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Journal of Cancer Research and Clinical Oncology

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02.03.2020 | Original Article – Cancer Research

Candidate lncRNA–microRNA–mRNA networks in predicting non-small cell lung cancer and related prognosis analysis

verfasst von: Sixuan Li, Zhigang Cui, Yuxin Zhao, Shuwen Ma, Yinghui Sun, Hang Li, Min Gao, Na Li, Ying Wang, Lianwei Tong, Mingyang Song, Zhihua Yin

Erschienen in: Journal of Cancer Research and Clinical Oncology | Ausgabe 4/2020

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Abstract

Purpose

The role of non-coding RNA, once thought to be dark matter, is increasingly prominent in cancer. Our article explores the effect of non-coding RNA in lung adenocarcinoma and lung squamous cell carcinoma by mining TCGA public database.

Methods

Download the data by applying the official TCGA software. The data were analyzed by R data analysis packages, ‘edgeR’, ‘gplots’ and ‘survival’. We better illustrate the potential networks of lung cancer genes by constructing ceRNAs, using Cytoscape software.

Results

We obtained genes which were differentially expressed in lung adenocarcinoma and lung squamous cell carcinoma analysis. Within these differentially expressed genes, we also conducted a survival analysis to find differentially expressed genes associated with prognosis in both lung adenocarcinoma and lung squamous cell carcinoma. Based on genes differentially expressed of both lung adenocarcinoma and lung squamous cell carcinoma, we constructed a ceRNA network to illustrate the mechanism of lung adenocarcinoma and lung squamous cell carcinoma. Our study analyzed genes which were differentially expressed in lung adenocarcinoma and lung squamous cell carcinoma using the TCGA database.

Conclusion

Based on this, the prognosis in both lung squamous cell carcinoma and lung adenocarcinoma was analyzed. We have also constructed a ceRNA network to provide a basis for the study of ceRNA in lung adenocarcinoma and lung squamous cell carcinoma.

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Titel: Candidate lncRNA–microRNA–mRNA networks in predicting non-small cell lung cancer and related prognosis analysis
verfasst von: Sixuan Li
Zhigang Cui
Yuxin Zhao
Shuwen Ma
Yinghui Sun
Hang Li
Min Gao
Na Li
Ying Wang
Lianwei Tong
Mingyang Song
Zhihua Yin
Publikationsdatum: 02.03.2020
Verlag: Springer Berlin Heidelberg
Erschienen in: Journal of Cancer Research and Clinical Oncology / Ausgabe 4/2020
Print ISSN: 0171-5216
Elektronische ISSN: 1432-1335
DOI: https://doi.org/10.1007/s00432-020-03161-6

Springer Medizin

Candidate lncRNA–microRNA–mRNA networks in predicting non-small cell lung cancer and related prognosis analysis