Identification of nine micro RNA s as potential biomarkers for lung adenocarcinoma

• Published in: FEBS open bio 2019-02, Vol.9 (2), p.315-327
• Main Authors: Ren, Zhi‐Peng, Hou, Xiao‐Bin, Tian, Xiao‐Dong, Guo, Jun‐Tang, Zhang, Lian‐Bin, Xue, Zhi‐Qiang, Deng, Jian‐Qing, Zhang, Shao‐Wei, Pan, Jun‐Yi, Chu, Xiang‐Yang
• Format: Article
• Language: English
• Subjects: Adenocarcinoma; Algorithms; Biomarkers; Classification; Decision trees; Encyclopedias; Gene expression; Genomes; Lung cancer; Medical prognosis; MicroRNAs; miRNA; Ontology; Software; Transcription; Tumors
• ISSN: 2211-5463; 2211-5463
• DOI: 10.1002/2211-5463.12572

Lung cancer is a leading global cause of cancer‐related death, and lung adenocarcinoma ( LUAD ) accounts for ~ 50% of lung cancer. Here, we screened for novel and specific biomarkers of LUAD by searching for differentially expressed mRNA s (DEmRNAs) and micro RNA s ( DE mi RNA s) in LUAD patient expression data within The Cancer Genome Atlas ( TCGA ). The identified optimal diagnostic mi RNA biomarkers were used to establish classification models (including support vector machine, decision tree, and random forest) to distinguish between LUAD and adjacent tissues. We then predicted the targets of identified optimal diagnostic mi RNA biomarkers, functionally annotated these target genes, and performed receiver operating characteristic curve analysis of the respective DE mi RNA biomarkers, their target DE m RNA s, and combinations of  DE mi RNA biomarkers. We validated the expression of selected DE mi RNA biomarkers by quantitative real‐time PCR ( qRT ‐ PCR ). In all, we identified a total of 13 DE mi RNA s, 2301 DE m RNA s and 232 DE mi RNA –target DE m RNA pairs between LUAD and adjacent tissues and selected nine DE mi RNA s ( hsa‐mir‐486‐1 , hsa‐mir‐486‐2 , hsa‐mir‐153 , hsa‐mir‐210 , hsa‐mir‐9‐1 , hsa‐mir‐9‐2 , hsa‐mir‐9‐3 , hsa‐mir‐577 , and hsa‐mir‐4732 ) as optimal LUAD ‐specific biomarkers with great diagnostic value. The predicted targets of these nine DE mi RNA s were significantly enriched in transcriptional misregulation in cancer and central carbon metabolism. Our qRT ‐ PCR results were generally consistent with our integrated analysis. In summary, our study identified nine DE mi RNA s that may serve as potential diagnostic biomarkers of LUAD . Functional annotation of their target DE m RNA s may provide information on their roles in LUAD.