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Exosomes have been suggested as promising biomarkers in NSCLC because they contain proteins from their originating cells and are readily available in plasma. In this study, we explored the potential of exosome protein profiling in diagnosing lung cancers of all stages and various histological subtypes in patients.Plasma was isolated from 581 patients (431 with lung cancer and 150 controls). The extracellular vesicle array was used to phenotype exosomes. The extracellular vesicle 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. Multimarker models were made by combining two or more markers. The optimal multimarker model was evaluated by area under the curve (AUC) and random forests analysis.The markers CD151, CD171, and tetraspanin 8 were the strongest separators of patients with cancer of all histological subtypes versus patients without cancer (CD151: AUC = 0.68, p = 0.0002; CD171: AUC = 0.60, p = 0.0002; and TSPAN8: AUC = 0.60, p = 0.0002). The multimarker models with the largest AUC in the cohort of patients with all lung cancer histological subtypes and in the cohort of patients with adenocarcinoma only covered 10 markers (all cancer: AUC = 0.74 [95% confidence interval: 0.70–0.80]; adenocarcinoma only: AUC = 0.76 [95% confidence interval: 0.70–0.83]). In squamous cell cancer and SCLC, multimarker models did not exceed CD151 as an individual marker in separating patients with cancer from controls.We have demonstrated exosome protein profiling to be a promising diagnostic tool in lung cancer independently of stage and histological subtype. Multimarker models could make a fair separation of patients, demonstrating the perspectives of exosome protein profiling as a biomarker.