Dataset Information

A Microdevice Platform Recapitulating Hypoxic Tumor Microenvironments.

ABSTRACT: Hypoxia plays a central role in cancer progression and resistance to therapy. We have engineered a microdevice platform to recapitulate the intratumor oxygen gradients that drive the heterogeneous hypoxic landscapes in solid tumors. Our design features a "tumor section"-like culture by incorporating a cell layer between two diffusion barriers, where an oxygen gradient is established by cellular metabolism and physical constraints. We confirmed the oxygen gradient by numerical simulation and imaging-based oxygen sensor measurement. We also demonstrated spatially-resolved hypoxic signaling in cancer cells through immunostaining, gene expression assay, and hypoxia-targeted drug treatment. Our platform can accurately generate and control oxygen gradients, eliminates complex microfluidic handling, allows for incorporation of additional tumor components, and is compatible with high-content imaging and high-throughput applications. It is well suited for understanding hypoxia-mediated mechanisms in cancer disease and other biological processes, and discovery of new therapeutics.

SUBMITTER: Ando Y

PROVIDER: S-EPMC5680268 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

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A Microdevice Platform Recapitulating Hypoxic Tumor Microenvironments.

Ando Yuta Y Ta Hoang P HP Yen Daniel P DP Lee Sang-Sin SS Raola Sneha S Shen Keyue K

Scientific reports 20171109 1

Hypoxia plays a central role in cancer progression and resistance to therapy. We have engineered a microdevice platform to recapitulate the intratumor oxygen gradients that drive the heterogeneous hypoxic landscapes in solid tumors. Our design features a "tumor section"-like culture by incorporating a cell layer between two diffusion barriers, where an oxygen gradient is established by cellular metabolism and physical constraints. We confirmed the oxygen gradient by numerical simulation and imag ...[more]

PMID: 29123197

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Project description:BackgroundWhile hypoxia has been well-studied in various tumor microenvironments, its role in cancer cell dormancy is poorly understood, in part due to a lack of well-established in vitro and in vivo models. Hypoxic conditions under conventional hypoxia chambers are relatively unstable and cannot be maintained during characterization outside the chamber since normoxic response is quickly established. To address this challenge, we report a robust in vitro cancer dormancy model under a hypoxia-mimicking microenvironment using cobalt chloride (CoCl2), a hypoxia-mimetic agent, which stabilizes hypoxia inducible factor 1-alpha (HIF1α), a major regulator of hypoxia signaling.MethodsWe compared cellular responses to CoCl2 and true hypoxia (0.1% O2) in different breast cancer cell lines (MCF-7 and MDA-MB-231) to investigate whether hypoxic regulation of breast cancer dormancy could be mimicked by CoCl2. To this end, expression levels of hypoxia markers HIF1α and GLUT1 and proliferation marker Ki67, cell growth, cell cycle distribution, and protein and gene expression were evaluated under both CoCl2 and true hypoxia. To further validate our platform, the ovarian cancer cell line OVCAR-3 was also tested.ResultsOur results demonstrate that CoCl2 can mimic hypoxic regulation of cancer dormancy in MCF-7 and MDA-MB-231 breast cancer cell lines, recapitulating the differential responses of these cell lines to true hypoxia in 2D and 3D. Moreover, distinct gene expression profiles in MCF-7 and MDA-MB-231 cells under CoCl2 treatment suggest that key cell cycle components are differentially regulated by the same hypoxic stress. In addition, the induction of dormancy in MCF-7 cells under CoCl2 treatment is HIF1α-dependent, as evidenced by the inability of HIF1α-suppressed MCF-7 cells to exhibit dormant behavior upon CoCl2 treatment. Furthermore, CoCl2 also induces and stably maintains dormancy in OVCAR-3 ovarian cancer cells.ConclusionsThese results demonstrate that this CoCl2-based model could provide a widely applicable in vitro platform for understanding induction of cancer cell dormancy under hypoxic stress.

Project description:While it has been established that a number of microenvironment components can affect the likelihood of metastasis, the link between microenvironment and tumor cell phenotypes is poorly understood. Here we have examined microenvironment control over two different tumor cell motility phenotypes required for metastasis. By high-resolution multiphoton microscopy of mammary carcinoma in mice, we detected two phenotypes of motile tumor cells, different in locomotion speed. Only slower tumor cells exhibited protrusions with molecular, morphological, and functional characteristics associated with invadopodia. Each region in the primary tumor exhibited either fast- or slow-locomotion. To understand how the tumor microenvironment controls invadopodium formation and tumor cell locomotion, we systematically analyzed components of the microenvironment previously associated with cell invasion and migration. No single microenvironmental property was able to predict the locations of tumor cell phenotypes in the tumor if used in isolation or combined linearly. To solve this, we utilized the support vector machine (SVM) algorithm to classify phenotypes in a nonlinear fashion. This approach identified conditions that promoted either motility phenotype. We then demonstrated that varying one of the conditions may change tumor cell behavior only in a context-dependent manner. In addition, to establish the link between phenotypes and cell fates, we photoconverted and monitored the fate of tumor cells in different microenvironments, finding that only tumor cells in the invadopodium-rich microenvironments degraded extracellular matrix (ECM) and disseminated. The number of invadopodia positively correlated with degradation, while the inhibiting metalloproteases eliminated degradation and lung metastasis, consistent with a direct link among invadopodia, ECM degradation, and metastasis. We have detected and characterized two phenotypes of motile tumor cells in vivo, which occurred in spatially distinct microenvironments of primary tumors. We show how machine-learning analysis can classify heterogeneous microenvironments in vivo to enable prediction of motility phenotypes and tumor cell fate. The ability to predict the locations of tumor cell behavior leading to metastasis in breast cancer models may lead towards understanding the heterogeneity of response to treatment.

Dataset Information

A Microdevice Platform Recapitulating Hypoxic Tumor Microenvironments.

Publications

A Microdevice Platform Recapitulating Hypoxic Tumor Microenvironments.

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