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27 May 2019 : Clinical Research  

Identification of a Combined RNA Prognostic Signature in Adenocarcinoma of the Lung

Si-Yu He1C, Wen-Jing Xi1D, Xin Wang1F, Chao-Han Xu1D, Liang Cheng1F, Si-Yao Liu1B, Qian-Qian Meng1C, Boyan Li1F, Yahui Wang1E, Hong-Bo Shi1D, Hong-Jiu Wang2B, Zhen-Zhen Wang1A*

DOI: 10.12659/MSM.913727

Med Sci Monit 2019; 25:3941-3956


BACKGROUND: Adenocarcinoma of the lung is a type of non-small cell lung cancer (NSCLC). Clinical outcome is associated with tumor grade, stage, and subtype. This study aimed to identify RNA expression profiles, including long noncoding RNA (lncRNA), microRNA (miRNA), and mRNA, associated with clinical outcome in adenocarcinoma of the lung using bioinformatics data.

MATERIAL AND METHODS: The miRNA and mRNA expression profiles were downloaded from The Cancer Genome Atlas (TCGA) database, and lncRNA expression profiles were downloaded from The Atlas of Noncoding RNAs in Cancer (TANRIC) database. The independent dataset, the Gene Expression Omnibus (GEO) accession dataset, GSE81089, was used. RNA expression profiles were used to identify comprehensive prognostic RNA signatures based on patient survival time.

RESULTS: From 7,704 lncRNAs, 787 miRNAs, and 28,937 mRNAs of 449 patients, four joint RNA molecular signatures were identified, including RP11-909N17.2, RP11-14N7.2 (lncRNAs), MIR139 (miRNA), KLHDC8B (mRNA). The random forest (RF) classifier was used to test the prediction ability of patient survival risk and showed a good predictive accuracy of 71% and also showed a significant difference in overall survival (log-rank P=0.0002; HR, 3.54; 95% CI, 1.74–7.19). The combined RNA signature also showed good performance in the identification of patient survival in the validation and independent datasets.

CONCLUSIONS: This study identified four RNA sequences as a prognostic molecular signature in adenocarcinoma of the lung, which may also provide an increased understanding of the molecular mechanisms underlying the pathogenesis of this malignancy.

Keywords: Biological Markers, Adenocarcinoma of Lung, Databases, Genetic, Gene Expression Profiling, Proportional Hazards Models, RNA, Messenger, ROC Curve

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DOI: 10.12659/MSM.945315

Med Sci Monit 2024; 30:e945315


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Medical Science Monitor eISSN: 1643-3750
Medical Science Monitor eISSN: 1643-3750