Longitudinal, label-free, quantitative tracking of cell death and viability in a 3D tumor model with OCT

Three-dimensional in vitro tumor models are highly useful tools for studying tumor growth and treatment response of malignancies such as ovarian cancer. Existing viability and treatment assessment assays, however, face shortcomings when applied to these large, complex, and heterogeneous culture systems. Optical coherence tomography (OCT) is a noninvasive, label-free, optical imaging technique that can visualize live cells and tissues over time with subcellular resolution and millimeters of optical penetration depth. Here, we show that OCT is capable of carrying out high-content, longitudinal assays of 3D culture treatment response. We demonstrate the usage and capability of OCT for the dynamic monitoring of individual and combination therapeutic regimens in vitro, including both chemotherapy drugs and photodynamic therapy (PDT) for ovarian cancer. OCT was validated against the standard LIVE/DEAD Viability/Cytotoxicity Assay in small tumor spheroid cultures, showing excellent correlation with existing standards. Importantly, OCT was shown to be capable of evaluating 3D spheroid treatment response even when traditional viability assays failed. OCT 3D viability imaging revealed synergy between PDT and the standard-of-care chemotherapeutic carboplatin that evolved over time. We believe the efficacy and accuracy of OCT in vitro drug screening will greatly contribute to the field of cancer treatment and therapy evaluation.

[1]  J. Schmitt,et al.  Speckle in optical coherence tomography. , 1999, Journal of biomedical optics.

[2]  R. Ozols Ovarian Cancer: American Cancer Society Atlas of Clinical Oncology , 2003 .

[3]  J. Schorge,et al.  Evidence for cancer stem cells contributing to the pathogenesis of ovarian cancer. , 2011, Frontiers in bioscience.

[4]  C. Evans,et al.  Longitudinal, quantitative monitoring of therapeutic response in 3D in vitro tumor models with OCT for high-content therapeutic screening. , 2014, Methods.

[5]  Delia Cabrera DeBuc,et al.  Fractal-based analysis of optical coherence tomography data to quantify retinal tissue damage , 2014, BMC Bioinformatics.

[6]  Alex Cable,et al.  Automated quantification of microstructural dimensions of the human kidney using optical coherence tomography (OCT). , 2009, Optics express.

[7]  Conor L Evans,et al.  Label-Free, Longitudinal Visualization of PDT Response In Vitro with Optical Coherence Tomography. , 2012, Israel journal of chemistry.

[8]  Oliver J. Klein,et al.  In vitro optimization of EtNBS-PDT against hypoxic tumor environments with a tiered, high-content, 3D model optical screening platform. , 2012, Molecular pharmaceutics.

[9]  Ruikang K. Wang,et al.  Theory, developments and applications of optical coherence tomography , 2005 .

[10]  T. Foster,et al.  ALA- and ALA-hexylester-induced protoporphyrin IX fluorescence and distribution in multicell tumour spheroids , 2001, British Journal of Cancer.

[11]  Tayyaba Hasan,et al.  Killing Hypoxic Cell Populations in a 3D Tumor Model with EtNBS-PDT , 2011, PloS one.

[12]  D. Roberts,et al.  CD133 Expression Defines a Tumor Initiating Cell Population in Primary Human Ovarian Cancer , 2009, Stem cells.

[13]  Paolo G. V. Martini,et al.  timeClip: pathway analysis for time course data without replicates , 2014, BMC Bioinformatics.

[14]  E. Roussakis,et al.  Oxygen-Sensing Methods in Biomedicine from the Macroscale to the Microscale. , 2015, Angewandte Chemie.

[15]  James R. Downing,et al.  Annual review of pathology : mechanisms of disease , 2006 .

[16]  D. Montell,et al.  Ovarian Cancer Metastasis: Integrating insights from disparate model organisms , 2005, Nature Reviews Cancer.

[17]  G. Ripandelli,et al.  Optical coherence tomography. , 1998, Seminars in ophthalmology.

[18]  Tayyaba Hasan,et al.  Synergistic enhancement of carboplatin efficacy with photodynamic therapy in a three-dimensional model for micrometastatic ovarian cancer. , 2010, Cancer research.

[19]  C. Mohan,et al.  Classifying murine glomerulonephritis using optical coherence tomography and optical coherence elastography , 2016, Journal of biophotonics.

[20]  Tayyaba Hasan,et al.  In vitro ovarian tumor growth and treatment response dynamics visualized with time-lapse OCT imaging. , 2009, Optics express.

[21]  Tayyaba Hasan,et al.  Imaging and photodynamic therapy: mechanisms, monitoring, and optimization. , 2010, Chemical reviews.

[22]  Tayyaba Hasan,et al.  Visualizing photodynamic therapy response with time-lapse OCT in an in vitro model of metastatic ovarian cancer , 2010, BiOS.

[23]  Tayyaba Hasan,et al.  Quantitative imaging reveals heterogeneous growth dynamics and treatment-dependent residual tumor distributions in a three-dimensional ovarian cancer model. , 2010, Journal of biomedical optics.

[24]  D. Hanahan,et al.  Hallmarks of Cancer: The Next Generation , 2011, Cell.

[25]  S. Sutton,et al.  Elemental tomography of cancer-cell spheroids reveals incomplete uptake of both platinum(II) and platinum(IV) complexes. , 2007, Journal of the American Chemical Society.

[26]  Ruikang K. Wang,et al.  Real-time flow imaging by removing texture pattern artifacts in spectral-domain optical Doppler tomography. , 2006, Optics letters.

[27]  Michael R Hamblin,et al.  Combination photoimmunotherapy and cisplatin: effects on human ovarian cancer ex vivo. , 1999, Journal of the National Cancer Institute.

[28]  C. Evans Three-dimensional in vitro cancer spheroid models for photodynamic therapy: strengths and opportunities , 2015, Front. Phys..