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A platform for artificial intelligence based identification of the extravasation potential of cancer cells into the brain metastatic niche.

ABSTRACT: 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 (?BBN) 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.

SUBMITTER: Oliver CR

PROVIDER: S-EPMC6510031 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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A platform for artificial intelligence based identification of the extravasation potential of cancer cells into the brain metastatic niche.

Oliver C Ryan CR Altemus Megan A MA Westerhof Trisha M TM Cheriyan Hannah H Cheng Xu X Dziubinski Michelle M Wu Zhifen Z Yates Joel J Morikawa Aki A Heth Jason J Castro Maria G MG Leung Brendan M BM Takayama Shuichi S Merajver Sofia D SD

Lab on a chip 20190301 7

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 ...[more]

PMID: 30810557

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Project description:Cancer progression towards metastasis follows a defined sequence of events described as the metastatic cascade. For extravasation and transendothelial migration metastatic cells interact first with endothelial cells. Yet the role of endothelial cells during the process of metastasis formation and extravasation is still unclear, and the interaction between metastatic and endothelial cells during transendothelial migration is poorly understood. Since tumor cells are well known to express TGF-?, and the compact endothelial layer undergoes a series of changes during metastatic extravasation (cell contact disruption, cytoskeletal reorganization, enhanced contractility), we hypothesized that an EndMT may be necessary for metastatic extravasation. We demonstrate that primary cultured rat brain endothelial cells (BEC) undergo EndMT upon TGF-?1 treatment, characterized by the loss of tight and adherens junction proteins, expression of fibronectin, ?1-integrin, calponin and ?-smooth muscle actin (SMA). B16/F10 cell line conditioned and activated medium (ACM) had similar effects: claudin-5 down-regulation, fibronectin and SMA expression. Inhibition of TGF-? signaling during B16/F10 ACM stimulation using SB-431542 maintained claudin-5 levels and mitigated fibronectin and SMA expression. B16/F10 ACM stimulation of BECs led to phosphorylation of Smad2 and Smad3. SB-431542 prevented SMA up-regulation upon stimulation of BECs with A2058, MCF-7 and MDA-MB231 ACM as well. Moreover, B16/F10 ACM caused a reduction in transendothelial electrical resistance, enhanced the number of melanoma cells adhering to and transmigrating through the endothelial layer, in a TGF-?-dependent manner. These effects were not confined to BECs: HUVECs showed TGF-?-dependent SMA expression when stimulated with breast cancer cell line ACM. Our results indicate that an EndMT may be necessary for metastatic transendothelial migration, and this transition may be one of the potential mechanisms occurring during the complex phenomenon known as metastatic extravasation.

Dataset Information

A platform for artificial intelligence based identification of the extravasation potential of cancer cells into the brain metastatic niche.

Publications

A platform for artificial intelligence based identification of the extravasation potential of cancer cells into the brain metastatic niche.

Similar Datasets

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