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CancerCellTracker: a brightfield time-lapse microscopy framework for cancer drug sensitivity estimation.
Jiang, Qibing; Sudalagunta, Praneeth; Silva, Maria C; Canevarolo, Rafael R; Zhao, Xiaohong; Ahmed, Khandakar Tanvir; Alugubelli, Raghunandan Reddy; DeAvila, Gabriel; Tungesvik, Alexandre; Perez, Lia; Gatenby, Robert A; Gillies, Robert J; Baz, Rachid; Meads, Mark B; Shain, Kenneth H; Silva, Ariosto S; Zhang, Wei.
Afiliación
  • Jiang Q; Department of Computer Science, University of Central Florida, Orlando, FL 32816, USA.
  • Sudalagunta P; Departments of Malignant Hematology and Chemical Biology and Molecular Medicine, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA.
  • Silva MC; Departments of Malignant Hematology and Chemical Biology and Molecular Medicine, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA.
  • Canevarolo RR; Departments of Malignant Hematology and Chemical Biology and Molecular Medicine, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA.
  • Zhao X; Departments of Malignant Hematology and Chemical Biology and Molecular Medicine, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA.
  • Ahmed KT; Department of Computer Science, University of Central Florida, Orlando, FL 32816, USA.
  • Alugubelli RR; Departments of Malignant Hematology and Chemical Biology and Molecular Medicine, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA.
  • DeAvila G; Departments of Malignant Hematology and Chemical Biology and Molecular Medicine, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA.
  • Tungesvik A; Departments of Malignant Hematology and Chemical Biology and Molecular Medicine, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA.
  • Perez L; Departments of Malignant Hematology and Chemical Biology and Molecular Medicine, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA.
  • Gatenby RA; Departments of Malignant Hematology and Chemical Biology and Molecular Medicine, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA.
  • Gillies RJ; Departments of Malignant Hematology and Chemical Biology and Molecular Medicine, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA.
  • Baz R; Departments of Malignant Hematology and Chemical Biology and Molecular Medicine, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA.
  • Meads MB; Departments of Malignant Hematology and Chemical Biology and Molecular Medicine, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA.
  • Shain KH; Departments of Malignant Hematology and Chemical Biology and Molecular Medicine, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA.
  • Silva AS; Departments of Malignant Hematology and Chemical Biology and Molecular Medicine, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA.
  • Zhang W; Department of Computer Science, University of Central Florida, Orlando, FL 32816, USA.
Bioinformatics ; 38(16): 4002-4010, 2022 08 10.
Article en En | MEDLINE | ID: mdl-35751591
MOTIVATION: Time-lapse microscopy is a powerful technique that relies on images of live cells cultured ex vivo that are captured at regular intervals of time to describe and quantify their behavior under certain experimental conditions. This imaging method has great potential in advancing the field of precision oncology by quantifying the response of cancer cells to various therapies and identifying the most efficacious treatment for a given patient. Digital image processing algorithms developed so far require high-resolution images involving very few cells originating from homogeneous cell line populations. We propose a novel framework that tracks cancer cells to capture their behavior and quantify cell viability to inform clinical decisions in a high-throughput manner. RESULTS: The brightfield microscopy images a large number of patient-derived cells in an ex vivo reconstruction of the tumor microenvironment treated with 31 drugs for up to 6 days. We developed a robust and user-friendly pipeline CancerCellTracker that detects cells in co-culture, tracks these cells across time and identifies cell death events using changes in cell attributes. We validated our computational pipeline by comparing the timing of cell death estimates by CancerCellTracker from brightfield images and a fluorescent channel featuring ethidium homodimer. We benchmarked our results using a state-of-the-art algorithm implemented in ImageJ and previously published in the literature. We highlighted CancerCellTracker's efficiency in estimating the percentage of live cells in the presence of bone marrow stromal cells. AVAILABILITY AND IMPLEMENTATION: https://github.com/compbiolabucf/CancerCellTracker. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias / Antineoplásicos Tipo de estudio: Diagnostic_studies / Prognostic_studies Límite: Humans Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias / Antineoplásicos Tipo de estudio: Diagnostic_studies / Prognostic_studies Límite: Humans Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido