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Competing endogenous RNA network analysis reveals potential long non-coding RNAs as predictive biomarkers of gastric cancer.

ABSTRACT: Gastric cancer (GC) is one of the most frequently occurring life-threatening malignancies worldwide. Due to its high mortality rate, the discovery of putative biomarkers that may be sensitive and specific to GC is of seminal importance. Long non-coding RNAs (lncRNAs) are non-translatable RNAs whose transcript length exceeds 200 base pairs. The dysregulation of lncRNA expression plays a key role in tumorigenesis and development. In the present study, the expression profiles of lncRNAs, microRNAs and mRNAs of 361 GC tissues (and 32 normal gastric tissues) were downloaded from The Cancer Genome Atlas database. Furthermore, differentially expressed RNAs were analyzed by the DEseq package. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses confirmed some significant dysregulated signaling pathways and target RNAs. As a result, an lncRNA-associated competing endogenous RNA (ceRNA) network was constructed. Kaplan-Meier analysis of the differentially expressed RNAs associated with GC pathogenesis confirmed that the lncRNAs PVT1, HAND2-AS1 and ZNF667-AS1 were potentially associated with the prognosis of GC (P<0.05). The present study suggests the mechanism of ceRNA networks in GC, and further demonstrates that aberrant lncRNA expression may be used as an effective diagnostic tool (or target) for the prognosis of GC.

SUBMITTER: Peng S

PROVIDER: S-EPMC7039062 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Competing endogenous RNA network analysis reveals potential long non-coding RNAs as predictive biomarkers of gastric cancer.

Peng Sanfei S Yin Xiangyang X Zhang Yizheng Y Mi Wunan W Li Tong T Yu Yang Y Jiang Jianwu J Liu Qi Q Fu Yang Y

Oncology letters 20200124 3

Gastric cancer (GC) is one of the most frequently occurring life-threatening malignancies worldwide. Due to its high mortality rate, the discovery of putative biomarkers that may be sensitive and specific to GC is of seminal importance. Long non-coding RNAs (lncRNAs) are non-translatable RNAs whose transcript length exceeds 200 base pairs. The dysregulation of lncRNA expression plays a key role in tumorigenesis and development. In the present study, the expression profiles of lncRNAs, microRNAs ...[more]

PMID: 32194716

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Project description:Gastric cancer (GC) is a common type of cancer, and identification of novel diagnostic biomarkers associated with this disease is important. The present study aimed to identify novel diagnostic biomarkers associated with the prognosis of GC, using an integrated bioinformatics approach. Differentially expressed long non-coding RNAs (lncRNAs) associated with GC were identified using Gene Expression Omnibus datasets (GSE58828, GSE72305 and GSE99416) and The Cancer Genome Atlas database. A competing endogenous RNA network that incorporated five lncRNAs [long intergenic non-protein coding RNA 501 (LINC00501), LINC00365, SOX21 antisense divergent transcript 1 (SOX21-AS1), GK intronic transcript 1 (GK-IT1) and DLEU7 antisense RNA 1 (DLEU7-AS1)], 29 microRNAs and 114 mRNAs was constructed. Gene Ontology and protein-protein interaction network analyses revealed that these lncRNAs may be involved in 'biological regulation', 'metabolic process', 'cell communication', 'developmental process', 'cell proliferation', 'reproduction' and the 'cell cycle'. The results of receiver operating characteristic curve analysis demonstrated that LINC00501 (AUC=0.819), LINC00365 (AUC=0.580), SOX21-AS1 (AUC=0.736), GK-IT1 (AUC=0.823) and DLEU7-AS1 (AUC=0.932) had the potential to become valuable diagnostic biomarkers for GC. Associations with clinicopathological characteristics demonstrated that LINC00501 expression was significantly associated with sex (P=0.015) and tumor grade (P=0.022). Furthermore, LINC00365 expression was significantly associated with lymph node metastasis (P=0.025). Gene set enrichment analysis revealed that LINC00501, LINC00365 and SOX21-AS1 were enriched in signaling pathways associated with GC. Reverse transcription-quantitative PCR analysis demonstrated that LINC00501 expression (P=0.043) was significantly upregulated in GC tissues, whereas the expression levels of LINC00365 (P=0.033) and SOX21-AS1 (P=0.037) were significantly downregulated in GC tissues. Taken together, the results of the present study suggest that LINC00501, LINC00365, SOX21-AS1, GK-IT1 and DLEU7-AS1 may be used as novel diagnostic biomarkers for GC, and may be functionally associated with GC development and progression.

Project description:Long non?coding RNAs (lncRNAs) represent potential biomarkers for the diagnosis and treatment of various diseases; however, the role of circulating acute ischemic stroke (AIS)?related lncRNAs remains relatively unknown. The present study aimed to screen crucial lncRNAs for AIS based on the competing endogenous RNA (ceRNA) hypothesis. The expression profile datasets for one mRNA, accession no. GSE16561, and four microRNAs (miRNAs), accession nos. GSE95204, GSE86291, GSE55937 and GSE110993, were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs), lncRNAs (DELs), and miRNAs (DEMs) were identified, and ClusterProfiler was used to interpret the function of the DEGs. Based on the protein?protein interaction (PPI) network and module analyses, hub DEGs were identified. A ceRNA network was established based on miRNA?mRNA or miRNA?lncRNA interaction pairs. In total, 2,041 DEGs and 5 DELs were identified between the AIS and controls samples in GSE16561, and 10 DEMs between at least two of the four miRNA expression profiles. A PPI network was constructed with 1,235 DEGs, among which 20 genes were suggested to be hub genes. The hub genes paxillin (PXN), FYN?proto?oncogene, Src family tyrosine kinase (FYN), ras homolog family member A (RHOA), STAT1, and growth factor receptor?bound protein 2 (GRB2), were amongst the most significantly enriched modules extracted from the PPI network. Functional analysis revealed that these hub genes were associated with inflammation?related signaling pathways. An AIS?related ceRNA network was constructed, in which 4 DELs were predicted to function as ceRNAs for 9 DEMs, to regulate the five identified hub genes; that is, minichromosome maintenance complex component 3 associated protein?antisense RNA 1 (MCM3AP?AS1)/long intergenic non?protein coding RNA 1089 (LINC01089)/hsa?miRNA (miR)?125a/FYN, inositol?tetrakisphosphate 1?kinase?antisense RNA 1 (ITPK1?AS1)/hsa?let?7i/RHOA/GRB2/STAT1, and human leukocyte antigen complex group 27 (HCG27)/hsa?-miR?19a/PXN interaction axes. In conclusion, MCM3AP?AS1, LINC01089, ITPK1?AS1, and HCG27 may represent new biomarkers and underlying targets for the treatment of AIS.

Project description: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.

Project description:Schizophrenia (SCZ) is a serious psychiatric condition with a 1% lifetime risk. SCZ is one of the top ten global causes of disabilities. Despite numerous attempts to understand the function of genetic factors in SCZ development, genetic components in SCZ pathophysiology remain unknown. The competing endogenous RNA (ceRNA) network has been demonstrated to be involved in the development of many kinds of diseases. The ceRNA hypothesis states that cross-talks between coding and non-coding RNAs, including long non-coding RNAs (lncRNAs), via miRNA complementary sequences known as miRNA response elements, creates a large regulatory network across the transcriptome. In the present study, we developed a lncRNA-related ceRNA network to elucidate molecular regulatory mechanisms involved in SCZ. Microarray datasets associated with brain regions (GSE53987) and lymphoblasts (LBs) derived from peripheral blood (sample set B from GSE73129) of SCZ patients and control subjects containing information about both mRNAs and lncRNAs were downloaded from the Gene Expression Omnibus database. The GSE53987 comprised 48 brain samples taken from SCZ patients (15 HPC: hippocampus, 15 BA46: Brodmann area 46, 18 STR: striatum) and 55 brain samples taken from control subjects (18 HPC, 19 BA46, 18 STR). The sample set B of GSE73129 comprised 30 LB samples (15 patients with SCZ and 15 controls). Differentially expressed mRNAs (DEmRNAs) and lncRNAs (DElncRNAs) were identified using the limma package of the R software. Using DIANA-LncBase, Human MicroRNA Disease Database (HMDD), and miRTarBase, the lncRNA- associated ceRNA network was generated. Pathway enrichment of DEmRNAs was performed using the Enrichr tool. We developed a protein-protein interaction network of DEmRNAs and identified the top five hub genes by the use of STRING and Cytoscape, respectively. Eventually, the hub genes, DElncRNAs, and predictive miRNAs were chosen to reconstruct the subceRNA networks. Our bioinformatics analysis showed that twelve key DEmRNAs, including BDNF, VEGFA, FGF2, FOS, CD44, SOX2, NRAS, SPARC, ZFP36, FGG, ELAVL1, and STARD13, participate in the ceRNA network in SCZ. We also identified DLX6-AS1, NEAT1, MINCR, LINC01094, DLGAP1-AS1, BABAM2-AS1, PAX8-AS1, ZFHX4-AS1, XIST, and MALAT1 as key DElncRNAs regulating the genes mentioned above. Furthermore, expression of 15 DEmRNAs (e.g., ADM and HLA-DRB1) and one DElncRNA (XIST) were changed in both the brain and LB, suggesting that they could be regarded as candidates for future biomarker studies. The study indicated that ceRNAs could be research candidates for investigating SCZ molecular pathways.

Project description:AimsThis study aimed to uncover the hub long non-coding RNAs (lncRNAs) differentially expressed in osteoarthritis (OA) cartilage using an integrated analysis of the competing endogenous RNA (ceRNA) network and co-expression network.MethodsExpression profiles data of ten OA and ten normal tissues of human knee cartilage were obtained from the Gene Expression Omnibus (GEO) database (GSE114007). The differentially expressed messenger RNAs (DEmRNAs) and lncRNAs (DElncRNAs) were identified using the edgeR package. We integrated human microRNA (miRNA)-lncRNA/mRNA interactions with DElncRNA/DEmRNA expression profiles to construct a ceRNA network. Likewise, lncRNA and mRNA expression profiles were used to build a co-expression network with the WGCNA package. Potential hub lncRNAs were identified based on an integrated analysis of the ceRNA network and co-expression network. StarBase and Multi Experiment Matrix databases were used to verify the lncRNAs.ResultsWe detected 1,212 DEmRNAs and 49 DElncRNAs in OA and normal knee cartilage. A total of 75 dysregulated lncRNA-miRNA interactions and 711 dysregulated miRNA-mRNA interactions were obtained in the ceRNA network, including ten DElncRNAs, 69 miRNAs, and 72 DEmRNAs. Similarly, 1,330 dysregulated lncRNA-mRNA interactions were used to construct the co-expression network, which included ten lncRNAs and 407 mRNAs. We finally identified seven hub lncRNAs, named MIR210HG, HCP5, LINC00313, LINC00654, LINC00839, TBC1D3P1-DHX40P1, and ISM1-AS1. Subsequent enrichment analysis elucidated that these lncRNAs regulated extracellular matrix organization and enriched in osteoclast differentiation, the FoxO signalling pathway, and the tumour necrosis factor (TNF) signalling pathway in the development of OA.ConclusionThe integrated analysis of the ceRNA network and co-expression network identified seven hub lncRNAs associated with OA. These lncRNAs may regulate extracellular matrix changes and chondrocyte homeostasis in OA progress.Cite this article: Bone Joint Res. 2020;9(3):90-98.

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Competing endogenous RNA network analysis reveals potential long non-coding RNAs as predictive biomarkers of gastric cancer.

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Competing endogenous RNA network analysis reveals potential long non-coding RNAs as predictive biomarkers of gastric cancer.

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