Label-free visualization and characterization of extracellular vesicles in breast cancer
Menée à l'aide de modèles murins de tumeur et d'échantillons de tissus mammaires prélevés sur des patientes atteintes d'un cancer du sein, cette étude présente une méthode optique, basée sur les propriétés fluorescentes de composés impliqués dans les réactions métaboliques (flavine adénine dinucléotide, nicotinamide adénine dinucléotide phosphate), pour analyser la distribution spatiale et les caractéristiques des vésicules extracellulaires tumorales
Direct in vivo identification and characterization of extracellular vesicles (EVs) in the authentic tumor microenvironment is essential for understanding cancer progression and developing new clinical biomarkers. Here, we introduce an optical-signature-based approach for visualizing, characterizing, and tracking EVs in unperturbed living systems by profiling their intrinsic metabolic and structural contrasts. Imaging of living tumor-bearing animals and fresh excised human breast tissue revealed abundance of NAD(P)H-rich EVs within the tumor, near the tumor boundary, and around vessel structures. In addition, the percentage of NAD(P)H-rich EVs is highly correlated with the human breast cancer diagnosis, which emphasizes the important role of metabolic imaging for EV characterization as well as for clinical applications.Despite extensive interest, extracellular vesicle (EV) research remains technically challenging. One of the unexplored gaps in EV research has been the inability to characterize the spatially and functionally heterogeneous populations of EVs based on their metabolic profile. In this paper, we utilize the intrinsic optical metabolic and structural contrast of EVs and demonstrate in vivo/in situ characterization of EVs in a variety of unprocessed (pre)clinical samples. With a pixel-level segmentation mask provided by the deep neural network, individual EVs can be analyzed in terms of their optical signature in the context of their spatial distribution. Quantitative analysis of living tumor-bearing animals and fresh excised human breast tissue revealed abundance of NAD(P)H-rich EVs within the tumor, near the tumor boundary, and around vessel structures. Furthermore, the percentage of NAD(P)H-rich EVs is highly correlated with human breast cancer diagnosis, which emphasizes the important role of metabolic imaging for EV characterization as well as its potential for clinical applications. In addition to the characterization of EV properties, we also demonstrate label-free monitoring of EV dynamics (uptake, release, and movement) in live cells and animals. The in situ metabolic profiling capacity of the proposed method together with the finding of increasing NAD(P)H-rich EV subpopulations in breast cancer have the potential for empowering applications in basic science and enhancing our understanding of the active metabolic roles that EVs play in cancer progression.
Proceedings of the National Academy of Sciences , résumé, 2018