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A rare PRIMER cell state in plant immunity.
Plants lack specialized and mobile immune cells. Consequently, any cell type that encounters pathogens must mount immune responses and communicate with surrounding cells for successful defence. However, the diversity, spatial organization and function of cellular immune states in pathogen-infected plants are poorly understood1. Here we infect Arabidopsis thaliana leaves with bacterial pathogens that trigger or supress immune responses and integrate time-resolved single-cell transcriptomic, epigenomic and spatial transcriptomic data to identify cell states. We describe cell-state-specific gene-regulatory logic that involves transcription factors, putative cis-regulatory elements and target genes associated with disease and immunity. We show that a rare cell population emerges at the nexus of immune-active hotspots, which we designate as primary immune responder (PRIMER) cells. PRIMER cells have non-canonical immune signatures, exemplified by the expression and genome accessibility of a previously uncharacterized transcription factor, GT-3A, which contributes to plant immunity against bacterial pathogens. PRIMER cells are surrounded by another cell state (bystander) that activates genes for long-distance cell-to-cell immune signalling. Together, our findings suggest that interactions between these cell states propagate immune responses across the leaf. Our molecularly defined single-cell spatiotemporal atlas provides functional and regulatory insights into immune cell states in plants.
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Uncovering the core genetic programs governing plant guard cell biology.
Guard cells (GCs) regulate gas exchange and water loss in plants and have been extensively studied in Arabidopsis thaliana. However, cross-species comparisons at single-cell resolution remain limited. To address this, we aimed to define conserved and divergent transcriptomic signatures of GCs by generating a comparative single-cell atlas encompassing five species: A. thaliana, soybean (Glycine max), tomato (Solanum lycopersicum), rice (Oryza sativa), and sorghum (Sorghum bicolor). We performed single-nucleus RNA sequencing (sNucRNA-seq) on leaf tissues from each species, followed by integrative bioinformatic analyses to identify and annotate GC populations. Orthology-informed transcriptomic comparisons and co-expression analyses were applied to assess shared and species-specific regulatory modules. Our analyses revealed a conserved core transcriptome in GCs across species, enriched for genes involved in stomatal movement, abscisic acid signaling, carbon dioxide signaling, reactive oxygen species metabolism, and ion transport. Conserved expression of transcription factors (e.g. MYB60, FAMA orthologs), transporters (e.g. KAT1, SLAC1), and stress-responsive genes was observed, despite considerable evolutionary divergence. These findings provide a reference framework for cross-species GC biology, reveal conserved regulatory features, and nominate candidate genes for functional validation. This work contributes molecular insights toward improving drought resilience and stomatal efficiency in crop species through targeted gene engineering.
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UBE2A as a prognostic indicator across human cancers: Insights from multi‑omics and immune landscape analyses.
Ubiquitin‑conjugating enzyme E2A (UBE2A), a member of the ubiquitin‑conjugating E2 enzyme family, has been implicated in tumor development; however, its role across human cancer types remains incompletely understood. The present study aimed to systematically characterize the expression pattern, prognostic importance and immune relevance of UBE2A in a pan‑cancer context. Public datasets, including The Cancer Genome Atlas, Gene Expression Omnibus and Genotype‑Tissue Expression, were integrated to evaluate UBE2A expression, clinical importance, molecular characteristics, immune associations and biological functions across cancer types. Single‑cell RNA sequencing data were analyzed to investigate the cellular distribution of UBE2A. Functional validation was performed through UBE2A knockdown in breast cancer cell lines. Results indicated that UBE2A was significantly upregulated in a number of cancer types and was associated with unfavorable overall and progression‑free survival. UBE2A expression exhibited significant correlations with immune cell infiltration and immune checkpoint‑associated genes across cancer types. Functional enrichment analyses indicated that UBE2A was primarily involved in cell cycle regulation and proliferative processes. Single‑cell analysis revealed preferential UBE2A expression in proliferative T‑cell populations. Furthermore, in vitro experiments demonstrated that UBE2A knockdown significantly suppressed breast cancer cell proliferation, migration and invasion. Overall, UBE2A was shown to be a promising prognostic biomarker associated with tumor progression, cell cycle activity and immune‑associated characteristics across cancer types. Its preferential expression in proliferative T‑cell populations and oncogenic role in breast cancer suggest that UBE2A may serve as a potential therapeutic target and a candidate biomarker for evaluating tumor prognosis and the tumor immune microenvironment.
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SAP-expressing T peripheral helper cells identify systemic lupus erythematosus patients with lupus nephritis.
INTRODUCTION: T follicular (TFH) and peripheral helper (TPH) cells have been increasingly recognized as a pathogenic subset of CD4 T cells in systemic lupus erythematosus (SLE). The SLAM Associated Protein (SAP) regulates TFH and TPH function by binding to the co-stimulatory signaling lymphocyte activation molecule family (SLAMF) receptors that mediate T cell - B cell interactions. SAP and SLAMF are critical for TPH-dependent B cell maturation into autoantibody-producing plasma cells that characterize SLE pathogenesis. We hypothesized that SAP-expressing TPH cells are involved in the pathogenesis of lupus nephritis (LN). METHODS: Peripheral blood mononuclear cells (PBMC) were isolated using density gradient separation from whole blood. Cells were stained for cell surface markers, followed by permeabilization and staining of intracellular SAP for spectral flow cytometry analysis. We also analyzed SAP expression from renal infiltrating LN T cells using the available single-cell RNA sequencing (scRNA seq) Accelerated Medicines Partnership (AMP) SLE dataset. RESULTS: PBMC from 30 patients with SLE (34 ± 10 years old, 83% female), including 10 patients with LN, were analyzed. We found an increase in total SAP-positive CD4 and CD8 T cells in SLE compared with controls (55.5 ± 2.6 vs. 41.3 ± 3.4, p=0.007, and 52.5 ± 3.0 vs. 39.2 ± 2.8, p=0.007 respectively). In CD4 T cells, the highest SAP expression was in the TPH subset. The frequency of SAP+TPH in circulation correlated with disease activity; SLE patients with renal disease had higher levels of circulating SAP+TPH that remained significant after adjusting for age, sex, race, low complements, and elevated anti-dsDNA (p=0.014). scRNA-seq data of renal infiltrating T cells in LN identified SAP expression to localize to the TFH-like CD4 cluster and GZMK+ CD8 cluster. Increased SAP expression in LN was associated with the differential expression of SLAMF3 and SLAMF7 and granzyme K and EOMES. The existence of two predominant SAP-expressing subsets, the TFH-like CD4 T cells, and GZMK+ effector CD8 T cells, was verified using scRNA-seq data from a human transcriptomic atlas of fifteen major organs. CONCLUSION: The expansion of SAP-expressing T helper cells was associated with LN in our cohort and verified using scRNA-seq data of renal infiltrating T cells. Improved SLAM and SAP signaling understanding can identify new therapeutic targets in LN.
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Identification and validation of SERPINE1 as a prognostic and immunological biomarker in pan-cancer and in ccRCC.
Background: SERPINE1, a serine protease inhibitor involved in the regulation of the plasminogen activation system, was recently identified as a cancer-related gene. However, its clinical significance and potential mechanisms in pan-cancer remain obscure. Methods: In pan-cancer multi-omics data from public datasets, including The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx), and online web tools were used to analyze the expression of SERPINE1 in different cancers and its correlation with prognosis, genetic alteration, DNA promoter methylation, biological processes, immunoregulator expression levels, immune cell infiltration into tumor, tumor mutation burden (TMB), microsatellite instability (MSI), immunotherapy response and drug sensitivity. Further, two single-cell databases, Tumor Immune Single-cell Hub 2 (TISCH2) and CancerSEA, were used to explore the expression and potential roles of SERPINE1 at a single-cell level. The aberrant expression of SERPINE1 was further verified in clear cell renal cell carcinoma (ccRCC) through qRT-PCR of clinical patient samples, validation in independent cohorts using The Gene Expression Omnibus (GEO) database, and proteomic validation using the Clinical Proteomic Tumor Analysis Consortium (CPTAC) database. Results: The expression of SERPINE1 was dysregulated in cancers and enriched in endothelial cells and fibroblasts. Copy number amplification and low DNA promoter methylation could be partly responsible for high SERPINE1 expression. High SERPINE1 expression was associated with poor prognosis in 21 cancers. The results of gene set enrichment analysis (GSEA) indicated SERPINE1 involvement in the immune response and tumor malignancy. SERPINE1 expression was also associated with the expression of several immunoregulators and immune cell infiltration and could play an immunosuppression role. Besides, SERPINE1 was found to be related with TMB, MSI, immunotherapy response and sensitivity to several drugs in cancers. Finally, the high expression of SERPINE1 in ccRCC was verified using qRT-PCR performed on patient samples, six independent GEO cohorts, and proteomic data from the CPTAC database. Conclusion: The findings of the present study revealed that SERPINE1 exhibits aberrant expression in various types of cancers and is associated with cancer immunity and tumor malignancy, providing novel insights for individualized cancer treatment.
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Integrative analysis of cuproptosis-associated genes for predicting immunotherapy response in single-cell and multi-cohort studies.
BACKGROUND: The role of genes associated with the cuproptosis cell signaling pathway in prognosis and immunotherapy in ovarian cancer (OC) has been extensively investigated. In this study, we aimed to explore these mechanisms and establish a prognostic model for patients with OC using bioinformatics techniques. METHODS: We obtained the single cell sequencing data of ovarian cancer from the Gene Expression Omnibus (GEO) database and preprocessed the data. We analyzed a variety of factors including cuproptosis cell signal score, transcription factors, tumorigenesis and progression signals, gene set variation analysis (GSVA) and intercellular communication. Differential gene analysis was performed between groups with high and low cuproptosis cell signal scores, as well as Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. Using bulk RNA sequencing data from The Cancer Genome Atlas, we used the least absolute shrinkage and selection operator (LASSO)-Cox algorithm to develop cuproptosis cell signaling pathword-related gene signatures and validated them with GEO ovarian cancer datasets. In addition, we analyzed the inherent rules of the genes involved in building the model using a variety of bioinformatics methods, including immune-related analyses and single nucleotide polymorphisms. Molecular docking is used to screen potential therapeutic drugs. To confirm the analysis results, we performed various wet experiments such as western blot, cell counting kit 8 (CCK8) and clonogenesis tests to verify the role of the Von Willebrand Factor (VWF) gene in two ovarian cancer cell lines. RESULTS: Based on single-cell data analysis, we found that endothelial cells and fibroblasts showed active substance synthesis and signaling pathway activation in OC, which further promoted immune cell suppression, cancer cell proliferation and metastasis. Ovarian cancer has a high tendency to metastasize, and cancer cells cooperate with other cells to promote disease progression. We developed a signature consisting of eight cuproptosis-related genes (CRGs) (MAGEF1, DNPH1, RARRES1, NBL1, IFI27, VWF, OLFML3 and IGFBP4) that predicted overall survival in patients with ovarian cancer. The validity of this model is verified in an external GEO validation set. We observed active infiltrating states of immune cells in both the high- and low-risk groups, although the specific cells, genes and pathways of activation differed. Gene mutation analysis revealed that TP53 is the most frequently mutated gene in ovarian cancer. We also predict small molecule drugs associated with CRGs and identify several potential candidates. VWF was identified as an oncogene in ovarian cancer, and the protein was expressed at significantly higher levels in tumor samples than in normal samples. The high-score model of the cuproptosis cell signaling pathway was associated with the sensitivity of OC patients to immunotherapy. CONCLUSIONS: Our study provides greater insight into the mechanisms of action of genes associated with the cuproptosis cell signaling pathway in ovarian cancer, highlighting potential targets for future therapeutic interventions.
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Identification of a six-gene prognostic signature for bladder cancer associated macrophage.
As major components of the tumor microenvironment (TME), tumor-associated macrophages (TAMs) play an exceedingly complicated role in tumor progression and tumorigenesis. However, few studies have reported the specific TAM gene signature in bladder cancer. Herein, this study focused on developing a TAM-related prognostic model in bladder cancer patients based on The Cancer Genome Atlas (TCGA) data. Weighted Gene Co-Expression Network Analysis (WGCNA) was used to identify key genes related to TAM (M2 macrophage). Gene ontology (GO) enrichment and the Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway analysis showed the functional categories of the key genes. Simultaneously, we used the Least Absolute Shrinkage and Selection Operator (LASSO) and univariate and multivariate Cox regressions to establish a TMA-related prognostic model containing six key genes: TBXAS1, GYPC, HPGDS, GAB3, ADORA3, and FOLR2. Subsequently, single-cell sequencing data downloaded from Gene Expression Omnibus (GEO) suggested that the six genes in the prognostic model were expressed in TAM specifically and may be involved in TAM polarization. In summary, our research uncovered six-TAM related genes that may have an effect on risk stratification in bladder cancer patients and could be regarded as potential TAM-related biomarkers.
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Spatially resolved transcriptomic analysis of the adult human prostate.
The prostate is an organ characterized by significant spatial heterogeneity. To better understand its intricate structure and cellular composition, we constructed a comprehensive single-cell atlas of the adult human prostate. Our high-resolution mapping effort identified 253,381 single cells and 34,876 nuclei sampled from 11 patients who underwent radical resection of bladder cancer, which were categorized into 126 unique subpopulations. This work revealed various new cell types in the human prostate and their specific spatial localization. Notably, we discovered four distinct acini, two of which were tightly associated with E-twenty-six transcription factor family (ETS)-fusion-negative prostate cancer. Through the integration of spatial, single-cell and bulk-seq analyses, we propose that two specific luminal cell types could serve as the common origins of prostate cancer. Additionally, our findings suggest that zone-specific fibroblasts may contribute to the observed heterogeneity among luminal cells. This atlas will serve as a valuable reference for studying prostate biology and diseases such as prostate cancer.
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TriLock-FISH enables in situ discrimination of influenza cRNA and mRNA for single-cell analysis of viral replication and transcription.
Influenza A virus produces three RNA species-viral RNA (vRNA), complementary RNA (cRNA), and messenger RNA (mRNA)-whose synthesis and trafficking are spatially compartmentalized. However, the high sequence similarity between cRNA and mRNA hinders their distinction in situ, limiting understanding of the spatial organization of the viral replication-transcription dynamics. Here, triple-lock fluorescence in situ hybridization (TriLock-FISH) was developed to distinguish vRNA, cRNA, and mRNA in situ with high specificity. TriLock-FISH enabled a genome-wide, time-resolved single-cell atlas of RNA abundance and localization, revealing marked cell-to-cell variation in RNA abundance but relatively conserved spatial organization. cRNA was found to be predominantly nuclear, with a small but reproducible cytoplasmic fraction. Application to infected mouse lung tissue demonstrated simultaneous spatial detection of all viral RNA species. This approach provides a highly specific framework for single-cell analysis of RNA virus replication and transcription.IMPORTANCEInfluenza virus relies on three closely related RNA molecules for replication and gene expression, yet distinguishing them inside infected cells has remained technically challenging. This limitation has hindered understanding of viral replication in space and time. We developed triple-lock fluorescence in situ hybridization, which enables simultaneous visualization of all three viral RNA species across all eight influenza genome segments in infected cells and tissues. Single-cell analysis revealed striking heterogeneity in viral RNA abundance across infected cells, whereas intracellular RNA localization patterns remained relatively conserved. Complementary RNA, a replication intermediate long thought to be strictly nuclear, was also detected at low levels in the cytoplasm. These findings provide new insight into influenza virus replication and establish a broadly applicable tool for studying RNA virus biology.
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Association analysis of FXYD5 with prognosis and immunological characteristics across pan-cancer.
BACKGROUND: The FXYD domain-containing ion transport regulator 5 (FXYD5) gene is a cancer promoter. However, evidence for an association between FXYD5 and various types of cancer is still lacking. Using multi-omics bioinformatics, our study aimed to reveal the expression distribution, prognostic value, immune infiltration correlation, and molecular functions of FXYD5. METHODS: Using pan-cancer multi-omics data (including The Cancer Genome Atlas, PrognoScan, Gene Expression Profiling Interactive Analysis, cBioPortal, Gene Expression Omnibus, TIMER and scTIME Portal), we assessed the differences in the expression and prognostic value of FXYD5 in malignant tumors. Furthermore, at the single-cell level, we analyze the expression distribution of FXYD5 across different cell types within the tumor microenvironment, and its relationship with the immune microenvironment. Finally, focusing on ovarian cancer, we conducted preliminary validation of the above findings using cell and molecular biology techniques. RESULTS: Our results indicated that FXYD5 was up-regulated in various tumor types and was positively associated with tumor progression. We also revealed that FXYD5 was ubiquitously expressed in microenvironmental cells at the single-cell level, and its upregulation was associated with enhanced immune infiltration, cancer-associated fibroblast infiltration, and dysfunction of tumor-infiltrating cytotoxic T lymphocyte. Additionally, its expression was positively correlated with immune checkpoint genes, DNA mismatch repair genes, MSI (microsatellite instability) and TMB (tumor mutational burden) across various cancers. Its higher expression in cytotoxic T lymphocytes attenuated its ability to predict patient survival with PD-L1 (programmed death-ligand 1) blockade therapy, and FXYD5 was found to be a potential regulator of tumor immune escape and resistance to cancer immunotherapies. Based on GSEA (gene set enrichment analysis) and experimental verification, FXYD5 activated TGF-β/SMAD signaling and drove EMT (epithelial-mesenchymal transition) to promote ovarian cancer progression. CONCLUSION: In summary, our study revealed that FXYD5-TGFβ axis may coregulate the interaction between tumors, CAFs (carcinoma-associated fibroblasts) and immune cells to reshape the tumor immune microenvironment and promote tumorigenesis and tumor progression. Thus, FXYD5 could be used as an immune-related biomarker for diagnosing and predicting the prognosis of multiple cancer types. Therefore, our findings suggest that targeting FXYD5 in TME (tumor microenvironment) may be a promising therapeutic strategy.