Clinical assessment of the miR-34, miR-200, ZEB1 and SNAIL EMT regulation hub underlines the differential prognostic value of EMT miRs to drive mesenchymal transition and prognosis in resected NSCLC

Abstract

Background: Patients with non-small cell lung cancer (NSCLC) receiving curative surgery have a risk of relapse, and adjuvant treatments only translate into a 5% increase in 5-year survival. We assessed the clinical significance of epithelial-mesenchymal transition (EMT) and explored its association with the [SNAIL/miR-34]:[ZEB/miR-200] regulation hub to refine prognostic information.

Methods: We validated a 7-gene EMT score using a consecutive series of 176 resected NSCLC. We quantified EMT transcription factors, microRNAs (miRs) of the miR-200, miR-34 families and miR-200 promoter hypermethylation to identify outcome predictors.

Results: Most tumours presented with an EMT-hybrid state and the EMT score was not predictive of outcome. Individually, all miR-200 were inversely associated with the EMT score, but only chromosome-1 miRs, miR-200a, b, 429, were associated with disease-free survival (p = 0.08, 0.05 and 0.025) and overall survival (p = 0.013, 0.003 and 0.006). We validated these associations on The Cancer Genome Atlas data. Tumour unsupervised clustering based on miR expression identified two good prognostic groups, unrelated to the EMT score, suggesting that miR profiling may have an important clinical value.

Conclusion: miR-200 family members do not have similar predictive value. Core EMT-miR, regulators and not EMT itself, identify NSCLC patients with a low risk of relapse after surgery.

Fig. 1. Correlation matrix of miR-34, miR-200, promoter methylation, epithelial and mesenchymal marker expression.

Circles represent the correlation coefficient when significant; the cross represents the absence of correlation.

Fig. 2. Unsupervised hierarchical clustering based on miR-34, miR-200 expression and promoter methylation status.

Five different clusters with differential methylation or miRs expression profiles are identified.

Fig. 3. Kaplan–Meier OS and RFS plots.

Disease-free survival according to miR-200a (a), miR-200b (b) and miR-429 (c) expressions. Overall survival according to miR-200a (d), miR-200b (e) and miR-429 (f) expressions.

Fig. 4. Kaplan–Meier OS and RFS plots.

Disease-free survival (a) and overall survival (b) according to different miR clusters showing two sub-groups, clusters 1 and 5, with low relapse risk (a) and longer OS (b). Disease-free survival (c) and overall survival (d) according to miR-200-chromosome-1 methylation status.