Cancer cell migration in 3d collagen gel matrix system

CANCER CELL MIGRATION IN 3D COLLAGEN GEL MATRIX SYSTEM SUN WEI (B.Eng Tsinghua Univ, Beijing) (MSc, NUS) A THESIS SUBMITTED FOR THE DEGREE OF DOCTOR OF PHILOSOPHY NATIONAL UNIVERSITY OF SINGAPORE 2010 Acknowledgements My sincere thanks must first go to my supervisor, Professor Lim Chwee Teck He is not only my academic advisor, but also a role model for us – a young generation of engineers who are determined to pursue a career out of the conventional engineering domain, by solving long standing questions in life sciences and medical sciences with engineering approaches or by adding to the human’s understanding of lives and diseases from new perspectives Although he never advocated with words, his achievements greatly inspired me when I made up my mind to switch my career, otherwise I will probably be designing an energy system for a building right at this moment I believe he as a good example will attract more and more young people with engineering background to contribute to improving the health of mankind He first directed me to this topic – studying cancer cell migration in 3D – in Feb 2007 Through guiding me to read relevant literatures, introducing me to the group leading the field, Professor Lim opened the door to a great new world for me and brought me the compass He is very supportive while I went through the period of protocol optimization, through generously funding the reagents, consumables, microscope and accessories and also investing in a very expensive software package for image analysis I had never ever worried about purchasing anything for the experiments throughout the years, all thanks to his great support As the research progressed, he went through the difficulties, unforeseeable adversaries together with me, keeping me encouraged all the time To solve technical problems, we had many discussions within the group and also with scientists of similar interests, who offered constructive advice To my surprise, he is not only making his best effort, but also engaging his friends to make their best effort to help my research When I was confused about choosing the direction, he helped me to set realistic goals His insight and detailed guidance ensured that the research is always on the right track and the project is making progresses i All in all, without Professor Lim as my supervisor, I will not be able to take this endeavour to explore cancer metastasis, not able to find the right paths, to proceed and complete the project, never mention presenting this thesis to all I am also deeply indebted to my co-supervisor Professor Raj Rajagopalan Among the committee who interviewed me for admission into NGS, it is his support on me that made everything possible Ever since joining his research group in the second year of my study, he treated me same as the graduate students that he guides as main supervisor On the project requiring collaboration between Nicholas and me, he invested tremendous time and energy to guide us His foresight of frontier science, his wisdom, enthusiasm and intelligence guided my research like a lighthouse Whenever I had difficulties in anything during the study, I would like to turn to him for advice because I know he is kind and ready to help me He always outlined the tasks and dissected them into detailed steps which were in turn explained in clarity with his experience As a result, I often came into his office confused, with fear over the challenges, and left his office with confidence, courage, and sometimes a big smile – thanks to his humour He really cares about the development of his graduate students and gives us career guide from time to time I benefitted from Prof Raj’s supervision a great deal and really feel that he is a great academic father to me All in all, I feel lucky to have good supervisors in the years working towards a PhD Besides, I am very grateful to all the past and current lab officers: Ms Tan Phay Shing, Eunice, Mr Hairul Nizam Bin Ramli and Ms Charlene Wang (Prof Seeram Ramakrishna’s Laboratory) for their good maintenance to the laboratory and their timely help throughout the course of my PhD study Since I became a member of NanoBiomechanics Lab four years ago, I often feel lucky to have a wonderful lab environment In this friendly and conducive lab, I am able to conduct experiments smoothly, to have my bench work time more enjoyable, my everyday life filled with fun My gratitude goes to everyone of my lab friends, for being kind colleagues to work ii with, for offering me help whenever requested, sharing your knowledge and experience to me without reservation, encouraging me in many ways and sharing countless cheerful occasions with me I appreciate being a student of NUS Graduate School for Integrative Sciences & Engineering (NGS), the privileged graduate school in Singapore, for a few reasons NGS offers me not only generous funding, but also a great opportunity to build up the background and carry out interdisciplinary research, because we are empowered by the innovative curriculum setting and the encouraging environment in NGS The community of NGS did take care of each of us postgraduate students with attention I also benefitted from support of the NGS office, for which I can never forget the kind assistance and guidance from Ms Ivy Wee, Ms Irene Chuan and Ms Neo Cheng Bee and many others, during the course of my stay in NGS Last, but most importantly, I would also like to thank my family for their love and understanding throughout My husband, parents and parents-in-law all supported my study whole-heartedly Their encouragement and caring kept me accompanied all the time despite that I was thousands of miles away Without my family standing behind, it would not be possible for me to start and complete the PhD study iii Table of Contents Acknowledgements i Table of Contents iv Summary vii List of Tables viii List of Figures ix List of Symbols xvi Chapter 1: Introduction 1.1 The significance of cancer metastasis research 1.1.1 The urgency of cancer research 1.1.2 Cancer metastasis research 1.2 Quantitative in vitro 3D cell migration assays 1.2.1 Values of in vitro drug assays 1.2.2 Advantages of 3D cell-based drug assay 1.2.3 Fundamentals of cell migration 1.2.4 Advantages of 3D cell invasive migration assays 1.2.5 Summary 11 1.3 Tissue mechanical factors in 3D cell migration assays 12 1.4 Objective 13 1.5 Scope and structure of the thesis 13 Chapter 2: Literature Review 15 2.1 In vitro 2D and 3D cancer metastasis studies 15 2.1.1 Tracking 2D cell migration 16 2.1.2 Micro-pore-based cell migration/ invasion assays 21 2.1.3 3D cell migration models 24 2.1.4 Discussion on cell migration assays 31 2.2 General anti-cancer drug assays in 3D 33 2.2.1 Introduction 33 2.2.2 Background: why 2D cell culture is insufficient for anti-cancer drug testing 34 iv 2.2.3 Techniques in 3D anti-cancer drug assays 36 2.2.4 Specific research questions 39 2.2.5 Comparing 3D substrates with different structures / properties 45 2.2.6 Summary 46 2.3 3D anti-migratory drug assays 47 2.4 Summary 49 Chapter 3: Materials and Methods 50 3.1 Malignant breast cancer cells 50 3.2 3D collagen model for cell invasion 51 3.3 Structure and mechanical property of collagen gel 53 3.3.1 Mechanical characterization 53 3.3.2 Scanning electron microscopy 55 3.4 Microscopy methods for cell migration study 56 3.4.1 Imaging and tracking cells 56 3.4.2 Cell track data analysis 59 3.4.3 Statistical methods 61 3.5 Summary of the chapter 63 Chapter 4: Mechanical Modulation of the Collagen Gel Matrix 64 4.1 Modulation of bulk elasticity of the gel 64 4.2 Non-linear elasticity of collagen 66 4.3 Micro-architecture of collagen matrices 69 4.3.1 Dependence of collagen fibril thickness on polymerization pH 70 4.3.2 Pore-size of the collagen network 73 4.4 Discussion 76 Chapter 5: 3D Cell Migration and Drug Effects 79 5.1 Innate cell migration 79 5.2 MMP inhibition by GM6001 89 5.3 ROCK-inhibition 96 5.4 Actin destabilization 104 5.5 Microtubules destabilization 111 v 5.6 Discussions on drug effects 118 Chapter 6: Conclusions and Future Work 122 6.1 Conclusions 122 6.2 Further modulation of the ECM environment 125 References 127 Appendix A The Time Dependence of Cell Motility 138 Appendix B Results of Statistical Tests 140 vi Summary Cancer has long been one of the leading causes of death in the industrial world The main reason for its high mortality is due to inefficient early detection which results in the spread of cancer cells to other distant sites in the body, via a process known as metastasis Metastasis causes the dissemination of cancer cells and accounts for 90% of cancer-induced deaths, thus requiring better therapeutic treatments The thesis examines a functional assay to study cancer cell invasive migration inside a three-dimensional (3D) collagen-I hydrogel, focusing on its micro-architecture and mechanics First part of the project is the tuning of 3D collagen hydrogel to achieve varying fibre network structure and gel mechanical properties Embedded in such collagen gels, breast cancer cells were tracked using live confocal imaging followed by quantitative 3D cell track analysis The second part evaluated drug effects on cell migration using the model Pharmacological inhibitions of cell-activated collagen matrix degradation and cytoskeletal reorganization reduced cell movement speed and directionality Interestingly, the drug effects depended on the matrix micro-structure and elasticity The study found that tissue mechanics is important in anti-migratory cancer drug assays, and incorporated ECM factors in interpreting results of drug assays vii List of Tables Table 2.1 In vitro cell migration assays 16 Table 2.2 Categorizing 3D cell migration assay 25 Table 4.1 The list of parameter values in the exponential models that G’ data were fitted with 68 Table 5.1 Case index of migration assays 79 Table 5.2 Effects of GM6001 on cell movement speed and track straightness 91 Table 5.3 Effects of Y27632 on cell movement speed and track straightness 99 Table 5.4 Effects of CytoD on cell movement speed and track straightness 106 Table 5.5 Effects of nocodazole on cell movement speed and track straightness 113 Table 5.6 Recommended collagen-I gel mechanical property for drug assay designs 120 Table B.1 Comparing cell speed in the five control conditions; p-values obtained from K-S tests 141 Table B.2 Comparing cell straightness in the five control conditions; p-values obtained from K-S tests 141 viii References Cidadao AJ 1989 Interactions between fibronectin, glycosaminoglycans and native collagen fibrils: an EM study in artificial three-dimensional extracellular matrices Eur J Cell Biol 48(2):303-12 Cleek RL, Rege AA, Denner LA, Eskin SG, Mikos AG 1997 Inhibition of smooth muscle cell growth in vitro by an antisense oligodeoxynucleotide released from poly(DL-lactic-co-glycolic acid) microparticles J Biomed Mater Res 35(4):525-30 Condeelis J, Segall JE 2003 Intravital imaging 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matrix stiffness along with cell-matrix adhesion and proteolysis Proc Natl Acad Sci U S A 103(29):10889-94 Zicha D, Dunn GA, Brown AF 1991 A new direct-viewing chemotaxis chamber J Cell Sci 99 ( Pt 4):769-75 136 Appendix 137 Appendix A The Time Dependence of Cell Motility We have examined the cell speed at different time points, and found that 1) cell speed of each track did not vary considerably over hours of live confocal fluorescence microscopy (Figure A.1); 2) cells maintained active migration from Day to Day 16, but decreased after that (Figure A.2), suggesting that the current assay is able to maintain reproducibility for at least two weeks On such basis, we averaged cell speed over each track to reflect the motility of an individual cell, and performed further analysis using these cell speed averaged by track Considering the assay stability is proved for the period from Day 10 to Day 16, all cell tracking and drug tests were performed between Day 10 and Day 14 cell speed at each 10 interval (μm/hr) 30 25 23.5 20 20.0 15 10 18.8 × 10 mins 13 19 25 31 37 43 cell speed at each 10 interval (μm/hr) 30 25 20 15 10 23.5 20.0 18.8 × 10 mins 13 19 25 31 37 43 Figure A.1 Cell speed calculated at each 10 interval, over hours of monitoring via confocal fluorescence microscopy The three lines represent three typical tracks in one test Cell speed did not show any trend of variation over time The three tracks maintained their relative positions across the entire period, and their difference can be reflected by the average speed, as labelled on the right of the chart 138 Cell speed (μm/hr) 12 10 Day-10 Day-16 Day-24 Figure A.2 Averaged cell speed on different days into the assay All data were collected from one experiment using pH7-2.5 mg/ml collagen gel Each sample contained more than 450 data, and the variances were < 0.02 μm/hr, which are not presented in the chart 139 Appendix B Results of Statistical Tests The cell speed and track straightness data not follow normal distribution Paired t-test or ANOVA is not applicable to compare the data in our study Mann-Whitney U test is an alternative to t-test when the data are not normally distributed, which is a test of population medians and the shape of the distribution functions, assuming that the data are from the same type of distributions However, this assumption was not valid here, since among these sets of cell speed data we found inconsistency in the types of distribution As a result, Mann-Whitney U test was not selected Instead, two-sample Kolmogorov-Smirnov (K-S) test was conducted using MATLAB (The two data vectors x1 and x2 The null hypothesis is that x1 and x2 are from the same MathWorks, Inc., Natick, MA, USA) K-S test compares the distributions of the values in the continuous distribution The alternative hypothesis is that they are from different continuous distributions The test statistic is: 𝑚𝑎𝑥(|𝐹1(𝑥) − 𝐹2(𝑥)|) of x1 values less than or equal to x and F2(x) is the proportion of x2 values less than or equal where F1 is the cumulative distribution function (CDF) of vector x1, F1(x) is the proportion to x So, the test statistic is the maximum difference between the two CDF curves The test does not specify what that common distribution is, thus it sets no limit to the form of data distribution To conclude from the K-S test, most of the cell speed data were from different distributions, through paired comparisons; and most drug-treated cell migration speed distributions differed from the corresponding control counterpart 140 Table B.1 Comparing cell speed in the five control conditions; p-values obtained from K-S tests p-value pH9-2.5 mg/ml pH7-4.0 mg/ml pH7-2.5 mg/ml pH7-1.5 mg/ml pH6-2.5 mg/ml pH9-50 0* 0 pH7-80 0 0 pH7-50 0.49 pH7-30 *When p450 The same applies to all tables in Appendix B Table B.2 Comparing cell straightness in the five control conditions; p-values obtained from K-S tests p-value pH9-50 pH7-80 pH7-50 pH7-30 pH9-2.5 mg/ml pH7-4.0 mg/ml pH7-2.5 mg/ml pH7-1.5 mg/ml pH6-2.5 mg/ml 0 0 0 0 0.81 141 Figure B.1 Summary of K-S test of cell speed data Column height = means the data from the paired drug treated– control conditions were from different distributions, suggesting the drug effect is statistically significant Column height = means the pair of data were not drawn from different distributions All tests were performed at a significance level = 0.05 Figure B.2 Summary of K-S test of cell track straightness data Column height = means the data from the paired drug treated–control conditions were from different distributions, suggesting the drug effect is statistically significant Column height = means the pair of data were not drawn from different distributions All tests were performed at a significance level = 0.05 142 ... studying migration- inducing ingredients in ECM To study the pathways involved in hyaluronan-induced pancreatic cancer cell motility, inhibitors were tested for effects on reducing cell migration. .. of cell distribution in a nested collagen gel after 12 days, showing cells spreading out from the inner -gel (the dashed line enclosed area) to the surrounding, originally cell- free outer gel. .. must be well defined and there is a need for modulating matrix mechanics in these assays 2.1 In vitro 2D and 3D cancer metastasis studies Research into cell migration involved in cancer metastasis