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Identification of a Combined RNA Prognostic Signature in Adenocarcinoma of the Lung.
- Source :
-
Medical science monitor : international medical journal of experimental and clinical research [Med Sci Monit] 2019 May 27; Vol. 25, pp. 3941-3956. Date of Electronic Publication: 2019 May 27. - Publication Year :
- 2019
-
Abstract
- 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.
- Subjects :
- Adenocarcinoma genetics
Carcinoma, Non-Small-Cell Lung genetics
Databases, Genetic
Female
Gene Expression Regulation, Neoplastic genetics
Humans
Kaplan-Meier Estimate
Lung Neoplasms pathology
Male
MicroRNAs genetics
Prognosis
Proportional Hazards Models
RNA, Long Noncoding genetics
RNA, Messenger genetics
ROC Curve
Survival Analysis
Adenocarcinoma of Lung genetics
Gene Expression Profiling methods
Transcriptome genetics
Subjects
Details
- Language :
- English
- ISSN :
- 1643-3750
- Volume :
- 25
- Database :
- MEDLINE
- Journal :
- Medical science monitor : international medical journal of experimental and clinical research
- Publication Type :
- Academic Journal
- Accession number :
- 31132294
- Full Text :
- https://doi.org/10.12659/MSM.913727