scholarly journals Identification of potential prognostic long non‑coding RNA signatures based on a competing endogenous RNA network in lung adenocarcinoma

2018 ◽  
Author(s):  
Xiaojuan Wang ◽  
Yawen Ding ◽  
Bangming Da ◽  
Yan Fei ◽  
Gang Feng
Keyword(s):  
Lung Adenocarcinoma ◽  
Competing Endogenous Rna ◽  
Non Coding Rna ◽  
Competing Endogenous Rna Network ◽  
Long Non Coding Rna

scholarly journals Construction of asthma related competing endogenous RNA network revealed novel long non-coding RNAs and potential new drugs

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Yifang Liao ◽  
Ping Li ◽  
Yanxia Wang ◽  
Hong Chen ◽  
Shangwei Ning ◽  
...  
Keyword(s):  
Gene Expression ◽  
Drug Repositioning ◽  
New Drugs ◽  
Differentially Expressed ◽  
Interaction Data ◽  
Competing Endogenous Rna ◽  
Non Coding Rna ◽  
Competing Endogenous Rna Network ◽  
Non Coding Rnas ◽  
Long Non Coding Rna

Abstract Background Asthma is a heterogeneous disease characterized by chronic airway inflammation. Long non-coding RNA can act as competing endogenous RNA to mRNA, and play significant role in many diseases. However, there is little known about the profiles of long non-coding RNA and the long non-coding RNA related competing endogenous RNA network in asthma. In current study, we aimed to explore the long non-coding RNA-microRNA-mRNA competing endogenous RNA network in asthma and their potential implications for therapy and prognosis. Methods Asthma-related gene expression profiles were downloaded from the Gene Expression Omnibus database, re-annotated with these genes and identified for asthma-associated differentially expressed mRNAs and long non-coding RNAs. The long non-coding RNA-miRNA interaction data and mRNA-miRNA interaction data were downloaded using the starBase database to construct a long non-coding RNA-miRNA-mRNA global competing endogenous RNA network and extract asthma-related differentially expressed competing endogenous RNA network. Finally, functional enrichment analysis and drug repositioning of asthma-associated differentially expressed competing endogenous RNA networks were performed to further identify key long non-coding RNAs and potential therapeutics associated with asthma. Results This study constructed an asthma-associated competing endogenous RNA network, determined 5 key long non-coding RNAs (MALAT1, MIR17HG, CASC2, MAGI2-AS3, DAPK1-IT1) and identified 8 potential new drugs (Tamoxifen, Ruxolitinib, Tretinoin, Quercetin, Dasatinib, Levocarnitine, Niflumic Acid, Glyburide). Conclusions The results suggested that long non-coding RNA played an important role in asthma, and these novel long non-coding RNAs could be potential therapeutic target and prognostic biomarkers. At the same time, potential new drugs for asthma treatment have been discovered through drug repositioning techniques, providing a new direction for the treatment of asthma.

scholarly journals Multi-Omics Integrative Bioinformatics Analyses Reveal Long Non-coding RNA Modulates Genomic Integrity via Competing Endogenous RNA Mechanism and Serves as Novel Biomarkers for Overall Survival in Lung Adenocarcinoma

2021 ◽  
Vol 9 ◽  
Author(s):  
Zhonglin Wang ◽  
Ziyuan Ren ◽  
Rui Li ◽  
Junpeng Ge ◽  
Guoming Zhang ◽  
...  
Keyword(s):  
Overall Survival ◽  
Lung Adenocarcinoma ◽  
Cancer Progression ◽  
Genome Instability ◽  
Genomic Integrity ◽  
Competing Endogenous Rna ◽  
Clinical Value ◽  
Bioinformatics Analyses ◽  
Non Coding Rna ◽  
Long Non Coding Rna

Long non-coding RNA (lncRNA) plays a crucial role in modulating genome instability, immune characteristics, and cancer progression, within which genome instability was identified as a critical regulator in tumorigenesis and tumor progression. However, the existing accounts fail to detail the regulatory role of genome instability in lung adenocarcinoma (LUAD). We explored the clinical value of genome instability-related lncRNA in LUAD with multi-omics bioinformatics analysis. We extracted the key genome instability-related and LUAD-related gene modules using weighted gene co-expression network analysis (WGCNA) and established a competing endogenous RNA (ceRNA) network using four lncRNAs (LINC01224, LINC00346, TRPM2-AS, and CASC9) and seven target mRNAs (CCNF, PKMYT1, GCH1, TK1, PSAT1, ADAM33, and DDX11). We found that LINC01224 is primarily located in the cytoplasm and that LINC00346 and TRPM2-AS are primarily located in the nucleus (CASC9 unknown). We found that all 11 genes were positively related to tumor mutational burden and involve drug resistance, cancer stemness, and tumor microenvironment infiltration. Additionally, an eight-lncRNA genome instability-related lncRNA signature was established and validated, predicting the overall survival and immunotherapy outcomes in LUAD. To conclude, we discovered that sponging microRNA, genome instability-related lncRNA functions as ceRNA, modulating genomic integrity. This research provides clinical references for LUAD immunotherapy and prognosis and interprets a potential genome instability-related ceRNA regulatory network in which LINC01224-miR-485-5p/miR-29c-3p-CCNF-RRM2 and LINC01224-miR485-5p-PKMYT1-CDK1 axes were the most promising pathways. However, the potential mechanisms underlying our findings still need biological validation through in vitro and in vivo experiments.

scholarly journals Identification of Long Non-Coding RNA-Associated Competing Endogenous RNA Network in the Differentiation of Chicken Preadipocytes

Genes ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 795 ◽  
Author(s):  
Chen ◽  
Zhang ◽  
Zhang ◽  
Huang ◽  
Zhang ◽  
...  
Keyword(s):  
Adipogenic Differentiation ◽  
Target Prediction ◽  
Competing Endogenous Rna ◽  
Chicken Fat ◽  
Cerna Network ◽  
Non Coding Rna ◽  
Competing Endogenous Rna Network ◽  
Gene Expression Correlation ◽  
Long Non Coding Rna

Emerging evidence indicates that long noncoding RNAs (lncRNAs) play important roles in the regulation of cell differentiation by acting as competing endogenous RNA (ceRNA). However, the regulatory mechanisms of lncRNA and the lncRNA-associated ceRNA network involved in adipogenic differentiation of chicken preadipocytes remain elusive. Here, we first constructed the chicken preadipocyte in vitro induction model. Then, we identified differentially expressed lncRNAs (DELs), miRNAs (DEMis), and mRNAs (DEMs) between differentiated and undifferentiated preadipocytes. Furthermore, we constructed the lncRNA associated ceRNA network by gene expression correlation analysis and target prediction of DELs, DEMis, and DEMs. Finally, we determined twelve candidate lncRNA-miRNA-mRNA interactions from the lncRNA associated ceRNA network. Eight out of the twelve interactions were validated by RT-qPCR, indicating their potential role in the regulation of chicken preadipocytes differentiation. Among the eight interactions, TCONS_00026544-gga-miR-128-1-5p-RASD1, TCONS_00055280-gga-miR-135a-5p-JAM3, TCONS_00055280-gga-miR-135a-5p-GPR133, TCONS_00055280-gga-miR-135a-5p-CLDN1, and TCONS_00055280-gga-miR-135a-5p-TMEM123 may promote adipogenic differentiation of chicken preadipocytes while TCONS_00057272-gga-miR-146a-3p-FOXO6, TCONS_00057242-gga-miR-6615-3p-FOXO6, and TCONS_00057242-gga-miR-6615-3p-ENSGALT00000043224 have the opposite effects. Our results not only provide novel insights into ceRNA roles of lncRNAs in chicken preadipocytes differentiation and but also contribute to a better understanding of chicken fat deposition.

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