Identification and validation of hub genes of synovial tissue for patients with osteoarthritis and rheumatoid arthritis

Ge, Yanzhi; Chen, Zuxiang; Fu, Yanbin; Xiao, Xue; Xu, Haipeng; Tong, Peijian; Zhou, Li

doi:10.1186/s41065-021-00201-0

Cited by 17 publications

(13 citation statements)

References 48 publications

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“…KEGG analysis of the target genes showed that endocytosis, salmonella infection, phagosome and ubiquitin-mediated proteolysis are involved in TMJOA. Previous studies have suggested that the biological process of ubiquitination leads to OA by regulating the expression of inflammatory cytokines ( Radwan et al, 2015 ; Ge et al, 2021 ). Zucker-Franklin (1966) showed that phagosomes participate in the regulation of synovial fluid leukocytes during RA development.…”

Section: Discussionmentioning

confidence: 99%

Whole-transcriptome sequencing and ceRNA interaction network of temporomandibular joint osteoarthritis

An²,

Zhou³

et al. 2022

Front. Genet.

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Purpose: The aim of this study was to conduct a comprehensive transcriptomic analysis to explore the potential biological functions of noncoding RNA (ncRNAs) in temporomandibular joint osteoarthritis (TMJOA).Methods: Whole transcriptome sequencing was performed to identify differentially expressed genes (DEGs) profiles between the TMJOA and normal groups. The functions and pathways of the DEGs were analyzed using Metascape, and a competitive endogenous RNA (ceRNA) network was constructed using Cytoscape software.Results: A total of 137 DEmRNAs, 65 DEmiRNAs, 132 DElncRNAs, and 29 DEcircRNAs were identified between the TMJOA and normal groups. Functional annotation of the DEmRNAs revealed that immune response and apoptosis are closely related to TMJOA and also suggested key signaling pathways related to TMJOA, including chronic depression and PPAR signaling pathways. We identified vital mRNAs, including Klrk1, Adipoq, Cryab, and Hspa1b. Notably, Adipoq expression in cartilage was significantly upregulated in TMJOA compared with normal groups (10-fold, p < 0.001). According to the functional analysis of DEmRNAs regulated by the ceRNA network, we found that ncRNAs are involved in the regulation of autophagy and apoptosis. In addition, significantly DEncRNAs (lncRNA-COX7A1, lncRNA-CHTOP, lncRNA-UFM1, ciRNA166 and circRNA1531) were verified, and among these, circRNA1531 (14.5-fold, p < 0.001) and lncRNA-CHTOP (14.8-fold, p < 0.001) were the most significantly downregulated ncRNAs.Conclusion: This study showed the potential of lncRNAs, circRNAs, miRNAs, and mRNAs may as clinical biomarkers and provides transcriptomic insights into their functional roles in TMJOA. This study identified the transcriptomic signatures of mRNAs associated with immunity and apoptosis and the signatures of ncRNAs associated with autophagy and apoptosis and provides insight into ncRNAs in TMJOA.

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Section: Discussionmentioning

confidence: 99%

Whole-transcriptome sequencing and ceRNA interaction network of temporomandibular joint osteoarthritis

An²,

Zhou³

et al. 2022

Front. Genet.

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“…CIBERSORT is a deconvolution algorithm that utilizes linear support vector regression to evaluate the expression matrices of immunocellular subtypes, and now is increasingly being used for immune infiltration characterization analysis in non-tumor tissues ( Ge et al, 2021 ). Infiltration analysis of immune cells in HCC patients using RNA-Seq data can be an important guide in disease research and treatment prognosis prediction, etc.…”

Section: Methodsmentioning

confidence: 99%

Diagnostic and prognostic value of m5C regulatory genes in hepatocellular carcinoma

Yang

Lan

et al. 2022

Front. Genet.

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Background: A high mortality rate makes hepatocellular carcinoma (HCC) one of the most common types of cancer globally. 5-methylcytosine (m5C) is an epigenetic modification that contributes to the prognosis of several cancers, but its relevance to HCC remains unknown. We sought to determine if the m5C-related regulators had any diagnostic or prognostic value in HCC.Methods: M5C regulatory genes were screened and compared between HCC and normal tissue from The Cancer Genome Atlas (TCGA)and Gene Expression Omnibus (GEO) databases. Least absolute shrinkage and selection operator method (LASSO) and univariate Cox regression analysis of differentially expressed genes were then performed to identify diagnostic markers. A LASSO prognostic model was constructed using M5C regulatory genes with prognostic values screened by TCGA expression data. HCC patients were stratified based on risk score, then clinical characteristics analysis and immune correlation analysis were performed for each subgroup, and the molecular functions of different subgroups were analyzed using both Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA). The prognostic model was evaluated using univariate and multivariate Cox analyses as well as a nomogram. Molecular typing was performed according to m5C regulatory genes and immune checkpoint genes expression respectively, and clinical characterization and immune correlation analysis were performed for each subgroup.Results: M5C regulatory genes are expressed differently in HCC patients with different clinical and pathological characteristics, and mutations in these genes are frequent. Based on five m5C regulators (NOP2, NSUN2, TET1, YBX1, and DNMT3B), we constructed a prognostic model with high predictive ability. The risk score was found to be an independent prognostic indicator. Additionally, risk scores can also be applied in subgroups with different clinical characteristics as prognostic indicators.Conclusion: The study combined data from TCGA and GEO for the first time to reveal the genetic and prognostic significance of m5C-related regulators in HCC, which provides new directions for identifying predictive biomarkers and developing molecularly targeted therapies for HCC.

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“…CIBERSORT is a deconvolution technique based on the premise of linear support vector regression for immune cell subtype expression matrices, CIBERSORT was initially used for the analysis of tumor microenvironment (TME) and is now being increasingly applied in the characteristic analysis of immune infiltration in non-tumor tissues ( Ge et al, 2021 ). The synovial tissue of rheumatoid arthritis is composed of various immune and inflammatory cells, interstitial tissue, cytokines, and chemokines, which is an integrated loading system.…”

Section: Materals and Methodsmentioning

confidence: 99%

CLP1 is a Prognosis-Related Biomarker and Correlates With Immune Infiltrates in Rheumatoid Arthritis

Zhao

Tang

et al. 2022

Front. Pharmacol.

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Rheumatoid arthritis (RA) is a chronic, heterogeneous autoimmune disease with a high disability rate that seriously affects society and individuals. However, there is a lack of effective and reliable diagnostic markers and therapeutic targets. In this study, we identified diagnostic markers of RA based on RNA modification and explored its role as well as degree of immune cell infiltration. We used the gene expression profile data of three synovial tissues (GSE55235, GSE55457, GSE77298) from the Gene Expression Omnibus (GEO) database and the gene of 5 RNA modification genes (including m6A, m1A, m5C, APA, A-1), combined with cluster analysis, identified four RNA modifiers closely related to RA (YTHDC1, LRPPRC, NOP2, and CLP1) and five immune cells namely T cell CD8, CD4 memory resting, T cells regulatory (Tregs) Macrophages M0, and Neutrophils. Based on the LASSO regression algorithm, hub genes and immune cell prediction models were established respectively in RA and a nomogram based on the immune cell model was built. Around 4 key RNA modification regulator genes, miRNA-mRNA, mRNA-TF networks have been established, and GSEA-GO, KEGG-GSEA enrichment analysis has been carried out. Finally, CLP1 was established as an effective RA diagnostic marker, and was highly positively correlated with T cells follicular helper (Tfh) infiltration. On the other hand, highly negatively correlated with the expression of mast cells. In short, CLP1 may play a non-negligible role in the onset and development of RA by altering immune cell infiltration, and it is predicted to represent a novel target for RA clinical diagnosis and therapy.

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Identification and validation of hub genes of synovial tissue for patients with osteoarthritis and rheumatoid arthritis

Cited by 17 publications

References 48 publications

Whole-transcriptome sequencing and ceRNA interaction network of temporomandibular joint osteoarthritis

Whole-transcriptome sequencing and ceRNA interaction network of temporomandibular joint osteoarthritis

Diagnostic and prognostic value of m5C regulatory genes in hepatocellular carcinoma

CLP1 is a Prognosis-Related Biomarker and Correlates With Immune Infiltrates in Rheumatoid Arthritis

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