Abstract

Background Extracellular vesicles (EVs) have shown great potential for targeted therapy, as they have a natural ability to pass through biological barriers and, depending on their origin, can preferentially accumulate at defined sites, including tumors. Analyzing the potential of EVs to target specific cells remains challenging, considering the unspecific binding of lipophilic tracers to other proteins, the limitations of fluorescence for deep tissue imaging and the effect of external labeling strategies on their natural tropism. In this work, we determined the cell-type specific tropism of B16F10-EVs towards cancer cell and metastatic tumors by using fluorescence analysis and quantitative gold labeling measurements. Surface functionalization of plasmonic gold nanoparticles was used to promote indirect labeling of EVs without affecting size distribution, polydispersity, surface charge, protein markers, cell uptake or in vivo biodistribution. Double-labeled EVs with gold and fluorescent dyes were injected into animals developing metastatic lung nodules and analyzed by fluorescence/computer tomography imaging, quantitative neutron activation analysis and gold-enhanced optical microscopy. Results We determined that B16F10 cells preferentially take up their own EVs, when compared with colon adenocarcinoma, macrophage and kidney cell-derived EVs. In addition, we were able to detect the preferential accumulation of B16F10 EVs in small metastatic tumors located in lungs when compared with the rest of the organs, as well as their precise distribution between tumor vessels, alveolus and tumor nodules by histological analysis. Finally, we observed that tumor EVs can be used as effective vectors to increase gold nanoparticle delivery towards metastatic nodules. Conclusions Our findings provide a valuable tool to study the distribution and interaction of EVs in mice and a novel strategy to improve the targeting of gold nanoparticles to cancer cells and metastatic nodules by using the natural properties of malignant EVs.