Nest expansion assay: a cancer systems biology approach to in vitro invasion measurements

BackgroundTraditional in vitro cell invasion assays focus on measuring one cell parameter at a time and are often less than ideal in terms of reproducibility and quantification. Further, many techniques are not suitable for quantifying the advancing margin of collectively migrating cells, arguably the most important area of activity during tumor invasion. We have developed and applied a highly quantitative, standardized, reproducible Nest Expansion Assay (NEA) to measure cancer cell invasion in vitro, which builds upon established wound-healing techniques. This assay involves creating uniform circular "nests" of cells within a monolayer of cells using a stabilized, silicone-tipped drill press, and quantifying the margin expansion into an overlaid extracellular matrix (ECM)-like component using computer-assisted applications.FindingsThe NEA was applied to two human-derived breast cell lines, MCF10A and MCF10A-CA1d, which exhibit opposite degrees of tumorigenicity and invasion in vivo. Assays were performed to incorporate various microenvironmental conditions, in order to test their influence on cell behavior and measures. Two types of computer-driven image analysis were performed using Java's freely available ImageJ software and its FracLac plugin to capture nest expansion and fractal dimension, respectively – which are both taken as indicators of invasiveness. Both analyses confirmed that the NEA is highly reproducible, and that the ECM component is key in defining invasive cell behavior. Interestingly, both analyses also detected significant differences between non-invasive and invasive cell lines, across various microenvironments, and over time.ConclusionThe spatial nature of the NEA makes its outcome susceptible to the global influence of many cellular parameters at once (e.g., motility, protease secretion, cell-cell adhesion). We propose the NEA as a mid-throughput technique for screening and simultaneous examination of factors contributing to cancer cell invasion, particularly suitable for parameterizing and validating Cancer Systems Biology approaches such as mathematical modeling.

[1]  Kenneth M. Yamada,et al.  Taking Cell-Matrix Adhesions to the Third Dimension , 2001, Science.

[2]  Michal Čeppan,et al.  Fractal analysis of printed structures , 2002 .

[3]  H. Thielecke,et al.  Biopsy on living cells by ultra slow instrument movement , 2006 .

[4]  Alissa M. Weaver,et al.  Tumor Morphology and Phenotypic Evolution Driven by Selective Pressure from the Microenvironment , 2006, Cell.

[5]  T F Nonnenmacher,et al.  Fractal dimension of pericellular membranes in human lymphocytes and lymphoblastic leukemia cells. , 1992, Pathology, research and practice.

[6]  E Claridge,et al.  Shape analysis for classification of malignant melanoma. , 1992, Journal of biomedical engineering.

[7]  Effects of GSM microwaves, pulsed magnetic field, and temperature on fractal dimension of brain tumors , 2004 .

[8]  Vito Quaranta,et al.  A novel circular invasion assay mimics in vivo invasive behavior of cancer cell lines and distinguishes single-cell motility in vitro , 2008, BMC Cancer.

[9]  N. Sato,et al.  A new model to study repair of gastric mucosa using primary cultured rabbit gastric epithelial cells. , 1995, Journal of clinical gastroenterology.

[10]  G. Christofori New signals from the invasive front , 2006, Nature.

[11]  J. Guan,et al.  Wound-healing assay. , 2005, Methods in molecular biology.

[12]  H. H. Lloyd,et al.  Kinetic parameters and growth curves for experimental tumor systems. , 1970, Cancer chemotherapy reports.

[13]  P. Spessotto,et al.  Fluorescence assays to study cell adhesion and migration in vitro. , 2000, Methods in molecular biology.

[14]  George M. Whitesides,et al.  Microcontact printing of self-assembled monolayers: applications in microfabrication , 1996 .

[15]  F. Miller,et al.  Xenograft model of progressive human proliferative breast disease. , 1993, Journal of the National Cancer Institute.

[16]  J. Guan,et al.  Cell migration : developmental methods and protocols , 2005 .

[17]  Stanislav Y Shvartsman,et al.  Role of boundary conditions in an experimental model of epithelial wound healing. , 2006, American journal of physiology. Cell physiology.

[18]  R. Simeonov,et al.  Fractal dimension of canine mammary gland epithelial tumors on cytologic smears. , 2006, Veterinary clinical pathology.

[19]  Paolo Gaetani,et al.  Fractal dimension as a quantitator of the microvasculature of normal and adenomatous pituitary tissue , 2007, Journal of anatomy.

[20]  Rangaraj M. Rangayyan,et al.  Fractal Analysis of Contours of Breast Masses in Mammograms , 2007, Journal of Digital Imaging.

[21]  W. Spillman,et al.  Complexity, fractals, disease time, and cancer. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[22]  S. Torquato,et al.  Pattern of self‐organization in tumour systems: complex growth dynamics in a novel brain tumour spheroid model , 2001, Cell proliferation.

[23]  Laurent Risser,et al.  From Homogeneous to Fractal Normal and Tumorous Microvascular Networks in the Brain , 2007, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[24]  Joachim Wegener,et al.  Electrical wound-healing assay for cells in vitro. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[25]  Lorenzo Scalise,et al.  Fractal characterisation of boundary irregularity in skin pigmented lesions , 2005, Medical and Biological Engineering and Computing.

[26]  Michal Veselý,et al.  Fractal Analysis of Image Structures , 2001 .

[27]  Fred R. Miller,et al.  Malignant MCF10CA1 Cell Lines Derived from Premalignant Human Breast Epithelial MCF10AT Cells , 2004, Breast Cancer Research and Treatment.

[28]  Caterina Guiot,et al.  Surgical impact on brain tumor invasion: A physical perspective , 2008, Annals of surgical innovation and research.