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.