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.University of Tennessee-Knoxville

August 2009

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Overview

• Introduction

• Significance

• Methodology

• The System

• Results

• Conclusion

• Future work

• Acknowledgments

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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

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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

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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

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Important players in the system

• NK cells

• Tumor Cells

• Matrix Metalloproteinases (MMPs)

• MICA

• Cytokines

• Extracellular matrix

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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

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Other Players

• ECM– 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

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Other Players

• Matrix Metalloproteinases (MMP)– 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

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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

http://www.immunesupportonline.com/Images/lymphocyte%20and%20nutrophil.jpg

http://myhealth.ucsd.edu/library/healthguide/en-us/images/media/medical/hw/n5550299.jpg

NK cell

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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

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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

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Biochemical Reactions

Figure 1: Output from Systems Biology Workbench

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Partial Differential Equations

MMPDNKpNKRpTMICAMMPkTMICAMMPkt

MMPmmpBR

233

TumorGTumorECMDTMICAMMPkt

TumorTT

2

6 )(

)()(2)(5

2211

TCNKRECMNKRNKRECMNKRDTMICANKRk

TMICANKRkTMICANKRkSMICANKRkSMICANKRkt

NKR

sMICADTMICAMMPkSMICANKRkSMICANKRkt

SMICAsMICA

2611

)()()( 24 TNKNK CNKECMNKECMDSMICANKRk

t

NK

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Results

AA

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

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Results

BB

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

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Results

CC

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

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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

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Future Work

• Design experiments to run based on mathematical model

• Revise and expand mathematical model based on experimental results

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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)

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Acknowledgements

• 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

Thanks to:

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Questions