Circulating cell-free and extracellular vesicles-derived microRNA as prognostic biomarkers in patients with early-stage NSCLC: results from RESTING study

Abstract

Background: Factors to accurately stratify patients with early-stage non-small cell lung cancer (NSCLC) in different prognostic groups are still needed. This study aims to investigate 1) the prognostic potential of circulating cell-free (CF) and extracellular vesicles (EVs)-derived microRNA (miRNAs), and 2) their added value with respect to known prognostic factors (PFs).

Methods: The RESTING study is a multicentre prospective observational cohort study on resected stage IA-IIIA patients with NSCLC. The primary end-point was disease-free survival (DFS), and the main analyses were carried out separately for CF- and EV-miRNAs. CF- and EV-miRNAs were isolated from plasma, and miRNA-specific libraries were prepared and sequenced. To reach the study aims, three statistical models were specified: one using the miRNA data only (Model 1); one using both miRNAs and known PFs (age, gender, and pathological stage) (Model 2), and one using the PFs alone (Model 3). Five-fold cross-validation (CV) was used to assess the predictive performance of each. Standard Cox regression and elastic net regularized Cox regression were used.

Results: A total of 222 patients were enrolled. The median follow-up time was 26.3 (95% CI 25.4-27.6) months. From Model 1, three CF-miRNAs and 21 EV-miRNAs were associated with DFS. In Model 2, two CF-miRNAs (miR-29c-3p and miR-877-3p) and five EV-miRNAs (miR-181a-2-3p, miR-182-5p, miR-192-5p, miR-532-3p and miR-589-5p) remained associated with DFS. From pathway enrichment analysis, TGF-beta and NOTCH were the most involved pathways.

Conclusion: This study identified promising prognostic CF- and EV-miRNAs that could be used as a non-invasive, cost-effective tool to aid clinical decision-making. However, further evaluation of the obtained miRNAs in an external cohort of patients is warranted.

Fig. 1

Performance of the models using cell-free miRNA data. From (A) to (C) 5-fold cross-validated Kaplan–Meier curves for the models derived using the miRNA data alone, miRNA and and basic prognostic factors (age, sex, and pathologic stage) data, and the prognostic factors data alone. From (D) to (F) Five-fold cross-validated time-dependent ROC curves (at 24 months) for the three models. DFS disease-free survival, TP true positive, FP false positive

Fig. 2

Performance of the models using extracellular vesicle miRNA data. From (A) to (C) 5-fold cross-validated Kaplan–Meier curves for the models derived using the miRNA data alone, miRNA and basic prognostic factors (age, sex, and pathologic stage) data, and prognostic factors data alone. From (D) to (F) Five-fold cross-validated time-dependent ROC curves (at 24 months) for the three models. DFS disease-free survival, TP true positive, FP false positive

Fig. 3

Pathway enrichment. A Bubble plot showing the most enriched pathways of 24 miRNAs (3 CF-miRNAs and the 21 EV-miRNAs) associated with disease-free survival. B Most significant enriched pathways targeted by EV-miRNAs under expressed in patients with worse outcome C Heatmap showing normalized expression levels of the 8 enriched miRNAs targeting TGF-beta pathways. Patients alive and not relapsed within 24 months are shown in green (on the right) whereas patients encountering disease relapse or death within 24 months are indicated in red (on the left). D) Kaplan Meier curves for disease-free survival for each miRNA