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Found: 4 939
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High-Resolution Spatial Profiling of Microglia Reveals Proximity Associated Immunometabolic Reprogramming in Alzheimer's Disease.
Single-cell RNA sequencing has demonstrated that the presence of parenchymal amyloid plaques and intracellular hyperphosphorylated tau pathology is associated with distinctive (and possibly disease-driving) microglial heterogeneity. However, our understanding of how proximity to these Alzheimer's disease (AD) pathological hallmarks in situ relates to microglial gene expression remains obscure. Here, we utilized high-resolution spatial transcriptomics (ST) via the Xenium platform with a fully customized gene panel to elucidate disease-associated microglial subtypes in tandem with examining metabolic signatures across AD-relevant mouse models and well-characterized human postmortem tissue. Three mouse models were evaluated: PS19, APP/PS1, and 5xFAD. Analyzing anatomical features across entire hemisections, our approach resolved the distribution of five disease-associated microglial subtypes, while deciphering how proximity to cerebral amyloid plaques influenced transcriptional mediators governing metabolic pathways. We observed robust alterations in glycolytic and cholesterol/lipid processing pathways in plaque-associated microglia, consistent with a specific switch to glycolysis and lipid-fueled metabolism in the plaque niche. Extending our analysis to human postmortem dorsolateral prefrontal cortex (dlPFC), we identified conserved disease-reactive microglial states, i.e., similar proximity-dependent metabolic shifts around amyloid plaques. Further, integrating spatial transcriptomics with machine-learning approaches revealed novel anatomic domain-specific cellular gene expression profiling features, highlighting differential vulnerabilities of neuronal, glial, and vascular populations near specific microglial subtypes. Together, our findings provide one of the first comprehensive and high-resolution atlas of microglial immunometabolic states across species, anatomical regions, and AD pathological burden.
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Transient Receptor Potential Melastatin 4 (TRPM4) is associated with an immuno-stimulatory TME and better prognosis in BLCA.
OBJECTIVE: Bladder cancer (BLCA) is one of the most invasive and malignant tumors in the world, thus leading to the urgent need of an accurate and recognizable biomarker. Several previous research has shown that Transient Receptor Potential Melastatin 4 (TRPM4) plays an important role in measuring vascular fragility and endothelial function. However, the role of TRPM4 in tumor hasn't been explored. METHODS: We obtained the clinical data and gene expression profiles of The Cancer Genome Atlas (TCGA) datasets via UCSC Xena. The tumor microenvironment (TME) was also evaluated by the amount of immunomodulators. The role of TRPM4 was demonstrated using the dataset GSE130001 via the website ( http://tisch.comp-genomics.org/ ). We also validated the results of the pathway analysis through the Polymerase Chain Reaction (PCR). RESULTS: Patients with higher TRPM4 expression showed better prognosis. We found out that high TRPM4 tended to shape an immuno-stimulatory TME with less T cell exhaustion and lower level of immune overdrive. We demonstrated that TRPM4 could predict the molecular subtype and different therapy options in BLCA. We also found the important influence of TRPM4 in P53 pathway and TNF-a pathway. Last but not least, we developed a prognostic model centered on TRPM4 using ten machine learning algorithms, which showed excellent predictive ability. CONCLUSION: High TRPM4 shapes a more immuno-stimulatory tumor microenvironment and can not only predict the immune phenotypes but also predict the clinical phenotypes in BLCA. High TRPM4 predicts better prognosis. TRPM4 is a potential biomarker in the future for identifying the immunogenicity and immune-therapy probability of BLCA.
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A high-definition spatiotemporal transcriptomic atlas of mammalian kidney development.
The structural composition of organs undergoes significant transformations during organogenesis, laying the foundation for their eventual functional architecture. In contrast, adult organs maintain structural homeostasis. However, the dynamics of organ structure during the organogenesis and homeostasis stages remain poorly understood. Here, we present a spatially resolved transcriptome atlas at single-cell resolution to explore the establishment and maintenance of kidney structure in mice. Our analysis reveals 40 migration-related cell-cell communication events during kidney organogenesis. Contrary to the traditional two-layer model (cortex and medulla), we demonstrate that the kidney develops a five-layer structure over time. Mechanistically, migration-related cell-cell communication drives this structural formation, with ephrin-A5 (Efna5) playing a key role in forming three distinct layers within the medulla. The spatial distribution of specific cell types and their gene expression patterns within these five layers likely enhances renal adaptation to hypoxic and hyperosmotic environments. Furthermore, Frizzled 4 receptor (Fzd4) is critical for the morphogenesis of the U-shaped loop of Henle (LoH). In the adult stage, when structural homeostasis prevails, only three migration-related ligand-receptor pairs are observed, and a stable four-layer structure is maintained due to the absence of progenitor cells. Overall, our findings illustrate the role of intercellular communication in driving the transition from structural establishment during organogenesis to stable maintenance in homeostasis. These insights provide new avenues for advancing organ regeneration strategies.
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Single-Cell Transcriptomics Reveals Rora-Associated Aberrant Granulosa Cell Differentiation in Polycystic Ovary Syndrome.
INTRODUCTION: Polycystic ovary syndrome (PCOS) is characterized by follicular developmental arrest, yet the molecular basis underlying impaired granulosa cell (GC) differentiation remains incompletely understood. METHODS: We constructed a single-cell transcriptomic atlas of ovaries from DHEA-induced PCOS-like mice and matched vehicle controls, and leveraged spatial transcriptomics as an orthogonal reference for major cell-type annotation, followed by in-depth profiling of GC heterogeneity. Pseudotime inference, co-expression networks, and regulon activity analysis were integrated, and findings were validated in independent human GC datasets. In silico Rora perturbation, cell-cell communication analysis, and drug repositioning were additionally performed. RESULTS: We identified a subset of luteinized mural GCs with robust Rora regulon activation, termed Rora-regulon-active GCs. This subset was markedly enriched in PCOS and was reproducibly observed in independent human GC datasets. Rora-regulon-active GCs exhibited an incomplete luteinization phenotype coupled with lipid-metabolic reprogramming. In silico Rora knockdown partially reconfigured GC differentiation trajectories and shifted the PCOS-skewed subset composition toward control, with concordant changes in metabolic transcriptional programs. Cell-cell communication analyses implicated stromal-derived Mdk-Sdc1 signaling and suggested additional crosstalk with macrophages potentially mediated by ligands such as Vegfa. In silico drug repositioning prioritized betaine hydrochloride and bempedoic acid as candidate therapeutics. DISCUSSION: Our study delineates a Rora-associated aberrant GC differentiation program linked to PCOS, nominating this aberrant program as a potential cellular basis of PCOS-associated follicular arrest and providing mechanistic and translational leads for precision-targeted therapy.
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Assessment of cancer-associated fibroblast signature genes in ovarian cancer patients: impact on immunity, drug resistance, and prognosis.
Ovarian cancer (OC) is women's third most common gynecologic tumor and is highly lethal. Cancer-associated fibroblasts (CAFs) are associated with cancer at all stages of disease progression and are involved in biological processes, including inflammatory processes, tumor development occurrence, and immune rejection. This study aimed to construct prognosis-related CAFs regulatory factors to predict the survival of OC patients. Datasets of OC patients with complete clinical information were collected from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) databases. First, we identified potential regulator factors of CAFs in OC based on the xCell algorithm and weighted gene co-expression analysis (WGCNA). Further screening using one-way cox regression analysis and LASSO regression models yielded 22 prognosis-related CAFs regulatory factors, using which a model was constructed. Subsequently, the diagnostic effectiveness of the model was assessed using receiver operating characteristic (ROC) curves, and the validity of the CAFs regulatory factors survival model was verified in three additional independent datasets and single cell data. Meanwhile, experimental validation was conducted using immunohistochemistry and Western blot. The results showed that GAS1 (Growth arrest specific 1) exhibited a higher expression pattern in fibroblasts from ovarian cancer patients. The assessment of resistance and immune checkpoint differences across various risk score groups indicates that the CAFs regulatory factor survival model is practical for guiding systemic treatment. In summary, this study establishes a prognostic model composed of 22 CAFs regulatory factors to predict the prognosis of ovarian cancer (OC), providing new perspectives for the clinical treatment of OC.
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Integrative multi-omics and network toxicology reveal candidate molecular targets of deoxynivalenol in melanoma.
Deoxynivalenol (DON) has been reported to exhibit skin toxicity and carcinogenic potential; however, its effects on melanoma remain unclear. We integrated network toxicology, single-cell transcriptomic analysis, molecular docking, and publicly available Human Protein Atlas immunohistochemical evidence to investigate the potential toxicological effects of DON on melanoma and identify candidate molecular targets. A total of 5283 DON-related genes were identified from the SwissTargetPrediction, CTD, and SEA databases, and 5101 melanoma-related genes were obtained from the GeneCards, TTD, and OMIM databases. Differentially expressed genes from the GSE15605 dataset were used for intersection validation. After further screening with three machine learning algorithms, MYEF2 was identified as a core target potentially involved in DON-induced melanoma. ROC analysis showed that MYEF2 achieved AUC values above 0.75 in both the training and validation cohorts. Single-cell transcriptomic analysis revealed the expression and distribution of MYEF2 across melanoma cell subtypes. Immune infiltration analysis further showed significant associations between MYEF2 and multiple immune cell populations. Molecular docking supported a stable interaction between DON and MYEF2, and HPA validation confirmed its elevated expression in melanoma. These findings suggest that MYEF2 may represent a candidate molecular target involved in DON-associated melanoma progression, providing a theoretical basis for future studies on the mechanisms and risk assessment of DON exposure.
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Integrative Single-Cell Transcriptomics, Multi-Omics Analyses, and Computational Pharmacology Reveal Macrophage Heterogeneity and the Putative THBS1-CD36 Axis in Coronary Atherosclerosis.
Coronary atherosclerosis (CA) is characterized by profound macrophage heterogeneity that drives plaque progression and vulnerability, yet the precise subpopulations and their niche-specific functions remain incompletely defined. Here, we constructed a single-cell transcriptomic atlas of human CA using dataset GSE131778 and identified six distinct macrophage subpopulations. Among these, the THBS1+ macrophage subset emerged as a terminally differentiated, hypoxia-adaptive population with elevated TGF-β signaling and FOSB-driven transcriptional regulation. High-dimensional weighted gene co-expression network analysis revealed 12 transcriptional modules, with module NEW10 serving as a specific molecular signature of THBS1+ macrophages. Cell-cell communication analysis predicted a THBS1-CD36 ligand-receptor interaction potentially contributing to crosstalk between THBS1+ macrophages and lymphatic endothelial cells. Molecular docking and 100-ns molecular dynamics simulations predicted a thermodynamically favorable and conformationally stable interaction between SMS121 and CD36, providing an initial computational rationale for further experimental evaluation. Finally, leveraging the NEW10 module genes, we trained 13 machine learning classifiers to distinguish ACS from sCAD and evaluated their performance in differentiating ruptured from stable plaques; Support Vector Machine with linear kernel and Naive Bayes achieved the highest accuracy in an independent testing cohort, both attaining an AUC of 0.9333. These findings illuminate macrophage heterogeneity and intercellular communication in CA, identify the predicted THBS1-CD36 interaction as a candidate for further mechanistic and pharmacological investigation, and establish a macrophage-derived transcriptional signature for precise risk stratification.
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Machine learning identifies PYGM as a macrophage polarization-linked metabolic biomarker in rectal cancer prognosis.
BACKGROUND: Macrophage polarization plays a pivotal role in shaping the tumor microenvironment and influencing rectal cancer progression. However, the metabolic and prognostic regulators governing this process remain largely undefined. METHODS: We constructed a macrophage polarization gene signature (MPGS) by integrating weighted gene co-expression network analysis (WGCNA) with multiple machine learning algorithms across two independent cohorts: 363 rectal cancer samples from GSE87211 and 177 samples from The Cancer Genome Atlas (TCGA). The prognostic performance of MPGS was evaluated across rectal and multiple other cancer types. Functional analyses, single-cell RNA sequencing, immunohistochemistry of clinical specimens, and in vitro cellular assays were employed to investigate the role of the MPGS hub gene, PYGM, in tumor biology and immune modulation. RESULTS: The MPGS exhibited robust prognostic capability and effectively predicted responses to immunotherapy and various chemotherapeutic agents. Both MPGS and its central metabolic component, PYGM, were closely linked to M2 macrophage infiltration, immunosuppressive tumor microenvironments, and poor clinical outcomes in rectal adenocarcinoma. Single-cell transcriptomic analysis revealed that malignant epithelial cells with elevated PYGM expression are metabolically active and closely interact with M2 macrophages. Clinical tissue analyses and functional assays confirmed that PYGM is upregulated in rectal cancer and promotes tumor cell proliferation, migration, and M2 macrophage polarization. CONCLUSIONS: This study firstly highlights PYGM as a key metabolic and immunological regulator in rectal cancer, with significant prognostic and therapeutic implications. MPGS and PYGM may serve as novel biomarkers for risk stratification and guide personalized treatment strategies in patients with rectal adenocarcinoma.
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MicroRNA-874 targets phosphomevalonate kinase and inhibits cancer cell growth via the mevalonate pathway.
The microRNA (miR) miR-874, a potential tumour suppressor, causes cell death via target gene suppression in various cancer types. Mevalonate pathway inhibition also causes cell death in breast cancer. However, the relationship between the mevalonate pathway and miR-874-induced apoptosis or its association with the tumour suppressor p53 has not been elucidated. We identified phosphomevalonate kinase (PMVK), a key mevalonate pathway enzyme, and sterol regulatory element-binding factor 2 (SREBF2), the master cholesterol biosynthesis regulator, as direct miR‑874 targets. Next-generation sequencing analysis revealed a significant miR-874-mediated downregulation of PMVK and SREBF2 gene expression and p53 pathway enrichment. Luciferase reporter assays showed that miR-874 directly regulated PMVK and SREBF2. miR-874-induced apoptosis was p53 dependent, and single-cell RNA sequencing analysis demonstrated that miR-874 transfection resulted in apoptosis and p53 pathway activation. Downregulation of PMVK expression also caused cell cycle arrest and p53 pathway activation, which was rescued by geranylgeranyl pyrophosphate (GGPP) supplementation. Analysis of The Cancer Genome Atlas (TCGA) database indicated a negative correlation between miR-874 and PMVK expression and between miR-874 and SREBF2 expression. These findings suggest that miR-874 suppresses the mevalonate pathway by targeting SREBF2 and PMVK, resulting in GGPP depletion, which activates the p53 pathway and promotes cycle arrest or apoptosis.
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Integrative network toxicology and experimental validation define mechanisms of perfluorodecanoic acid (PFDA) induced granulosa cell toxicity and attenuation by kaempferol in HGrC1 cells.
Per- and polyfluoroalkyl substances (PFAS) are persistent environmental contaminants increasingly linked to female reproductive toxicity. Among them, perfluorodecanoic acid (PFDA) has been implicated in ovarian dysfunction, yet the molecular basis of its ovotoxicity remains insufficiently defined. Here, we investigated PFDA-induced granulosa cell injury and examined whether kaempferol, a naturally occurring flavonoid, could mitigate these effects using an integrative approach combining network toxicology, single-cell transcriptomic projection, and in vitro validation. Computational analysis identified 121 shared targets among PFDA, kaempferol, and ovotoxicity-related gene sets, with enrichment in oxidative stress, inflammatory, and nuclear receptor-associated pathways. Single-cell projection of PFDA- and kaempferol-associated gene sets onto a human ovarian reference atlas localized these signatures across multiple ovarian cell populations, including granulosa cell clusters. In the human granulosa cell line HGrC1, PFDA significantly reduced cell viability, increased reactive oxygen species (ROS), impaired nuclear factor erythroid 2-related factor 2 (NRF2)-associated antioxidant defense, shifted apoptosis-related gene expression toward a pro-apoptotic profile, and suppressed steroidogenic gene expression. Co-treatment with kaempferol alleviated several of these changes, lowering ROS levels and partially restoring antioxidant and steroidogenic markers. Together, these findings indicate that PFDA disrupts granulosa cell homeostasis through redox imbalance and modulation of steroidogenesis-related gene expression, while kaempferol mitigates part of this response in the present in vitro model. This study provides mechanistic insight into PFDA-induced granulosa cell toxicity and supports further investigation of bioactive flavonoids as modulators of pollutant-related ovarian injury.