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A Spatial and Temporal Transcriptomic Atlas of Mouse Intestinal Regeneration.
BACKGROUND & AIMS: The intestinal epithelium exhibits a remarkable capacity for regeneration following injury. However, the spatial and temporal dynamics of the injury-repair cycle remain incompletely understood. METHODS: We employ spatial transcriptomics to create an atlas of the damage and repair response to ionizing radiation in the mouse intestine. We map molecular events driving epithelial recovery over a six-day period and 23 biological samples, spanning the early apoptotic response to tissue remodeling and repair. RESULTS: The datasets capture mRNA of 19,042 genes in ∼26 million bins at 2µm resolution. Analysis revealed transcriptional patterns and niche signals that would remain undetected in bulk or single-cell approaches, including a non-random activation of interferon-target genes. Temporal shifts in cytokine and growth factor gene expression, particularly in the crypt and lower villus regions, corroborate published studies and reveal new predictions of the mechanisms governing intestinal healing. Global transcriptional upregulation was observed in the regenerating epithelium, suggesting hypertranscription is a hallmark of intestinal repair. Furthermore, we observe altered cellular differentiation trajectories and villus patterning at the early stages of regeneration. CONCLUSIONS: Together, our work provides a detailed spatiotemporal map of intestinal regeneration at subcellular resolution and nearly whole-genome scale. These data lay the groundwork for future discoveries and therapeutic strategies to enhance epithelial repair in inflammatory bowel diseases and other gastrointestinal pathologies or in response to side-effects of cancer therapies.
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Multi-omics analysis of NET+ TAN explains the immunosuppressive TME and prognosis value of malignant clinical characteristics in TNBC.
Triple-negative breast cancer (TNBC) continues to exhibit a poor response to both immunotherapy and endocrine therapy, primarily due to its complex genetic heterogeneity and tumor immune microenvironment (TIME). Neutrophil extracellular traps (NETs) are involved in neutrophil development and degranulation in treatment-resistant tumors, particularly TNBC and metastatic cases. Using a combination of single-cell RNA sequencing (scRNA-seq) datasets, bulk mRNA sequencing data from The Cancer Genome Atlas (TCGA) cohort, microarray data from the METABRIC and GEO databases, and epigenetic sequencing resources, we comprehensively investigated the functional characteristics and prognostic potential of NET-positive tumor-associated neutrophils (NET+ TAN) in TNBC. A six-gene panel derived from NET+ TAN has been identified as a reliable diagnostic biomarker for the survival of patients with TNBC and has been validated across several independent cohorts. Notably, our findings indicate that NET+ TAN facilitate T cell reprogramming in TNBC, thereby establishing a suppressive TIME and promoting tumor progression. This study provides a comprehensive perspective on the significance of NETs in patients with TNBC, with the aim of offering genetic and epigenetic insights into the mechanisms by which NETs may transition from cold to hot tumor phenotype, as well as valuable recommendations for therapeutic strategies.
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A high-resolution route map reveals distinct stages of chondrocyte dedifferentiation for cartilage regeneration.
Articular cartilage damage is a universal health problem. Despite recent progress, chondrocyte dedifferentiation has severely compromised the clinical outcomes of cell-based cartilage regeneration. Loss-of-function changes are frequently observed in chondrocyte expansion and other pathological conditions, but the characteristics and intermediate molecular mechanisms remain unclear. In this study, we demonstrate a time-lapse atlas of chondrocyte dedifferentiation to provide molecular details and informative biomarkers associated with clinical chondrocyte evaluation. We performed various assays, such as single-cell RNA sequencing (scRNA-seq), live-cell metabolic assays, and assays for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq), to develop a biphasic dedifferentiation model consisting of early and late dedifferentiation stages. Early-stage chondrocytes exhibited a glycolytic phenotype with increased expression of genes involved in metabolism and antioxidation, whereas late-stage chondrocytes exhibited ultrastructural changes involving mitochondrial damage and stress-associated chromatin remodeling. Using the chemical inhibitor BTB06584, we revealed that early and late dedifferentiated chondrocytes possessed distinct recovery potentials from functional phenotype loss. Notably, this two-stage transition was also validated in human chondrocytes. An image-based approach was established for clinical use to efficiently predict chondrocyte plasticity using stage-specific biomarkers. Overall, this study lays a foundation to improve the quality of chondrocytes in clinical use and provides deep insights into chondrocyte dedifferentiation.
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Digital Spatial Profiling of Glomerular Gene Expression in Pauci-Immune Focal Necrotizing Glomerulonephritis.
Pauci-immune focal necrotizing glomerulonephritis (piFNGN) involves asynchronous onset and progression of injurious lesions in biopsies. Pathologists can describe this heterogeneity within a biopsy, but translating the information into prognostic or expression analyses is challenging. Understanding the underlying molecular processes could improve treatment; however, bulk or single-cell transcriptomic analyses of dissociated tissue disregard the heterogeneity of glomerular injury. We characterize protein and mRNA expression of individual glomeruli in 20 biopsies from 18 patients with antineutrophil cytoplasmic antibody-associated piFNGN using the NanoString digital spatial profiling (DSP) platform. For this purpose, circular annotations of glomeruli were analyzed using protein, immuno-oncology RNA, and Cancer Transcriptome Atlas panels (n=120, 72, and 48 glomeruli, respectively). Histologic evaluation of glomerular patterns of injury was performed in adjacent serial sections. Expression data were processed by log2 transformation, quantile normalization, and batch adjustment. DSP revealed distinct but overlapping gene expression profiles relating to the morphological evolution of injurious lesions, including dynamic expression of various immune checkpoint regulators. Enrichment analysis indicated deregulated pathways that underline known and highlight novel potential mechanisms of disease. Moreover, by capturing individual glomeruli, DSP describes heterogeneity between and within biopsies. We demonstrate the benefit of spatial profiling for characterization of heterogeneous glomerular injury, indicating novel molecular correlates of glomerular injury in piFNGN.
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Construction of Metastasis Prediction Models and Screening of Anti-Metastatic Drugs Based on Pan-Cancer Single-Cell EMT Features.
Tumor metastasis is the leading cause of death in cancer patients, with epithelial-mesenchymal transition (EMT) playing a key role. To systematically elucidate the cellular mechanisms and molecular networks through which EMT drives metastasis across cancers, this study integrated transcriptomic data from over 1.2 million single cells across 265 samples representing 12 primary epithelial cancers, constructing a comprehensive pan-cancer single-cell atlas covering diverse stages and metastatic states. By analyzing the metastatic features and interaction networks of malignant epithelial cells and cancer-associated fibroblasts (CAFs), we identified cancer-specific metastasis-related gene sets. Based on these genes, multiple machine learning algorithms were applied to build cancer-specific and cross-cancer metastasis prediction models, leading to the development of the metastasis prediction score (MPS) and global metastasis prediction score (GMPS). Both scores showed excellent predictive performance in independent test and external validation cohorts. MPS exhibited higher cancer specificity, whereas GMPS showed stronger cross-cancer generalization. Moreover, elevated MPS and GMPS reflected immunosuppressive tumor microenvironment features and were significantly associated with poor prognosis across multiple cancer types. Finally, through a drug repositioning framework, we identified several potential anti-metastatic compounds targeting the metastasis network, among which Fostamatinib demonstrated broad-spectrum therapeutic potential against metastasis in multiple cancers.
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Metabolic profiling of glioblastoma and identification of G0S2 as a metabolic target.
INTRODUCTION: Metabolic reprogramming is a hallmark of cancer, yet its role in glioma remains poorly understood. Gliomas are characterized by a highly immunosuppressive tumor microenvironment (TME) and poor prognosis. This study systematically explores the relationship between glioma metabolomics, tumor phenotype, and the immune microenvironment. METHODS: Bulk RNA sequencing data were retrieved from the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA). Single-cell gene set enrichment analysis (ssGSEA) was employed to quantify seven nutrient metabolic pathways and immune infiltration. Consensus clustering was applied to group gliomas based on metabolic gene expression, and survival analysis was performed to evaluate survival differences across these clusters. A predictive model was constructed and validated using our cohort. Finally, we knocked out G0S2 in glioma cells and performed RNA sequencing to investigate differentially activated pathways. Additionally, in vivo experiments were conducted to explore the antitumor effects of G0S2 knockout in combination with PD-1 monoclonal antibody. RESULTS: Significant metabolic differences were identified between low-grade gliomas (LGG) and glioblastomas (GBM), with consistent findings across both databases. We found that LGGs and GBMs exhibit distinct metabolic patterns. Consensus clustering revealed three metabolic subgroups, with the C3 subgroup demonstrating poor survival and enhanced infiltration of immunosuppressive cells. The predictive model showed robust performance in forecasting the survival of glioma patients. Functional analysis identified G0S2 as a key metabolic regulator highly expressed in gliomas. G0S2 knockout activated the type I interferon signaling pathway, enhanced CD8+ T cell functionality, and synergized with anti-PD-1 therapy, resulting in suppressed tumor growth and prolonged survival in vivo. CONCLUSION: These findings provide a comprehensive analysis of glioma metabolic patterns and identify G0S2 as a promising therapeutic target.
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Uncovering the prominent role of satellite cells in paravertebral muscle development and aging by single-nucleus RNA sequencing.
To uncover the role of satellite cells (SCs) in paravertebral muscle development and aging, we constructed a single-nucleus transcriptomic atlas of mouse paravertebral muscle across seven timepoints spanning the embryo (day 16.5) to old (month 24) stages. Eight cell types, including SCs, fast muscle cells, and slow muscle cells, were identified. An energy metabolism-related gene set, TCA CYCLE IN SENESCENCE, was enriched in SCs. Forty-two skeletal muscle disease-related genes were highly expressed in SCs and exhibited similar expression patterns. Among them, Pdha1 was the core gene in the TCA CYCLE IN SENESCENCE; Pgam2, Sod1, and Suclg1 are transcription factors closely associated with skeletal muscle energy metabolism. Transcription factor enrichment analysis of the 42 genes revealed that Myod1 and Mef2a were also highly expressed in SCs, which regulated Pdha1 expression and were associated with skeletal muscle development. These findings hint that energy metabolism may be pivotal in SCs development and aging. Three ligand-receptor pairs of extracellular matrix (ECM)-receptor interactions, Lamc1-Dag1, Lama2-Dag1, and Hspg2-Dag1, may play a vital role in SCs interactions with slow/fast muscle cells and SCs self-renewal. Finally, we built the first database of a skeletal muscle single-cell transcriptome, the Musculoskeletal Cell Atlas (http://www.mskca.tech), which lists 630,040 skeletal muscle cells and provides interactive visualization, a useful resource for revealing skeletal muscle cellular heterogeneity during development and aging. Our study could provide new targets and ideas for developing drugs to inhibit skeletal muscle aging and treat skeletal muscle diseases.
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A spatially-resolved transcriptional atlas of the murine dorsal pons at single-cell resolution.
The "dorsal pons", or "dorsal pontine tegmentum" (dPnTg), is part of the brainstem. It is a complex, densely packed region whose nuclei are involved in regulating many vital functions. Notable among them are the parabrachial nucleus, the Kölliker Fuse, the Barrington nucleus, the locus coeruleus, and the dorsal, laterodorsal, and ventral tegmental nuclei. In this study, we applied single-nucleus RNA-seq (snRNA-seq) to resolve neuronal subtypes based on their unique transcriptional profiles and then used multiplexed error robust fluorescence in situ hybridization (MERFISH) to map them spatially. We sampled ~1 million cells across the dPnTg and defined the spatial distribution of over 120 neuronal subtypes. Our analysis identified an unpredicted high transcriptional diversity in this region and pinpointed many neuronal subtypes' unique marker genes. We also demonstrated that many neuronal subtypes are transcriptionally similar between humans and mice, enhancing this study's translational value. Finally, we developed a freely accessible, GPU and CPU-powered dashboard (http://harvard.heavy.ai:6273/) that combines interactive visual analytics and hardware-accelerated SQL into a data science framework to allow the scientific community to query and gain insights into the data.
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Spatial transcriptomics reveals distinct and conserved tumor core and edge architectures that predict survival and targeted therapy response.
The spatial organization of the tumor microenvironment has a profound impact on biology and therapy response. Here, we perform an integrative single-cell and spatial transcriptomic analysis on HPV-negative oral squamous cell carcinoma (OSCC) to comprehensively characterize malignant cells in tumor core (TC) and leading edge (LE) transcriptional architectures. We show that the TC and LE are characterized by unique transcriptional profiles, neighboring cellular compositions, and ligand-receptor interactions. We demonstrate that the gene expression profile associated with the LE is conserved across different cancers while the TC is tissue specific, highlighting common mechanisms underlying tumor progression and invasion. Additionally, we find our LE gene signature is associated with worse clinical outcomes while TC gene signature is associated with improved prognosis across multiple cancer types. Finally, using an in silico modeling approach, we describe spatially-regulated patterns of cell development in OSCC that are predictably associated with drug response. Our work provides pan-cancer insights into TC and LE biology and interactive spatial atlases ( http://www.pboselab.ca/spatial_OSCC/ ; http://www.pboselab.ca/dynamo_OSCC/ ) that can be foundational for developing novel targeted therapies.
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A single-cell atlas to map sex-specific gene-expression changes in blood upon neurodegeneration.
The clinical course and treatment of neurodegenerative disease are complicated by immune-system interference and chronic inflammatory processes, which remain incompletely understood. Mapping immune signatures in larger human cohorts through single-cell gene expression profiling supports our understanding of observed peripheral changes in neurodegeneration. Here, we employ single-cell gene expression profiling of over 909k peripheral blood mononuclear cells (PBMCs) from 121 healthy individuals, 48 patients with mild cognitive impairment (MCI), 46 with Parkinson's disease (PD), 27 with Alzheimer's disease (AD), and 15 with both PD and MCI. The dataset is interactively accessible through a freely available website ( https://www.ccb.uni-saarland.de/adrcsc ). In this work, we identify disease-associated changes in blood cell type composition and the gene expression in a sex-specific manner, offering insights into peripheral and solid tissue signatures in AD and PD.