Profiling Plasma Extracellular Vesicle Metabotypes and miRNAs: An Unobserved Clue for Predicting Relapse in Patients with Early-Stage NSCLC.

Background And Objective: Lung cancer, the second most prevalent cancer globally, poses significant challenges in early detection and prognostic assessment. Despite advancements in targeted therapies and immunotherapy, the timely identification of relapse remains elusive. Blood-based liquid biopsy biomarkers, including circulating tumor cells (CTCs), cell-free DNA (cfDNA), circulating tumor DNA (ctDNA), circulating-free RNAs (cfRNAs), and extracellular vesicles (EVs)/exosomes, offer promise for non-invasive monitoring.

Methods: We employ a comprehensive approach integrating miRNA/lncRNA/metabolomic datasets, following a mixed-methods content analysis, to identify candidate biomarkers in NSCLC. NSCLC-associated miRNA/gene/lncRNA associations were linked to in silico-derived molecular pathways.

Results: For data validation, mass spectrometry-based untargeted metabolomics of plasma EVs highlighted miRNA/lncRNA/metabotypes, linking "glycerophospholipid metabolism" to and "alanine, aspartate and glutamate metabolism" to . Prognostic significance was established for , showing lower expression in NSCLC patients with disease progression compared to stable disease ( = 0.004). Kaplan-Meier survival analysis indicated that patients with under-expression had significantly shorter overall survival (OS) ( = 0.038). Despite the expression of in plasma EVs being undetected, its expression in plasma cfRNAs correlated significantly with disease progression ( = 0.035).

Conclusions: Herein, we showcase the potential of plasma EV-derived as a prognostic biomarker and underscore the intricate interplay of miRNAs, lncRNAs, and metabolites in NSCLC biology. Our findings offer new insights and avenues for further exploration, contributing to the ongoing quest for effective biomarkers in early-stage NSCLC.