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Cancer Cell Chemotaxis in Microfluidic Devices
Dallas Reilly, ChemistryCarthage CollegeFaculty Mentor: Noo Li Jeon, Biomedical EngineeringUniversity of California, Irvine
Chemotaxis-movement of cells due to a chemical presence
Outline
Basics– Cancer
Breast Cancer– Epidermal Growth Factor
Metastasis
– Microfluidic devices can help
Microfluidic Devices– What are they?– How I use them
My Research– Outline– Experiments– Results– Conclusions
Acknowledgements References
What is Cancer?
“Cancer” is a wide range of diseases involving irregular growth of cells– Normal cells vs. Cancer cells
Cancerhelp.org
Epidermal Growth Factor (EGF)
What is it?
EGF and EGF receptor
What happens to a cell that binds to EGF?
Cancer and EGF
Wikipedia.org
Metastasis
Metastasis- cancer cell migration
– Tumors– Cancer cells move
through the bloodstream and lymphatic system
EGF and metastasis MDA-MB 231
Metastatic Breast Cancer Cells
Gary Carlson
Vitalex
Microfluidics can help
Microfluidic devices:– Gradients– Advantages– Modeling the body
If scientists can discover how and why cancer cells migrate we can start creating chemicals that stop or prevent them from doing so
What is a Microfluidic Device?
•Many uses and applications: pharmaceuticals, biotechnology, the life sciences, defense, public health, and agriculture
•Polydimethylsiloxane (PDMS) and soft lithography
•Gradients
George Whitesides group, Harvard
Saadi, Jeon, Wang, Lin
My Research
Goals
Cont.
Procedure– 10X Hoffman– 3 Hours– Bell-curve gradient
Analysis– Metamorph– Excel– Oriana
Metamorph images
7/18/06, 7/21/06, 7/25/06
EGF Gradient
48/64 cells moved towards gradient-75%
43/66 cells moved towards gradient-65% 91/130-69%
Conditions: 50ng/mL EGF, cells not starved
Summary
Angles
15 15
15
15
12.5 12.5
12.5
12.5
10 10
10
10
7.5 7.5
7.5
7.5
5 5
5
5
2.5 2.5
2.5
2.5
0
90
180
270
Angles
6 6
6
6
5 5
5
5
4 4
4
4
3 3
3
3
2 2
2
2
1 1
1
1
0
90
180
270
Average P-value: .0115
Average Degree (R/L): 97/262
CI Value (R/L): .13/.12
Standard Deviation (R/L): .12/.04
LHG
7/28/06 and 8/1/06
EGF Gradient
25/51 cells moved towards gradient-49%
18/44 cells moved towards gradient-41% 43/95-45%
Conditions: 500ng/mL EGF, cells not starved
Summary
Angles
6 6
6
6
5 5
5
5
4 4
4
4
3 3
3
3
2 2
2
2
1 1
1
1
0
90
180
270
Angles
6 6
6
6
5 5
5
5
4 4
4
4
3 3
3
3
2 2
2
2
1 1
1
1
0
90
180
270
Average P-value: . 612
Average Degree (R/L): 209/154
Average CI Value (R/L): .38/.01
Average Standard Deviation (R/L): .44/.24LHG
8/7/06
2 Exp.
EGF Gradient20/43-47%
Conditions: 50ng/mL EGF, cells starved (~12 hours)
Summary
Average P-value: . 695
Average Degree (R/L): 217/23
Average CI Value (R/L): .33/.07
Average Standard Deviation (R/L): .48/.18
8/19 cells moved towards gradient-42%
12/24 cells moved towards gradient-50%
Angles
4 4
4
4
3 3
3
3
2 2
2
2
1 1
1
1
0
90
180
270
Angles
4 4
4
4
3 3
3
3
2 2
2
2
1 1
1
1
0
90
180
270
RHG
8/8/06
Exp. 3
EGF Gradient
4/5 cells moved towards gradient-80%
8/11 cells moved towards gradient-72.7%
12/16-75%
Conditions: 50ng/mL EGF, cells starved (~5 hours)
Angles
2 2
2
2
1.5 1.5
1.5
1.5
1 1
1
1
0.5 0.5
0.5
0.5
0
90
180
270
Angles
2 2
2
2
1.5 1.5
1.5
1.5
1 1
1
1
0.5 0.5
0.5
0.5
0
90
180
270
8/24/06 and 8/25/06
3 Exp.
EGF Gradient67/101-66%
Conditions: 50ng/mL EGF, cells starved (1-3 hours)
Summary
Average P-value: .016
Average Degree (R/L): 106/260
CI Value (R/L): .12/.09
Standard Deviation (R/L): .08/.06
31/46 cells moved towards gradient-67%
36/55 cells moved towards gradient-65%
Angles
8 8
8
8
6 6
6
6
4 4
4
4
2 2
2
2
0
90
180
270
Angles
8 8
8
8
6 6
6
6
4 4
4
4
2 2
2
2
0
90
180
270
RHG
Conclusions
EGF High Concentration Starvation
The Future (and present)
More growth factors Cells Chemo-repellants Devices that better model the body Extracellular matrices
Acknowledgements
I’d like to thank my mentor, Noo Li Jeon, my graduate student, Carlos Huang, and the rest of the great people in my lab for teaching me such an incredible amount in such a short time and for taking their time to assist my research
I’d also like to thank the UROP program, with which this research opportunity would have never been possible, their time and effort
References and works cited:George M. Whitesides. The Origins and the Future of Microfluidics. Nature Publishing Group, July 2006.George M.Whitesides, Emanuele Ostuni, Shuichi Takayama, Xingyu Jiang, and Donald E. Ingber. Soft Lithography in Biology and Biochemistry. Annual Review of Biomedical Engineering, 2001 (335-573).Noo Li Jeon, Harihara Baskaran, Stephan K.W. Dertinger, George M. Whitesides, Livingston Van De Water, and Mehmet Toner. Neutrophil Chemotaxis in Linear and Complex Gradients of Interleukin-8 Formed in a Microfabricated Device. Nature Publishing Group, 2002.Stephan K. W. Dertinger, Daniel T. Chiu, Noo Li Jeon, and George M. Whitesides. Generation of Gradients Having Complex Shapes Using Microfluidic Networks. Analytical Chemistry (ACS), 2001.Noo Li Jeon, Stephan K. W. Dertinger, Daniel T. Chiu, Insung S. Choi,Abraham D. Stroock, and George M. Whitesides. Generation of Solution and Surface Gradients Using Microfluidic Systems. Langmuir (ACS), 2000.Shur-Jen Wang, Wajeeh Saadi, Francis Lin, Connie Minh-Canh Nguyen, Noo Li Jeon. Differential Effects of EGF Gradient Profiles oN MDA-MB-231 Breast Cancer Cell Chemotaxis. Elsevier, INC, 2004.Wajeeh Saadi · Shur-Jen Wang · Francis Lin · Noo Li Jeon. A Parallel-Gradient Microfluidic Chamber for Quantitative Analysis of Breast Cancer Cell Chemotaxis. Biomedical Devices (109-118), 2006.Jennifer Ouellette. A new wave of microfluidic devices. The Industrial Physicist (14-17), 2003.Laurie Tarkan. Scientists Begin to Grasp the Stealthy Spread of Cancer. The New York Times, 2006.