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Found: 4 939
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High-Dimensional Single-Cell Multimodal Landscape of Human Carotid Atherosclerosis.
BACKGROUND: Atherosclerotic plaques are complex tissues composed of a heterogeneous mixture of cells. However, we have limited understanding of the comprehensive transcriptional and phenotypical landscape of the cells within these lesions. METHODS: To characterize the landscape of human carotid atherosclerosis in greater detail, we combined cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) and single-cell RNA sequencing (scRNA-seq) to classify all cell types within lesions (n=21; 13 symptomatic) to achieve a comprehensive multimodal understanding of the cellular identities of atherosclerosis and their association with clinical pathophysiology. RESULTS: We identified 25 distinct cell populations each having a unique multi-omic signature, including macrophages, T cells, NK cells, mast cells, B cells, plasma cells, neutrophils, dendritic cells, endothelial cells, fibroblasts, and smooth muscle cells (SMCs). Within the macrophage populations, we identified 2 proinflammatory subsets that were enriched in IL1B or C1Q expression, 2 distinct TREM2 positive foam cell subsets, one of which also expressed inflammatory genes, as well as subpopulations displaying a proliferative gene expression signature and one expressing SMC-specific genes and upregulation of fibrotic pathways. An in-depth characterization uncovered several subsets of SMCs and fibroblasts, including a SMC-derived foam cell. We localized this foamy SMC to the deep intima of coronary atherosclerotic lesions. Using CITE-seq data, we also developed the first flow cytometry panel, using cell surface proteins CD29, CD142, and CD90, to isolate SMC-derived cells from lesions. Last, we found that the proportion of efferocytotic macrophages, classically activated endothelial cells, contractile and modulated SMC-derived cell types were reduced, and inflammatory SMCs were enriched in plaques of clinically symptomatic vs. asymptomatic patients. CONCLUSIONS: Our multimodal atlas of cell populations within atherosclerosis provides novel insights into the diversity, phenotype, location, isolation, and clinical relevance of the unique cellular composition of human carotid atherosclerosis. This facilitates both the mapping of cardiovascular disease susceptibility loci to specific cell types as well as the identification of novel molecular and cellular therapeutic targets for treatment of the disease.
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Identification of Novel Prognostic Markers Associated With Laryngeal Squamous Cell Carcinoma Using Comprehensive Analysis.
BACKGROUND: Laryngeal squamous cell carcinoma (LSCC) is a leading malignant cancer of the head and neck. Patients with LSCC, in which the cancer has infiltrated and metastasized, have a poor prognosis. Therefore, there is an urgent need to identify more potential targets for drugs and biomarkers for early diagnosis. METHODS: RNA sequence data from LSCC and patients' clinical traits were obtained from the Gene Expression Omnibus (GEO) (GSE142083) and The Cancer Genome Atlas (TCGA) database. Differentially expressed gene (DEG) analysis and weighted gene co-expression network analysis (WGCNA) were performed to identify hub genes. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, prognostic value analysis, receiver operating characteristic (ROC) curve analysis, gene mutation analysis, tumor-infiltrating immune cell abundance profile estimation, gene set variation analysis (GSVA), and gene set enrichment analysis (GSEA) were performed. Single-gene RNA sequencing data were obtained from the GSE150321 dataset. Cell proliferation and viability were confirmed by the CCK-8 assay and real-time PCR. RESULTS: A total of 701 DEGs, including 329 upregulated and 372 downregulated genes, were screened in the GSE142083 dataset. Using WGCNA, three modules were identified to be closely related to LSCC. After intersecting the DEGs and performing univariate and multivariate Cox analyses, a novel prognostic model based on three genes (SLC35C1, HOXB7, and TEDC2) for LSCC was established. Interfering TEDC2 expression inhibited tumor cell proliferation and migration. CONCLUSIONS: Our results show that SLC35C1, HOXB7, and TEDC2 have the potential to become new therapeutic targets and prognostic biomarkers for LSCC.
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Chromatin accessibility landscapes define stromal cell identities across tissues.
Chromatin accessibility is crucial in regulating gene expression and maintaining cellular identity. While single-cell RNA sequencing has revolutionized transcriptomic profiling, the understanding of chromatin dynamics across diverse tissues remains limited. Here, we use single-cell Assay for Transposase-Accessible Chromatin sequencing (scATAC-seq) to explore chromatin accessibility landscapes across murine tissues. We profile chromatin accessibility in 51,248 cells from nine mouse tissues, identifying 28 major cell types with distinct accessibility signatures. Our data reveal both conserved and tissue-specific cis-regulatory elements, highlighting the dynamic interplay between transcription factors and chromatin states in cell differentiation and tissue function. Motif enrichment analyses uncover transcription factor motifs driving these regulatory landscapes. Notably, we demonstrate that chromatin accessibility profiles enable tracing stromal cells, including endothelial cells, fibroblasts, and macrophages back to their tissue of origin. Using a metacell approach, we identify specific chromatin modules reflecting tissue-specific epigenomic landscapes, underscoring the role of chromatin accessibility in defining stromal cell identities. Our study provides a comprehensive atlas of chromatin accessibility across murine tissues, offering insights into the regulatory architecture that governs tissue and cell-type specificity. The ability to trace stromal cells to their tissue of origin through chromatin signatures holds important implications for diagnostics and therapeutic interventions in disease contexts.
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Unraveling tumoral heterogeneity and angiogenesis-associated mechanisms of PD-1 and LAG-3 dual inhibition in lung cancers by single-cell RNA sequencing.
BACKGROUND: Lymphocyte activation gene 3 (LAG-3) is a promising immune checkpoint for combination immunotherapy. This study aims to elucidate the exact synergistic anti-tumor mechanism of programmed death 1 (PD-1) and LAG-3 dual inhibition in lung cancer. METHODS: Multiple patient-derived xenograft (PDX) models of lung cancer were constructed and analyzed by single-cell RNA sequencing (scRNA-seq). Clustering of all human-derived cells, identification of biomarker genes of three cell types, trajectory analysis, and calculation of tumor heterogeneity scores were performed. Differentially expressed genes (DEGs) were identified and functional enrichment analyses of cancer-associated genes were conducted. The functional significance of DEGs in the immune system was evaluated using the Reactome online server. Major histocompatibility complex (MHC) pathways and angiogenesis-associated pathways were analyzed. The Cancer Genome Atlas (TCGA) was used for further verification. RESULTS: PD-1 and LAG-3 dual inhibition achieved synergistic tumor inhibition in squamous cell carcinoma (SCC) PDX models, but not in adenocarcinoma and small cell lung cancer PDX models. A total of 8127 cells, including 2699 basal, 4109 malignant, and 1319 epithelial cells, were identified by scRNA-seq. Malignant cells evolved from basal and epithelial cells in the trajectory analysis. The responders to the combination therapy of PD-1 and LAG-3 inhibitors had lower heterogeneity scores than non-responders. Compared with anti-PD-1 monotherapy, the combination group exhibited higher levels of neutrophil degranulation. The DEGs were correlated with disease, metabolism, and programmed cell death-associated pathways. The MHC class I-associated pathways and pericyte pathways were upregulated, whereas the vascular endothelial growth factor pathway was downregulated in the combination group. CONCLUSION: We discovered the superior efficacy of PD-1 and LAG-3 dual inhibition in SCC PDX models, and showed that it may be associated with low tumor heterogeneity scores, upregulation of the MHC class I pathway, and normalization of tumor angiogenesis.
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The expression of mercaptopyruvate sulfurtransferase serves as a potential biomarker for prognostic stratification and immunotherapy in certain cancers.
INTRODUCTION: 3 - Mercaptopyruvate Sulfurtransferase (3 - MST) is an enzyme encoded by the Mercaptopyruvate Sulfurtransferase (MPST) gene. The enzyme is associated with a variety of cancers such as lung adenocarcinoma. However, there is a lack of comprehensive pan-cancer analysis on the potential impact of MPST on cancer diagnosis, prognosis, and immune response. METHODS: Based on data from The Cancer Genome Atlas and the Human Protein Atlas, we conducted a comprehensive bioinformatic analysis to investigate the oncogenic role of MPST. Immune-related characteristics and tumor microenvironment infiltration were assessed using TIMER2.0. Protein-protein interaction networks were constructed via STRING, while DNA methylation differences across cancers were analyzed with UALCAN. Further insights into genetic alterations and functional states at the single-cell level were obtained from cBioPortal and CancerSEA. Finally, clinical samples were collected and subjected to immunohistochemical staining to preliminarily validate the bioinformatic findings. RESULT: The research assessed the links between MPST levels and various cancer outcomes, genetic alterations, immune cell presence, and DNA methylation patterns. Single-cell sequencing was utilized to deepen our comprehension of its functional importance. Furthermore, the unique immunohistochemical profiling of MPST in patient tissue was confirmed. Significant expression differences between tumors and normal tissues in certain cancer types suggest a correlation between MPST expression and clinical outcomes. Furthermore, correlations exist between MPST expression levels in different immune cells and the tumor immune microenvironment. Our observations also indicate a role for MPST methylation, along with the advantageous effects of highly amplified mutations and deletions of the MPST gene. DISCUSSION: Significantly, MPST shows potential for early cancer identification and as a predictive factor for various tumor forms.
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Single-cell expression profiling of bat wing development.
Bats are the only true-flight mammals, with wings formed by elongated digits and wing membranes. Despite the uniqueness, the cellular and molecular aspects of bat wing development remain largely unknown. Here, we use single-cell transcriptomic sequencing to map ~39,000 cells from the limbs of bats (Rhinolophus sinicus) at developmental stages Carnegie stages (CS) 16, 18, and 20. We identify 16 distinct cell populations, including a specific mesenchymal progenitor population (PDGFD+) in bat forelimbs, which may differentiate into the interdigital membrane and promote bone cell proliferation. Developing bat forelimbs exhibit prolonged chondrogenesis and delayed osteogenesis, resulting in more chondrocytes and fewer osteoblasts. The integrative analyses of data from single-cell and bulk RNA sequencing highlight the crucial roles of Notch signaling activation and WNT/β-catenin signaling suppression in bat forelimb development. Our findings provide a comprehensive single-cell atlas of developing bat limbs, offering insights into the mechanisms underlying bat wing development.
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Involvement of the disulfidptosis-related immune checkpoint gene, CD276, in glioblastoma malignant phenotype and poor prognosis.
BACKGROUND: Immunotherapy has promise for glioblastoma multiforme (GBM) treatment and disulfidptosis, a form of cell death involving disintegration of the actin cytoskeleton, is a potential target. The aim of the current study was to identify genes associated with disulfidptosis-related immune checkpoints in GBM and to analyze connections with malignancy. METHODS: Two expression matrices from The Cancer Genome Atlas-Genotype Tissue Expression (TCGA-GTEx) and Chinese Glioma Genome Atlas (CGGA) cyber public data were utilized to analyze differentially expressed genes (DEGs) in GBM and interaction networks for DEG-coded proteins constructed with protein-protein interaction network analysis. Functional annotation was conducted to indicate DEG function. Hub genes were identified by machine-learning, using Least Absolute Shrinkage and Selection Operator (LASSO) and Support Vector Machine Recursive Feature Elimination (SVM-RFE). Gene expression, immune cell composition and single-cell expression were assessed via bioinformatics and in vitro assays. Finally, xenograft nude mouse models were constructed for in vivo validation. RESULTS: 35 DEGs were found in the TCGA-GTEx and 13 in the CGGA databases and linked to immune regulation and GBM progression. The key gene CD276 was screened by bioinformatics methods. CD276 had higher expression in GBM tissues than in control and was higher expression in GBM strain than in normal astrocytes. In vitro CD276 knockdown reduced GBM cell malignancy. Furthermore, CD276 knockdown suppressed tumor growth in vivo. CONCLUSION: CD276 was the most significant hub gene involved in disulfidptosis and immune checkpoints in GBM. Anti-CD276 therapy may have promise for GBM treatment.
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Identification of Periostin as a Potential Biomarker in Gliomas by Database Mining.
BACKGROUND: Bioinformatics analysis integrating microenvironmental factors and single cell analysis segregated the glioblastoma (GBM) subtype into 3 subtypes: proneural, classic, and mesenchymal. Mesenchymal GBM tends to have the worst survival but benefits from aggressive treatment protocols. Therefore, it is clinically meaningful to identify relevant biomarkers to distinguish the mesenchymal subtype. Moreover, in developing nations with limited resources, rigorous examinations are costly and inefficient for patient care. METHODS: In this study, we analyzed The Cancer Genome Atlas (TCGA)-Glioblastoma and TCGA-Low-Grade Glioma RNA sequencing (RNAseq) cohorts and confirmed that the mesenchymal subtype was associated with the worst prognosis. RESULTS: We identified periostin (POSTN) as a mesenchymal subtype biomarker with prognostic value across histologic grades and confirmed the reliability of POSTN by gene expression meta-analysis combining TCGA, Chinese Glioma Genome Atlas (CGGA) and REMBRANDT (Repository for Molecular Brain Neoplasia Data) GBM cohorts (hazard ratio, 1.71 [range, 1.47-2.07], n = 693) and LGG cohorts (hazard ratio, 2.55 [range, 1.61-4.05], n = 1226). CONCLUSIONS: By using available online glioma databases, our study provided an insight into the expression of POSTN as an independent predictor for patients with glioma (GBM and LGG) and could be useful for diagnostic simplification to identify high-risk groups.
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A Transcriptional Atlas of Endothelial Cell Zonation Along the Pulmonary Vascular Tree.
BACKGROUND: The lung vasculature is comprised of a series of branching vessels extending from the main pulmonary artery to the alveolar capillaries, then back to the pulmonary veins. Lung endothelial cells (EC) exist along this continuum, exposed to gradients of shear stress, oxygen tension and pressure. Single cell RNA sequencing (scRNA-seq) has identified lung EC subsets, but many aspects of the vascular continuum, including vessel size and capillary polarity remain undefined from transcriptomic data. METHODS: We created an endothelial-enriched scRNA-seq dataset from the P3 mouse lung. Using diffusion pseudotime across all lung EC, we developed an analytical framework to delineate transcriptomic gradients and assign vessel-size scores to categorize individual endothelial cells (EC) along the vascular continuum. We confirmed size-related gene expression patterns with fluorescence in situ hybridization. RESULTS: We categorized capillary 1, arterial and venous EC along two gradients: arterio-venous zonation and vessel size. This approach distinguished large arteries from arterioles, large veins from venules, and revealed arterio-venous polarity within the capillaries. Our data recapitulated previously established zonally defined cell signaling axes, such as high Cxcl12-Cxcr4 signaling in arterioles. We also identified unique cellular communication occurring in large versus small arteries and veins, and localized injury-induced venous EC proliferation to vessels of specific size. This analytical framework was successfully applied to several published mouse and human datasets across different stages of lung development. CONCLUSIONS: These findings provide a comprehensive transcriptional map of EC across the pulmonary vascular tree, enabling assignment of each individual cell to vessels with defined size and position. This framework offers spatial inferences and novel mechanistic insights from scRNA-seq data sets that may elucidate therapeutic targets to treat pulmonary vascular diseases affecting specific vascular segments. We speculate that similar frameworks could be applied to tissues outside the lung.
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CREM Marks TCR-Driven T-Cell Activation and Associates with Favorable Prognosis in Papillary Thyroid Carcinoma: A Single-Cell and Bulk Transcriptomic Study.
Although papillary thyroid carcinoma (PTC) is widely considered an immunologically cold tumor, detectable T-cell infiltration can influence disease progression in selected patients. Previous bulk analyses have linked cAMP-responsive element modulator (CREM) expression to a favorable progression-free interval and an inverse correlation with regulatory T-cell infiltration but have not resolved the cellular origin or functional state. In this study, we integrate single-cell RNA-sequencing data from a 23-sample PTC atlas with bulk Cancer Genome Atlas Thyroid Carcinoma (TCGA-THCA) validation. We show that CREM marks a T-cell receptor (TCR)-driven immediate early gene activation state in tumor-infiltrating T cells rather than a cAMP program; this state is consistently and modestly enriched within the FOXP3+ regulatory T-cell compartment, challenging the interpretation that bulk inverse Treg-CREM correlations reflect Treg-intrinsic repression. CREM-high T cells upregulate ANXA1, and permutation-controlled analysis identifies a candidate paracrine axis from CD4/CD8 T cells to the epithelial epidermal growth factor receptor (EGFR). At the bulk level, CREM expression correlates with reduced proliferation programs and is associated with a prolonged progression-free interval (multivariate HR 0.56, 95% CI 0.31-1.00, p = 0.050), with the effect direction preserved after immune and sex adjustment. Genome-wide differential expression and gene-set enrichment in an independent cohort (GSE193581) confirm that CREM-detected T cells are enriched for a TCR-driven immediate early transcriptional program, supporting the reinterpretation of CREM as a marker of TCR-driven IEG activation.