No abstract

BackgroundExosomes are one of the several types of cell-derived vesicles with a diameter of 30–100 nm. These extracellular vesicles are recognized as potential markers of human diseases such as cancer. However, their use in diagnostic tests requires an objective and high-throughput method to define their phenotype and determine their concentration in biological fluids. To identify circulating as well as cell culture-derived vesicles, the current standard is immunoblotting or a flow cytometrical analysis for specific proteins, both of which requires large amounts of purified vesicles.MethodsBased on the technology of protein microarray, we hereby present a highly sensitive Extracellular Vesicle (EV) Array capable of detecting and phenotyping exosomes and other extracellular vesicles from unpurified starting material in a high-throughput manner. To only detect the exosomes captured on the EV Array, a cocktail of antibodies against the tetraspanins CD9, CD63 and CD81 was used. These antibodies were selected to ensure that all exosomes captured are detected, and concomitantly excluding the detection of other types of microvesicles.ResultsThe limit of detection (LOD) was determined on exosomes derived from the colon cancer cell line LS180. It clarified that supernatant from only approximately 104 cells was needed to obtain signals or that only 2.5×104 exosomes were required for each microarray spot (~1 nL). Phenotyping was performed on plasma (1–10 µL) from 7 healthy donors, which were applied to the EV Array with a panel of antibodies against 21 different cellular surface antigens and cancer antigens. For each donor, there was considerable heterogeneity in the expression levels of individual markers. The protein profiles of the exosomes (defined as positive for CD9, CD63 and CD81) revealed that only the expression level of CD9 and CD81 was approximately equal in the 7 donors. This implies questioning the use of CD63 as a standard exosomal marker since the expression level of this tetraspanin was considerably lower.

BackgroundLung cancer is one of the leading causes of cancer-related death. At the time of diagnosis, more than half of the patients will have disseminated disease and, yet, diagnosing can be challenging. New methods are desired to improve the diagnostic work-up. Exosomes are cell-derived vesicles displaying various proteins on their membrane surfaces. In addition, they are readily available in blood samples where they constitute potential biomarkers of human diseases, such as cancer. Here, we examine the potential of distinguishing non-small cell lung carcinoma (NSCLC) patients from control subjects based on the differential display of exosomal protein markers.MethodsPlasma was isolated from 109 NSCLC patients with advanced stage (IIIa–IV) disease and 110 matched control subjects initially suspected of having cancer, but diagnosed to be cancer free. The Extracellular Vesicle Array (EV Array) was used to phenotype exosomes directly from the plasma samples. The array contained 37 antibodies targeting lung cancer-related proteins and was used to capture exosomes, which were visualised with a cocktail of biotin-conjugated CD9, CD63 and CD81 antibodies.ResultsThe EV Array analysis was capable of detecting and phenotyping exosomes in all samples from only 10 µL of unpurified plasma. Multivariate analysis using the Random Forests method produced a combined 30-marker model separating the two patient groups with an area under the curve of 0.83, CI: 0.77–0.90. The 30-marker model has a sensitivity of 0.75 and a specificity of 0.76, and it classifies patients with 75.3% accuracy.ConclusionThe EV Array technique is a simple, minimal-invasive tool with potential to identify lung cancer patients.

Overall, the use of EV analysis as a diagnostic and prognostic tool has prodigious clinical potential.

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.