Quantification of Dynamic Morphological Drug Responses in 3D Organotypic Cell Cultures by Automated Image Analysis

Glandular epithelial cells differentiate into complex multicellular or acinar structures, when embedded in three-dimensional (3D) extracellular matrix. The spectrum of different multicellular morphologies formed in 3D is a sensitive indicator for the differentiation potential of normal, non-transformed cells compared to different stages of malignant progression. In addition, single cells or cell aggregates may actively invade the matrix, utilizing epithelial, mesenchymal or mixed modes of motility. Dynamic phenotypic changes involved in 3D tumor cell invasion are sensitive to specific small-molecule inhibitors that target the actin cytoskeleton. We have used a panel of inhibitors to demonstrate the power of automated image analysis as a phenotypic or morphometric readout in cell-based assays. We introduce a streamlined stand-alone software solution that supports large-scale high-content screens, based on complex and organotypic cultures. AMIDA (Automated Morphometric Image Data Analysis) allows quantitative measurements of large numbers of images and structures, with a multitude of different spheroid shapes, sizes, and textures. AMIDA supports an automated workflow, and can be combined with quality control and statistical tools for data interpretation and visualization. We have used a representative panel of 12 prostate and breast cancer lines that display a broad spectrum of different spheroid morphologies and modes of invasion, challenged by a library of 19 direct or indirect modulators of the actin cytoskeleton which induce systematic changes in spheroid morphology and differentiation versus invasion. These results were independently validated by 2D proliferation, apoptosis and cell motility assays. We identified three drugs that primarily attenuated the invasion and formation of invasive processes in 3D, without affecting proliferation or apoptosis. Two of these compounds block Rac signalling, one affects cellular cAMP/cGMP accumulation. Our approach supports the growing needs for user-friendly, straightforward solutions that facilitate large-scale, cell-based 3D assays in basic research, drug discovery, and target validation.

[1]  Stephanie Alexander,et al.  Cancer Invasion and the Microenvironment: Plasticity and Reciprocity , 2011, Cell.

[2]  Brendon M. Baker,et al.  Deconstructing the third dimension – how 3D culture microenvironments alter cellular cues , 2012, Journal of Cell Science.

[3]  A. Ridley,et al.  PAK1 and PAK2 have different roles in HGF-induced morphological responses. , 2009, Cellular signalling.

[4]  Subir Ghosh,et al.  Nonparametric Analysis of Longitudinal Data in Factorial Experiments , 2003, Technometrics.

[5]  Olli Yli-Harja,et al.  Software for quantification of labeled bacteria from digital microscope images by automated image analysis. , 2005, BioTechniques.

[6]  Bahram Parvin,et al.  Molecular Predictors of 3D Morphogenesis by Breast Cancer Cell Lines in 3D Culture , 2010, PLoS Comput. Biol..

[7]  Oliver Schmitt,et al.  Radial symmetries based decomposition of cell clusters in binary and gray level images , 2008, Pattern Recognit..

[8]  Christopher Thrasivoulou,et al.  A Novel Role for Wnt/Ca2+ Signaling in Actin Cytoskeleton Remodeling and Cell Motility in Prostate Cancer , 2010, PloS one.

[9]  O. Kallioniemi,et al.  Systematic knockdown of epigenetic enzymes identifies a novel histone demethylase PHF8 overexpressed in prostate cancer with an impact on cell proliferation, migration and invasion , 2012, Oncogene.

[10]  Scott E. Fraser,et al.  Imaging in Systems Biology , 2007, Cell.

[11]  Hans Clevers,et al.  Long-term expansion of epithelial organoids from human colon, adenoma, adenocarcinoma, and Barrett's epithelium. , 2011, Gastroenterology.

[12]  Chien-Feng Li,et al.  Vav3-rac1 signaling regulates prostate cancer metastasis with elevated Vav3 expression correlating with prostate cancer progression and posttreatment recurrence. , 2012, Cancer research.

[13]  G. Viglietto,et al.  Mammosphere-forming cells from breast cancer cell lines as a tool for the identification of CSC-like- and early progenitor-targeting drugs , 2010, Cell cycle.

[14]  Audrey K. Ellerbee,et al.  Using Magnetic Levitation for Three Dimensional Self‐Assembly , 2011, Advanced materials.

[15]  J. Brugge Into the deep: Refocusing on 3D , 2012, Nature Cell Biology.

[16]  Wolfgang Moritz,et al.  Towards automated production and drug sensitivity testing using scaffold-free spherical tumor microtissues. , 2011, Biotechnology journal.

[17]  Mikala Egeblad,et al.  Dynamic interplay between the collagen scaffold and tumor evolution. , 2010, Current opinion in cell biology.

[18]  Christopher S. Poultney,et al.  A physical sciences network characterization of non-tumorigenic and metastatic cells , 2013, Scientific Reports.

[19]  A. Coulson,et al.  A functional genomic analysis of cell morphology using RNA interference , 2003, Journal of biology.

[20]  Jörg Rahnenführer,et al.  Changes in cortical cytoskeletal and extracellular matrix gene expression in prostate cancer are related to oncogenic ERG deregulation , 2010, BMC Cancer.

[21]  Samir J. Courdy,et al.  Patient‐Derived Models of Human Breast Cancer: Protocols for In Vitro and In Vivo Applications in Tumor Biology and Translational Medicine , 2013, Current protocols in pharmacology.

[22]  V. Quaranta,et al.  Computational investigation of intrinsic and extrinsic mechanisms underlying the formation of carcinoma. , 2012, Mathematical medicine and biology : a journal of the IMA.

[23]  Mina J Bissell,et al.  Modeling dynamic reciprocity: engineering three-dimensional culture models of breast architecture, function, and neoplastic transformation. , 2005, Seminars in cancer biology.

[24]  O. Kallioniemi,et al.  Lysophosphatidic acid and sphingosine-1-phosphate promote morphogenesis and block invasion of prostate cancer cells in three-dimensional organotypic models , 2011, Oncogene.

[25]  R. Elble,et al.  Enrichment for breast cancer cells with stem/progenitor properties by differential adhesion. , 2010, Stem cells and development.

[26]  D. Wendt,et al.  The role of bioreactors in tissue engineering. , 2004, Trends in biotechnology.

[27]  Andrew J Ewald,et al.  Cellular mechanisms regulating epithelial morphogenesis and cancer invasion. , 2010, Current opinion in cell biology.

[28]  V. Smith,et al.  An Analytical Approach Differentiates Between Individual and Collective Cancer Invasion , 2011, Analytical cellular pathology.

[29]  Matthew J. Paszek,et al.  Balancing forces: architectural control of mechanotransduction , 2011, Nature Reviews Molecular Cell Biology.

[30]  R. M. Sharrard,et al.  Prostate epithelial cell lines form spheroids with evidence of glandular differentiation in three-dimensional Matrigel cultures , 2001, British Journal of Cancer.

[31]  R. Meehan,et al.  Targeting of Rac GTPases blocks the spread of intact human breast cancer , 2012, Oncotarget.

[32]  P. Danielsson Euclidean distance mapping , 1980 .

[33]  F. Yuan,et al.  A review of three-dimensional in vitro tissue models for drug discovery and transport studies. , 2011, Journal of pharmaceutical sciences.

[34]  D. Shelton,et al.  Development of a screen to identify selective small molecules active against patient-derived metastatic and chemoresistant breast cancer cells , 2013, Breast Cancer Research.

[35]  A. Ridley Rho GTPases and cell migration. , 2001, Journal of cell science.

[36]  Constance Holden Into the deep , 1998 .

[37]  Nicholas Hamilton,et al.  Quantification and its Applications in Fluorescent Microscopy Imaging , 2009, Traffic.

[38]  I. Garraway,et al.  Epcam, CD44, and CD49f Distinguish Sphere-Forming Human Prostate Basal Cells from a Subpopulation with Predominant Tubule Initiation Capability , 2012, PloS one.

[39]  D. Harrison,et al.  Determining tamoxifen sensitivity using primary breast cancer tissue in collagen-based three-dimensional culture. , 2012, Biomaterials.

[40]  Anne E Carpenter,et al.  CellProfiler: image analysis software for identifying and quantifying cell phenotypes , 2006, Genome Biology.

[41]  V. Virador,et al.  In vitro three‐dimensional (3D) models in cancer research: An update , 2013, Molecular carcinogenesis.

[42]  P. Friedl,et al.  Cancer invasion and resistance: interconnected processes of disease progression and therapy failure. , 2012, Trends in molecular medicine.

[43]  K. Rejniak,et al.  Current trends in mathematical modeling of tumor–microenvironment interactions: a survey of tools and applications , 2010, Experimental biology and medicine.

[44]  Anne E Carpenter,et al.  Improved structure, function and compatibility for CellProfiler: modular high-throughput image analysis software , 2011, Bioinform..

[45]  R. Meehan,et al.  An In Vitro Model That Recapitulates the Epithelial to Mesenchymal Transition (EMT) in Human Breast Cancer , 2011, PloS one.

[46]  Jyrki Lötjönen,et al.  A Comprehensive Panel of Three-Dimensional Models for Studies of Prostate Cancer Growth, Invasion and Drug Responses , 2010, PloS one.

[47]  Olli Yli-Harja,et al.  Quantification of vesicles in differentiating human SH-SY5Y neuroblastoma cells by automated image analysis , 2006, Neuroscience Letters.

[48]  Du-Ming Tsai,et al.  A fast thresholding selection procedure for multimodal and unimodal histograms , 1995, Pattern Recognit. Lett..

[49]  G. Lajoie,et al.  Matrigel: A complex protein mixture required for optimal growth of cell culture , 2010, Proteomics.

[50]  I. Bisson,et al.  WNT signaling regulates self-renewal and differentiation of prostate cancer cells with stem cell characteristics , 2009, Cell Research.

[51]  Genee Y. Lee,et al.  The morphologies of breast cancer cell lines in three‐dimensional assays correlate with their profiles of gene expression , 2007, Molecular oncology.

[52]  Christopher S. Chen,et al.  Deconstructing Dimensionality , 2013, Science.

[53]  Gordon B Mills,et al.  Inhibition of PI3K/mTOR leads to adaptive resistance in matrix-attached cancer cells. , 2012, Cancer cell.

[54]  Bahram Parvin,et al.  Linking Changes in Epithelial Morphogenesis to Cancer Mutations Using Computational Modeling , 2010, PLoS Comput. Biol..

[55]  Luc Stoppini,et al.  OrganDots – an organotypic 3D tissue culture platform for drug development , 2012, Expert opinion on drug discovery.

[56]  Chris Albanese,et al.  ROCK inhibitor and feeder cells induce the conditional reprogramming of epithelial cells. , 2012, The American journal of pathology.

[57]  Mina J. Bissell,et al.  Extracellular matrix control of mammary gland morphogenesis and tumorigenesis: insights from imaging , 2008, Histochemistry and Cell Biology.

[58]  Anne E Carpenter,et al.  CellProfiler: free, versatile software for automated biological image analysis. , 2007, BioTechniques.

[59]  Jos B. T. M. Roerdink,et al.  The Watershed Transform: Definitions, Algorithms and Parallelization Strategies , 2000, Fundam. Informaticae.

[60]  Karolin Papst Into The Deep , 2016 .

[61]  I. Garraway,et al.  Isolation and characterization of human prostate stem/progenitor cells. , 2012, Methods in molecular biology.

[62]  Scott E. Fraser,et al.  Digitizing life at the level of the cell: high-performance laser-scanning microscopy and image analysis for in toto imaging of development , 2003, Mechanisms of Development.