C. Ryan Oliver, Megan A. Altemus, Trisha M. Westerhof, Hannah Cheriyan, Xu Cheng, Michelle Dziubinski, Zhifen Wu, Joel Yates, Aki Morikawa, Jason Heth, Maria G. Castro, Brendan M. Leung, Shuichi Takayama, Sofia D. Merajver. A platform for artificial intelligence based identification of the extravasation potential of cancer cells into the brain metastatic niche. (2019) LAB ON A CHIP 2019. [DOI: 10.1039/C8LC01387J ]
Brain metastases are the most lethal complication of advanced cancer; therefore, it is critical to identify when a tumor has the potential to metastasize to the brain. There are currently no interventions that shed light on the potential of primary tumors to metastasize to the brain. We constructed and tested a platform to quantitatively profile the dynamic phenotypes of cancer cells from aggressive triple negative breast cancer cell lines and patient derived xenografts (PDXs), generated from a primary tumor and brain metastases from tumors of diverse organs of origin. Combining an advanced live cell imaging algorithm and artificial intelligence, we profile cancer cell extravasation within a microfluidic blood-brain niche (µBBN) chip, to detect the minute differences between cells with brain metastatic potential and those without with a PPV of 0.91 in the context of this study. The results show remarkably sharp and reproducible distinction between cells that do and those which do not metastasize inside of the device.
Disclaimer: The PDF documents on this webpage are provided for educational and personal purposes alone and are subject to copyrights of the respective publishers.
