post-splenectomy patients. Together, these findings support a model in which PV is driven by stable, progenitor-derived inflammatory programs that persist across myeloid differentiation while incorporating compartment-specific adaptations, and highlight the value of multi-compartment, network-based approaches for translational biomarker development. Full article

Systemic lupus erythematosus (SLE) is a prototypic systemic autoimmune disorder arising from the convergence of genetic susceptibility, epigenetic remodeling, environmental exposures, and dysregulated immune networks. Although traditionally characterized by autoantibody production and immune complex mediated tissue injury, advances in genomics, systems immunology, and multi-omics profiling have revealed that lupus represents a multilayered failure of immune homeostasis driven by interconnected molecular circuits. Genetic variants enriched in regulatory immune enhancers establish a permissive transcriptional landscape that sensitizes innate nucleic acid sensing pathways and interferon signaling. Epigenetic remodeling further amplifies inflammatory transcriptional programs, while environmental triggers such as ultraviolet radiation and viral infection initiate bursts of nucleic acid release and immune activation. Defective apoptotic cell clearance, mediated in part by scavenger receptor dysfunction and complement abnormalities, increases the availability of immunogenic nucleic acids that engage pattern recognition receptors and drive chronic type I interferon production. This interferon-dominated environment rewires immune cell metabolism, alters differentiation trajectories of T and B lymphocytes, and sustains autoreactive immune circuits. Emerging multi-omics studies reveal distinct molecular endotypes defined by interferon signatures, metabolic states, and immune cell composition, highlighting the heterogeneity of disease mechanisms across patients. In this review, we integrate genetic, epigenetic, metabolic, and immunological insights to propose a systems-level model of lupus pathogenesis in which defective debris clearance, nucleic acid sensing, interferon amplification, and metabolic reprograming form a self-reinforcing pathogenic network. Understanding this integrated molecular architecture provides a foundation for biomarker-guided therapeutic strategies and precision medicine approaches aimed at disrupting the key nodes that sustain chronic autoimmunity in SLE. Full article

Background: Glioblastoma (GBM) is the most aggressive primary brain tumor with extremely poor prognosis. Conventional diagnostic and prognostic approaches remain inadequate, highlighting the need for integrative strategies to improve patient outcomes. Methods: We analyzed ligand–receptor (L–R) interactions in TCGA-GBM transcriptomes using BulkSignaL-R, and validated their spatial expression patterns with single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics datasets. Prognostic histopathological features were extracted from hematoxylin and eosin (H&E)-stained sections through omics-guided feature identification, followed by classification using machine learning algorithms. Results: We identified four pivotal L–R pairs (LTB–CD40, VEGFA–ITGB1, FN1–COL13A1, and TGM2–ITGB1) to construct a risk model, which served as an independent prognostic factor for overall survival. The multivariate Cox regression analyses revealed that the risk score was significantly associated with Overall Survival (OS) (HR = 1.67, 95% CI: 1.25–2.25, p < 0.001). High-risk patients exhibited distinct molecular signatures, including CALN1 mutations, specific CNV patterns, and enriched Notch/interferon-γ signalings. scRNA-seq and spatial transcriptomics revealed that these L–R pairs were predominantly expressed in gMES-like glioma cells, OPC-like cells, and pericytes. Finally, our deep learning model successfully stratified risk groups based on histological features, identifying specific tumor regions (Clusters 0, 2, 4, and 5) as critical determinants of prognosis (AUC = 0.750 by Logistic Regression). Conclusions: We developed a novel multi-modal framework integrating L–R interactomics and deep learning-based pathomics. This approach not only elucidates the molecular and spatial landscape of glioma intercellular communication but also provides a methodological framework for risk stratification. Full article

Background: Immunotherapy has transformed cancer treatment by enhancing cytotoxic T-cell activity and interferon-γ (IFN-γ)-mediated tumor clearance. However, glioblastoma (GBM) remains largely refractory to these approaches, reflecting a profoundly immunosuppressive and myeloid-dominant tumor microenvironment. IFN-γ is central to antitumor immunity, yet chronic exposure can paradoxically promote adaptive resistance. How GBM cells respond to sustained IFN-γ signaling, and whether these responses differ across tumor states, remains poorly understood. Methods: To address this, we modeled chronic IFN-γ exposure in mesenchymal-like (U87) and proneural-like (U251) GBM cells over 28 days and performed integrated analyses of transcriptional, proteomic, and secretory responses. Results: While IFN-γ initially suppressed growth in both models, their long-term adaptations diverged. U87 cells developed a persistence-prone state characterized by progressive activation of PI3K–AKT signaling, whereas U251 cells exhibited sustained interferon signaling with persistent interferon-related DNA damage resistance signature (IRDS) expression and suppressed AKT activity. These transcriptional and signaling programs were incompletely reversible after cytokine withdrawal, indicating stable interferon conditioning. Analysis of TCGA glioblastoma datasets demonstrated that interferon-associated transcriptional programs are present across human tumors and are positively associated with PI3K–AKT pathway activity across molecular subtypes. Conclusions: Together, these findings reveal that chronic IFN-γ exposure drives distinct, lineage-dependent adaptive states in GBM, linking interferon signaling to divergent survival and immune-modulatory programs. While IFN-γ enhances immune activation, prolonged signaling may also promote tumor persistence. These results support therapeutic strategies that combine IFN-based approaches with interventions targeting adaptive survival pathways and immune reprogramming. Full article

This study aimed to develop and validate a transcriptomic risk signature for uterine corpus endometrial carcinoma (UCEC) and to investigate whether the identified prognostic program reflects immune–tumor uncoupling within the tumor microenvironment. Using transcriptomic data from The Cancer Genome Atlas (TCGA) UCEC cohort, we identified a 28-gene transcriptomic signature defining a high-risk state. The derived risk score robustly stratified patients into distinct survival groups and remained an independent predictor of overall survival after adjustment for clinical covariates. Functional analyses revealed that high-risk tumors are characterized by a distinct immune–tumor uncoupling phenotype, in which interferon-gamma (IFNG)-associated inflammatory signaling is preserved but fails to translate into effective antitumor immune activity. Specifically, effector immune programs, including CD8 T cell-related signatures and cytotoxic activity, were consistently reduced despite elevated IFNG-associated signaling, indicating a functional discordance between immune activation and immune execution rather than classical T cell exhaustion. In parallel, high-risk tumors exhibited consistently elevated cell cycle and DNA repair-associated transcriptional programs, suggesting that proliferative and stress-adaptive mechanisms represent dominant drivers of poor prognosis. External assessment in an independent GEO cohort (GSE17025) demonstrated consistent associations between signature activity, tumor status, and histological grade, supporting the reproducibility of the underlying transcriptional program at the biological and clinicopathological level. Collectively, this study provides transcriptomic evidence for a previously underappreciated immune–tumor uncoupling state in UCEC and highlights the importance of integrating immune signaling and tumor-intrinsic programs to understand disease progression. Full article

Coronavirus Disease 2019 (COVID-19) and other lower respiratory tract diseases (LRTDs), including bacterial pneumonia and acute respiratory distress syndrome, share overlapping clinical features but arise from distinct pathophysiological mechanisms. The molecular signatures that distinguish these diseases remain insufficiently characterized in African populations, where genetic background, endemic infections, and environmental exposures may substantially shape immune responses. We integrated spatially resolved single-cell transcriptomic profiles from lung autopsy specimens of 30 Malawian patients, including 10 with COVID-19, 12 with other LRTDs, and 8 non-LRTD controls. In total, 61,391 cells representing 15 cell types and 36,602 gene expression features were analyzed. Using an integrated machine learning framework that combined nine feature-ranking algorithms with incremental feature selection, we identified potential molecular signatures that could discriminate among disease states within this cohort. The optimal classification models achieved weighted F1 scores greater than 0.94, demonstrating a robust capacity to differentiate COVID-19 from other LRTDs in our dataset. Notably, the macrophage-associated state in COVID-19 was dominated by an IFN-γ response with upregulation of CD163 and HLA-DQA2, contrasting sharply with the type I/III interferon signature reported in European cohorts. In addition, we observed cell-type-specific COVID-19 signatures, including downregulation of CAV1 in AT1 cells, consistent with epithelial damage; dysregulation of SFTPC in AT2 cells, suggesting surfactant dysfunction; and upregulation of NFKBIA in neutrophils, indicating altered inflammatory regulation. Gene Ontology enrichment further revealed universal disruption of protein synthesis machinery, along with cell-type-specific alterations in immune activation, epithelial repair, and inflammatory signaling pathways. Full article