Dataset Information

Construction and analysis for differentially expressed long non-coding RNAs and MicroRNAs mediated competing endogenous RNA network in colon cancer.

ABSTRACT: Long non-coding RNA (lncRNA) has been confirmed to act as a key regulatory molecule in different types of cancers and play a significant role in tumors initiation and progression. LncRNA can be as acompeting endogenous RNA(ceRNA) to regulate the expression of targeted genes by sponging miRNA. In the present study, we explore the functional roles and regulatory mechanisms of lncRNAs as ceRNAs in colon cancer and their potential implications for prognosis.The lncRNAs, miRNAs and mRNAs expression profiles of 341 colon cancer tissues and 27 non-tumor colon tissues were downloaded from The Cancer Genome Atlas (TCGA) database. Differential expression of RNAs was identified using the "DESeq" bioconductor package in R. PPI network of differentially expressed genes was constructed using the STRING database. Survival analysis was estimated based on Kaplan-Meier curve analysis. We used KOBAS 3.0 to analyze the KEGG pathway of DEGs. The dysregulated lncRNA-associated ceRNA network was constructed in colon cancer based on bioinformatics generated from miRanda, PicTar, TargetScan, miRDB and miRcode. A total of 791 DElncRNAs and 200 DEmiRNAs were identified in colon cancer compared with matched normal tissues with thresholds of |log2foldChange (FC)| >3.0and adjusted P value<0.05.Twenty DElncRNAs were identified, may be related to tumorigenesis and/or progression of colon cancer. Nine out of 20 dysregulated lncRNA were found to be significantly associated with overall survival (P value<0.05). Finally, we successfully constructed colon cancer-associated ceRNA network, including 9 colon cancer-specific lncRNAs, 13 miRNAS and 70 mRNAs. In conclusion, our study will contribute to improve the understanding of ceRNA network regulatory mechanisms in colon cancer. These identified novel lncRNAs can be as candidate prognostic biomarkers or potential therapeutic targets.

SUBMITTER: Li F

PROVIDER: S-EPMC5805314 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Construction and analysis for differentially expressed long non-coding RNAs and MicroRNAs mediated competing endogenous RNA network in colon cancer.

Li Fengxi F Li Qian Q Wu Xianghua X

PloS one 20180208 2

Long non-coding RNA (lncRNA) has been confirmed to act as a key regulatory molecule in different types of cancers and play a significant role in tumors initiation and progression. LncRNA can be as acompeting endogenous RNA(ceRNA) to regulate the expression of targeted genes by sponging miRNA. In the present study, we explore the functional roles and regulatory mechanisms of lncRNAs as ceRNAs in colon cancer and their potential implications for prognosis.The lncRNAs, miRNAs and mRNAs expression p ...[more]

PMID: 29420609

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Project description:The competing endogenous RNA (ceRNA) network is crucial for the development and progression of tumors, including non?small cell lung cancer (NSCLC). However, what type of ceRNA network regulates NSCLC has not been clarified. The present study aimed to elucidate the long non?coding RNA (lncRNA)/microRNA (miRNA)/mRNA ceRNA network in NSCLC, particularly for the significance of lncRNAs in NSCLC. NSCLC?specific differentially expressed lncRNAs, miRNAs and mRNAs in the Cancer Genome Atlas (TCGA) were analyzed and their relationship was analyzed by a ceRNA network. Their potential functions of differentially expressed mRNAs were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Furthermore, the expression levels of four selected lncRNAs in TCGA were determined and their associated survival of patients was examined. In addition, the expression profiles of these four lncRNAs in 48 NSCLC specimens and cell lines, their cellular distribution and associated clinical parameters were examined. We successfully constructed a ceRNA network, including 113 lncRNAs, 12 miRNAs and 36 mRNAs differentially expressed between NSCLC and non?tumor tissues. LINC00525, MED4?AS1, STEAP2?AS1 and SYNPR?AS1 lncRNAs were selected and validated for their association with the survival of NSCLC patients. The expression of these lncRNAs was upregulated in 48 NSCLC tissues and was varying in NSCLC cells. While LINC00525 was mainly expressed in the cytoplasm, MED4?AS1 was in both the nucleus and cytoplasm of A549 cells. In addition, the expression of LINC00525 was significantly associated with smoking history (P<0.05); MED4?AS1 was significantly associated with women, poor differentiation and lymph node metastasis (P<0.05); STEAP2?AS1 was significantly associated with women (P<0.01); and SYNPR?AS1 was significantly associated with women and adenocarcinoma (P<0.05). These lncRNAs may be valuable biomarkers for prognosis of NSCLC and the ceRNA network may provide new insights in the pathogenesis of NSCLC.

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Project description:The aim of the present study was to identify novel microRNA (miRNA) or long noncoding RNA (lncRNA) signatures of laryngeal cancer recurrence and to investigate the regulatory mechanisms associated with this malignancy. Datasets of recurrent and nonrecurrent laryngeal cancer samples were downloaded from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus database (GSE27020 and GSE25727) to examine differentially expressed miRNAs (DE‑miRs), lncRNAs (DE‑lncRs) and mRNAs (DEGs). miRNA‑mRNA and lncRNA‑miRNA networks were constructed by investigating the associations among these RNAs in various databases. Subsequently, the interactions identified were combined into a competing endogenous RNA (ceRNA) regulatory network. Feature genes in the miRNA‑mRNA network were identified via topological analysis and a recursive feature elimination algorithm. A support vector machine (SVM) classifier was established using the betweenness centrality values in the miRNA‑mRNA network, consisting of 32 optimal feature‑coding genes. The classification effect was tested using two validation datasets. Furthermore, coding genes in the ceRNA network were examined via pathway enrichment analyses. In total, 21 DE‑lncRs, 507 DEGs and 55 DE‑miRs were selected. The SVM classifier exhibited an accuracy of 94.05% (79/84) for sample classification prediction in the TCGA dataset, and 92.66 and 91.07% in the two validation datasets. The ceRNA regulatory network comprised 203 nodes, corresponding to mRNAs, miRNAs and lncRNAs, and 346 lines, corresponding to the interactions among RNAs. In particular, the interactions with the highest scores were HLA complex group 4 (HCG4)‑miR‑33b, HOX transcript antisense RNA (HOTAIR)‑miR‑1‑MAGE family member A2 (MAGEA2), EMX2 opposite strand/antisense RNA (EMX2OS)‑miR‑124‑calcitonin related polypeptide α (CALCA) and EMX2OS‑miR‑124‑γ‑aminobutyric acid type A receptor γ2 subunit (GABRG2). Gene enrichment analysis of the genes in the ceRNA network identified that 11 pathway terms and 16 molecular function terms were significantly enriched. The SVM classifier based on 32 feature coding genes exhibited high accuracy in the classification of laryngeal cancer samples. miR‑1, miR‑33b, miR‑124, HOTAIR, HCG4 and EMX2OS may be novel biomarkers of recurrent laryngeal cancer, and HCG4‑miR‑33b, HOTAIR‑miR‑1‑MAGEA2 and EMX2OS‑miR‑124‑CALCA/GABRG2 may be associated with the molecular mechanisms regulating recurrent laryngeal cancer.

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Dataset Information

Construction and analysis for differentially expressed long non-coding RNAs and MicroRNAs mediated competing endogenous RNA network in colon cancer.

Publications

Construction and analysis for differentially expressed long non-coding RNAs and MicroRNAs mediated competing endogenous RNA network in colon cancer.

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