Browsing by Author "Nunez, Asael"

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    High-Throughput Acoustofluidic Fabrication of Tumor Spheroids
    (RSC, 2019) Chen, Bin; Wu, Yue; Ao, Zheng; Cai, Hongwei; Nunez, Asael; Liu, Yunhua; Foley, John; Nephew, Kenneth; Lu, Xiongbin; Guo, Feng; Medical and Molecular Genetics, School of Medicine
    Three-dimensional (3D) culture of multicellular spheroids, offering a desirable biomimetic microenvironment, is appropriate for recapitulating tissue cellular adhesive complexity and revealing a more realistic drug response. However, current 3D culture methods are suffering from low-throughput, poor controllability, intensive-labor, and variation in spheroid size, thus not ready for many high-throughput screening applications including drug discovery and toxicity testing. Herein, we developed a high-throughput multicellular spheroid fabrication method using acoustofluidics. By acoustically-assembling cancer cells with low-cost and disposable devices, our method can produce more than 12 000 multicellular aggregates within several minutes and allow us to transfer these aggregates into ultra-low attachment dishes for long-term culture. This method can generate more than 6000 tumor spheroids per operation, and reduce tumor spheroid formation time to one day. Our platform has advantages in forming spheroids with high throughput, short time, and long-term effectiveness, and is easy-to-operation. This acoustofluidic spheroid assembly method provides a simple and efficient way to produce large numbers of uniform-sized spheroids for biomedical applications in translational medicine, pharmaceutical industry and basic life science research.
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    Microfluidics guided by deep learning for cancer immunotherapy screening
    (National Academy of Science, 2022) Ao, Zheng; Cai, Hongwei; Wu, Zhuhao; Hu, Liya; Nunez, Asael; Zhou, Zhuolong; Liu, Hongcheng; Bondesson, Maria; Lu, Xiongbin; Lu, Xin; Dao, Ming; Guo, Feng; Medical and Molecular Genetics, School of Medicine
    Immune-cell infiltration and cytotoxicity to pathogens and diseased cells are ubiquitous in health and disease. To better understand immune-cell behavior in a 3D environment, we developed an automated high-throughput microfluidic platform that enables real-time imaging of immune-cell infiltration dynamics and killing of the target cancer cells. We trained a deep learning algorithm using clinical data and integrated the algorithm with our microfluidic platform to effectively identify epigenetic drugs that promote T cell tumor infiltration and enhance cancer immunotherapy efficacy both in vitro and in vivo. Our platform provides a unique method to investigate immune-tissue interactions, which can be widely applied to oncology, immunology, neurology, microbiology, tissue engineering, regenerative medicine, translational medicine, and so on.