Exosomes are endosome‐derived vesicles enriched in body fluids such as urine, blood, and saliva. So far, they have been recognized as potential biomarkers for cancer diagnostics. However, the present single‐variate analysis of exosomes has greatly limited the accuracy and specificity of diagnoses. Besides, most diagnostic approaches focus on bulk analysis using lots of exosomes and tend to be less accurate because they are vulnerable to impure extraction and concentration differences of exosomes. To address these challenges, a quantitative analysis platform is developed to implement a sequential quantification analysis of multiple exosomal surface biomarkers at the single‐exosome level, which utilizes DNA‐PAINT and a machine learning algorithm to automatically analyze the results. As a proof of concept, the profiling of four exosomal surface biomarkers (HER2, GPC‐1, EpCAM, EGFR) is developed to identify exosomes from cancer‐derived blood samples. Then, this technique is further applied to detect pancreatic cancer and breast cancer from unknown samples with 100% accuracy.

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Exosomes are small homogenous membrane vesicles that derive from the exocytosis process of cells and can contain DNA, microRNAs (miRNAs), and/or proteins. Characterization of the content profile of exosomes may reflect the state of the cells that release them, and this could be predictive of disease. In this study, to explore the potential biomarkers for melanoma, we isolated serous exosomes from 30 patients with melanoma and 30 healthy individuals using the ultracentrifugation method. Five miRNAs were subsequently detected in each sample by quantitative reverse transcription-PCR: miRNA-532-5p, miRNA-106b, miRNA-200c, miRNA-199a-5p, and miRNA-210. Only the levels of exo-miRNA-532-5p and exo-miRNA-106b differed between the two groups (Z=-4.17 and -4.57, respectively, P<0.0001). When these two miRNAs were evaluated individually and in combination in 95 melanoma patients and 95 healthy individuals serum samples, the area under the receiver operating characteristic curve values were 0.867, 0.820, and 0.936, respectively. Furthermore, in blinded tests of samples from 25 melanoma patients and 25 healthy individuals, this panel of miRNAs identified 23/25 patients with melanoma (92.0% sensitivity) and 22/25 healthy individuals (88.0% sensitivity). Our exo-miRNA panel also distinguished patients with metastasis from those without metastasis, patients with stage I-II disease from those with stage III-IV disease, and patients who had received pembrolizumab treatment from those who were untreated. Overall, these results indicate that serum exosomal miRNAs, especially exo-miRNA-532-5p and exo-miRNA-106b, have the potential to be used for monitoring and/or a diagnosis of melanoma in a clinical setting.