Your browser does not allow saving data (e.g. private mode): bookmarks will be lost when the tab closes.
Search PubMed
Keywords, author, journal, years — results from PubMed, abstracts with Russian translation, bookmarks in your browser.
Found: 4 924
Page 218 of 493-
Transcriptional profiling and therapeutic targeting of oxidative stress in neuroinflammation.
Oxidative stress is a central part of innate immune-induced neurodegeneration. However, the transcriptomic landscape of central nervous system (CNS) innate immune cells contributing to oxidative stress is unknown, and therapies to target their neurotoxic functions are not widely available. Here, we provide the oxidative stress innate immune cell atlas in neuroinflammatory disease and report the discovery of new druggable pathways. Transcriptional profiling of oxidative stress-producing CNS innate immune cells identified a core oxidative stress gene signature coupled to coagulation and glutathione-pathway genes shared between a microglia cluster and infiltrating macrophages. Tox-seq followed by a microglia high-throughput screen and oxidative stress gene network analysis identified the glutathione-regulating compound acivicin, with potent therapeutic effects that decrease oxidative stress and axonal damage in chronic and relapsing multiple sclerosis models. Thus, oxidative stress transcriptomics identified neurotoxic CNS innate immune populations and may enable discovery of selective neuroprotective strategies.
-
Spatial Transcriptomics: Constructing a Single-Cell Resolution Transcriptome-Wide Expression Atlas.
The method described here aims at the construction of a single-cell resolution gene expression atlas for an animal or tissue, combining in situ hybridization (ISH) and single-cell mRNA-sequencing (scRNAseq).A high resolution and medium-coverage gene expression atlas of an animal or tissue of interest can be obtained by performing a series of ISH experiments, followed by a process of image registration and gene expression averaging. Using the overlapping fraction of the genes, concomitantly obtained scRNAseq data can be fitted into the spatial context of the gene expression atlas, complementing the coverage by genes.
-
Systematic characterization of the tumor microenvironment in Chinese patients with hepatocellular carcinoma highlights intratumoral B cells as a potential immunotherapy target.
Hepatocellular carcinoma (HCC) is an immunogenic malignancy, which exhibits low responsiveness to programmed cell death protein‑1 (PD‑1)/programmed death ligand‑1 (PD‑L1) antibodies. Therefore, the identification of novel immunotherapeutic targets to treat HCC is imperative. Systematic characterization of the HCC tumor microenvironment (TME) can provide novel insight into additional therapeutic approaches. In the present study, the RNA‑sequencing (RNA‑seq) data of 360 patients with HCC were integrated from The Cancer Genome Atlas to assess the expression of membrane spanning 4‑domains A1 (MS4A1; encoding CD20) in tumors and normal liver tissues. Immunofluorescence and multiplex tissue fluorescence analyses were performed and combined with flow cytometry staining to measure CD20/CD19 expression at the protein level. In addition, published single cell RNA‑seq data of CD45+ cells were derived from 16 treatment‑naïve patients from Beijing Shijitan Hospital with HCC to illustrate the characteristics of CD19+ B cells. The results indicated that the HCC TME included nuclear receptor subfamily 4 group A member 2+ (NR4A2) B cells. Patients with HCC and high density of intratumoral B cells demonstrated compromised antitumor immunity manifested by low percentages of cytotoxic CD8+ T cells and high density of regulatory T cells. Furthermore, PD‑L1 expression was significantly correlated with the B cell signature marker CD20. The present study indicated that tumor‑infiltrating B cells may play a negative role in antitumor immunity and serve as a promising target for HCC immunotherapy, alone or in combination with anti‑PD‑L1/PD‑1 antibodies.
-
StrokeTime: A comprehensive longitudinal scRNA-seq atlas of the ischemic mouse brain.
Ischemic stroke triggers profound, dynamic changes in the brain's cellular landscape. To systematically characterize these dynamics, we integrated single-cell RNA-sequencing data from 21 mouse stroke studies (103 samples; 414,359 cells) spanning multiple models and post-stroke intervals. Using a harmonized computational workflow, we constructed StrokeTime, a single-cell mouse brain atlas covering hyperacute, acute, subacute, and chronic stages post-ischemia. The atlas contains 17 major cell classes and 120 fine-grained transcriptional states within myeloid, lymphoid, vascular, epithelial, neuronal, and glial populations. Myeloid cells showed the greatest plasticity, including disease-associated microglia/macrophage programs shared across resident and infiltrating cells, whereas lymphocytes featured activation and regulatory signatures within lineage constraints. Vascular and mural cells shifted from early inflammatory and barrier-disruptive programs to later fibrotic and angiogenic states. StrokeTime delineates both convergent and cell type-specific injury responses, offering a resource for studying post-ischemic brain immunity, tissue remodeling, and benchmarking future single-cell and single-nucleus studies of cerebrovascular disease.
-
An integrated transcriptomic cell atlas of human neural organoids.
Human neural organoids, generated from pluripotent stem cells in vitro, are useful tools to study human brain development, evolution and disease. However, it is unclear which parts of the human brain are covered by existing protocols, and it has been difficult to quantitatively assess organoid variation and fidelity. Here we integrate 36 single-cell transcriptomic datasets spanning 26 protocols into one integrated human neural organoid cell atlas totalling more than 1.7 million cells1-26. Mapping to developing human brain references27-30 shows primary cell types and states that have been generated in vitro, and estimates transcriptomic similarity between primary and organoid counterparts across protocols. We provide a programmatic interface to browse the atlas and query new datasets, and showcase the power of the atlas to annotate organoid cell types and evaluate new organoid protocols. Finally, we show that the atlas can be used as a diverse control cohort to annotate and compare organoid models of neural disease, identifying genes and pathways that may underlie pathological mechanisms with the neural models. The human neural organoid cell atlas will be useful to assess organoid fidelity, characterize perturbed and diseased states and facilitate protocol development.
-
A spatiotemporal transcriptomic atlas of mouse placentation.
The placenta, a temporary but essential organ for gestational support, undergoes intricate morphological and functional transformations throughout gestation. However, the spatiotemporal patterns of gene expression underlying placentation remain poorly understood. Utilizing Stereo-seq, we constructed a Mouse Placentation Spatiotemporal Transcriptomic Atlas (MPSTA) spanning from embryonic day (E) 7.5 to E14.5, which includes the transcriptomes of large trophoblast cells that were not captured in previous single-cell atlases. We defined four distinct strata of the ectoplacental cone, an early heterogeneous trophectoderm structure, and elucidated the spatial trajectory of trophoblast differentiation during early postimplantation stages before E9.5. Focusing on the labyrinth region, the interface of nutrient exchange in the mouse placenta, our spatiotemporal ligand-receptor interaction analysis unveiled pivotal modulators essential for trophoblast development and placental angiogenesis. We also found that paternally expressed genes are exclusively enriched in the placenta rather than in the decidual regions, including a cluster of genes enriched in endothelial cells that may function in placental angiogenesis. At the invasion front, we identified interface-specific transcription factor regulons, such as Atf3, Jun, Junb, Stat6, Mxd1, Maff, Fos, and Irf7, involved in gestational maintenance. Additionally, we revealed that maternal high-fat diet exposure preferentially affects this interface, exacerbating inflammatory responses and disrupting angiogenic homeostasis. Collectively, our findings furnish a comprehensive, spatially resolved atlas that offers valuable insights and benchmarks for future explorations into placental morphogenesis and pathology.
-
Single-cell RNA sequencing reveals atlas of dairy goat testis cells.
Single-cell RNA sequencing (scRNA-seq) is useful for exploring cell heterogeneity. For large animals, however, little is known regarding spermatogonial stem cell (SSC) self-renewal regulation, especially in dairy goats. In this study, we described a high-resolution scRNA-seq atlas derived from a dairy goat. We identified six somatic cell and five spermatogenic cell subtypes. During spermatogenesis, genes with significantly changed expression were mainly enriched in the Notch, TGF-β, and Hippo signaling pathways as well as the signaling pathway involved in the regulation of stem cell pluripotency. We detected and screened specific candidate marker genes ( TKTL1 and AES) for spermatogonia. Our study provides new insights into goat spermatogenesis and the development of testicular somatic cells.
-
A cDC1-NK/T-Malignant Cell Circuit Drives Immunogenic Remodeling Under PD-1 Blockade in Gastric Cancer.
The gastric cancer (GC) tumor microenvironment (TME) constitutes a complex and dynamic ecosystem in which immune, stromal, and malignant cells (MCs) collectively shape therapeutic responses. The dynamics of GC TME remodeling in different treatment contexts remain unclear. We performed single-cell RNA sequencing (scRNA-seq) of GC biopsy specimens from treatment-naïve patients (TN) and patients treated with chemotherapy (C), chemotherapy plus nivolumab (CN), or chemotherapy plus trastuzumab (CT), and found that CN treatment enhanced natural killer (NK)/T cell-associated immunogenicity in GC TMEs. In CN TMEs, MCs upregulate MHC-I- and inflammation-related genes. Conventional type 1 dendritic cells (cDC1), one subcluster of dendritic cells (DCs), concurrently exhibited activation of antigen-presentation and T cell-stimulatory programs, indicating intensified communication between NK/CD8+ T cells and cDC1 in the CN TMEs. The cell-cell interaction analyses uncovered an intensified X-C Motif Chemokine Ligand 1 (XCL1) - X-C motif chemokine receptor 1 (XCR1) chemotactic axis linking NK/CD8+ T cells and cDC1, highlighting the formation of "the MCs-cDC1-NK/CD8+ T cells circuit" to reinforce antitumor immunity in the CN TMEs. Furthermore, a reduced cytotoxic NK sub-cluster, which showed high XCL1 expression, was enriched among CN responders, and its transcriptional signature was significantly correlated with favorable survival in the Cancer Genome Atlas GC cohort. Our findings delineate an immunostimulatory circuit driven by NK/CD8+ T-DCs-MCs interactions to orchestrate the immune cycle under CN therapy in GC TMEs.
-
Integration of unpaired single cell omics data by deep transfer graph convolutional network.
The rapid advance of large-scale atlas-level single cell RNA sequences and single-cell chromatin accessibility data provide extraordinary avenues to broad and deep insight into complex biological mechanism. Leveraging the datasets and transfering labels from scRNA-seq to scATAC-seq will empower the exploration of single-cell omics data. However, the current label transfer methods have limited performance, largely due to the lower capable of preserving fine-grained cell populations and intrinsic or extrinsic heterogeneity between datasets. Here, we present a robust deep transfer model based graph convolutional network, scTGCN, which achieves versatile performance in preserving biological variation, while achieving integration hundreds of thousands cells in minutes with low memory consumption. We show that scTGCN is powerful to the integration of mouse atlas data and multimodal data generated from APSA-seq and CITE-seq. Thus, scTGCN shows high label transfer accuracy and effectively knowledge transfer across different modalities.
-
CD44 upregulation in chronic liver disease marks the transition to hepatocellular carcinoma and portends poor prognosis.
BACKGROUND: Hepatocellular carcinoma (HCC) often arises from chronic liver disease, but early biomarkers of malignant transformation are lacking. CD44, a transmembrane glycoprotein with multiple isoforms, has been implicated in cancer progression and immune modulation. METHODS: We analysed CD44 expression in mouse models of chronic and acute liver injury and assessed its clinical relevance in human HCC using bulk and single-cell transcriptomic datasets. RESULTS: CD44 and its isoforms v6 and v10 were progressively upregulated in chronic liver injury, peaking in HCC. CD44-positive hepatocytes increased with fibrosis severity and were abundant in murine liver tumours. In human HCC, CD44 expression was significantly elevated compared to non-tumorous liver and was associated with reduced overall survival. CD44high tumours showed enrichment in oncogenic signalling pathways and greater infiltration of immunosuppressive cells, including M2 macrophages and Th2 cells. Single-cell RNA-seq confirmed CD44 expression in both tumour and immune cells, linking it to a protumor immune microenvironment. CONCLUSIONS: CD44 is a promising early biomarker of hepatocarcinogenesis and a potential therapeutic target. Its expression reflects disease progression from fibrosis to cancer and is associated with poor prognosis and immune evasion in HCC.