Exosomal Proteins as a Diagnostic Biomarkers in Lung Cancer

BACKGROUND: Exosomes have been suggested as promising biomarkers in non-small cell lung cancer (NSCLC), since they contain proteins from their originating cells and are readily available in plasma. In this study, we explore the potential of exosome protein profiling in diagnosing lung cancer patients of all stages and various histological subtypes.

METHODS: Plasma was isolated from 581 patients (431 with lung cancer, 150 controls). The Extracellular Vesicle (EV) Array was used to phenotype exosomes. The EV Array contained 49 antibodies for capturing exosomes. Subsequently, a cocktail of biotin-conjugated CD9, CD81 and CD63 antibodies was used to detect and visualize captured exosomes. Multi-marker models were made combining two or more markers. The optimal multi-marker model was evaluated by Area under the curve (AUC) and Random Forests analysis.

RESULTS: The markers CD151, CD171 and Tspan8 were the strongest separators of cancer of all histologies versus non-cancer patients (CD151: AUC=0.68; p=0.0002, CD171: AUC=0.60; p=0.0002, Tspan8: AUC=0.60; p=0.0002). The multi-marker models with the largest AUC in the cohort of all lung cancer histologies (C) and the cohort of only adenocarcinoma (AC) covered 10 markers (C: AUC=0.74 (95%CI 0.70 - 0.80), AC: AUC=0.76 (95%CI 0.70 - 0.83)). In squamous-cell-cancer and small cell lung cancer, multi-marker models did not exceed CD151 as an individual marker in separating cancer patients from controls.

CONCLUSION: We demonstrate exosome protein profiling as a promising diagnostic tool in lung cancer independently of stage and histology. Multi-marker models could make a fair separation of patients demonstrating the perspectives of exosome-protein-profiling as a biomarker.