Search Results (623)

Background—Pancreatic ductal adenocarcinoma (PDAC) is among the deadliest malignancies, with a dismal 5-year survival rate. Despite continuous efforts to study its molecular signatures, the high degree of tumor-associated cellular heterogeneity in PDAC introduces extraneous microenvironmental components that complicate analysis. In recent years, multi-omics approaches have shown promise in deconvoluting cellular composition and enabling more specific, comprehensive cancer profiling. Method—To better characterize PDAC, we analyzed transcriptomic and proteomic data from 140 tumor tissues with 67 paired normal adjacent tissues and single-cell RNA sequencing data from 73 tumor tissues. Results—Using this approach, we successfully attributed molecular signatures to distinct cell-type populations. Overall, we found 59 tumor-cell-derived PDAC molecular signatures and evaluated them for functional relevance, prognostic value, and potential therapeutic implications. Among these, we identified molecular features associated with increased tumorigenic activity and immunosuppression. Moreover, survival analysis of protein phosphorylation and overall expression informed prognostic significance for potential therapeutic targets. Notably, we found that several phosphorylation changes correlate with poor patient survival, suggesting potential paths for therapeutic intervention by targeting protein post-translational modifications. Conclusion—Our study provides a detailed understanding of PDAC by characterizing key tumor-specific signatures that could serve as potential targets to improve clinical outcomes for this disease. Full article

Background: Tertiary lymphoid structures (TLSs) play a crucial role in regulating tumor invasion and metastasis and serve as a promising prognostic biomarker in immunotherapy, influencing survival and immune response in multiple cancers. However, existing studies rely on limited gene signatures to assess TLSs, and there remains a lack of comprehensive TLS-related features for pan-cancer prognosis or immunotherapy response prediction. Methods: Based on published TLS gene signatures, mutation data, and expression profiles from 33 tumor types in TCGA, along with data from 15 immune checkpoint blockade (ICB) cohorts, we first systematically evaluated six TLS gene signatures in relation to immune-related indicators and assessed their predictive and prognostic performance across tumors and immunotherapy. Subsequently, using meta-analysis, we constructed a de novo TLS-related gene feature set, termed predictTLS, designed to predict ICB efficacy and prognosis. The rationality and effectiveness of predictTLS were validated using internal validation sets, single-cell transcriptomic, and spatial transcriptomic data. Results: The evaluation revealed associations between TLS gene signatures and key immune-related indicators. The newly constructed predictTLS feature set demonstrated effectiveness in predicting both ICB therapy outcomes and patient prognosis across the analyzed cohorts. Validation across internal datasets, single-cell profiles, and spatial transcriptomics supported the robustness and biological relevance of predictTLS. Conclusions: This study provides a systematically validated, de novo TLS-related gene signature that can serve as a clinical biomarker for predicting immunotherapy response and prognosis in pan-cancer settings. These findings offer new tools for risk stratification and potential therapeutic targeting in tumor immunotherapy. Full article

Extrachromosomal circular DNA (eccDNA) has emerged as a pivotal contributor to cancer progression, facilitating oncogene amplification, dysregulated gene expression, and tumor heterogeneity. Despite its significance in cancer, the interplay between eccDNA and key epigenetic regulators such as EZH2 remains largely unexplored. In this study, we systematically investigate the correlation between Tazemetostat, a highly selective EZH2 inhibitor, and alterations in the eccDNA landscape and transcriptional programs in ovarian cancer. Through integrated profiling using Circle-seq and RNA sequencing, we demonstrate that EZH2 inhibition is associated with markedly reprogrammed eccDNA dynamics. Furthermore, multi-omics integration identified that 67 genes exhibited concordant changes in both eccDNA abundance and transcript expression. Subsequent analyses also pinpointed 11 genes as putative effectors of drug response. Notably, spatial single-cell transcriptomics identified SFRP1 as the most consistently reactivated tumor suppressor across eccDNA, bulk expression, and spatial datasets, based on predefined statistical and biological criteria, by Tazemetostat. Moreover, SFRP1 was one of the genes that varied the most within cancer-associated fibroblast populations, exhibiting distinct spatial expression patterns. Taken together, this study establishes the first potential evidence that EZH2 inhibition may reprogram eccDNA dynamics to potentially restore SFRP1 tumor suppressor expression in ovarian cancer. By integrating multi-omics and spatial single-cell transcriptomics, we uncovered a novel epigenetic–eccDNA axis that may contribute to oncogenic plasticity and therapeutic resistance. This could result in a paradigm shift in targeting eccDNA-driven malignancies. Full article

Lung adenocarcinoma (LUAD) remains a leading cause of cancer-related mortality worldwide, highlighting the urgent need to identify novel prognostic biomarkers and therapeutic targets. Kinesin Family Member 18B (KIF18B) is implicated in mitosis, yet its precise role in LUAD pathogenesis remains poorly defined. This study investigates the oncogenic and therapeutic role of KIF18B in LUAD. Integrated analysis of The Cancer Genome Atlas Program (TCGA) and Gene Expression Omnibus (GEO) datasets revealed that KIF18B is significantly upregulated in LUAD tissues, with its elevated expression strongly associated with an advanced pathological stage, high grade, and poor patient survival. Single-cell sequencing data analysis further indicated that KIF18B expression in LUAD is closely linked to key malignant processes, including cell cycle progression, proliferation, migration, and epithelial–mesenchymal transition (EMT). Functional experiments demonstrated that KIF18B knockdown markedly suppressed LUAD cell proliferation, migration, and invasion in vitro and inhibited tumor growth in vivo. Mechanistically, transcriptomic and pathway analyses revealed that KIF18B depletion downregulates Early 2 Factor (E2F) target genes. Luciferase reporter assays confirmed diminished E2F reporter activity as well as E2F2 promoter activity upon KIF18B silencing, while overexpression of E2F1, E2F2, or E2F3 rescued the inhibited proliferative phenotypes induced by KIF18B loss. Collectively, our findings establish KIF18B as an essential driver of LUAD progression that acts through the E2F transcriptional network, nominating it as a promising diagnostic and therapeutic target. Full article

Background: Oxidative stress (OS) plays an important role in oral lichen planus (OLP) development; however, the precise functions of the genes associated with OS (OSRGs) remain unclear. This study aimed to identify and characterize OS-linked molecular markers in OLP. Methods: Data were obtained from the GSE38616 and GSE211630 datasets, along with 467 OSRGs. Candidate genes were identified by cross-referencing differentially expressed genes with OSRGs. Biomarkers were then selected through a protein–protein interaction network analysis using Cytoscape. Functional enrichment analysis, regulatory network mapping, therapeutic compound prediction, molecular docking simulations, and RNA modification profiling were also performed. Single-cell RNA sequencing was used to characterize biomarker distribution among the distinct cell populations. Gene expression was validated using quantitative real-time PCR (qRT-PCR). Results: Five genes emerged as key biomarkers: TGFB1, KLF4, TNF, NQO1, and MMP9. Functional enrichment analysis revealed that these markers are involved in immune regulatory pathways between lymphoid and nonlymphoid cellular compartments. Network analysis identified hsa-miR-449a and hsa-miR-449b-5p as potential regulators of NQO1 and KLF4. Pharmaceutical screening identified several potential therapeutic compounds, such as meropenem anhydrous and hydroxyurea, which exhibit targeted binding affinity for key biomarkers. Docking simulations indicated robust binding interactions (binding energies < −5 kcal/mol) for most compound–biomarker combinations, excluding the KLF4–hydroxyurea pairing. In addition, putative m6A methylation sites were identified in the TNF, KLF4, and TGFB1 transcripts. Single-cell analysis identified T lymphocytes as the primary cell type of interest, with TGFB1 expression increasing progressively during T-cell maturation. Validation by qRT-PCR confirmed the transcriptomic results, demonstrating elevated expression of TGFB1, TNF, and MMP9, along with reduced NQO1 expression in OLP tissues. Conclusions: TGFB1, KLF4, TNF, NQO1, and MMP9 were identified as potential OS-associated biomarkers in OLP. These findings provide insights into disease mechanisms and reveal potential therapeutic targets. Full article

Background/Objectives: Metaplastic breast carcinoma (MpBC) is a rare and aggressive malignancy characterized by significant histological heterogeneity and limited response to standard chemotherapy. Due to its morphological diversity, MpBC often presents diagnostic challenges and can overlap with other mesenchymal tumors. This study aimed to characterize the genomic landscape of MpBC using a nationwide Japanese database and to explore the molecular basis of its diagnostic ambiguities and therapeutic responses. Methods: We retrospectively analyzed genomic and clinical data from 123 MpBC cases registered in the Center for Cancer Genomics and Advanced Therapeutics (C-CAT) database. To evaluate diagnostic boundaries, genomic profiles of histological mimickers, including 19 cases of angiosarcoma and eight cases of myoepithelial carcinoma, were also examined. Furthermore, an exploratory single-cell RNA-sequencing analysis was performed on 3274 cells from independent MpBC datasets to investigate cellular heterogeneity and potential lineage plasticity. Results: TP53 (73.2%) and PIK3CA (46.0%) were the most prevalent genomic alterations in the MpBC cohort. Exploratory analysis suggested that PIK3CA mutations may be associated with an improved disease control rate in patients receiving taxane-based therapy (p = 0.028). Comparisons with mimickers identified distinctive molecular signatures, such as MED12 and HRAS hotspot mutations, across entities. Single-cell transcriptomics identified a distinct subpopulation (7.02% of malignant cells) co-expressing epithelial and phyllodes-like signatures. Conclusions: These findings suggest that MpBC harbors hybrid malignant cell populations that may contribute to its complex morphological diversity. While the therapeutic associations are based on a limited cohort and require prospective validation, the integration of comprehensive genomic and single-cell profiling provides an exploratory framework that may potentially enhance diagnostic accuracy in the future. However, these associations remain preliminary and require prospective validation to confirm their clinical utility. Full article

Objective: Myxofibrosarcoma (MXF) and undifferentiated pleomorphic sarcoma (UPS) are common and aggressive subtypes of cancer differing by clinical characteristics and prognosis; however, their differential diagnosis is difficult. Elucidation of cellular and transcriptomic discrepancies between these diseases that could improve their identification was the aim of our study. Methods: We applied single-cell RNA sequencing to compare MXF and UPS by tumor cell clusters and cell–cell ligand–receptor interactions, using five tumor samples of both subtypes. Results: We identify nine major cell types in all tumors analyzed. Any significant differences in their proportions between MXF and UPS were not found. Further reclusterization of lymphoid cells showed that cytotoxic CD8+ T cell proportion was higher in the MXF samples. In UPS cancer cells, the pathways maintaining extracellular matrix components (including collagens, proteoglycans, and other proteins) were highly active, while MXF cells were characterized by high activity of growth factors and angiogenesis pathways. The ligand–receptor interactions between cancer cells and the microenvironment differed significantly between MXF and UPS. In UPS, CD80 of dendritic cells and macrophages prominently interacted with T cell co-inhibitory CTLA-4 receptors, whereas the activating CD80-CD28 interaction was predominant in MXF. Moreover, in UPS, CD44 and integrins of cytotoxic CD8+ T cells prominently interacted with COL1A1/2, while in MXF CD44, interaction with FN1, COL6A1, and LAMC1 prevailed. Conclusions: Differences were identified between UPS and MFS in the composition of lymphoid cell populations and in the intercellular interactions. This proposes deeper understanding of the biological differences between these sarcoma subtypes and may be important for the development of new therapeutic approaches, although further validation of the findings is required. Full article

Spatial transcriptomics (ST) enables genome-wide gene expression profiling while preserving tissue architecture, bridging the gap between bulk, single-cell, and histological analyses. Originating in 2016 and rapidly evolving since, ST has transformed infectious disease research by mapping host–pathogen interactions directly within intact tissues. Current platforms fall into two categories: sequencing-based methods (Visium, GeoMx, Stereo-seq) offering whole-transcriptome coverage at modest resolution and imaging-based platforms (Xenium, CosMx, MERFISH) providing single-cell or subcellular detail with targeted gene panels. These technologies reveal spatially organized immune responses, local tissue remodeling, and pathogen niches across viruses, bacteria, and parasites. In viral infection, ST uncovered heterogeneity in COVID-19 lung microenvironments, spatial immune activation in lymphoid tissues, and variant-specific inflammatory patterns. In bacterial disease, ST delineated granuloma architecture in tuberculosis and mapped vaccine-induced lung responses in Shigella studies. Parasitic infection studies identified localized inflammatory hotspots and microenvironmental control of T-cell differentiation in malaria. Despite powerful insights, ST faces constraints including RNA quality limitations, tradeoffs between resolution and transcript breadth, high cost, and analytical complexity. Nonetheless, ST increasingly informs vaccine design by identifying tissue-specific immune programs and protective microenvironments and is poised to become a standard tool for infectious disease biology. Full article

Migraine is a complex neurovascular disorder in which immune signaling intersects with vascular and neural circuits, yet the tissue and cell-type context of common genetic risk remains incompletely defined. We integrated large-scale migraine genome-wide association study (GWAS) summary statistics with Genotype-Tissue Expression (GTEx) v8 expression and splicing quantitative trait loci (eQTLs and sQTLs), Bayesian co-localization, single-cell RNA sequencing of peripheral blood mononuclear cells (PBMCs) from migraine cases and controls, a healthy single-cell multi-omics atlas (assay for transposase-accessible chromatin (ATAC) plus RNA), high-dimensional weighted gene co-expression network analysis (hdWGCNA), and embryo-level spatial transcriptomics. Genetic signals were enriched in peripheral arteries, heart, and blood, and gene-level enrichment highlighted mucosal–smooth muscle organs including the bladder and the cervix endocervix. Cell-type prioritization consistently implicated endothelial and vascular smooth muscle lineages, with additional support for inhibitory interneurons and bladder epithelium. In PBMC T cells, co-expression modules capturing cytotoxic/activation and T-cell receptor signaling programs contained migraine-prioritized genes, including PTK2B, nominating immune activation circuitry as a component of genetic susceptibility. Spatial projection further localized risk concordance to craniofacial/meningeal interfaces and visceral smooth muscle–mucosal structures. Together, these analyses delineate a systemic neuroimmune–vascular architecture for migraine and provide genetically anchored candidate pathways and targets for mechanistic and therapeutic follow-up. Full article

Single-cell RNA sequencing (scRNA-seq) provides a comprehensive understanding of cellular complexity; however, its requirement for fresh or frozen samples limits its flexibility. To overcome this limitation to effectively leverage clinical samples, Chromium Fixed RNA Profiling on formalin-fixed paraffin-embedded (FFPE) tissue blocks (scFFPE-seq) was developed to perform single-nucleus RNA sequencing from nuclei isolated from FFPE. In this study, we utilized fresh tissue samples from colon, ileum, and skin to assess the viability of scFFPE-seq compared to these fresh samples. We were able to recover unique cell types from challenging FFPE tissues and validated scFFPE-seq findings through Hematoxylin and Eosin (H&E) images. The results demonstrated that scFFPE-seq effectively captured the single-cell transcriptome in FFPE tissues, obtaining comparable cell abundance, cell type annotation, and pathway characterization to those in fresh tissues. Overall, the study presents strong evidence of the potential of scFFPE-seq to enhance scientific knowledge by enabling the generation of high-quality, sensitive single-nucleus RNA-seq data from preserved tissue samples. This technique unlocks the vast archives of FFPE samples for extensive retrospective genomic studies. Full article

RNA sequencing (scRNA-seq) has emerged as a transformative technology for dissecting cellular heterogeneity and immune complexity in livestock species. This review summarizes recent advances in the application of single-cell transcriptomics to livestock health, with a particular focus on immune system organization and host–pathogen interactions in cattle, pigs, poultry, and small ruminants. We highlight the development of large-scale, multi-tissue cell atlases—such as the Cattle Cell Atlas and resources generated through the Farm Animal Genotype-Tissue Expression (FarmGTEx) consortium—that provide foundational reference frameworks for livestock genomics. These atlases have enabled the identification of tissue- and species-specific immune cell populations, clarified cellular tropism of major bacterial and viral pathogens, and revealed distinctive immunological features, including the prominent role of γδ T cells in ruminant immunity. We discuss how single-cell immune receptor sequencing has advanced monoclonal antibody discovery and informed rational vaccine design. Key technical and analytical challenges, including incomplete genome annotations, tissue processing constraints, and cross-platform data integration, are critically assessed. Finally, we outline future directions integrating spatial transcriptomics and multi-omics approaches to further resolve immune function within tissue contexts. Collectively, these advances position single-cell transcriptomics as a central framework for improving disease resistance, vaccine efficacy, and translational research in livestock health. Full article

Immune checkpoint inhibitors (ICIs) targeting PD-1/PD-L1 and CTLA-4 are widely used in the treatment of several cancers and have significantly improved survival outcomes in responsive patients. However, a substantial proportion of patients fail to benefit from these therapies, underscoring the urgent need for accurate prediction of ICI response. We propose a deep learning framework, ICIsc, to accurately predict ICI response by integrating single-cell RNA sequencing (scRNA-seq) data with protein large language models. Specifically, patient representations are constructed using transcriptomic profiles and immune-related gene set scores as latent embedding features, while drug representations are derived from amino acid sequences of ICI encoded by the Evolutionary Scale Modeling 2 (ESM2). For bulk data, ICIsc employs a bilinear attention module to fuse patient and drug embeddings for response prediction. For scRNA-seq data, ICIsc infers cell–cell interactions using a single-sample network (SSN) approach and applies GATv2 to model immune microenvironment heterogeneity at the single-cell level. Benchmark evaluations and independent validation demonstrate that ICIsc consistently outperforms baseline models and exhibits robust generalization performance. SHAP-based interpretability analysis further identifies key genes (e.g., GAPDH) associated with immunotherapy response and patient prognosis. Overall, ICIsc provides an accurate and interpretable framework for predicting immunotherapy outcomes and elucidating underlying mechanisms. Full article

Background: Diabetes increases the risk of cataract formation fivefold. Immune-mediated inflammation has been reported to play a role in this process; however, whether alterations in the immune landscape are involved remains unknown. Therefore, we conducted a multi-omics analysis to evaluate the impact of immune inflammation on the lens. Methods: Bulk RNA sequencing was performed on peripheral blood mononuclear cells (PBMCs) from diabetic patients and lens tissues from diabetic rats. Single-cell RNA sequencing was utilized to characterize intercellular interactions. Key gene and protein expressions were validated via laboratory assays. Results: An integrated RNA-seq analysis revealed a disruption of the blood–aqueous barrier integrity in the diabetic group, enhanced monocyte migration and adhesion, increased differentiation from classical to non-classical monocytes, and the upregulation of TNF and IFN-γ signaling pathways. The transcriptomic profiling of rat lenses revealed an increased proportion of monocytes and the activation of apoptotic pathways in lens epithelial cells. Immunohistochemistry and immunofluorescence staining demonstrated elevated caspase-3 and IL-6 levels in lens epithelial cells and increased immune cell infiltration in the diabetic group. The qRT-PCR and ELISA confirmed elevated levels of the pro-inflammatory cytokines IL-6 and IFN-γ, alongside reduced anti-inflammatory cytokine IL-10 in the peripheral blood and aqueous humor of diabetic patients. Conclusions: Diabetes alters the peripheral immune microenvironment and disrupts the blood–aqueous barrier, promoting intraocular inflammation and lens epithelial cell apoptosis, thereby accelerating cataract development. Full article

Understanding the intimate interactions between plants and their microbiota at the cellular level is essential for unlocking the full potential of plant holobionts in agricultural systems. Traditional bulk and microbial community-level sequencing approaches reveal broad community patterns but fail to resolve how distinct plant cell types interact with or regulate microbial colonization, as well as the diverse antagonistic and synergistic interactions and responses existing between various microbial populations. Recent advances in single-cell and spatial multi-omics have transformed our understanding of plant cell identities as well as gene regulatory programs and their dynamic regulation in response to environmental stresses and plant development. In this review, we highlight the single-cell discoveries that uncover the plant cell-type-specific microbial perception, immune activation, and symbiotic differentiation, particularly in roots, nodules, and leaves. We further discuss how integrating transcriptomic, epigenomic, and spatial data can reconstruct multilayered interaction networks that connect plant cell-type-specific regulatory states with microbial spatial niches and inter-kingdom signaling (e.g., ligand–receptor and metabolite exchange), providing a foundation for developing new strategies to engineer crop–microbiome interactions to support sustainable agriculture. We conclude by outlining key methodological challenges and future research priorities that point toward building a fully integrated cellular interactome of the plant holobiont. Full article

We present the single-cell transcriptomic analysis of peripheral blood mononuclear cells (PBMC) from individuals during acute HIV-1 infection caused by viral strains circulating in Russia and the Former Soviet Union (FSU) countries. Using 10x Genomics single-cell RNA sequencing (scRNA-seq) on the Illumina NextSeq 550 platform, we have analyzed scRNA-seq data from three treatment-naive patients (viral load > 1 × 10⁶ copies/mL, estimated infection duration ≤ 4 weeks) and three healthy donors. Data integration (Seurat, Harmony), automated cell-type annotation (CellTypist), and GeneOntology (GO) enrichment analysis for highly expressed and low-expressed genes revealed a profound reorganization of transcriptional programs across key immune populations, including memory CD4⁺ and CD8⁺ T cells, non-classical monocytes and natural killer cells (NK-cells). We observed signatures of hyperactivation of pro-inflammatory pathways (NF-kB, TNF, and type I/II interferon signaling), upregulation of genes associated with cellular migration (CXCR4, CCR7) and metabolic adaptation (oxidative phosphorylation components), alongside a mixed pro- and anti-apoptotic expression profile. Notably, our data pointed to a pronounced dysregulation of the TGF-β and mTOR signaling cascades, disrupted intercellular communication networks—particularly between cytotoxic cells and their regulators—altered expression of genes implicated in disease progression (OLR1, SERPINB2, COPS9) and viral persistence control (NEAT1, NAF1). This work provides an initial single-cell transcriptional atlas characterizing early immune responses to HIV-1 sub-subtypes A6 and CRF63_02A6, the predominant drivers of the HIV epidemic across the FSU region. Full article