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Single cell atlas of the comorbidity mechanism between chronic obstructive pulmonary disease and lung adenocarcinoma: a study of multi-omics combined analysis.
PURPOSE: Chronic obstructive pulmonary disease (COPD) is a recognized risk factor for lung adenocarcinoma (LUAD), but the molecular mechanisms behind this association are still unclear. This study aims to reveal shared key genes and pathways involved in both COPD and LUAD, and identify potential biomarkers and therapeutic targets. METHODS: Two-sample Mendelian randomization (MR) analysis using Genome-Wide Association Study (GWAS) data was performed to evaluate genetic causality. Differential expression analysis was performed on GSE76925 (COPD) and GSE116959 (LUAD), followed by LASSO regression, enrichment analysis, immune cell infiltration analysis, RNA modification analysis, competing endogenous RNA (ceRNA) network construction, and drug sensitivity prediction. Single-cell RNA sequencing data (GSE270667, GSE189357) were used to explore cell-type-specific expression, and qPCR was performed to validate gene expression in patient blood samples. RESULTS: MR confirmed the genetic relationship between COPD and LUAD. Three key genes (FCRLA, GREM1, and MMP9) were significantly upregulated and involved in immune regulation, extracellular matrix (ECM) remodeling, and the PI3K-Akt signaling pathway. Single-cell analysis revealed that these genes were specifically expressed in B cells, T cells, and monocytes. Multiple omics analyses indicated epigenetic and RNA level regulation. Several candidate drugs have been identified. CONCLUSION: FCRLA, GREM1, and MMP9 are inflammation-associated genes that may link the pathobiology of COPD and LUAD, and serve as valuable biomarkers with therapeutic potential in high-risk populations.
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Changes in genome architecture and transcriptional dynamics progress independently of sensory experience during post-natal brain development.
Both transcription and three-dimensional (3D) architecture of the mammalian genome play critical roles in neurodevelopment and its disorders. However, 3D genome structures of single brain cells have not been solved; little is known about the dynamics of single-cell transcriptome and 3D genome after birth. Here, we generated a transcriptome (3,517 cells) and 3D genome (3,646 cells) atlas of the developing mouse cortex and hippocampus by using our high-resolution multiple annealing and looping-based amplification cycles for digital transcriptomics (MALBAC-DT) and diploid chromatin conformation capture (Dip-C) methods and developing multi-omic analysis pipelines. In adults, 3D genome "structure types" delineate all major cell types, with high correlation between chromatin A/B compartments and gene expression. During development, both transcriptome and 3D genome are extensively transformed in the first post-natal month. In neurons, 3D genome is rewired across scales, correlated with gene expression modules, and independent of sensory experience. Finally, we examine allele-specific structure of imprinted genes, revealing local and chromosome (chr)-wide differences. These findings uncover an unknown dimension of neurodevelopment.
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Gene expression patterns of the developing human face at single cell resolution reveal cell type contributions to normal facial variation and disease risk.
Craniofacial development gives rise to the complex structures of the face and involves the interplay of diverse cell types. Despite its importance, our understanding of human-specific craniofacial developmental mechanisms and their genetic underpinnings remains limited. Here, we present a comprehensive single-nucleus RNA sequencing (snRNA-seq) atlas of human craniofacial development from craniofacial tissues of 24 embryos that span six key time points during the embryonic period (4-8 post-conception weeks). This resource resolves the transcriptional dynamics of seven major cell types and uncovers distinct major cell types, including muscle progenitors and cranial neural crest cells (CNCCs), as well as dozens of subtypes of ectoderm and mesenchyme. Comparative analyses reveal substantial conservation of major cell types, alongside human biased differences in gene expression programs. CNCCs, which play a crucial role in craniofacial morphogenesis, exhibit the lowest marker gene conservation, underscoring their evolutionary plasticity. Spatial transcriptomics further localizes cell populations, providing a detailed view of their developmental roles and anatomical context. We also link these developmental processes to genetic variation, identifying cell type-specific enrichments for common variants associated with facial morphology and rare variants linked to orofacial clefts. Intriguingly, Neanderthal-introgressed sequences are enriched near genes with biased expression in cartilage and specialized ectodermal subtypes, suggesting their contribution to modern human craniofacial features. This atlas offers unprecedented insights into the cellular and genetic mechanisms shaping the human face, highlighting conserved and distinctly human aspects of craniofacial biology. Our findings illuminate the developmental origins of craniofacial disorders, the genetic basis of facial variation, and the evolutionary legacy of ancient hominins. This work provides a foundational resource for exploring craniofacial biology, with implications for developmental genetics, evolutionary biology, and clinical research into congenital anomalies.
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Single-Cell Atlas of Subchondral Bone Marrow Lesions Reveals Proteostasis Dysfunction as a Druggable Mechanism for Early Osteoarthritis.
Subchondral bone marrow lesions (BMLs) constitute a pathognomonic imaging feature of both incipient and progressive osteoarthritis (OA). However, the pathological features and molecular mechanisms underlying BMLs remain poorly characterized. Here, we innovatively established and dynamically characterized a standardized mouse model, simulating human BMLs on magnetic resonance imaging (MRI) that correlates significantly with cartilage degeneration, while revealing substantial aberrant bone matrix accumulation within BML regions. By establishing an osteochondral single-cell atlas of mouse knee joints during BML development, we found that proteasome dysfunction and abnormal secretion of misfolded collagen, driven by dysregulated heat shock protein 70 (HSP70) and deubiquitinase 19 (USP19) expression in osteoarthritic subchondral osteoblasts, constitute a key mechanism of BML formation. Furthermore, cell-cell communication and Col10a1-Cre; R26tdt+ fate-mapping analyses uncovered that osteoblast-secreted WNT5A mediates crosstalk with hypertrophic chondrocytes (HTCs), accelerating their hypertrophy and cell death. Critically, pharmacological HSP70 targeting by TRC051384 inhibited collagen misfolding/secretion, preventing BML formation. Notably, results of Mendelian randomization demonstrated a significant correlation between proteasome gene expression and OA risk in humans, further supporting a potential role of proteasome dysfunction in BML pathogenesis. Collectively, these data reveal mechanisms underlying BML formation and therapeutic targets for early OA intervention.
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Single cell spatial profiling of the matrisome identifies region-specific adhesion and signaling networks in glioblastoma.
The human brain contains a milieu of extracellular matrix (ECM) components that promote normal development and physiology. ECM signaling pathways are often dysregulated in brain pathologies including the malignant cancer glioblastoma (GBM). Here, we used single-cell spatial transcriptomic platforms to map the expression of nearly 400 ECM genes in matching non-cancerous brain and GBM samples. At least four different GBM cell populations have been identified that show unique ECM expression profiles and spatial enrichment in distinct intratumor regions. Spatial mapping demonstrates largely non-overlapping expression signatures of ECM components in GBM stromal cell types, particularly in vascular endothelial cells and microglia/macrophages. Comparisons of GBM versus lower grade astrocytoma samples identifies differential expression of key ECM components. Computational analysis reveals novel ECM ligand-receptor networks between GBM and stromal cells. This spatial atlas provides new insights into ECM control of brain tumor initiation and progression and identifies potential targets for therapy in GBM.
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A single-cell transcriptomic atlas of sensory-dependent gene expression in developing mouse visual cortex.
Sensory experience drives the maturation of neural circuits during postnatal brain development through molecular mechanisms that remain to be fully elucidated. One likely mechanism involves the sensory-dependent expression of genes that encode direct mediators of circuit remodeling within developing cells. To identify potential drivers of sensory-dependent synaptic development, we generated a single-nucleus RNA sequencing dataset describing the transcriptional responses of cells in the mouse visual cortex to sensory deprivation or to stimulation during a developmental window when visual input is necessary for circuit refinement. We sequenced 118,529 nuclei across 16 neuronal and non-neuronal cell types isolated from control, sensory deprived and sensory stimulated mice, identifying 1268 sensory-induced genes within the developing brain. While experience elicited transcriptomic changes in all cell types, excitatory neurons in layer 2/3 exhibited the most robust changes, and the sensory-induced genes in these cells are poised to strengthen synapse-to-nucleus crosstalk and to promote cell type-specific axon guidance pathways. Altogether, we expect this dataset to significantly broaden our understanding of the molecular mechanisms through which sensory experience shapes neural circuit wiring in the developing brain.
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Integrated single-cell and bulk RNA sequencing revealed the molecular characteristics and prognostic roles of neutrophils in pancreatic cancer.
Pancreatic cancer, one of the most prevalent tumors of the digestive system, has a dismal prognosis. Cancer of the pancreas is distinguished by an inflammatory tumor microenvironment rich in fibroblasts and different immune cells. Neutrophils are important immune cells that infiltrate the microenvironment of pancreatic cancer tumors. The purpose of this work was to examine the complex mechanism by which neutrophils influence the carcinogenesis and development of pancreatic cancer and to construct a survival prediction model based on neutrophil marker genes. We incorporated the GSE111672 dataset, comprising RNA expression data from 27,000 cells obtained from 3 patients with PC, and conducted single-cell data analysis. Thorough investigation of pancreatic cancer single-cell RNA sequencing data found 350 neutrophil marker genes. Using The Cancer Genome Atlas (TCGA), GSE28735, GSE62452, GSE57495, and GSE85916 datasets to gather pancreatic cancer tissue transcriptome data, and consistent clustering was used to identify two categories for analyzing the influence of neutrophils on pancreatic cancer. Using the Random Forest algorithm and Cox regression analysis, a survival prediction model for pancreatic cancer was developed, the model showed independent performance for survival prognosis, clinic pathological features, immune infiltration, and drug sensitivity. Multivariate Cox analysis findings revealed that the risk scores derived from predictive models is independent prognostic markers for pancreatic patients. In conclusion, based on neutrophil marker genes, this research created a molecular typing and prognostic grading system for pancreatic cancer, this system was very accurate in predicting the prognosis, tumor immune microenvironment status, and pharmacological treatment responsiveness of pancreatic cancer patients.
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Integrated Single-Cell Atlas of Endothelial Cells of the Human Lung.
BACKGROUND: Cellular diversity of the lung endothelium has not been systematically characterized in humans. We provide a reference atlas of human lung endothelial cells (ECs) to facilitate a better understanding of the phenotypic diversity and composition of cells comprising the lung endothelium. METHODS: We reprocessed human control single-cell RNA sequencing (scRNAseq) data from 6 datasets. EC populations were characterized through iterative clustering with subsequent differential expression analysis. Marker genes were validated by fluorescent microscopy and in situ hybridization. scRNAseq of primary lung ECs cultured in vitro was performed. The signaling network between different lung cell types was studied. For cross-species analysis or disease relevance, we applied the same methods to scRNAseq data obtained from mouse lungs or from human lungs with pulmonary hypertension. RESULTS: Six lung scRNAseq datasets were reanalyzed and annotated to identify >15 000 vascular EC cells from 73 individuals. Differential expression analysis of EC revealed signatures corresponding to endothelial lineage, including panendothelial, panvascular, and subpopulation-specific marker gene sets. Beyond the broad cellular categories of lymphatic, capillary, arterial, and venous ECs, we found previously indistinguishable subpopulations; among venous EC, we identified 2 previously indistinguishable populations: pulmonary-venous ECs (COL15A1neg) localized to the lung parenchyma and systemic-venous ECs (COL15A1pos) localized to the airways and the visceral pleura; among capillary ECs, we confirmed their subclassification into recently discovered aerocytes characterized by EDNRB, SOSTDC1, and TBX2 and general capillary EC. We confirmed that all 6 endothelial cell types, including the systemic-venous ECs and aerocytes, are present in mice and identified endothelial marker genes conserved in humans and mice. Ligand-receptor connectome analysis revealed important homeostatic crosstalk of EC with other lung resident cell types. scRNAseq of commercially available primary lung ECs demonstrated a loss of their native lung phenotype in culture. scRNAseq revealed that endothelial diversity is maintained in pulmonary hypertension. Our article is accompanied by an online data mining tool (www.LungEndothelialCellAtlas.com). CONCLUSIONS: Our integrated analysis provides a comprehensive and well-crafted reference atlas of ECs in the normal lung and confirms and describes in detail previously unrecognized endothelial populations across a large number of humans and mice.
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ITGB4 upregulation is associated with progression of lower grade glioma.
Gliomas originating in the neuroepithelium account for about 80% of brain malignancies and are the most common cancer of the central nervous system. Clinical management of gliomas remains challenging despite significant advances in comprehensive therapies, including radiotherapy, chemotherapy, and surgery. The ITGB4 (Integrin subunit beta 4) gene encodes a receptor for laminins and its upregulation in tumor tissues is associated with poor prognosis. However, its role in glioma is not well understood. First, we performed a pan cancer analysis of ITGB4 expression in The Cancer Genome Atlas (TCGA) dataset. Survival analysis was done on Chinese Glioma Genome Atlas (CGGA) and TCGA. Immunohistochemistry was then used to validate the expression and role of ITGB4 in glioma. We finally analyzed the possible mechanism by immune infiltration and single-cell sequencing analysis. Here, we found that ITGB4 is upregulated in glioma and accurately predicts the prognosis of lower grade glioma (LGG). Univariate and multivariate Cox regression analyses showed that ITGB4 is a risk factor for LGG. Immunohistochemical analysis confirmed that ITGB4 accurately predicts LGG prognosis. Non-negative matrix factorization (NMF) cluster analysis showed that ITGB4 was closely related to immune related genes. Immune cell infiltration and single cell sequencing analyses indicated that ITGB4 may be closely related to the microenvironment of gliomas, especially tumor-associated fibroblasts. ITGB4 is a promising diagnostic and therapeutic factor in LGG patients.
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Integrative single-cell atlas unveils heterogeneity and prognostic value of cancer-associated fibroblasts in gastric cancer.
Gastric cancer (GC) exhibits molecular heterogeneity and diverse immune cell infiltration patterns closely associated with patient prognosis. However, a comprehensive understanding of the variations in immune cell phenotypes among different patient subgroups still needs to be improved. In this study, we performed a detailed analysis of the tumor microenvironment in GC by integrating 200,466 single cells from 72 patients across six datasets. We classified patients into immune-deserted, B, T, and myeloid cell subtypes. Using genomic and clinical data from TCGA samples, we identified cellular components associated with tumor histology and genotypes. GC patients were stratified into immune-deserted, B cell, T cell, and myeloid cell subtypes, and we described the pathway and transcription factor activity characteristics of different microenvironment subtypes. Integration of bulk RNA-seq data reveals that fibroblasts and endothelial cells were associated with adverse patient outcomes whereas NK and T cells were notably correlated with improved prognosis. Subsequently, we focused on characterizing cancer-associated fibroblasts (CAFs) and discovered that they acquire new functional properties within the tissue microenvironment, providing evidence of CAF plasticity. We constructed a novel four-gene CAF signature including SPARC, EFEMP1, RGS5 and SERPINE1 which may enhance patient stratification and prognostic prediction of GC patients. qPCR analysis revealed that the significant expressions of SPARC, EFEMP1, RGS5 and SERPINE1 were significantly upregulated in gastric cancer tissues compared to the normal tissues. Our study provides insights into the composition of the tumor microenvironment and construction of a four-gene CAF signature associated with clinical prognosis, offering new perspectives for the clinical management of gastric cancer.