Identification of microRNAs involved in pathways which characterize the expression subtypes of NSCLC

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.

Keywords: adenocarcinoma; expression subtypes; microRNA; non-small-cell lung cancer; pathway; predicted target; squamous cell carcinoma.

Figure 1

shows the frequency of the expression subtypes for AD and SCC in the Oslo cohort and the TCGA cohort.

Figure 2

Dunn’s test was applied to explore the microRNA expression between the molecular subtypes. The heatmaps display the P‐values (‐log10) from the test, where blue color means significantly different expressed microRNA, and dark‐red means not significantly expressed microRNA. We included the microRNAs that were significantly different in both the Oslo cohort and the TCGA cohorts. A. The P‐values obtained from Dunn’s test performed on adenocarcinomas (LUAD). B The P‐values obtained from Dunn’s test performed on SCC (LUSC).

Figure 3

shows the correlation between the subtype‐specific microRNAs and the hallmark gene set for AD and SCC in the Oslo cohort. Subtype annotation indicates which subtype the different microRNAs are associated with. To identify up‐ or downregulated pathways, the correlation coefficient for downregulated microRNAs (annotated with black/low) must be multiplied with −1 (this will switch the red pixels into blue and vice versa).