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Effect of astragalosides on long non-coding RNA expression profiles in rats with adjuvant-induced arthritis.

ABSTRACT: Rheumatoid arthritis (RA) is an autoimmune disease of unknown etiology, which occurs in ~1.0% of the general population. Increasing studies have suggested that long non?coding RNAs (lncRNAs) may serve important roles in various biological processes and may be associated with the pathogenesis of different types of disease, including RA. Astragalosides (AST) has been used as a traditional Chinese medicine for the treatment of RA. However, the mechanism underlying its therapeutic effect has remained unclear to date. Thus, there is an urgent need to elucidate the possible mechanism of AST in the treatment of RA from the perspective of lncRNAs. In the present study, the lncRNAs and mRNAs of a vehicle group, animal model group and AST treatment (control) group were determined by Arraystar Rat lncRNA/mRNA microarray. The differentially expressed genes with a fold change >1.5 and P<0.05 were selected and analyzed. Gene Ontology (GO) and pathway analysis was performed using the Database for Annotation, Visualization and Integration Discovery, and the coding?non?coding gene co?expression network was drawn based on the correlation analysis between the differentially expressed lncRNAs and mRNAs. Based on node degree and the correlation between bioinformatics analysis and RA, the critical differentially expressed lncRNAs were selected, analyzed and verified by reverse transcription?quantitative PCR (RT?qPCR) analysis. The results showed that, following AST treatment, up to 75 lncRNAs and 247 mRNAs were found to be differentially expressed among the three groups. GO and pathway analysis manifested that 135 GO terms and 17 pathways were enriched by differentially expressed genes. Four lncRNAs (MRAK012530, MRAK132628, MRAK003448 and XR_006457) were selected as the critical lncRNAs and their trend in expression showed consistency between the RT?qPCR and microarray data. In conclusion, AST had a regulatory effect on differentially expressed lncRNAs during the development of RA, and four lncRNAs could be selected as critical therapeutic targets of AST.

SUBMITTER: Jiang H

PROVIDER: S-EPMC6713426 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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Effect of astragalosides on long non-coding RNA expression profiles in rats with adjuvant-induced arthritis.

Jiang Hui H Wu Fu-Rong FR Liu Jian J Qin Xiu-Juan XJ Jiang Nan-Nan NN Li Wei-Ping WP

International journal of molecular medicine 20190722 4

Rheumatoid arthritis (RA) is an autoimmune disease of unknown etiology, which occurs in ~1.0% of the general population. Increasing studies have suggested that long non‑coding RNAs (lncRNAs) may serve important roles in various biological processes and may be associated with the pathogenesis of different types of disease, including RA. Astragalosides (AST) has been used as a traditional Chinese medicine for the treatment of RA. However, the mechanism underlying its therapeutic effect has remaine ...[more]

PMID: 31364738

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Project description:BackgroundLong non-coding RNAs (lncRNAs) have been implicated in diagnosis and prognosis in various cancers. However, few lncRNA signatures have been established for prediction of gastrointestinal stromal tumors (GIST). We aimed to explore a lncRNA signature profile that associated with clinical relevance by mining data from Gene Expression Ominus (GEO) and Surveillance, Epidemiology, and End Results (SEER) Program.MethodsUsing a lncRNA-mining approach, we performed non-negative matrix factorization (NMF) consensus algorithm in Gastrointestinal stromal tumors (GISTs) cohorts (61 patients from GSE8167 and GSE17743) to cluster LncRNA expression profiles. Comparative markers selection, and Gene Set Enrichment Analysis (GSEA) algorithm were performed between distinct molecular subtypes of GIST. The survival rate of GIST patients from SEER stratified by gender were compared by Kaplan-Meier method and log-rank analysis. lncRNA-mRNA co-expression analysis was performed by Pearson correlation coefficients (PCC) using R package LINC. Somatic copy number alterations of GIST patients (GSE40966) were analyzed via web server GenePattern GISTIC2 algorithm.ResultsA total of four lncRNA molecular subtypes of GIST were identified with distinct biological pathways and clinical characteristics. LncRNA expression profiles well clustered the GIST samples into small size (<5 mm) and large size tumors (>5 mm), which is a fundamental index for GIST malignancy diagnosis. Several lncRNAs with abundant expression (LRRC75A-AS1, HYMAI, NEAT1, XIST and FTX) were closely associated with tumor size, which may suggest to be biomarkers for the GIST malignancy. Particularly, LRRC75A-AS1 was positively associated with tumor diameters and suggested an oncogene in GIST. Co-expression analysis suggested that chromosome region 17p11.2-p12 may contribute to the oncogenic process in malignant GIST. Interestingly, the gender had a strong influence on clustering by lncRNA expression profile. Data from the Surveillance, Epidemiology, and End Results (SEER) Program were further explored and 7983 patients who were diagnosed with GISTs from 1973 to 2014 were enrolled for analysis. The results also showed the favorable prognosis for female patients. The survival rate between male and female with GIST was statistically significant (P < 0.0001). Gene set enrichment analysis (GSEA) indicated distinct pathways between female and male, and malignant GIST was associated with several cancer metabolism and cell cycle associated pathways.ConclusionsThis lncRNAs-based classification for GISTs may provide a molecular classification applicable to individual GIST that has implications to influence lncRNA markers selection and prediction of tumor progression.

Dataset Information

Effect of astragalosides on long non-coding RNA expression profiles in rats with adjuvant-induced arthritis.

Publications

Effect of astragalosides on long non-coding RNA expression profiles in rats with adjuvant-induced arthritis.

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