Modeling the Effect of Melanoma Tumor Cell Growth in the Presence of Natural Killer Cells Ann Wells University of Tennessee-Knoxville Kara Kruse, M.S.E. Richard C. Ward, Ph.D. Computational Sciences and Engineering Division Sharon Bewick, Ph.D. August 2009 Cray Confidential Cray Proprietary

Overview Introduction Significance Methodology The System Results Conclusion Future work Acknowledgments

Introduction Cancer 2nd leading cause of death Tumor cells often evade the immune system and immune cells may evade tumor cells Many immune cells have tumor cell lysis potential Natural Killer (NK) cells show tumor cell lysis potential Create a mathematical model showing the interactions between NK cells and tumor cells Create a theoretical model that simulates the effects of natural killer cells on tumor cells Tumor cells often evade the immune system and continue to proliferate. Once this happens metastases becomes a problem It is not understood why tumors are able to evade the immune system People are now trying to understand why the immune system can’t handle tumor cells Natural killer cells show potential to kill tumors

Significance Predict behavior of the NK cell Predict behavior of the tumor cell Predict interaction between immune cells and tumor cells Create new ways to treat cancer Immunotherapy Less invasive This is important research because it tells us more about the wat tumor cells evade the immune system as well as why immune cells are at a disadvantage. Immunotherapies may also be developed from this research.

Methodology Searched for experimental data in previous literature Biochemical reactions Important receptors Created a series of continuous PDEs Simulate interaction between NK cells and tumor cells Show effects of matrix metalloproteinases (MMPs) on receptors, Extracellular Matrix (ECM) and NKG2D receptor Used MATLAB and Systems Biology Workbench

Important players in the system NK cells Tumor Cells Matrix Metalloproteinases (MMPs) MICA Cytokines Extracellular matrix

Natural Killer Cells Large granular lymphocytes Part of the innate immune system Contains receptors and ligands that bind to foreign substances NKp30, NKp44, NKp46 and C-type lectin receptor, NKG2D Does not require prior sensitization Shows tumor cell lysis potential http://www.iayork.com/Images/2008/2-25-08/NKTumorCell.jpg

Other Players ECM Cytokines Provides structural support to cells Usually made from collagen and/or fibronectin Blocks tumor from NK cells Cytokines Signaling molecules Proteins, peptides or glycoproteins Tumor cells secrete cytokines which act as chemoattractants for NK cells

Other Players Matrix Metalloproteinases (MMP) Ligand Degrades extracellular matrix proteins Known to cleave cell surface receptors Secreted by NK cells Allows NK cells to migrate Ligand Binds substances together to create complexes Causes conformational changes MICA is a ligand and binds to NKG2D receptor when soluble

Biological interactions NK cells that express NKG2D recognize and kill tumor cells Tumor cells that come in contact with MMPs shed MICA making them invisible Soluble MICA can bind to NKG2D receptor, down-regulating surface density of NKG2D receptors NK cell http://www.immunesupportonline.com/Images/lymphocyte%20and%20nutrophil.jpg http://myhealth.ucsd.edu/library/healthguide/en-us/images/media/medical/hw/n5550299.jpg

Biological interactions cont. NK cells follow a tumor secreted cytokine gradient The ECM surrounds tumor cells creating a barrier preventing NK cells from invading the tumor NK cells can breakdown ECM through the secretion of MMPs http://sciencecodex.com/files/sciencecodex-oZsXUwc08Fbda46Z.jpg

Steps to creating model 1. Enter biochemical reactions into Systems Biology Workbench (SBW) 2. Check ordinary differential equations (ODEs) created from SBW 3. Add spatial component to ODEs to create partial differential equations (PDEs) 4. Write Matlab code for solving PDEs 5. Verify model with experimental data

Biochemical Reactions Figure 1: Output from Systems Biology Workbench

Partial Differential Equations

Results A Figure 2: Matlab graph depicting results for high concentration of MMP input

Results B Figure 3: Matlab graph depicting results for normal concentration of MMP input

Results C Figure 4: Matlab graph depicting results for low concentration of MMP input

Conclusion Numerical solution gives expected behavior for this model Change in MMP concentration effects behavior of system http://www.drugabuse.gov/NIDA_notes/NNvol21N6/killercell.jpg

Future Work Design experiments to run based on mathematical model Revise and expand mathematical model based on experimental results

References Zwirner, N. W., M. B. Fuertes, M. V. Girart, C. I. Domaica, L. E. Rossi. Cytokine-driven regulation of NK cell functions in tumor immunity: Role of the MICA-NKG2D system. Cytokine and Growth Factors Reviews. 18 (2007) Kuppen, P. J. K., M. M. van der Eb, L. E. Jonges, M. Hagenaars, M. E. Hokland, U. Nannmark, R. H. Goldfarb, P. H. Basse, G. Jan Fleuren, R. C. Hoeben, C. J.H. van de Velde. Tumor structure and extracellular matrix as a possible barrier for therapeutic approaches using immune cells or adenoviruses in colorectal cancer. Histochemistry Cell Biology. 115 (2001)

Acknowledgements Thanks to: Kara Kruse, M.S.E. Richard Ward, Ph.D. Sharon Bewick, Ph.D. John Biggerstaff, Ph.D. Debbie McCoy ORNL UT-Batelle Department of Energy

Questions

Photo Citations http://www.iayork.com/Images/2008/2-25-08/NKTumorCell.jpg http://www.real-estate-marketing-link.info/image-files/question-mark.jpg http://1.bp.blogspot.com/_SwokdFQUN2Y/R- Owx8qwfVI/AAAAAAAAAPo/0hcLHaHR0l0/s320/question+markSml.JPG http://www.topofthecue.com/blog/uploaded_images/question-mark- 717218.jpg http://kara.allthingsd.com/files/2008/05/475px-inverted_question_mark.png http://i22.photobucket.com/albums/b326/jessehouse/Question_Mark2.jpg http://thumbs.dreamstime.com/thumb_217/11975404602o2VgL.jpg http://wme.lzu.edu.cn/kimpton/img/question-mark.jpg http://school.discoveryeducation.com/clipart/images/questns.gif