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Glioblastomas are known for their poor clinical prognosis, with recurrent tumors often exhibiting greater invasiveness and faster growth rates compared to primary tumors. To understand the intratumoral changes driving this phenomenon, we employed single-cell sequencing to analyze the differences between two pairs of primary and recurrent glioblastomas. Our findings revealed an upregulation of ferroptosis in endothelial cells within recurrent tumors, identified by the significant overexpression of the NOX4 gene. Further analysis indicated that knocking down NOX4 in endothelial cells reduced the activity of the ferroptosis pathway. Utilizing conditioned media from endothelial cells with lower ferroptosis activity, we observed a decrease in the growth rate of glioblastoma cells. These results highlighted the complex role of ferroptosis within tumors and suggested that targeting ferroptosis in the treatment of glioblastomas requires careful consideration of its effects on endothelial cells, as it may otherwise produce counterproductive outcomes.
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Objective:To delve deeply into the dynamic trajectories of cell subpopulations and the communication network among immune cell subgroups during the malignant progression of glioblastoma(GBM),and to endeavor to unearth key risk biomarkers in the GBM malignancy progression,so as to provide a more profound understanding for the treatment and prognosis of this disease by integrating tran-scriptomic data and clinical information of the GBM patients.Methods:Utilizing single-cell sequencing data analysis,we constructed a cell subgroup atlas during the malignant progression of GBM.The Mono-cle2 tool was employed to build dynamic progression trajectories of the tumor cell subgroups in GBM.Through gene enrichment analysis,we explored the biological processes enriched in genes that significant-ly changed with the malignancy progression of GBM tumor cell subpopulations.CellChat was used to identify the communication network between the different immune cell subgroups.Survival analysis helped in identifying risk molecular markers that impacted the patient prognosis during the malignant pro-gression of GBM.This methodological approach offered a comprehensive and detailed examination of the cellular and molecular dynamics within GBM,providing a robust framework for understanding the disease's progression and potential therapeutic targets.Results:The analysis of single-cell sequencing data identified 6 different cell types,including lymphocytes,pericytes,oligodendrocytes,macrophages,glioma cells,and microglia.The 27 151 cells in the single-cell dataset included 3 881 cells from the pa-tients with low-grade glioma(LGG),10 166 cells from the patients with newly diagnosed GBM,and 13 104 cells from the patients with recurrent glioma(rGBM).The pseudo-time analysis of the glioma cell subgroups indicated significant cellular heterogeneity during malignant progression.The cell interaction analysis of immune cell subgroups revealed the communication network among the different immune sub-groups in GBM malignancy,identifying 22 biologically significant ligand-receptor pairs across 12 key bio-logical pathways.Survival analysis had identified 8 genes related to the prognosis of the GBM patients,among which SERPINE1,COL6A1,SPP1,LTF,C1S,AEBP1,and SAA1L were high-risk genes in the GBM patients,and ABCC8 was low-risk genes in the GBM patients.These findings not only provided new theoretical bases for the treatment of GBM,but also offered fresh insights for the prognosis assessment and treatment decision-making for the GBM patients.Conclusion:This research comprehensively and pro-foundly reveals the dynamic changes in glioma cell subpopulations and the communication patterns among the immune cell subgroups during the malignant progression of GBM.These findings are of significant im-portance for understanding the complex biological processes of GBM,providing crucial new insights for precision medicine and treatment decisions in GBM.Through these studies,we hope to provide more ef-fective treatment options and more accurate prognostic assessments for the patients with GBM.
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Currently, single-cell multi-omics technologies including single-cell DNA sequencing (scDNA-seq) and single-cell RNA sequencing (scRNA-seq) have been used to reveal the heterogeneity of malignant tumor cells, elucidate their pathogenesis, drug resistance and recurrence mechanisms, which provide new strategies for the diagnosis and prognostic assessment of malignant tumors. This article reviews the application of single-cell sequencing technology in the diagnosis and prognostic assessment of acute leukemia based on the progress reported at the 65th American Society of Hematology Annual Meeting.
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Interactions between brain-resident and peripheral infiltrated immune cells are thought to contribute to neuroplasticity after cerebral ischemia. However, conventional bulk sequencing makes it challenging to depict this complex immune network. Using single-cell RNA sequencing, we mapped compositional and transcriptional features of peri-infarct immune cells. Microglia were the predominant cell type in the peri-infarct region, displaying a more diverse activation pattern than the typical pro- and anti-inflammatory state, with axon tract-associated microglia (ATMs) being associated with neuronal regeneration. Trajectory inference suggested that infiltrated monocyte-derived macrophages (MDMs) exhibited a gradual fate trajectory transition to activated MDMs. Inter-cellular crosstalk between MDMs and microglia orchestrated anti-inflammatory and repair-promoting microglia phenotypes and promoted post-stroke neurogenesis, with SOX2 and related Akt/CREB signaling as the underlying mechanisms. This description of the brain's immune landscape and its relationship with neurogenesis provides new insight into promoting neural repair by regulating neuroinflammatory responses.
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Humans , Ischemic Stroke , Brain/metabolism , Macrophages , Brain Ischemia/metabolism , Microglia/metabolism , Gene Expression Profiling , Anti-Inflammatory Agents , Neuronal Plasticity/physiology , Infarction/metabolismABSTRACT
Glioblastoma multiforme (GBM), a highly malignant and heterogeneous brain tumor, contains various types of tumor and non-tumor cells. Whether GBM cells can trans-differentiate into non-neural cell types, including mural cells or endothelial cells (ECs), to support tumor growth and invasion remains controversial. Here we generated two genetic GBM models de novo in immunocompetent mouse brains, mimicking essential pathological and molecular features of human GBMs. Lineage-tracing and transplantation studies demonstrated that, although blood vessels in GBM brains underwent drastic remodeling, evidence of trans-differentiation of GBM cells into vascular cells was barely detected. Intriguingly, GBM cells could promiscuously express markers for mural cells during gliomagenesis. Furthermore, single-cell RNA sequencing showed that patterns of copy number variations (CNVs) of mural cells and ECs were distinct from those of GBM cells, indicating discrete origins of GBM cells and vascular components. Importantly, single-cell CNV analysis of human GBM specimens also suggested that GBM cells and vascular cells are likely separate lineages. Rather than expansion owing to trans-differentiation, vascular cell expanded by proliferation during tumorigenesis. Therefore, cross-lineage trans-differentiation of GBM cells is very unlikely to occur during gliomagenesis. Our findings advance understanding of cell lineage dynamics during gliomagenesis, and have implications for targeted treatment of GBMs.
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Mice , Animals , Humans , Glioblastoma/pathology , Endothelial Cells/pathology , DNA Copy Number Variations , Brain/metabolism , Brain Neoplasms/pathologyABSTRACT
Objective To understand the current status of research on lung cancer immunotherapy to provide a reference for further investigation and future topic selection in this field. Methods CiteSpace visualization analysis software was used to analyze 400 Chinese studies in CNKI and 5 001 English studies in the Web of Science database from 2005 to 2021, with "lung cancer" and "immunotherapy" as keywords. Keyword co-occurrence analysis was performed on 17 English studies of "Lung Cancer" "Immunotherapy" and "Single cell sequencing" in the Web of Science database. Results "Non-small cell lung cancer" "immunosuppressants" "PD-L1" "dendritic cells" and "cytokine-induced killer cells" are current research hotspots in lung cancer immunotherapy. Monoclonal antibody drugs including nivolumab, pembrolizumab, atezolizumab, and durvalumab are hotspot drugs. Immunotherapy combined with chemotherapy as well as PD-L1 expression have become the focus of continuous research. The majority of studies on lung cancer immunotherapy are conducted in the United States, followed by China. Conclusion Lung cancer immunotherapy has gradually become a research hot spot in China. In the future, in-depth research is needed to provide cutting-edge directions for lung cancer immunotherapy.
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Single-cell sequencing (SCS) sequences the genetic information of a single cell to better understand the differences amongst cells and reveal the unique changes of each cell type. The specific analysis of cell subsets at the single-cell level can accurately evaluate tumor cells and microenvironment cells to reveal the complexity of molecular components and the difference from the corresponding components in non-malignant tissues. Lymphoma is highly heterogeneous, some have unknown pathological types, etiology and poor prognosis. SCS is helpful to clarify the molecular mechanisms of lymphomagenesis and pathological staging, and guide clinical practice. This article reviews SCS and its application in lymphoma.
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The liver is a highly proliferative organ. As the liver injured, the hepatocytes can quickly enter the cell cycle to restore the volume and function of liver. Liver regeneration involves complex processes that depend on the interaction of many different cell types. As limited by the average cell change level in tissues, traditional sequencing methods can only acquire the average genetic information reflecting dominant cell subpopulations, but ignore the secondary cell subpopu-lations, which leads to the loss of cellular heterogeneity information. Single-cell sequencing tech-nology can analyze the biological behavior of single cell, which helps to better understand the distri-bution, interaction and cell heterogeneity of different cells during liver regeneration. The authors review the application of single cell sequencing technology in liver regeneration.
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Objective:To investigate the appropriate pretreatment methods for single cell RNA sequencing of airway aspirate cells.Methods:Four fresh airway aspirate specimens were collected from four patients with acute respiratory tract infections. These specimens were digested with airway aspirate digester and prepared into single cell suspension. The cells were used for library construction directly (DE), or fixed with 10×Genomics Chromium Next GEM Single Cell Fixed RNA Sample Preparation Kit and then mixed to construct the library (DF), or cryopreserved, thawed, fixed (FF) before mixed to construct the library. All three methods were treated with oil emulsion using 10 4 cells and subjected to single-cell sequencing using the 10×Genomics platform. The number of obtained cells, data quality, annotated cell types and expression of marker genes were analyzed. Differences in the expression of highly variable genes (HVGs) of the same cell subsets obtained by the three pretreatment methods were compared using Pearson correlation. Expression of the differentially expressed genes in the same cell subpopulation obtained by different pretreatment methods was also compared. The correlation of the expression of differentially expressed genes between the same cell subsets obtained by the three pretreatment methods was analyzed by Pearson correlation. Results:The median numbers of single cells obtained using DE, FF and DF methods were 2 733, 1 140 and 5 897 ( P>0.05). The unique molecular identifiers were higher than 500. The median numbers of genes obtained using the three methods were 801, 887 and 1 259 ( P>0.05). The cells with novelty score over 0.8 accounted for 99%, 87% and 93%, respectively. There were nine cell subsets obtained by the three methods, including squamous cells, secretory cells, ciliated cells, T cells, B cells, macrophages, plasma cells and neutrophils. DF and FF methods could obtain more basal cells with specific high expression of keratin 5 than DE method. The differentially expressed and highly variable genes in the same cell subsets obtained by the three pretreatment methods showed high consistency in their expression with a significant correlation ( P<0.001). Conclusions:Under the same sequencing data volume, the quality of data obtained from fixed airway aspirate single-cell suspensions using the method of probe hybridization and transcriptome sequencing was comparable to that obtained directly from fresh cells. This method was more suitable for the pretreatment of clinical samples used for single-cell RNA sequencing.
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Objective The aim of this study was to draw single-cell transcriptome profiles of high-grade serous ovarian cancer(HGSOC),borderline ovarian cancer(OC),and normal ovaries in order to identify biomarkers that can diagnose and predict the prognosis of OC.Methods The differentially expressed genes between HGSOC,borderline OC,and normal ovarian tissues were ana-lyzed using single-cell data sequenced(SRA database:PRJNA756768).The cell subsets associated with tumor progression were screened by functional enrichment,cell communication between different subsets was analyzed by Cellchat,and cell differentiation traj-ectories were explored by pseudotime analysis to finally determine the subsets most relevant to tumor progression.Combined with OC transcriptome data of OC from the Cancer Genome Atlas(TCGA)with patient prognosis,biomarkers for diagnosing and predicting sur-vival of OC patients were ultimately screened.Results After using t-distribution stochastic neighbor embedding(t-SNE)for di-mensionality reduction,nine cell subpopulations were obtained:endothelial cells,myeloid cells,fibroblasts,T cells,stromal cells,B cells,and 3 epithelial cell subpopulations(C1,C4,and C7).Further analysis revealed that copy number variation(CNV)in the C4 group had the highest score in HGSOC,higher than those of borderline OC and normal ovaries,and was negatively correlated with prognosis.DMKN was a key marker gene in this group.Transcriptome analysis of OC in the TCGA database showed a close correlation between DMKN and poor prognosis(P=0.026),and the diagnostic efficacy of DMKN for OC was significant(A UC=0.906).Con-clusion This study is based on single-cell sequencing data to screen for DMKN,which can effectively diagnose and predict the prognosis of OC.This study provides new ideas for the diagnosis and prognosis prediction of OC.
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Tbx18,Wt1,and Tcf21 have been identified as epicardial markers during the early embryonic stage.However,the gene markers of mature epicardial cells remain unclear.Single-cell transcriptomic analysis was performed with the Seurat,Monocle,and CellphoneDB packages in R software with standard pro-cedures.Spatial transcriptomics was performed on chilled Visium Tissue Optimization Slides(10x Genomics)and Visium Spatial Gene Expression Slides(10x Genomics).Spatial transcriptomics analysis was performed with Space Ranger software and R software.Immunofluorescence,whole-mount RNA in situ hybridization and X-gal staining were performed to validate the analysis results.Spatial transcriptomics analysis revealed distinct transcriptional profiles and functions between epicardial tissue and non-epicardial tissue.Several gene markers specific to postnatal epicardial tissue were identified,including Msln,C3,Efemp1,and Upk3b.Single-cell transcriptomic analysis revealed that cardiac cells from wildtype mouse hearts(from embryonic day 9.5 to postnatal day 9)could be categorized into six major cell types,which included epicardial cells.Throughout epicardial development,Wt1,Tbx18,and Upk3b were consistently expressed,whereas genes including Msln,C3,and Efemp1 exhibited increased expression during the mature stages of development.Pseudotime analysis further revealed two epicardial cell fates during maturation.Moreover,Upk3b,Msln,Efemp1,and C3 positive epicardial cells were enriched in extracellular matrix signaling.Our results suggested Upk3b,Efemp1,Msln,C3,and other genes were mature epicardium markers.Extracellular matrix signaling was found to play a critical role in the mature epicardium,thus suggesting potential therapeutic targets for heart regeneration in future clinical practice.
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Single-cell sequencing is a new technology for high-throughput sequencing analysis of the genome, transcriptome, and epigenome at the single-cell level. Currently, single-cell sequencing technology has been widely used in bladder cancer research, opening up new ways to understand the biology of subtle bladder tumors by identifying different cell subpopulations, immune microenvironment, and single-cell technology is expected to make important changes in bladder diagnosis and treatment by identifying new biomarkers and using targeted therapies. This paper discussed the application of single-cell sequencing in bladder cancer research and clinical practice by summarizing recent advances in heterogeneous cell subpopulations, developmental patterns, and immune microenvironment and drug resistance in bladder cancer.
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Ulcerative colitis (UC) is a disease characterized by chronic inflammation of the intestinal mucosa. However, its exact pathogenesis is not fully understood. Zhi Ciweipi (ZCWP), as a traditional Chinese medicine (TCM), has demonstrated suitable anti-inflammatory effects in the treatment of patients with bloody stool and hemorrhoids. However, its therapeutic effects on ulcerative colitis have yet to be investigated in depth. The aim of this study was to investigate the protective effect of the aqueous extract of ZCWP against dextran sulfate sodium salt (DSS)-induced ulcerative colitis in mice and its possible mechanism of action. Successful simulation of ulcerative colitis was achieved by providing mice with drinking water containing 3% DSS. The HE staining results revealed that the aqueous extract of ZCWP could significantly reduce DSS-induced colonic injuries. Transcriptome sequencing analysis identified 10 key inflammation-related genes (IL⁃6, IL⁃1β, CSF2, TNF, IL10, IFN⁃γ, CXCL1, CXCL2, CXCL9, CXCL10), all of which were significantly downregulated (P<0. 05) in response to treatment with the aqueous extract of ZCWP according to qRT-PCR and Western blotting analyses. The immunofluorescence results further indicated that the aqueous extract of ZCWP was able to reduce the DSS-induced increase in the proportion of M1-type macrophages in the colon. Using single-cell sequencing, we thoroughly investigated the signaling relationships between different cell types, which revealed particularly strong communication between M1-type macrophages and fibroblasts. Subsequent qRT-PCR and Western blot analyses verified that the aqueous extract of ZCWP significantly downregulated the expression of DSS-induced fibrosis-related genes in colonic tissues (P<0. 05). In conclusion, the results of this study suggest that the aqueous extract of prepared ZCWP exerts a protective effect against DSS-induced ulcerative colitis by inhibiting M1-type macrophage polarization, downregulating the expression of inflammatory factors, and preventing strong communication between M1-type macrophages and fibroblasts. These findings not only reveal the therapeutic mechanism by which ZCWP aqueous extract treats colitis, but also provide a new theoretical basis for its application in clinical practice.
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Objective To explore the cell subsets and characteristics related to the prognosis of osteosarcoma by analyzing the cellular composition of tumor tissue samples from different osteosarcoma patients.Methods The single-cell sequencing data and bulk sequencing data of different osteosarcoma patients were downloaded.We extracted the information of cell samples for dimensionality reduction,annotation,and cell function analysis,so as to identify the cell subsets and clarify the cell characteristics related to the prognosis of osteosarcoma.The development trajectory of macrophages with prognostic significance was analyzed,and the prognostic model of osteosarcoma was established based on the differentially expressed genes of macrophage differentiation.Results The cellular composition presented heterogeneity in the patients with osteosarcoma.The infiltration of mononuclear phagocytes in osteosarcoma had prognostic significance(P=0.003).Four macrophage subsets were associated with prognosis,and their signature transcription factors included RUNX3(+),ETS1(+),HOXD11(+),ZNF281(+),and PRRX1(+).Prog_Macro2 and Prog_Macro4 were located at the end of the developmental trajectory,and the prognostic ability of macrophage subsets increased with the progression of osteosarcoma.The prognostic model established based on the differentially expressed genes involved in macrophage differentiation can distinguish the survival rate of osteosarcoma patients with different risks(P<0.001).Conclusion Macrophage subsets are closely related to the prognosis of osteosarcoma and can be used as the key target cells for the immunotherapy of osteosarcoma.
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Humans , Prognosis , Osteosarcoma/genetics , Immunotherapy , Macrophages , Transcription Factors , Bone Neoplasms/genetics , Homeodomain Proteins , Repressor ProteinsABSTRACT
Autism spectrum disorder (ASD) is a highly heritable neurodevelopmental disorder characterized by deficits in social interactions and repetitive behaviors. Although hundreds of ASD risk genes, implicated in synaptic formation and transcriptional regulation, have been identified through human genetic studies, the East Asian ASD cohorts are still under-represented in genome-wide genetic studies. Here, we applied whole-exome sequencing to 369 ASD trios including probands and unaffected parents of Chinese origin. Using a joint-calling analytical pipeline based on GATK toolkits, we identified numerous de novo mutations including 55 high-impact variants and 165 moderate-impact variants, as well as de novo copy number variations containing known ASD-related genes. Importantly, combined with single-cell sequencing data from the developing human brain, we found that the expression of genes with de novo mutations was specifically enriched in the pre-, post-central gyrus (PRC, PC) and banks of the superior temporal (BST) regions in the human brain. By further analyzing the brain imaging data with ASD and healthy controls, we found that the gray volume of the right BST in ASD patients was significantly decreased compared to healthy controls, suggesting the potential structural deficits associated with ASD. Finally, we found a decrease in the seed-based functional connectivity between BST/PC/PRC and sensory areas, the insula, as well as the frontal lobes in ASD patients. This work indicated that combinatorial analysis with genome-wide screening, single-cell sequencing, and brain imaging data reveal the brain regions contributing to the etiology of ASD.
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Humans , Autism Spectrum Disorder/metabolism , Autistic Disorder , Exome Sequencing , DNA Copy Number Variations , East Asian People , Brain/metabolism , Mutation/genetics , Genetic Predisposition to Disease/geneticsABSTRACT
Efforts have been made to establish various human pluripotent stem cell lines. However, such methods have not yet been duplicated in non-human primate cells. Here, we introduce a multiplexed single-cell sequencing technique to profile the molecular features of monkey pluripotent stem cells in published culture conditions. The results demonstrate suboptimized maintenance of pluripotency and show that the selected signaling pathways for resetting human stem cells can also be interpreted for establishing monkey cell lines. Overall, this work legitimates the translation of novel human cell line culture conditions to monkey cells and provides guidance for exploring chemical cocktails for monkey stem cell line derivation.
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Animals , Haplorhini , Single-Cell Gene Expression Analysis , Pluripotent Stem Cells/metabolism , Cell Line , Signal Transduction , Cell Differentiation , TranscriptomeABSTRACT
Globally, lung cancer is the leading cause of cancer death. Although survival rates for lung cancer patients have improved over the past few decades, the survival rates have not yet reached the levels of other common malignancies. In recent years, immune checkpoint inhibitors (ICIs) have shown great promise in clinical trials and have been rapidly incorporated into the standard of care for patients with advanced non-small cell lung cancer (NSCLC). However, many patients do not benefit from treatment. Our findings suggest that the heterogeneity of the tumor microenvironment (TME) is closely related to the efficacy of ICIs. Single-cell sequencing is a technology that can specifically analyze cell populations at the genome and transcriptome levels at the single-cell level. This article reviews the potential value of single-cell sequencing technology in predicting immune responses to lung cancer.
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The technique of prenatal diagnosis before embryo implantation has been greatly developed in assisted reproduction, especially for the people with abnormal genetic material to provide the technical possibility of eugenics and eugenics. As an emerging sequencing technology, single-cell sequencing can analyze the genome and transcriptome of cells from the level of a single cell, and reflect the heterogeneity between cells, thus helping to reveal the mechanism of the occurrence and development of diseases. Through prenatal diagnosis before embryo implantation and high-throughput sequencing of single cells obtained from embryo biopsy, euploidy of embryonic chromosomes can be effectively detected, and SNPs and chromosomal copy number variation, insertion, deletion and other variations can also be better detected. It can conduct the comprehensive detection and research of genomic polymorphism and mutation of individual and other species. In this paper, the single-cell sequencing technology and relevant methods was introduced, and the application scenarios of single-cell sequencing in genetic reproduction diagnosis were summarized. The applications of the technology in the field of genetic reproduction were described, and the future directions of the technology were discussed.
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Objective:To identify key genes and their potential biological mechanisms in the progression of non-alcoholic fatty liver disease (NAFLD) using bioinformatics technology.Methods:Genes differentially expressed in simple non-alcoholic fatty liver disease (NAFL) and non-alcoholic steatohepatitis (NASH) were analyzed by integrating NAFLD-related sequencing datasets GSE135251 and GSE167523 from the Gene Expression Omnibus (GEO) datebase. Gene Ontology (GO) functional enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Reactome signaling pathway analysis were performed. Key genes were identified by STRING database and Cytoscape3.7.2 software, and the expression of key genes under different fibrosis grades and activity scores was observed. In addition, the expression of key genes in different cell clusters was observed based on the single-cell RNA-seq dataset of NAFLD mice.Results:Bioinformatics methods were used to obtain 97 common differential genes in NAFLD from two datasets. GO functional enrichment analysis was mainly performed in Extracellular Matrix (ECM) tissues. The main signaling pathway is ECM-receptor interaction. Five key genes were identified based on PPI network and Cytoscape software: COL1A1, THBS2, CXCL8, THY1 and LOXL1. The expression of key genes was significantly positively correlated with fibrosis grade and activity score, indicating that they were closely related to the progression of NAFLD. These key genes are highly expressed in hepatic stellate cells (HSCs) and natural killer/T cells (NK/T cells).Conclusion:In this study, bioinformatics technology was used to identify five key genes that may be involved in the NAFL-NASH transformation, suggesting that the ECM-receptor interaction signaling pathway may be a key molecular mechanism of NAFLD disease progression.
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Aging-induced changes in the immune system are associated with a higher incidence of infection and vaccination failure. Lymph nodes, which filter the lymph to identify and fight infections, play a central role in this process. However, careful characterization of the impact of aging on lymph nodes and associated autoimmune diseases is lacking. We combined single-cell RNA sequencing (scRNA-seq) with flow cytometry to delineate the immune cell atlas of cervical draining lymph nodes (CDLNs) of both young and old mice with or without experimental autoimmune uveitis (EAU). We found extensive and complicated changes in the cellular constituents of CDLNs during aging. When confronted with autoimmune challenges, old mice developed milder EAU compared to young mice. Within this EAU process, we highlighted that the pathogenicity of T helper 17 cells (Th17) was dampened, as shown by reduced GM-CSF secretion in old mice. The mitigated secretion of GM-CSF contributed to alleviation of IL-23 secretion by antigen-presenting cells (APCs) and may, in turn, weaken APCs' effects on facilitating the pathogenicity of Th17 cells. Meanwhile, our study further unveiled that aging downregulated GM-CSF secretion through reducing both the transcript and protein levels of IL-23R in Th17 cells from CDLNs. Overall, aging altered immune cell responses, especially through toning down Th17 cells, counteracting EAU challenge in old mice.