Literature DB >> 27826625

Integrated analysis of long non-coding RNA‑associated ceRNA network reveals potential lncRNA biomarkers in human lung adenocarcinoma.

Jing Sui1, Yun-Hui Li1, Yan-Qiu Zhang1, Cheng-Yun Li1, Xian Shen1, Wen-Zhuo Yao1, Hui Peng1, Wei-Wei Hong1, Li-Hong Yin1, Yue-Pu Pu1, Ge-Yu Liang1.   

Abstract

Accumulating evidence has highlighted the important roles of long non-coding RNAs (lncRNAs) acting as competing endogenous RNAs (ceRNAs) in tumor biology. However, the roles of cancer specific lncRNAs in lncRNA-related ceRNA network of lung adenocarcinoma (LUAD) are still unclear. In the present study, the 465 RNA sequencing profiles in LUAD patients were obtained from the cancer genome atlas (TCGA) database, which provides large sample RNA sequencing data free of charge, and 41 cancer specific lncRNAs, 25 miRNAs and 1053 mRNAs (fold change >2, p<0.05) were identified. Then, the lncRNA-miRNA-mRNA ceRNA network of LUAD was constructed with 29 key lncRNAs, 24 miRNAs and 72 mRNAs. Subsequently, we selected these 29 key lncRNAs to analyze their correlation with clinical features, and 21 of them were aberrantly expressed with tumor pathological stage, TNM staging system, lymph node metastasis and patient outcome assessment, respectively. Furthermore, there were 5 lncRNAs (BCRP3, LINC00472, CHIAP2, BMS1P20 and UNQ6494) positively correlated with overall survival (OS, log-rank p<0.05). Finally, 7 cancer specific lncRNAs were randomly selected to verify the expression in 53 newly diagnosed LUAD patients using qRT-PCR. The expression results between TCGA and qRT-PCR were 100% in agreement. The correlation between AFAP1-AS1 and LINC00472 and clinical features were also confirmed. Thus, our results showed the lncRNA expression profiles and we constructed an lncRNA-miRNA-mRNA ceRNA network in LUAD. The present study provides novel insight for better understanding of lncRNA-related ceRNA network in LUAD and facilitates the identification of potential biomarkers for diagnosis and prognosis.

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Year:  2016        PMID: 27826625     DOI: 10.3892/ijo.2016.3716

Source DB:  PubMed          Journal:  Int J Oncol        ISSN: 1019-6439            Impact factor:   5.650


  69 in total

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7.  Competing endogenous RNA network identifies mRNA biomarkers for overall survival of lung adenocarcinoma: two novel on-line precision medicine predictive tools.

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9.  Survival prediction of kidney renal papillary cell carcinoma by comprehensive LncRNA characterization.

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Journal:  Oncotarget       Date:  2017-11-28

10.  Identification of lung adenocarcinoma specific dysregulated genes with diagnostic and prognostic value across 27 TCGA cancer types.

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