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Tumor cells and their crosstalk with endothelial cells in 3D spheroids

Recapitulating the tumor microenvironment is a central challenge in the development of experimental model for cancer. To provide a reliable tool for drug development and for personalized cancer therapy, it is critical to maintain key features that  exist in the original tumor. Along with this effort...

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Detalles Bibliográficos
Autores principales: Shoval, Hila, Karsch-Bluman, Adi, Brill-Karniely, Yifat, Stern, Tal, Zamir, Gideon, Hubert, Ayala, Benny, Ofra
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5585367/
https://www.ncbi.nlm.nih.gov/pubmed/28874803
http://dx.doi.org/10.1038/s41598-017-10699-y
Descripción
Sumario:Recapitulating the tumor microenvironment is a central challenge in the development of experimental model for cancer. To provide a reliable tool for drug development and for personalized cancer therapy, it is critical to maintain key features that  exist in the original tumor. Along with this effort, 3-dimentional (3D) cellular models are being extensively studied. Spheroids are self-assembled cell aggregates that possess many important components of the physiological spatial growth and cell-cell interactions. In this study we aimed to investigate the interconnection between tumor and endothelial cells (EC) in hybrid spheroids containing either tumor cell (TC) lines or patient derived cancer cells. Preparation protocols of hybrid spheroids were optimized and their morphology and tissue-like features were analyzed. Our finding show that capillary-like structures are formed upon assembly and growth of TC:EC spheroids and that spheroids’ shape and surface texture may be an indication of spatial invasiveness of cells in the extra-cellular matrix (ECM). Establishing a model of hybrid tumor/stroma spheroids has a crucial importance in the experimental approach for personalized medicine, and may offer a reliable and low-cost method for the goal of predicting drug effects.