Dataset Information

Single-cell and bulk tissue sequencing unravels the heterogeneity of synovial microenvironment in arthrofibrosis.

ABSTRACT: Arthrofibrosis (AF) is a debilitating complication that occurs after trauma or surgery, leading to functional impairment and surgical failures worldwide. This study aimed to uncover the underlying mechanism of AF. A total of 141 patients were enrolled, and synovial samples were collected from both patients and animal models at different time points. Single-cell RNA-sequencing (scRNA-seq) and bulk tissue RNA sequencing (bulk-seq) were employed to profile the distinct synovial microenvironment. This study revealed changes in cell proportions during AF pathogenesis and identified Engrailed-1 (EN1) as a key transcription factor strongly associated with disease severity and clinical prognosis. Additionally, the researchers discovered a specific type of synovial fibroblast called DKK3-SLF, which played a critical role in driving AF development. These findings shed light on the composition and heterogeneity of the synovial microenvironment in AF, offering potential avenues for identifying therapeutic targets and developing clinical treatments for AF and other fibrotic diseases.

SUBMITTER: Chen X

PROVIDER: S-EPMC10495645 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature

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Single-cell and bulk tissue sequencing unravels the heterogeneity of synovial microenvironment in arthrofibrosis.

Chen Xi X Gong Lihua L Li Cheng C Wang Siyuan S Wang Ziyuan Z Chu Ming M Zhou Yixin Y

iScience 20230713 9

Arthrofibrosis (AF) is a debilitating complication that occurs after trauma or surgery, leading to functional impairment and surgical failures worldwide. This study aimed to uncover the underlying mechanism of AF. A total of 141 patients were enrolled, and synovial samples were collected from both patients and animal models at different time points. Single-cell RNA-sequencing (scRNA-seq) and bulk tissue RNA sequencing (bulk-seq) were employed to profile the distinct synovial microenvironment. Th ...[more]

PMID: 37705954

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Project description:BackgroundHepatocellular carcinoma (HCC) is the main histological subtype of liver cancer, which has the characteristics of poor prognosis and high fatality rate. Single-cell sequencing can provide quantitative and unbiased characterization of cell heterogeneity by analyzing the molecular profile of the whole genome of thousands of single cells. Thus, the purpose of this study was to identify novel prognostic markers for HCC based on single-cell sequencing data.MethodsSingle-cell sequencing of 21 HCC samples and 256 normal liver tissue samples in the GSE124395 dataset was collected from the Gene Expression Omnibus (GEO) database. The quality-controlled cells were grouped by unsupervised cluster analysis and identified the marker genes of each cell cluster. Hereafter, these cell clusters were annotated by singleR and CellMarker according to the expression patterns of the marker genes. Pseudotime analysis was performed to construct the trajectory of cell evolution and to define hub genes in the evolution process. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were used to explore the potential regulatory mechanism of hub genes in HCC. Next, the differential expression of hub genes and the correlation of the expression of these genes with patients' survival and diagnosis were investigated in The Cancer Genome Atlas (TCGA) database.ResultsA total of 9 clusters corresponding to 9 cell types, including NKT cells, hepatocytes, endothelial cells, Kupffer cells, EPCAM+ cells, cancer cells, plasma cells (B cells), immature B cells, and myofibroblasts were identified. We screened 63 key genes related to cell differentiation through trajectory analysis, which were enriched in the process of coagulation. Ultimately, we identified 10 survival-related hub genes in the TCGA database, namely ALDOB, APOC3, APOH, CYP2E1, CYP3A4, GC, HRG, LINC01554, PDK4, and TXN.ConclusionIn conclusion, ALDOB, APOC3, APOH, CYP2E1, CYP3A4, GC, HRG, LINC01554, PDK4, and TXN may serve as hub genes in the diagnosis and prognosis for HCC.

Dataset Information

Single-cell and bulk tissue sequencing unravels the heterogeneity of synovial microenvironment in arthrofibrosis.

Publications

Single-cell and bulk tissue sequencing unravels the heterogeneity of synovial microenvironment in arthrofibrosis.

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