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The Influence of 3D Cell Organization in Tumor Spheroid on Natural Killer Cell Infiltration and Migration

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The Influence of 3D Cell Organization in Tumor Spheroid on Natural Killer Cell Infiltration and Migration DEGREE PROJECT IN MEDICAL ENGINEERING, SECOND CYCLE, 30 CREDITS STOCKHOLM, SWEDEN 2020 The Influence of 3D Cell Organization in Tumor Spheroid on Natural Killer Cell Infiltration and Migration LUIGI MORRONE KTH ROYAL INSTITUTE OF TECHNOLOGY SCHOOL OF ENGINEERING SCIENCES IN CHEMISTRY, BIOTECHNOLOGY AND HEALTH The Influence of 3D Cell Organization in Tumor Spheroid on Natural Killer Cell Infiltration and Migration Inverkan av 3D-cellorganisation i tumorsfäroid på naturlig mördarcellinfiltration och migration Luigi Morrone Degree Project in Medical Engineering Supervisor: Quentin Verron Reviewer: Carsten Mim KTH Royal Institute of Technology, Stockholm, Sweden School of Engineering Sciences in Chemistry, Biotechnology and Health Abstract Natural Killer cells are a type of lymphocyte belonging to the innate immune system and they operate cell-mediated cytotoxicity and release of pro-inflammatory cytokines against cancerous cells. However, in vivo testings have shown a reduced activity of NK cells against solid tumors probably due to the negative influence of the immunosuppressive tumor microenvironment. Multicellular tumor spheroids may constitute an advantageous model in cancer biology for studying the mechanisms behind cancer immune editing since it more closely mimics the complexity of the human body compared with the 2D model counterpart. This study investigated the interaction between NK cells isolated from blood and tumor spheroids obtained from A498 renal carcinoma cells, using light-sheet microscopy imaging which allows satisfactory cell tracking in the inner layers of the spheroids. NK cells not only indeed interact with tumor spheroids, but many of them were able to penetrate the spheroids inducing some changes in the structure of the latter. NK cells were also tracked over time, displaying the migration path and calculating the speed. The fluorescence intensity of the NK cells was found reduced as soon as they penetrate the spheroid but, conversely, the speed seems to increase inside the spheroid, a possible sign of the fallibility of the tracking algorithm in this specific case. We propose solutions for more sophisticated future implementations, involving the use of marks during the experimental phase and drift corrections at the data analysis level. iv Sammanfattning NK-celler är en typ av lymfocyter som hör till det ospecifika immunförsvaret. NK- celler utför cellmedierad cytotoxicitet samt utsöndrar proinflommatoriska cytokiner mot cancerceller. Dock har In vivo-tester visat på minskad aktivitet av NK-celler mot solida tumörer - troligtvis på grund av negativ påverkan från tumörens mikromiljö och dess tillhörande hämmande kroniska inflammation. Multicellulära tumörsfäroider kan innebära en fördelaktig modell inom cancerbiologi för att studera mekanismerna bakom immunoediting vid cancer eftersom de bättre speglar komplexiteten hos den mänskliga kroppen jämfört med motsvarande 2D-modell. Denna studie undersöker interaktionen mellan NK-celler isolerade från blod och tumörsfäroider erhållna från A498 njurkarcinomceller, med hjälp av light-sheet-mikrosopi som möjliggör tillfredsställande cellspårning i de inre skikten av sfäroiderna. NK-celler interagerar inte bara med tumörsfäroider. Många av dem kunde även tränga in i sfäroiderna, vilket inducerade förändringar i sfäroidernas struktur. NK-celler studerades även över tid, vilket visade migreringsvägen samt tillät beräkning av rörelsehastigheten. Intensiteten hos NK-cellernas flourescens visade sig reducerad så snart de penetrerat sfäroiden. Omvänt verkade hastigheten öka inuti sfäroiden - ett möjligt tecken på spårningsalgoritmens felbarhet i det specifika fallet. Vi föreslår lösningar för mer sofistikerade framtida implementeringar, med användning av markörer under experimentfasen och korrigering av drift under dataanalysen. v Acknowledgements I would like to thank the professor Björn Önfelt for the opportunity to participate in this project, including me in his research group. I would like to thank my supervisor Quentin Verron for guiding me during the whole thesis project with useful suggestions and constructive critiques. I would like to thank Valentina Carannante and Steven Edwards involved in the experiments setting and data collection. Lastly, but not least, I want to thank my family and my friends for their emotional support. Also worth special mention my sister Noemi with whom I share an unique and indissoluble bond and my best friend Alice who is my role model and my confidant. vi Contents Abstract iv Sammanfattning v Acknowledgements vi List of Figures ix Glossary x 1 Introduction 1 2 Methods 3 2.1 Experimental setup and data acquisition .................. 3 2.2 First approach to the data .......................... 4 2.3 Pre processing ................................ 5 2.4 Segmentation and the Batch Pipeline ................... 5 2.5 How to evaluate infiltration ......................... 7 2.6 Natural Killer cells tracking ......................... 8 3 Results 10 3.1 Infiltration ................................... 10 3.2 Tracking .................................... 12 3.3 Killing ..................................... 14 4 Discussion 16 5 Conclusions 18 References 19 vii CONTENTS A State of the Art 24 A.1 Human immune system ........................... 24 A.2 Optical Microscopy .............................. 29 A.3 Image processing and recognition for biological images ......... 33 B List of Parameters 36 B.1 Surfaces creation parameters ........................ 36 B.2 Spots and Tracks creation parameters ................... 37 viii List of Figures 2.1.1 Sample setup ................................. 3 2.2.1 Data displayed and segmented in ImageJ ................. 4 2.3.1 Background Subtraction ........................... 5 2.4.1 Segmentation ................................. 6 2.5.1 Infiltration .................................. 7 2.5.2Shells approach ............................... 8 2.6.1 Tracking groups ............................... 9 2.6.2Tracking ................................... 9 3.1.1 Labeled spheroids .............................. 10 3.1.2 Number of cells inside the spheroid .................... 11 3.1.3 The drift of the spheroids .......................... 11 3.1.4 Distance distribution over time ....................... 12 3.1.5 NK cell infiltration related to the spheroid volume . 13 3.2.1 Number of tracks of a given duration ................... 14 3.2.2NK cells speed distribution ......................... 14 3.2.3NK cells intensity mean ........................... 15 3.3.1 Killing ..................................... 15 A.1.1 Inhibition and activation of NK cells through receptors activity . 25 A.1.2Internal structure of a tumor spheroid ................... 28 A.1.3The creation of MCTS using agarose as coating for the wells . 29 A.1.4The creation of multicellular tumor spheroids using ultrasonic standing waves ..................................... 30 A.2.1Confocal microscope ............................. 31 A.2.2The principle of light sheet microscopy . 32 ix Glossary CCD Charged-coupled device, a transistorized light sensor on an integrated circuit DNAM-1 Activating receptor expressed on subsets of natural killer and T cells ECM Extracellular matrix FOV Field of view LSFM Light sheet fluorescence microscopy MCTS Multicellular tumor spheroid MHC Major histocompatibility complex, group of genes that code for proteins found on the surfaces of cells that help the immune system recognize foreign substances NK Natural killer cell PVR Poliovirus receptor, a cell adhesion protein involved in the transendothelial migration of leukocytes TIGIT T cell immunoreceptor with immunoglobulin and immunoreceptor tyrosine- based inhibition motif domains present on some T cells and Natural Killer Cells USW Ultrasonic standing wave x Chapter 1 Introduction Understanding the mechanisms behind treatment resistance is a challenging task for oncological research. It has been shown that natural killer (NK) cells have dynamic cytotoxic activity against tumor cells also thanks to the ability to discriminate between ‘‘normal and altered self’’ through MHC class I-specific receptors considering that MHC-I expression levels can be altered upon cell stress and tumor transformation. The tumor microenvironment may interfere with NK-cell activation pathways or the complex receptor array that regulate NK-cell activation and antitumor activity. Now the research is focused on how functional NK cells can be efficiently delivered and maintained at the tumor site, in spite of the numerous suppressive actions promoted by the tumor [1, 2]. Traditionally, cancer cell proliferation is first measured, culturing and treating the cells in standard microplates and later transferred to a 3D in vivo model (typically animal) to study the drug effect in an environment more similar to the human body. Multicellular tumor spheroids are models of increasing interest since they allow considering cellular interactions in exploring cell cycle and cell division mechanisms, relieving laboratories of the financial burden and the ethical aspect of animal testing. However, 3D imaging of cell division in living tumor spheroids is often time-consuming, arduous, and lack reproducibility, in addition to the issue of poorly visualized core region [3–5]. As compared to other techniques, fluorescence microscopy offers the possibility to image from multiple views large, living and fluorescently labeled samples preserving a sufficient spatio-temporal resolution. Long-term live fluorescence imaging allows
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