The use of lncRNA analysis for stratification management of prognostic risk in patients with NSCLC.

Abstract Lung cancer is the most frequent cancer in China and worldwide. Long noncoding RNAs (lncRNAs) have been shown to play important regulatory roles in human cancer biology. The aim of the present study was to investigate the relationship between genomics and prognosis among lung cancer patients. We collected specimens from non-small cell lung cancer (NSCLC) patients after surgery. Q-PCR was performed to investigate the expression level of lncRNAs in cancerous and adjacent normal tissue. Patients were divided into different risk groups according to lncRNA expression levels and then follow-up. The lncRNAs HOTAIR, H19 and MALAT1 were up-regulated, while PANDAR and TUG1 were down-regulated in NSCLC cancer tissues compared with the corresponding adjacent normal tissue. After two years of follow-up time, the disease-free survival time (DFS) curves were significantly different between the high-risk, moderate-risk and low-risk patient groups. Our results suggest that lncRNAs are involved in the process of NSCLC and that the use of genetic analysis for stratification management of prognostic risk could help us to implement individualized treatment for patients with NSCLC and ultimately to improve the patient prognosis.