Identification of microRNAs involved in pathways which characterize the expression subtypes of NSCLC. Issue 12 (22nd September 2019)

• Record Type: Journal Article
• Authors: Halvorsen, Ann Rita; Ragle Aure, Miriam; Õjlert, Åsa Kristina; Brustugun, Odd Terje; Solberg, Steinar; Nebdal, Daniel; Helland, Åslaug
• Is Part Of: Molecular oncology. Volume 13:Issue 12(2019)
• Page Start: 2604
• Page End: 2615
• Publication Date: 2019-09-22
• Subjects: adenocarcinoma -- expression subtypes -- microRNA -- non‐small‐cell lung cancer -- pathway -- predicted target -- squamous cell carcinoma; Cancer -- Molecular aspects -- Periodicals; 616.994005
• DOI: 10.1002/1878-0261.12571
• Languages: English
• ISSNs: 1574-7891

Abstract

Abstract : Dysregulation of microRNAs is a common mechanism in the development of lung cancer, but the relationship between microRNAs and expression subtypes in non‐small‐cell lung cancer (NSCLC) is poorly explored. Here, we analyzed microRNA expression from 241 NSCLC samples and correlated this with the expression subtypes of adenocarcinomas (AD) and squamous cell carcinomas (SCC) to identify microRNAs specific for each subtype. Gene set variation analysis and the hallmark gene set were utilized to calculate gene set scores specific for each sample, and these were further correlated with the expression of the subtype‐specific microRNAs. In ADs, we identified nine aberrantly regulated microRNAs in the terminal respiratory unit (TRU), three in the proximal inflammatory (PI), and nine in the proximal proliferative subtype (PP). In SCCs, 1, 5, 5, and 9 microRNAs were significantly dysregulated in the basal, primitive, classical, and secretory subtypes, respectively. The subtype‐specific microRNAs were highly correlated to specific gene sets, and a distinct pattern of biological processes with high immune activity for the AD PI and SCC secretory subtypes, and upregulation of cell cycle‐related processes in AD PP, SCC primitive, and SCC classical subtypes were found. Several in silico predicted targets within the gene sets were identified for the subtype‐specific microRNAs, underpinning the findings. The results were significantly validated in the LUAD ( n = 492) and LUSC ( n = 380) TCGA dataset (False discovery rates‐corrected P ‐value < 0.05). Our study provides novel insight into how expression subtypes determined with discrete biological processes may be regulated by subtype‐specific microRNAs. These results may have importance for the development of combinatory therapeutic strategies for lung cancer patients. Abstract : Aberrant expression of microRNAs is an important factor in lung cancer development and differs across different lung cancer expression subtypes. In this study, we identified subtype‐specific microRNAs which may be involved in essential processes characterizing the expression subtypes of ADs and SCCs. Several in silico predicted targets were found within the specific processes.