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Identification of lncRNA biomarkers in lung squamous cell carcinoma using comprehensive analysis of lncRNA mediated ceRNA network.
Artif Cells Nanomed Biotechnol. 2019 Dec; 47(1):3246-3258.AC

Abstract

Long non-coding RNAs (lncRNAs) act as a member of competing endogenous RNAs (ceRNAs) and plays a significant role in tumorigenesis. The aim of this study was to identify potential lncRNA biomarkers for predicting the prognosis of lung squamous cell carcinoma (LUSC) using a comprehensive analysis of lncRNA mediated ceRNA network. Differentially expressed RNAs datasets were obtained using edge R package in 502 LUSC tissues and 49 adjacent non-LUSC tissues from the Cancer Genome Atlas (TCGA). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed to identify functional enrichment implication of lncRNA related differentially expressed mRNAs. Survival analysis was used Kaplan-Meier curve method. Univariate and multivariate Cox regression analysis were performed to construct a predictive model with lncRNA biomarkers. A total of 2185 lncRNAs, 170 miRNAs and 2053 mRNAs were differentially expressed between LUSC tissues and adjacent non-LUSC tissues. The novel constructed ceRNA network incorporated 184 LUSC-specific lncRNAs, 18 miRNAs, and 49 mRNAs. About 11 of 184 differentially expressed lncRNAs and 1 of 18 differentially expressed miRNAs and 5 of 49 differentially expressed mRNAs were conspicuously related to overall survival (p < .05). Univariate and multivariate cox regression analysis showed that 6 lncRNAs were retrieved to construct a predictive model to predict the overall survival in LUSC patients. In conclusion, CeRNAs contributed to the progression of LUSC and a model with 6 lncRNAs might be potential biomarker for predicting the prognosis of LUSC.

Authors+Show Affiliations

a Department of Respiratory and Critical Care Medicine, Qilu Hospital of Shandong University , Jinan , People's Republic of China.b Department of Clinical Laboratory, Qianfoshan Hospital of Shandong Province , Jinan , People's Republic of China.c Department of Cardiology, Zhangqiu District People's Hospital of Jinan , Shandong , China.a Department of Respiratory and Critical Care Medicine, Qilu Hospital of Shandong University , Jinan , People's Republic of China.a Department of Respiratory and Critical Care Medicine, Qilu Hospital of Shandong University , Jinan , People's Republic of China.a Department of Respiratory and Critical Care Medicine, Qilu Hospital of Shandong University , Jinan , People's Republic of China.a Department of Respiratory and Critical Care Medicine, Qilu Hospital of Shandong University , Jinan , People's Republic of China.a Department of Respiratory and Critical Care Medicine, Qilu Hospital of Shandong University , Jinan , People's Republic of China.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

31364871

Citation

Li, Rui, et al. "Identification of lncRNA Biomarkers in Lung Squamous Cell Carcinoma Using Comprehensive Analysis of lncRNA Mediated ceRNA Network." Artificial Cells, Nanomedicine, and Biotechnology, vol. 47, no. 1, 2019, pp. 3246-3258.
Li R, Yang YE, Jin J, et al. Identification of lncRNA biomarkers in lung squamous cell carcinoma using comprehensive analysis of lncRNA mediated ceRNA network. Artif Cells Nanomed Biotechnol. 2019;47(1):3246-3258.
Li, R., Yang, Y. E., Jin, J., Zhang, M. Y., Liu, X., Liu, X. X., Yin, Y. H., & Qu, Y. Q. (2019). Identification of lncRNA biomarkers in lung squamous cell carcinoma using comprehensive analysis of lncRNA mediated ceRNA network. Artificial Cells, Nanomedicine, and Biotechnology, 47(1), 3246-3258. https://doi.org/10.1080/21691401.2019.1647225
Li R, et al. Identification of lncRNA Biomarkers in Lung Squamous Cell Carcinoma Using Comprehensive Analysis of lncRNA Mediated ceRNA Network. Artif Cells Nanomed Biotechnol. 2019;47(1):3246-3258. PubMed PMID: 31364871.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Identification of lncRNA biomarkers in lung squamous cell carcinoma using comprehensive analysis of lncRNA mediated ceRNA network. AU - Li,Rui, AU - Yang,Yi-E, AU - Jin,Jia, AU - Zhang,Meng-Yu, AU - Liu,Xiao, AU - Liu,Xiao-Xia, AU - Yin,Yun-Hong, AU - Qu,Yi-Qing, PY - 2019/8/1/entrez PY - 2019/8/1/pubmed PY - 2019/12/31/medline KW - 6-lncRNA signature KW - Competing endogenous RNA KW - biomarker KW - lung squamous cell carcinoma SP - 3246 EP - 3258 JF - Artificial cells, nanomedicine, and biotechnology JO - Artif Cells Nanomed Biotechnol VL - 47 IS - 1 N2 - Long non-coding RNAs (lncRNAs) act as a member of competing endogenous RNAs (ceRNAs) and plays a significant role in tumorigenesis. The aim of this study was to identify potential lncRNA biomarkers for predicting the prognosis of lung squamous cell carcinoma (LUSC) using a comprehensive analysis of lncRNA mediated ceRNA network. Differentially expressed RNAs datasets were obtained using edge R package in 502 LUSC tissues and 49 adjacent non-LUSC tissues from the Cancer Genome Atlas (TCGA). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed to identify functional enrichment implication of lncRNA related differentially expressed mRNAs. Survival analysis was used Kaplan-Meier curve method. Univariate and multivariate Cox regression analysis were performed to construct a predictive model with lncRNA biomarkers. A total of 2185 lncRNAs, 170 miRNAs and 2053 mRNAs were differentially expressed between LUSC tissues and adjacent non-LUSC tissues. The novel constructed ceRNA network incorporated 184 LUSC-specific lncRNAs, 18 miRNAs, and 49 mRNAs. About 11 of 184 differentially expressed lncRNAs and 1 of 18 differentially expressed miRNAs and 5 of 49 differentially expressed mRNAs were conspicuously related to overall survival (p < .05). Univariate and multivariate cox regression analysis showed that 6 lncRNAs were retrieved to construct a predictive model to predict the overall survival in LUSC patients. In conclusion, CeRNAs contributed to the progression of LUSC and a model with 6 lncRNAs might be potential biomarker for predicting the prognosis of LUSC. SN - 2169-141X UR - https://www.unboundmedicine.com/medline/citation/31364871/Identification_of_lncRNA_biomarkers_in_lung_squamous_cell_carcinoma_using_comprehensive_analysis_of_lncRNA_mediated_ceRNA_network_ L2 - http://www.tandfonline.com/doi/full/10.1080/21691401.2019.1647225 DB - PRIME DP - Unbound Medicine ER -