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Atlas of Fshr expression from novel reporter mice.
The FSH-FSHR pathway has been considered an essential regulator in reproductive development and fertility. But there has been emerging evidence of FSHR expression in extragonadal organs. This poses new questions and long-term debates regarding the physiological role of the FSH-FSHR, and underscores the need for reliable, in vivo analysis of FSHR expression in animal models. However, conventional methods have proven insufficient for examining FSHR expression due to several limitations. To address this challenge, we developed Fshr-ZsGreen reporter mice under the control of Fshr endogenous promoter using CRISPR-Cas9. With this novel genetic tool, we provide a reliable readout of Fshr expression at single-cell resolution level in vivo and in real time. Reporter animals were also subjected to additional analyses,to define the accurate expression profile of FSHR in gonadal and extragonadal organs/tissues. Our compelling results not only demonstrated Fshr expression in intragonadal tissues but also, strikingly, unveiled notably increased expression in Leydig cells, osteoblast lineage cells, endothelial cells in vascular structures, and epithelial cells in bronchi of the lung and renal tubes. The genetic decoding of the widespread pattern of Fshr expression highlights its physiological relevance beyond reproduction and fertility, and opens new avenues for therapeutic options for age-related disorders of the bones, lungs, kidneys, and hearts, among other tissues. Exploiting the power of the Fshr knockin reporter animals, this report provides the first comprehensive genetic record of the spatial distribution of FSHR expression, correcting a long-term misconception about Fshr expression and offering prospects for extensive exploration of FSH-FSHR biology.
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Integrated bioinformatics and experimental analysis of CHAF1B as a novel biomarker and immunotherapy target in LUAD.
The prognosis and treatment efficacy of lung adenocarcinoma (LUAD), a disease with a high incidence, remains unsatisfactory. Identifying new biomarkers and therapeutic targets for LUAD is essential. Chromosomal assembly factor 1B (CHAF1B), a p60 component of the CAF-1 complex, is closely linked to tumor incidence and cell proliferation. However, CHAF1B's biological role and molecular mechanism in LUAD remain unclear. Here, CHAF1B expression in LUAD was examined using the GEPIA2 and UALCAN databases. Using The Cancer Genome Atlas (TCGA) LUAD database, we analyzed the diagnostic and prognostic significance of CHAF1B and its association with immune infiltration and immunological checkpoints. Gene ontology (GO) enrichment and single-cell function analyses were employed to investigate CHAF1B's possible biological roles. Drug sensitivity analysis predicted CHAF1B's effect on chemotherapeutic drug sensitivity. We also predicted lncRNAs-miRNA-CHAF1B axis to explore the molecular mechanism of CHAF1B in LUAD. Preliminary in vitro studies using qRT-PCR, CCK8, Transwell, glucose, and lactate metabolism confirmed CHAF1B's expression and role in LUAD. Its expression is associated with drug sensitivity, immunological checkpoints, and immune cell infiltration. We predicted that three miRNAs (miR-29c-3p, miR-145-5p, miR-1247-5p) and three lncRNAs (AL139287.1, NEAT1, SHG1) may be target miRNAs and target lncRNAs that regulate CHAF1B. In vitro tests showed that CHAF1B suppression decreased LUAD's migration, invasion, proliferation, and glycolysis. Overall, CHAF1B may be an innovative biomarker and therapeutic target for LUAD.
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Identification of immune-related targets of N6-methyladenosine regulators in hepatocellular carcinoma via RNA-seq analysis.
BACKGROUND: N6-methyladenosine (m6A) regulators are involved in hepatocellular carcinoma (HCC) development. However, the functions of m6A regulators in HCC have not yet been elucidated. This study aimed to evaluate the potential of m6A methylation regulators as biomarkers and immunotherapeutic targets in HCC. METHODS: RNA sequencing data were obtained from publicly available databases including The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Bioinformatics analysis was conducted, including Kaplan-Meier (KM) survival analysis, univariate and multivariate Cox regression, receiver operating characteristic (ROC) curve analysis and immune-related signatures were assessed using single-sample gene set enrichment analysis (ssGSEA) and drug sensitivity prediction was performed to identify potential small-molecule compounds. In vitro, small interfering RNA (siRNA)-mediated knockdown of selected m6A regulators was performed in three HCC cell lines (HepG2, HuH7 and MHCC-97H). Quantitative polymerase chain reaction (qPCR) and Western blot (WB) were subsequently conducted to validate gene expression changes. Additionally, WB was performed after treatment with candidate drugs to evaluate their functional impact. RESULTS: The five upregulated m6A regulators in HCC, KIAA1429, METTL3, PRRC2A, RBMX, and ZC3H3, were related to worse outcomes in HCC. ROC curves showed that m6A regulators could accurately distinguish between normal and HCC tumor tissues. Furthermore, differential m6A regulator expression was affected by immune infiltration. In advanced HCC patients, m6A regulators were important in determining clinical outcomes. Drug response analysis demonstrated m6A regulators as potential therapeutic agents that could be used as guidance for patients with HCC. PCR and WB analysis showed that m6A regulators could act on immune-related sites, interact with immune tolerance, and inhibit it. CONCLUSIONS: This study indicates that KIAA1429, METTL3, PRRC2A, RBMX, and ZC3H3 may be potential immunotherapeutic targets and biomarkers in HCC.
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Machine learning-based in-silico analysis identifies signatures of lysyl oxidases for prognostic and therapeutic response prediction in cancer.
BACKGROUND: Lysyl oxidases (LOX/LOXL1-4) are crucial for cancer progression, yet their transcriptional regulation, potential therapeutic targeting, prognostic value and involvement in immune regulation remain poorly understood. This study comprehensively evaluates LOX/LOXL expression in cancer and highlights cancer types where targeting these enzymes and developing LOX/LOXL-based prognostic models could have significant clinical relevance. METHODS: We assessed the association of LOX/LOXL expression with survival and drug sensitivity via analyzing public datasets (including bulk and single-cell RNA sequencing data of six datasets from Gene Expression Omnibus (GEO), Chinese Glioma Genome Atlas (CGGA) and Cancer Genome Atlas Program (TCGA)). We performed comprehensive machine learning-based bioinformatics analyses, including unsupervised consensus clustering, a total of 10 machine-learning algorithms for prognostic prediction and the Connectivity map tool for drug sensitivity prediction. RESULTS: The clinical significance of the LOX/LOXL family was evaluated across 33 cancer types. Overexpression of LOX/LOXL showed a strong correlation with tumor progression and poor survival, particularly in glioma. Therefore, we developed a novel prognostic model for glioma by integrating LOX/LOXL expression and its co-expressed genes. This model was highly predictive for overall survival in glioma patients, indicating significant clinical utility in prognostic assessment. Furthermore, our analysis uncovered a distinct LOXL2-overexpressing malignant cell population in recurrent glioma, characterized by activation of collagen, laminin, and semaphorin-3 pathways, along with enhanced epithelial-mesenchymal transition. Apart from glioma, our data revealed the role of LOXL3 overexpression in macrophages and in predicting the response to immune checkpoint blockade in bladder and renal cancers. Given the pro-tumor role of LOX/LOXL genes in most analyzed cancers, we identified potential therapeutic compounds, such as the VEGFR inhibitor cediranib, to target pan-LOX/LOXL overexpression in cancer. CONCLUSIONS: Our study provides novel insights into the potential value of LOX/LOXL in cancer pathogenesis and treatment, and particularly its prognostic significance in glioma.
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Single-nucleus transcriptome profiling unveils cell-type-specific ethylene and TOR signaling in tomato.
Plant etiolation, a critical process for seedling emergence, is regulated by ethylene and target of rapamycin (TOR) signaling pathways. However, the cell-type-specific regulation of these pathways remains poorly understood. To address this, we generated a comprehensive single-nucleus RNA transcriptome atlas of etiolated apical hooks and hypocotyls in tomato seedlings treated with the ethylene precursor aminocyclopropane-1-carboxylic acid (ACC), the TOR inhibitor Torin2, or a mock treatment. In total, we obtained high-quality gene expression profiles for 117 929 nuclei across these tissues and treatments. Our analysis identified seven major cell types within each tissue, revealing distinct cellular compositions and transcriptional programs. ACC treatment increased the proportion of epidermal cells in apical hooks, while Torin2 had limited impact on cellular composition. Differential gene expression analysis demonstrated tissue-specific sensitivity to these treatments: apical hooks exhibited extensive ACC-responsive differentially expressed genes, whereas hypocotyls were highly responsive to Torin2. Cellular responsiveness analysis uncovered divergent ethylene/auxin pathway activities, such as ACC-repressed auxin transport in hook endodermis-like cells. Dynamic trajectory analysis indicated both treatments altered cell differentiation, authenticating epidermis as the key cell type for ethylene-mediated etiolated growth. Crucially, we identified JA1 (HD-ZIP I TF) as a negative ethylene regulator enriched in epidermis, and CRISPR knockout ja1 mutants exhibited hypersensitivity to ACC. This study deciphers cell-type-specific ethylene-TOR crosstalk, providing a robust single-cell RNA sequencing framework to dissect signaling networks in crops.
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Single-cell transcriptomic analysis reveals disparate effector differentiation pathways in human Treg compartment.
Human FOXP3+ regulatory T (Treg) cells are central to immune tolerance. However, their heterogeneity and differentiation remain incompletely understood. Here we use single-cell RNA and T cell receptor sequencing to resolve Treg cells from healthy individuals and patients with or without acute graft-versus-host disease (aGVHD) who undergo stem cell transplantation. These analyses, combined with functional assays, separate Treg cells into naïve, activated, and effector stages, and resolve the HLA-DRhi, LIMS1hi, highly suppressive FOXP3hi, and highly proliferative MKI67hi effector subsets. Trajectory analysis assembles Treg subsets into two differentiation paths (I/II) with distinctive phenotypic and functional programs, ending with the FOXP3hi and MKI67hi subsets, respectively. Transcription factors FOXP3 and SUB1 contribute to some Path I and Path II phenotypes, respectively. These FOXP3hi and MKI67hi subsets and two differentiation pathways are conserved in transplanted patients, despite having functional and migratory impairments under aGVHD. These findings expand the understanding of Treg cell heterogeneity and differentiation and provide a single-cell atlas for the dissection of Treg complexity in health and disease.
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An aging-related gene signature to predict the prognosis of hepatocellular carcinoma.
Aging increases the susceptibility of various diseases, including hepatocellular carcinoma (HCC). This study aimed to establish an aging-related prognostic model for HCC and to investigate the role of aging-related genes in HCC progression. Transcriptome and clinical information of HCC cases were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Aging-related prognostic genes were identified through univariate Cox regression analysis, protein-protein interaction analysis, and least absolute shrinkage and selection operator (LASSO) analysis. An aging-related risk signature was then constructed, including LDHA, MMP12, ATAD3A, CD8A, TPI1, CST3, and TPM1. The risk score was inversely associated with the overall survival of patients with HCC and correlated well with known prognostic factors. The area under the curve of 1-, 3-, and 5-year survival in the training dataset was 0.83, 0.83, and 0.84, respectively. Univariate and multivariate cox regression analysis verified that the aging-related risk signature independently predicted the overall survival in HCC. To increase the clinical utility of the prognostic model, a nomogram was developed by incorporating the risk score with key clinical features. Finally, single-cell transcriptomes of HCC were analyzed to elucidate the expression pattern of the prognostic genes across different tissues, pathologic stages, and cell types. Collectively, the aging-related prognostic model shed light on HCC pathogenesis and held potential for optimizing the management of HCC.
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ZIC3 expression identifies a developmental transcriptional axis in IDH-wildtype glioblastoma.
OBJECTIVE: IDH-wildtype glioblastoma exhibits substantial biological heterogeneity despite current molecular classification. Although dynamic malignant cell states have been described, molecular features that position tumors along these states remain incompletely defined. We investigated whether ZIC3 expression identifies a transcriptional state associated with clinical outcome in IDH-wildtype glioblastoma. METHODS: RNA sequencing and clinical data from The Cancer Genome Atlas glioblastoma cohort were analyzed after restriction to genomically confirmed IDH-wildtype tumors (n = 167). Survival analyses were performed in patients with available survival data (n = 161) using Cox proportional hazards regression and Kaplan-Meier analysis. Associations with MGMT promoter methylation, tumor microenvironment scores, differential expression, gene set enrichment, and single-cell RNA sequencing data were evaluated to characterize transcriptional programs associated with ZIC3 expression. RESULTS: Higher ZIC3 expression was associated with longer overall and progression-free survival and remained associated with a more favorable survival profile after adjustment for age, sex, radiotherapy, and temozolomide treatment. ZIC3 expression was not associated with MGMT promoter methylation or with ESTIMATE-derived stromal, immune, or composite scores. In the single-cell dataset, ZIC3-positive cells were more frequent in malignant tumor cells than in non-malignant cells. ZIC3-high tumors showed enrichment of neural lineage-associated and blood-brain barrier-related programs, whereas ZIC3-low tumors showed enrichment of hypoxia-related, glycolytic, and metabolic stress programs. Ordered heatmap analysis showed that lineage-associated genes and hypoxia-related genes varied inversely across tumors ordered by ZIC3 expression. CONCLUSIONS: ZIC3 expression appears to mark a developmental transcriptional axis in IDH-wildtype glioblastoma that links neural lineage-associated programs to hypoxia-adaptive tumor states.
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A basophil-fibroblast pro-inflammatory axis fuels type 2 skin inflammation.
Chronic inflammatory skin diseases arise from dysregulated interactions between tissue-resident and infiltrating cells, the complexity of which hinders disease understanding and treatment. To address this, here, we present a single-cell spatiotemporal atlas of murine type 2 skin inflammation using MERFISH and scRNA-seq. Analyzing ∼430,000 cells during MC903- and oxazolone-induced dermatitis, we identify 39 cell types, including pro-inflammatory fibroblasts that resemble those in human atopic dermatitis. Spatial neighborhood analyses reveal basophils as potent activators of pro-inflammatory fibroblasts, with basophil-derived oncostatin-M (OSM) and IL-4 synergizing fibroblast-mediated feedforward basophil and immune recruitment. While fibroblast-specific deletion of the IL-4Rα receptor disrupts inflammation in vivo, the addition of pharmacologic gp130 inhibition, a core component of the OSM receptor, results in synergistic reduction of inflammation. Our study establishes a basophil-fibroblast circuitry as a critical regulator of type 2 skin inflammation, redefining basophil biology and positioning fibroblasts as dynamic immune regulators and therapeutic targets in inflammatory skin disease.
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High-resolution spatial transcriptomic atlas of mouse soleus muscle: Unveiling single cell and subcellular heterogeneity in health and denervation.
Skeletal muscle exhibits pronounced cellular and subcellular heterogeneity, but comprehensive spatial mapping has been constrained by cell/nuclei dissociation-based methods that lose tissue architecture and by spatial platforms with insufficient resolution or limited transcriptome coverage. Here, we present a high-resolution spatial transcriptomic atlas of mouse soleus muscle in longitudinal sections with unbiased whole-transcriptome coverage, enabling myofiber-resolved transcriptomes while preserving subcellular expression domains across the length of fibers. Combining histology-guided myofiber segmentation with unbiased grid-based mapping, we recover canonical fiber types and reveal widespread hybrid myofiber states in situ, including type IIb-associated signatures that are rare in soleus muscle and evident only when intramyofiber heterogeneity is assessed. At subcellular scale, we delineate the neuromuscular junction (NMJ) as a multicompartment niche comprising postsynaptic myonuclei and spatially distinct perisynaptic and myelinating Schwann cell-associated regions, each with characteristic gene programs. Applying this framework to denervation (3 and 7 days) identifies robust fiber-type-specific stress responses, coordinated remodeling of macrophage and fibroblast transcriptomes, and marked intramyofiber heterogeneity, including spatially nonuniform activation of damage-response genes along individual myofibers, with distinct transcriptional domains proximal and distal to the NMJ and associated degenerative histological features. Together, this atlas provides a high-resolution reference for muscle biology and clarifies how denervation reshapes myofiber, synaptic, and stromal-immune programs across cells and within cells in intact tissue.