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Cellular heterogeneity and dynamics of the human uterus in healthy premenopausal women.
The human uterus is a complex and dynamic organ whose lining grows, remodels, and regenerates every menstrual cycle or upon tissue damage. Here, we applied single-cell RNA sequencing to profile more the 50,000 uterine cells from both the endometrium and myometrium of five healthy premenopausal individuals, and jointly analyzed the data with a previously published dataset from 15 subjects. The resulting normal uterus cell atlas contains more than 167K cells, representing the lymphatic endothelium, blood endothelium, stromal, ciliated epithelium, unciliated epithelium, and immune cell populations. Focused analyses within each major cell type and comparisons with subtype labels from prior studies allowed us to document supporting evidence, resolve naming conflicts, and propose a consensus annotation system of 39 subtypes. We release their gene expression centroids, differentially expressed genes, and messenger Ribonucleic Acid (mRNA) patterns of literature-based markers as a shared community resource. We identify multiple potential progenitor cells: compartment-wide progenitors for each major cell type and potential cross-lineage multipotent stromal progenitors that may replenish the epithelial, stromal, and endothelial compartments. Furthermore, many cell types and subtypes exhibit shifts in cell number and transcriptomes across different phases of the menstrual cycle. Finally, comparisons between premenopausal, postpartum, and postmenopausal samples revealed substantial alterations in tissue composition, particularly in the proportions of stromal, endothelial, and immune cells. The cell taxonomy and molecular markers we report here are expected to inform studies of both basic biology of uterine function and its disorders.
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Tissue signatures of human macrophages during homeostasis and activation.
Human macrophages (MΦs) reside in tissues and develop tissue-specific identities. While studies in mice have identified molecular signatures for site-specific MΦ differentiation, less is known about the transcriptional profiles of human MΦs in distinct sites, including mucosal tissues and lymphoid organs during homeostasis and activation. Here, we use multimodal single-cell sequencing and ex vivo stimulation assays to define tissue signatures for populations of human MΦs isolated from lungs, small intestine, spleen, bone marrow, and lymph nodes obtained from individual organ donors. Our results reveal distinct tissue-adapted gene and protein profiles of metabolic, adhesion, and immune interaction pathways, which are specific to MΦs and not monocytes isolated from the same sites and exhibit homology to murine MΦs from the same sites. Tissue-adapted MΦs remained responsive to polarizing cytokine stimuli ex vivo, with upregulation of expected transcripts and secreted proteins, while retaining tissue-specific profiles. Patterns of chromatin accessibility in tissue MΦs identified from single-nucleus assay for transposase-accessible chromatin by sequencing reflected gene expression signatures and indicate that differential utilization of transcription factors may drive stable tissue-adapted profiles. Together, our findings show how human MΦ identity is coupled to their site of residence for mucosal and lymphoid organs and is intrinsically maintained during activation and polarization.
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A multi-dimensional omics framework identifies GPR35 as a driver of M2 macrophage activation and poor prognosis in colorectal cancer.
INTRODUCTION: Colorectal cancer (CRC) remains a leading cause of global cancer mortality, with therapeutic outcomes heavily reliant on the tumor microenvironment (TME). While immunotherapy has revolutionized treatment for distinct subsets, the mechanisms driving immune evasion in the majority of patients remain elusive. METHODS: In this study, we constructed a comprehensive single-cell atlas of the CRC TME by integrating multi-cohort scRNA-seq data. RESULTS: Through non-negative matrix factorization (NMF), we identified nine intratumoral heterogeneity meta-programs (MPs), among which MP8 was robustly linked to M2 macrophage activation. High-dimensional WGCNA further pinpointed GPR35 as a master regulator within the MP8-associated gene network. Clinical analysis across four independent cohorts validated GPR35 as a significant predictor of poor prognosis. Functionally, GPR35 knockdown in vitro markedly impaired CRC cell proliferation, migration, and invasion. Mechanistically, high GPR35 expression orchestrated an immune-excluded microenvironment characterized by diminished cytotoxic T cell and NK cell recruitment, yet paradoxically elevated immune checkpoint expression. Furthermore, GPR35 expression was negatively correlated with eight established immunotherapy response signatures and associated with aggressive mutational landscapes. DISCUSSION: Collectively, our findings identify GPR35 as a novel cancer cell-intrinsic driver of immune evasion and immunotherapy resistance, positioning it as a promising therapeutic target to sensitize "cold" CRC tumors to immune checkpoint blockade.
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Matrix Metalloproteinase-9 is associated with tumor microenvironment remodeling of bladder cancer.
Tumor microenvironment (TME) takes an essential part in the bladder cancer progression, which is associated with intercellular cross-talk between stroma cells and cancer. We aimed use bioinformatics tools to analyze tumor microenvironment remodeling in bladder cancer. CIBERSORT and ESTIMATE are bioinformatics tools based on deconvolution for calculating proportions of tumor-infiltrating immune cells and stromal components in TME. We utilized these two algorithms to analyze the immune components of 433 bladder cancer cases from The Cancer Genome Atlas database, aiming to compensate for the current lack of large-sample single-cell information. Then we used Cox regression to analyze the prognostic value of differentially expressed genes, and the protein-protein interaction network was constructed. Matrix Metalloproteinase-9 (MMP9) was identified as a predictive biomarker related to immune microenvironment. Using Gene Set Enrichment Analysis, the genes from the group with high MMP9 expression gathered in items related to immune diseases, and genes in the group with low MMP9 expression were negatively associated with valine, leucine and isoleucine degradation and glycosylphosphatidylinositol anchor biosynthesis. MMP9 expression and presence of macrophages M0 were positively correlated, while naïve B cells, activated dendritic cells, monocytes and plasma cells were negatively correlated. The results were confirmed by brightfield and multiplex fluorescence immunohistochemistry using stained bladder cancer and normal tissue.
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NRG1/ErbB signalling controls the dialogue between macrophages and neural crest-derived cells during zebrafish fin regeneration.
Fish species, such as zebrafish (Danio rerio), can regenerate their appendages after amputation through the formation of a heterogeneous cellular structure named blastema. Here, by combining live imaging of triple transgenic zebrafish embryos and single-cell RNA sequencing we established a detailed cell atlas of the regenerating caudal fin in zebrafish larvae. We confirmed the presence of macrophage subsets that govern zebrafish fin regeneration, and identified a foxd3-positive cell population within the regenerating fin. Genetic depletion of these foxd3-positive neural crest-derived cells (NCdC) showed that they are involved in blastema formation and caudal fin regeneration. Finally, chemical inhibition and transcriptomic analysis demonstrated that these foxd3-positive cells regulate macrophage recruitment and polarization through the NRG1/ErbB pathway. Here, we show the diversity of the cells required for blastema formation, identify a discrete foxd3-positive NCdC population, and reveal the critical function of the NRG1/ErbB pathway in controlling the dialogue between macrophages and NCdC.
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Identification of Molecular Subtypes and Prognostic Features of Breast Cancer Based on TGF-β Signaling-related Genes.
OBJECTIVES: The TGF-β signaling pathway is widely acknowledged for its role in various aspects of cancer progression, including cellular invasion, epithelial-mesenchymal transition, and immunosuppression. Immune checkpoint inhibitors (ICIs) and pharmacological agents that target TGF-β offer significant potential as therapeutic options for cancer. However, the specific role of TGF-β in prognostic assessment and treatment strategies for breast cancer (BC) remains unclear. METHODS: The Cancer Genome Atlas (TCGA) database was utilized to develop a predictive model incorporating five TGF-β signaling-related genes (TSRGs). The GSE161529 dataset from the Gene Expression Omnibus was employed to conduct single-cell analyses aimed at further elucidating the characteristics of these TSRGs. Additionally, an unsupervised clustering algorithm was applied to categorize BC patients into two distinct groups based on the five TSRGs, with a focus on immune response and overall survival (OS). Further investigations were conducted to explore variations in pharmacotherapy and the tumor microenvironment across different patient cohorts and clusters. RESULTS: The predictive model for BC identified five TSRGs: FUT8, IFNG, ID3, KLF10, and PARD6A. Single-cell analysis revealed that IFNG is predominantly expressed in CD8+ T cells. Consensus clustering effectively categorized BC patients into two distinct clusters, with cluster B demonstrating a longer OS and a more favorable prognosis. Immunological assessments indicated a higher presence of immune checkpoints and immune cells in cluster B, suggesting a greater likelihood of responsiveness to ICIs. CONCLUSION: The findings of this study highlight the potential of the TGF-β signaling pathway for prognostic classification and the development of personalized treatment strategies for BC patients, thereby enhancing our understanding of its significance in BC prognosis.
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MICA+ Tumor Cells Modulate Macrophage Phenotype and Function via PPAR/EHHADH-Mediated Fatty Acid Metabolism in Hepatocellular Carcinoma (HCC).
Background: Tumor-associated macrophages (TAMs) play a crucial role in the tumor microenvironment (TME), and the metabolic activities of both tumor cells and TAMs have an impact on the TME. Moreover, the expression of MICA in tumor cells is closely associated with immune cells in hepatocellular carcinoma (HCC). However, it remains unclear whether MICA expression correlates with TAMs and influences the switch in macrophage phenotype by mediating metabolic alterations. Methods: Various biostatistical tools, qPCR, and IHC staining experiments were utilized to analyze data from The Cancer Genome Atlas (TCGA) and collected HCC tumor tissues. Single-cell RNA sequencing (scRNA-seq) analyses and a co-culture model of HCC cells with macrophages were performed to validate the findings from the biostatistical analyses. Results: Through the intersection of differentially expressed genes (DEGs), metabolism-related genes (MRGs), and co-expression genes (CEGs) with MICA in HCC, the EHHADH gene was identified. Gene set enrichment analyses were conducted to further confirm the role of EHHADH. EHHADH expression is decreased in HCC tumors and can serve as a prognostic biomarker for HCC. Expressions of MICA and EHHADH exhibited significant correlations with various phenotypic macrophages and exerted opposing effects on M1-like and M2-like macrophages infiltrating HCC. The underlying metabolic and molecular mechanisms revealed that MICA in tumor cells induced M2-like polarization through the PPAR/EHHADH pathway, which regulates the fatty acid oxidation (FAO) in macrophages. Conclusions: The metabolic gene EHHADH, which is associated with MICA, led to alterations in M2-like macrophages by promoting heightened fatty acid uptake and augmenting levels of FAO within macrophages.
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Association between high immune activity and worse prognosis in uveal melanoma and low-grade glioma in TCGA transcriptomic data.
BACKGROUND: Immune status in the tumor microenvironment is an important determinant of cancer progression and patient prognosis. Although a higher immune activity is often associated with a better prognosis, this trend is not absolute and differs across cancer types. We aimed to give insights into why some cancers do not show better survival despite higher immunity by assessing the relationship between different biological factors, including cytotoxicity, and patient prognosis in various cancer types using RNA-seq data collected by The Cancer Genome Atlas. RESULTS: Results showed that a higher immune activity was associated with worse overall survival in patients with uveal melanoma and low-grade glioma, which are cancers of immune-privileged sites. In these cancers, epithelial or endothelial mesenchymal transition and inflammatory state as well as immune activation had a notable negative correlation with patient survival. Further analysis using additional single-cell data of uveal melanoma and glioma revealed that epithelial or endothelial mesenchymal transition was mainly induced in retinal pigment cells or endothelial cells that comprise the blood-retinal and blood-brain barriers, which are unique structures of the eye and central nervous system, respectively. Inflammation was mainly promoted by macrophages, and their infiltration increased significantly in response to immune activation. Furthermore, we found the expression of inflammatory chemokines, particularly CCL5, was strongly correlated with immune activity and associated with poor survival, particularly in these cancers, suggesting that these inflammatory mediators are potential molecular targets for therapeutics. CONCLUSIONS: In uveal melanoma and low-grade glioma, inflammation from macrophages and epithelial or endothelial mesenchymal transition are particularly associated with a poor prognosis. This implies that they loosen the structures of the blood barrier and impair homeostasis and further recruit immune cells, which could result in a feedback loop of additional inflammatory effects leading to runaway conditions.
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WormGUIDES: an interactive single cell developmental atlas and tool for collaborative multidimensional data exploration.
BACKGROUND: Imaging and image analysis advances are yielding increasingly complete and complicated records of cellular events in tissues and whole embryos. The ability to follow hundreds to thousands of cells at the individual level demands a spatio-temporal data infrastructure: tools to assemble and collate knowledge about development spatially in a manner analogous to geographic information systems (GIS). Just as GIS indexes items or events based on their spatio-temporal or 4D location on the Earth these tools would organize knowledge based on location within the tissues or embryos. Developmental processes are highly context-specific, but the complexity of the 4D environment in which they unfold is a barrier to assembling an understanding of any particular process from diverse sources of information. In the same way that GIS aids the understanding and use of geo-located large data sets, software can, with a proper frame of reference, allow large biological data sets to be understood spatially. Intuitive tools are needed to navigate the spatial structure of complex tissue, collate large data sets and existing knowledge with this spatial structure and help users derive hypotheses about developmental mechanisms. RESULTS: Toward this goal we have developed WormGUIDES, a mobile application that presents a 4D developmental atlas for Caenorhabditis elegans. The WormGUIDES mobile app enables users to navigate a 3D model depicting the nuclear positions of all cells in the developing embryo. The identity of each cell can be queried with a tap, and community databases searched for available information about that cell. Information about ancestry, fate and gene expression can be used to label cells and craft customized visualizations that highlight cells as potential players in an event of interest. Scenes are easily saved, shared and published to other WormGUIDES users. The mobile app is available for Android and iOS platforms. CONCLUSION: WormGUIDES provides an important tool for examining developmental processes and developing mechanistic hypotheses about their control. Critically, it provides the typical end user with an intuitive interface for developing and sharing custom visualizations of developmental processes. Equally important, because users can select cells based on their position and search for information about them, the app also serves as a spatially organized index into the large body of knowledge available to the C. elegans community online. Moreover, the app can be used to create and publish the result of exploration: interactive content that brings other researchers and students directly to the spatio-temporal point of insight. Ultimately the app will incorporate a detailed time lapse record of cell shape, beginning with neurons. This will add the key ability to navigate and understand the developmental events that result in the coordinated and precise emergence of anatomy, particularly the wiring of the nervous system.
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Decoding regional keratinization in human oral mucosa through high-resolution spatial transcriptomics.
Oral mucosa exhibits region-specific keratinization, essential for periodontal health, yet the spatial and molecular mechanisms driving these differences remain poorly understood. This study aimed to generate a high-resolution spatial transcriptomic atlas of the human oral mucosa around the mucogingival junction, to reveal stromal-epithelial interactions, that distinguish keratinized from non-keratinized programs. Formalin-fixed paraffin-embedded specimens from the mucogingival junction area of two healthy donors were analyzed with the 10 × Genomics Visium HD platform, yielding two keratinized and two non-keratinized regions. Spatial clustering, pseudotime trajectory inference, cell-type integration with a single-cell reference, and ligand-receptor network analysis were applied to delineate epithelial and stromal compartments. Sixteen reproducible clusters, recapitulating tissue architecture, were identified and revealed distinct transcriptional signatures, distinguishing gingiva from lining mucosa. Pseudotime analysis revealed bifurcating epithelial lineages, originating from a shared basal progenitor layer into keratinized and non-keratinized programs. Gingival keratinization was driven by stromal collagen ligands (COL1A1, COL1A2, COL6A1, COL6A2) engaging epithelial receptors (CD44, SDC1), further reinforced within the epithelium by desmosomal adhesion via DSG1-DSC2/3. Gingival keratinization emerges from integrated stromal collagen signaling and epithelial adhesion. This spatially resolved framework advances understanding of oral mucosal specialization and provides a foundation for biologically guided regenerative therapies.