Comprehensive Bioinformatics Analysis of Lipopolysaccharide-Induced Altered Autophagy in Acute Lung Injury and Construction of Underlying Competing Endogenous RNA Regulatory Mechanism

Background. Acute lung injury (ALI) is a fatal syndrome frequently induced by lipopolysaccharide (LPS) released from the bacterial cell wall. LPS could also trigger autophagy of lung bronchial epithelial cell to relieve the inflammation, while the overwhelming LPS would impair the balance of autophagy consequently inducing serious lung injury. Methods. We observed the autophagy variation of 16HBE, human bronchial epithelial cell, under exposure to different concentrations of LPS through western blot, immunofluorescence staining, and electron microscopy. Eight strands of 16HBE were divided into two groups upon 1000 ng/ml LPS stimulation or not, which were sent to be sequenced at whole transcriptome. Subsequently, we analyzed the sequencing data in functional enrichment, pathway analysis, and candidate gene selection and constructed a hsa-miR-663b-related competing endogenous RNA (ceRNA) network. Results. We set a series of concentrations of LPS to stimulate 16HBE and observed the variation of autophagy in related protein expression and autophagosome count. We found that the effective concentration of LPS was 1000 ng/ml at 12 hours of exposure and sequenced the 1000 ng/ml LPS-stimulated 16HBE. As a result, a total of 750 differentially expressed genes (DEGs), 449 differentially expressed lncRNAs (DElncRNAs), 76 differentially expressed circRNAs (DEcircRNAs), and 127 differentially expressed miRNAs (DEmiRNAs) were identified. We constructed the protein-protein interaction (PPI) network to visualize the interaction between DEGs and located 36 genes to comprehend the core discrepancy between LPS-stimulated 16HBE and the negative control group. In combined analysis of differentially expressed RNAs (DERNAs), we analyzed all the targeted relationships of ceRNA in DERNAs and figured hsa-miR-663b as a central mediator in the ceRNA network to play when LPS induced the variation of autophagy in 16HBE. Conclusion. Our research indicated that the hsa-miR-663b-related ceRNA network may contribute to the key regulatory mechanism in LPS-induced changes of autophagy and ALI.

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Essential Role of Visfatin in Lipopolysaccharide and Colon Ascendens Stent Peritonitis-Induced Acute Lung Injury

International Journal of Molecular Sciences ◽

10.3390/ijms20071678 ◽

2019 ◽

Vol 20 (7) ◽

pp. 1678 ◽

Cited By ~ 1

Author(s):

Yi-Chen Lee ◽

Chun-Yu Lin ◽

Yen-Hsu Chen ◽

Wen-Chin Chiu ◽

Yen-Yun Wang ◽

...

Keyword(s):

Acute Lung Injury ◽

Epithelial Cell ◽

Lung Injury ◽

Cell Lines ◽

Inflammatory Cytokines ◽

Bronchial Epithelial Cell ◽

Bronchial Epithelial ◽

Epithelial Cell Lines ◽

Nfκb Pathway ◽

Pro Inflammatory Cytokines

Acute lung injury (ALI) is a life-threatening syndrome characterized by acute and severe hypoxemic respiratory failure. Visfatin, which is known as an obesity-related cytokine with pro-inflammatory activities, plays a role in regulation of inflammatory cytokines. The mechanisms of ALI remain unclear in critically ill patients. Survival in ALI patients appear to be influenced by the stress generated by mechanical ventilation and by ALI-associated factors that initiate the inflammatory response. The objective for this study was to understand the mechanisms of how visfatin regulates inflammatory cytokines and promotes ALI. The expression of visfatin was evaluated in ALI patients and mouse sepsis models. Moreover, the underlying mechanisms were investigated using human bronchial epithelial cell lines, BEAS-2B and NL-20. An increase of serum visfatin was discovered in ALI patients compared to normal controls. Results from hematoxylin and eosin (H&E) and immunohistochemistry staining also showed that visfatin protein was upregulated in mouse sepsis models. Moreover, lipopolysaccharide (LPS) induced visfatin expression, activated the STAT3/NFκB pathway, and increased the expression of pro-inflammatory cytokines, including IL1-β, IL-6, and TNF-α in human bronchial epithelial cell lines NL-20 and BEAS-2B. Co-treatment of visfatin inhibitor FK866 reversed the activation of the STAT3/NFκB pathway and the increase of pro-inflammatory cytokines induced by LPS. Our study provides new evidence for the involvement of visfatin and down-stream events in acute lung injury. Further studies are required to confirm whether the anti-visfatin approaches can improve ALI patient survival by alleviating the pro-inflammatory process.

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Identification of differentially expressed genes in immortalized human bronchial epithelial cell line as a model forin vitrostudy of lung carcinogenesis

International Journal of Cancer ◽

10.1002/ijc.10807 ◽

2002 ◽

Vol 103 (2) ◽

pp. 194-204 ◽

Cited By ~ 19

Author(s):

Qian An ◽

Manuela Pacyna-Gengelbach ◽

Karsten Schlüns ◽

Nicole Deutschmann ◽

Suping Guo ◽

...

Keyword(s):

Epithelial Cell ◽

Cell Line ◽

Differentially Expressed Genes ◽

Bronchial Epithelial Cell ◽

Human Bronchial Epithelial Cell ◽

Differentially Expressed ◽

Epithelial Cell Line ◽

Lung Carcinogenesis ◽

Bronchial Epithelial

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A Three-Gene Prognostic Signature Based on Circular RNA-Associated Competing Endogenous RNA Network for Patients with Lung Adenocarcinoma

10.21203/rs.3.rs-84423/v1 ◽

2020 ◽

Author(s):

Xuelong Wang ◽

Bin Zhou ◽

Yuxin Xia ◽

Jianxin Zuo ◽

Yanchao Liu ◽

...

Keyword(s):

Regulatory Mechanism ◽

Cox Regression ◽

Differentially Expressed ◽

Ppi Network ◽

Prognostic Signature ◽

Competing Endogenous Rna ◽

Cox Regression Analysis ◽

Prognostic Performance ◽

Cerna Network ◽

Lasso Method

Abstract Background: Evidence is increasingly indicating that circular RNAs (circRNAs) are closely involved in tumorigenesis and cancer progression. However, functions of circRNAs in lung adenocarcinoma (LUAD) are still unknown. It is necessary to investigate the regulatory mechanism of circRNAs based on competing endogenous RNA (ceRNA) network in LUAD procession and further construct a prognostic signature for predicting overall survival of LUAD patients.Methods: Differentially expressed circRNAs (DEcircRNAs), differentially expressed miRNAs (DEmiRNAs) and differentially expressed mRNAs (DEmRNAs) were selected to construct the ceRNA network based on TargetScan prediction tool and Pearson correlation coefficient. Functional and pathway enrichment analysis were performed using DAVID database. A PPI network was constructed and then visualized by Cytoscape software. Finally, we constructed a prognostic signature for LUAD patients using LASSO method and assessed the prognostic performance in the validation cohort.Results: A total of 38 DEcircRNAs, 56 DEmiRNAs, and 960 DEmRNAs were identifed. Based on the interactions predicted by TargetScan, we constructed a circRNA-associated ceRNA network including 11 DEcircRNAs, 8 DEmiRNAs and 49 DEmRNAs. GO and KEGG pathway analysis indicated that the circRNA-associated ceRNA network might be involved in regulation of GTPase activity and endothelial cell differentiation. After removing the discrete points, a PPI network containing 12 DEmRNAs was constructed. Univariate cox regression analysis showed that three DEmRNAs were significantly associated with overall survival. Therefore, we constructed a three-gene prognostic signature for LUAD patients using LASSO method. By applying the signature, patients in the training cohort could be categorized into high-risk or low-risk subgroup with significant survival difference (HR: 1.62, 95% CI: 1.12-2.35, log-rank p = 0.009). The prognostic performance was confirmed in an independent GEO cohort (HR: 2.59, 95% CI: 1.32-5.10, log-rank p = 0.004). Multivariate cox regression analysis proved that the three-gene signature was an independent prognostic factor for LUAD.Conclusions: Our findings provided a deeper understanding of the circRNA-associated ceRNA regulatory mechanism in LUAD pathogenesis and constructed a prognostic signature that could be a useful guide for personalized treatment of LUAD patients.

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Building a Competing Endogenous RNA Network to Find Potential Long Non-Coding RNA Biomarkers for Pheochromocytoma

Cellular Physiology and Biochemistry ◽

10.1159/000496043 ◽

2018 ◽

Vol 51 (6) ◽

pp. 2916-2924 ◽

Cited By ~ 8

Author(s):

Ying-Chun Liang ◽

Yu-Peng Wu ◽

Dong-Ning Chen ◽

Shao-Hao Chen ◽

Xiao-Dong Li ◽

...

Keyword(s):

Digital Gene Expression ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Differentially Expressed ◽

Competing Endogenous Rna ◽

Cerna Network ◽

Competing Endogenous Rna Network ◽

Patient Prognosis

Background/Aims: Accumulating evidence has shown that long non-coding RNAs (lncRNAs) in competing endogenous RNA (ceRNA) networks play crucial roles in tumor survival and patient prognosis; however, studies investigating ceRNA networks in pheochromocytoma (PCC) are lacking. In this study, we investigated the pathogenesis of PCC and whether lncRNAs acting through ceRNAs networks were associated with prognosis. Methods: A total of 183 PCC samples and 3 control samples from The Cancer Genome Atlas database were analyzed. The Empirical Analysis of Digital Gene Expression Data package in R (edgeR) was used to analyze differentially expressed RNAs. Biological processes and pathways functional enrichment analysis were performed based on the Database for Annotation, Visualization, and Integrated Discovery (DAVID) database. LncRNA/mRNA/miRNA ceRNA network was constructed by Cytoscape v3.0 software based on the differentially expressed RNAs Survival package in R was used to perform survival analysis. Results: In total, 554 differentially expressed lncRNAs, 1775 mRNAs and 40 miRNAs were selected for further analysis. Subsequently, 23 lncRNAs, 22 mRNAs, and 6 miRNAs were included in the constructed ceRNA network. Meanwhile, two of the 23 lncRNAs (C9orf147 and BSN-AS2) were identified as independent predictors of overall survival in PCC patients (P< 0.05). Conclusion: This study improves the understanding of lncRNA-related ceRNA networks in PCC and suggests that the lncRNAs C9orf147 and BSN-AS2 could be independent prognostic biomarkers and potential therapeutic targets for PCC.

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Predictions of the dysregulated competing endogenous RNA signature involved in the progression of human lung adenocarcinoma

Cancer Biomarkers ◽

10.3233/cbm-200133 ◽

2020 ◽

Vol 29 (3) ◽

pp. 399-416

Author(s):

Dan Yang ◽

Yang He ◽

Bo Wu ◽

Ruxi Liu ◽

Nan Wang ◽

...

Keyword(s):

Lung Adenocarcinoma ◽

Risk Score ◽

Molecular Mechanisms ◽

Cox Regression ◽

Functional Enrichment ◽

Differentially Expressed ◽

Competing Endogenous Rna ◽

Score System ◽

Cerna Network ◽

Risk Score System

BACKGROUND: Lung adenocarcinoma (LUAD) is the most common histological subtype of lung cancer worldwide. Until now, the molecular mechanisms underlying LUAD progression have not been fully explained. This study aimed to construct a competing endogenous RNA (ceRNA) network to predict the progression in LUAD. METHODS: Differentially expressed lncRNAs (DELs), miRNAs (DEMs), and mRNAs (DEGs) were identified from The Cancer Genome Atlas (TCGA) database with a |log2FC|> 1.0 and a false discovery rate (FDR) < 0.05. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), protein-protein interaction (PPI) network, and survival analyses were performed to analyse these DEGs involved in the ceRNA network. Subsequently, the drug-gene interaction database (DGIdb) was utilized to select candidate LUAD drugs interacting with significant DEGs. Then, lasso-penalized Cox regression and multivariate Cox regression models were used to construct the risk score system. Finally, based on the correlations between DELs and DEGs involved in the risk score system, the final ceRNA network was identified. Meanwhile, the GEPIA2 database and immunohistochemical (IHC) results were utilized to validate the expression levels of selected DEGs. RESULTS: A total of 340 DELs, 29 DEMs, and 218 DEGs were selected to construct the initial ceRNA network. Functional enrichment analyses indicated that 218 DEGs were associated with the KEGG pathway terms “microRNAs in cancer”, “pathways in cancer”, “cell cycle”, “HTLV-1 infection”, and the “PI3K-Akt signalling pathway”. K-M survival analysis of all differentially expressed genes involved in the ceRNA network identified 24 DELs, 4 DEMs, and 29 DEGs, all of which were significantly correlated with LUAD progression (P< 0.05). Furthermore, 15 LUAD drugs interacting with 29 significant DEGs were selected. After lasso-penalized Cox regression and multivariate Cox regression modelling, PRKCE, DLC1, LATS2, and DPY19L1 were incorporated into the risk score system, and the results suggested that LUAD patients who had the high-risk score always suffered from a poorer overall survival. Additionally, the correlation coefficients between these 4 DEGs and their corresponding DELs involved in the ceRNA network suggested that there were 2 significant DEL-DEG pairs, NAV2-AS2 – PRKCE (r= 0.430, P< 0.001) and NAV2-AS2 – LATS2 (r= 0.338, P< 0.001). And NAV2-AS2 – mir-31 – PRKCE and NAV2-SA2 – mir-31 – LATS2 were finally identified as ceRNA network involved in the progression of LUAD. CONCLUSIONS: The lncRNA-miRNA-mRNA ceRNA network plays an essential role in predicting the progression of LUAD. These results may improve our understanding and provide novel mechanistic insights to explore prognosis and therapeutic drugs for LUAD patients.

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Comprehensive analysis of the putative competing endogenous RNA network in human lung adenocarcinoma

10.21203/rs.2.24823/v1 ◽

2020 ◽

Author(s):

Dan Yang ◽

Yang He ◽

Bo Wu ◽

Yan Deng ◽

Ruxi Liu ◽

...

Keyword(s):

Lung Adenocarcinoma ◽

Risk Score ◽

Cox Regression ◽

Roc Curves ◽

Functional Enrichment ◽

Differentially Expressed ◽

Competing Endogenous Rna ◽

Score System ◽

Cerna Network ◽

Risk Score System

Abstract Background Lung adenocarcinoma (LUAD) is the most common histological subtype of lung cancer worldwide. Until now, the molecular mechanisms underlying LUAD progression have not been fully explained. This study aimed to identify a competing endogenous RNA (ceRNA) network in LUAD. Methods Differentially expressed lncRNAs (DELs), miRNAs (DEMs), and mRNAs (DEGs) were identified from The Cancer Genome Atlas (TCGA) database with a |log2FC| > 1.0 and a false discovery rate (FDR) < 0.05. Then, these DELs, DEMs, and DEGs were used to construct the initial ceRNA network. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), protein-protein interaction (PPI) network, and survival analyses were performed to analyse these DEGs involved in the ceRNA network. Subsequently, the drug-gene interaction database (DGIdb) was utilized to select candidate LUAD drugs interacting with significant DEGs. Then, lasso-penalized Cox regression and multivariate Cox regression models were used to construct the risk score system. Kaplan-Meier (K-M) survival curves and receiver operating characteristic (ROC) curves were utilized to validate the reliability of the risk score system. Finally, based on the correlations between DELs and DEGs involved in the risk score system, the final ceRNA network was identified. Results A total of 340 DELs, 29 DEMs, and 218 DEGs were selected to construct the initial ceRNA network. Functional enrichment analyses indicated that 218 DEGs were significantly enriched in the GO terms “nucleoplasm”, “transcription factor complex”, “protein binding”, and “metal ion binding”, whereas these DEGs were associated with the KEGG pathway terms “microRNAs in cancer”, “pathways in cancer”, “cell cycle”, “HTLV-1 infection”, and the “PI3K-Akt signalling pathway”. K-M survival analysis of all differentially expressed genes involved in the ceRNA network identified 24 DELs, 4 DEMs, and 29 DEGs, all of which were significantly correlated with LUAD progression (P < 0.05). Furthermore, 15 LUAD drugs interacting with 29 DEGs were selected. After lasso-penalized Cox regression and multivariate Cox regression modelling, 4 DEGs, PRKCE, DLC1, LATS2, and DPY19L1, were incorporated into the risk score system. The area under the curve (AUC) values of the time-dependent ROC curves at 3 years and 5 years were both higher than 0.5. Finally, the correlation coefficients between these 4 DEGs and their corresponding DELs involved in the ceRNA network suggested that there were 2 DEL-DEG pairs, NAV2-AS2 – PRKCE (r = 0.430, P < 0.001) and NAV2-AS2 – LATS2 (r = 0.338, P < 0.001). Considering the previously constructed ceRNA network, NAV2-AS2 – mir-31 – PRKCE and NAV2-SA2 – mir-31 – LATS2 were identified. Conclusions The lncRNA-miRNA-mRNA ceRNA network plays an essential role in LUAD. These results may improve our understanding and provide novel mechanistic insights to explore diagnostics, tumourigenesis, prognosis, and therapeutic drugs for LUAD patients.

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