Identification of Potential ceRNA Network and Patterns of Immune Cell Infiltration in Systemic Sclerosis-Associated Interstitial Lung Disease

Oleanolic acid attenuates hydrogen peroxide-induced apoptosis of IPEC-J2 cells through suppressing c-Jun and MAPK pathway

Oleanolic acid (OA) is a natural triterpenoid with therapeutic potential for a multitude of diseases. However, the precise mechanism by which OA influences stress-induced apoptosis of intestinal epithelial cells remains elusive. Therefore, the effect of OA on intestinal diseases under stressful conditions and its possible mechanisms have been investigated. In a hydrogen peroxide (H2 O2 )-induced oxidative stress model, OA attenuated H2 O2 -induced apoptosis in a concentration-dependent manner. To investigate the underlying mechanisms, the gene expression profile of OA on IPEC-J2 cells was analyzed using an RNA sequencing system. Results from gene ontology and Kyoto encyclopedia of genes and genomes analysis confirmed that OA may mitigate the cytotoxic effects of H2 O2 by downregulating gene expression through the MAPK signaling pathway. Furthermore, Quantitative real-time polymerase chain reaction results validated the differentially expressed genes data. Western blot analysis further demonstrated that OA effectively suppressed the expression level of c-Jun protein induced by H2 O2 in IPEC-J2 cells. Collectively, our results indicate that OA pretreatment significantly attenuated H2 O2 -induced apoptosis in intestinal epithelial cells through suppressing c-Jun and MAPK pathway.

Identification and Validation of Genes Exhibiting Dynamic Alterations in Response to Bleomycin-Induced Pulmonary Fibrosis

Idiopathic pulmonary fibrosis (IPF) carries a high mortality rate and has a poor prognosis. The pathogenesis of pulmonary fibrosis (PF) is highly related to dysregulation of multiple RNAs. This study aims to identify and validate dysregulated RNAs that exhibited dynamic alterations in response to bleomycin (BLM)-induced PF. The results will provide therapeutic targets for patients suffering from IPF. Whole transcriptomic profiles of BLM-induced PF were obtained through high-throughput RNA sequencing. miRNA profiling was downloaded from GSE45789 database in the Gene Expression Omnibus (GEO). We identified the differentially expressed RNAs (DERNAs) that exhibited dynamic alterations in response to BLM-induced PF. Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) pathway enrichment analysis were conducted to discovery regulatory processes of PF. Weighted gene co-expression network analysis (WGCNA), protein-protein interaction (PPI) analysis, and co-expression analysis were performed to identify key genes and pathogenic pattern during the progression of PF. MiRanda, miRcode, and TargetScan were utilized to predict target relationships in the potential competing endogenous RNA (ceRNA) network. The results were verified by qRT-PCR analysis. In the context of BLM-induced PF, this study identified a total of 167 differentially expressed messenger RNAs (DEmRNAs), 115 differentially expressed long non-coding RNAs (DElncRNAs), 45 differentially expressed circular RNAs (DEcircRNAs), and 87 differentially expressed microRNAs (DEmiRNAs). These RNA molecules showed dynamic alterations in response to BLM-induced PF. These DEmRNAs exhibited a predominant association with the biological processes pertaining to the organization of extracellular matrix. A regulatory network was built in PF, encompassing 31 DEmRNAs, 18 DE lncRNAs, 13 DEcircRNAs, and 13 DEmiRNAs. Several DERNA molecules were subjected to validate using additional BLM-induced PF model. The outcomes of this validation process shown a strong correlation with the results obtained from RNA sequencing analysis. The GSE213001 dataset was utilized to validate the expression levels and diagnostic efficacy of four specific hub mRNAs (CCDC80, CLU, COL5A1, and COL6A3) in individuals diagnosed with PF. In this study, we identified and validated several RNA molecules that exhibited dynamic alternations in response to BLM-induced PF. These dysregulated RNAs participated in the pathogenesis of PF and can be used as therapeutic targets for early-stage IPF. Although more work must be done to confirm the results, our study may provide directions for future studies.

Identification of lncRNA-miRNA-mRNA networks in circulating exosomes as potential biomarkers for systemic sclerosis

Objective

This study aimed to analyze potential biomarkers for systemic sclerosis (SSc) by constructing lncRNA-miRNA-mRNA networks in circulating exosomes (cirexos).

Materials and methods

Differentially expressed mRNAs (DEmRNAs) and lncRNAs (DElncRNAs) in SSc cirexos were screened using high-throughput sequencing and detected with real-time quantitative PCR (RT-qPCR). Differentially expressed genes (DEGs) were analyzed using the DisGeNET, GeneCards, GSEA4.2.3, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Receiver operating characteristic (ROC) curves, correlation analyses, and a double-luciferase reporter gene detection assay were used to analyze competing endogenous RNA (ceRNA) networks and clinical data.

Results

In this study, 286 DEmRNAs and 192 DElncRNAs were screened, of which 18 DEGs were the same as the SSc-related genes. The main SSc-related pathways included extracellular matrix (ECM) receptor interaction, local adhesion, platelet activation, and IgA production by the intestinal immune network. A hub gene, COL1A1, was obtained by a protein-protein interaction (PPI) network. Four ceRNA networks were predicted through Cytoscape. The relative expression levels of COL1A1, ENST0000313807, and NON-HSAT194388.1 were significantly higher in SSc, while the relative expression levels of hsa-miR-29a-3p, hsa-miR-29b-3p, and hsa-miR-29c-3p were significantly lower in SSc (P < 0.05). The ROC curve showed that the ENST00000313807-hsa-miR-29a-3p-COL1A1 network as a combined biomarker of SSc is more valuable than independent diagnosis, and that it is correlated with high-resolution CT (HRCT), Scl-70, C-reactive protein (CRP), Ro-52, IL-10, IgM, lymphocyte percentage, neutrophil percentage, albumin divided by globulin, urea, and RDW-SD (P < 0.05). Double-luciferase reporter gene detection showed that ENST00000313807 interacts with hsa-miR-29a-3p, which interacts with COL1A1.

Conclusion

The ENST00000313807-hsa-miR-29a-3p-COL1A1 network in plasma cirexos represents a potential combined biomarker for the clinical diagnosis and treatment of SSc.

Identification and Validation of CDKN1A and HDAC1 as Senescence-Related Hub Genes in Chronic Obstructive Pulmonary Disease

Purpose

Cellular senescence participates in the occurrence and development of chronic obstructive pulmonary disease (COPD). This study aimed to identify senescence-related hub genes and explore effective diagnostic markers and therapeutic targets for COPD.

Methods

The microarray data from the GSE38974 dataset was downloaded from the Gene Expression Omnibus (GEO) database. The overlapping genes between genes from the GSE38974 dataset and CellAge database were considered differentially expressed senescence-related genes (DESRGs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using R software. Protein-protein interaction (PPI), miRNA-mRNA network, and competitive endogenous RNA (ceRNA) network were constructed and visualized by Cytoscape software. GSE100281 and GSE103174 datasets were employed to validate the expression and diagnostic value of hub genes. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was used to measure the mRNA levels of hub genes in peripheral blood mononuclear cells (PBMCs) from COPD and control samples.

Results

A total of 23 DESRGs were identified between COPD samples and healthy controls. Enrichment analysis revealed that DESRGs were mainly related to apoptosis and senescence. Moreover, four hub genes and two key clusters were acquired by Cytohubba and MCODE plugin, respectively. CDKN1A and HDAC1 were verified as final hub genes based on GSE100281 and GSE103174 datasets validation. The mRNA expression level of CDKN1A was negatively related to forced expiratory volume in 1 second/forced vital capacity (FEV1/FVC), and HDAC1 expression had the opposite correlation. Finally, an HDAC1-based ceRNA network, including 6 miRNAs and 11 lncRNAs, was constructed.

Conclusion

We identified two senescence-related hub genes, CDKN1A and HDAC1, which may be effective biomarkers for COPD diagnosis and treatment. An HDAC1-related ceRNA network was constructed to clarify the role of senescence in COPD pathogenesis.

Construction, bioinformatics analysis, and validation of competitive endogenous RNA networks in ulcerative colitis

Background: Ulcerative colitis (UC) is a common chronic disease of the digestive system. Recently, competitive endogenous RNAs (ceRNAs) have been increasingly used to reveal key mechanisms for the pathogenesis and treatment of UC. However, the role of ceRNA in UC pathogenesis has not been fully clarified. This study aimed to explore the mechanism of the lncRNA-miRNA-mRNA ceRNA network in UC and identify potential biomarkers and therapeutic targets.

Materials and Methods: An integrative analysis of mRNA, microRNA (miRNA), and long non-coding RNA (lncRNA) files downloaded from the Gene Expression Omnibus (GEO) was performed. Differentially expressed mRNA (DE-mRNAs), miRNA (DE-miRNAs), and lncRNA (DE-lncRNAs) were investigated between the normal and UC groups by the limma package. A weighted correlation network analysis (WGCNA) was used to identify the relative model for constructing the ceRNA network, and, concurrently, miRWalk and DIANA-LncBase databases were used for target prediction. Consecutively, the Gene Ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG) pathway, and Reactome pathway enrichment analyses, protein-protein interaction (PPI) network, Cytohubba, and ClueGO were performed to identify hub genes. Additionally, we examined the immune infiltration characteristics of UC and the correlation between hub genes and immune cells using the immuCellAI database. Finally, the expression of potential biomarkers of ceRNA was validated via qRT-PCR in an experimental UC model induced by dextran sulfate sodium (DSS).

Result: The ceRNA network was constructed by combining four mRNAs, two miRNAs, and two lncRNAs, and the receiver operating characteristic (ROC) analysis showed that two mRNAs (CTLA4 and STAT1) had high diagnostic accuracy (area under the curve [AUC] > 0.9). Furthermore, CTLA4 up-regulation was positively correlated with the infiltration of immune cells. Finally, as a result of this DSS-induced experimental UC model, CTLA4, MIAT, and several associate genes expression were consistent with the results of previous bioinformatics analysis, which proved our hypothesis.

Conclusion: The investigation of the ceRNA network in this study could provide insight into UC pathogenesis. CTLA4, which has immune-related properties, can be a potential biomarker in UC, and MIAT/miR-422a/CTLA4 ceRNA networks may play important roles in UC.

Novel Concepts in Systemic Sclerosis Pathogenesis: Role for miRNAs

Systemic sclerosis (SSc) is a rare connective tissue disease with heterogeneous clinical phenotypes. It is characterized by the pathogenic triad: microangiopathy, immune dysfunction, and fibrosis. Epigenetic mechanisms modulate gene expression without interfering with the DNA sequence. Epigenetic marks may be reversible and their differential response to external stimuli could explain the protean clinical manifestations of SSc while offering the opportunity of targeted drug development. Small, non-coding RNA sequences (miRNAs) have demonstrated complex interactions between vasculature, immune activation, and extracellular matrices. Distinct miRNA profiles were identified in SSc skin specimens and blood samples containing a wide variety of dysregulated miRNAs. Their target genes are mainly involved in profibrotic pathways, but new lines of evidence also confirm their participation in impaired angiogenesis and aberrant immune responses. Research approaches focusing on earlier stages of the disease and on differential miRNA expression in various tissues could bring novel insights into SSc pathogenesis and validate the clinical utility of miRNAs as biomarkers and therapeutic targets.