Towards a fast, efficient assay for isolating circulating tumor cells

1. Towards a fast, efficientassay for isolating circulating tumor cells July 30, 2009 PI: Professor David Eddington Grad Student: Cari Launiere Me: Joey Labuz

2. Introduction • Breast, colon, prostate, and lung cancers accounted for nearly half of cancer deaths (American Cancer Society, 2008) • All 4 can be metastatic diseases • Circulating tumor cells (CTCs) • Rare in blood (as low as 1 in 1,000,000,000) • Alternative to biopsy screenings • High expression of epithelial cell adhesion molecule (EpCAM) (Went et al., 2004)

3. CTC-chip assay • Posts fabricated from Si wafer • 100 µm diameter • 100 µm tall • Posts coated with anti-EpCAM • Whole blood flowed through device by pressure source • mL-scale volumes SEM of Si posts with captured cancer cell (colored red for visibility) (S Nagrath, et al. 2007)

4. Pros Simpler than other methods (immunomagnetic beads) No pre-processing of blood necessary High sensitivity (99.1%) Improved purity (over two times better) Cons Complex fabrication process (DRIE) Max flow of ~1 mL/hr 1-2 hours to run sample We can do ~6x faster High cost Low efficiency (~60%) Low purity (~50%) CTC-chip assay (cont.)

5. Photo/SoftLithography • Rapid prototyping of polydimethylsiloxane channels • Benefits of PDMS • Good optical clarity • Good scalability • PDMS channel placed on glass slide with proteins Rapid prototyping of PDMS channels (JS Mohammed, et al. 2008)

6. Cav-1 expression generally inversely proportional to EpCAM expression Explore as way to isolate CTCs with low EpCAM expression (i.e. MDA-MB-231) (Sieuwerts, et al, 2009) Caveolin-1 Capture Computer generated images of various Cav-1 conformations (Cai, et al)

7. Present in physiological flow situations (e.g. blood vessels) Binds to cancer as well as blood cells (e.g. leukocytes) Catch bond mechanism pulls cells out of flow Chinese finger trap of proteins E-Selectin Binding Catch bonds’ strength increases as tensile force, until a maximum, where the force begins to overcome the bond strength (Thomas W, 2009).

8. Mixer Optimization • Force cells down to proteins on slide • Channel height: 100 µm • Groove height: 160 µm • Grooves lead to transverse flow Channel Groove Transverse Flow Flow Slide with protein coat (NS Lynn and DS Dandy, 2007)

9. Imaging Problem – Clumped Cells • Clumped cells are often counted as one, instead of several • Watersheding methods inadequate for separating cells and maintaining image quality

10. Imaging Solution – Clumped Cells • Use ImageJ • Macro executes series of commands • Output text file to MatLab • Use MatLab • Find clumped cells based on average area and standard deviation • Using average, separate clumps into individual cells Cell area histogram: All cells with areas greater than the mean + standard deviation are considered clumps

11. Imaging Solution – Clumped Cells • Validate method by using hand counts • Image 1 • By hand: 97 • Using program: 98 • Error: 1 % • Image 2 • By hand: 841 • Using program: 831 • Error: 1.2 % Image 1 Image 2

12. Imaging Problem – Mixer • Mixer pattern diffracts light • Creates problems during image processing

13. Use subtract function in ImageJ Subtracts grayscale values pixel by pixel Subtract image from control Imaging Solution – Mixer _ Control image Image with cells

14. Imaging Solution – Mixer

15. Run trials with HL-60 and MDA-MB-231 cells, respectively Cells roll on E-selectin as expected Observed under the microscope at 0.1 mL/min Anti-EpCAM helped maintain new capture Anti-CAV1 helped facilitate stationary capture Cells detach upon entering mixer Could be due to overly turbulent flow Or due to poor protein coating – adjust method for future experiments Preliminary results

16. Summary • CTCs attractive option for cancer screening • Less invasive than biopsy • Broader, earlier detection • Channel optimized to increase cell contact with protein-functionalized surface • Use protein cocktail to optimize capture • E-selectin to pull cells out of flow • Anti-EpCAM and anti-CAV1 to bind CTCs • Wrote programs for rapid image analysis

17. Acknowledgements • Financial support • NSF • DoD • Cari Launiere • Prof. David Eddington • REU advisors • The BML lab • My roommate

18. References Cai, Q. C. et al. Putative caveolin-binding sites in SARS-CoV proteins. Acta Pharmacologica Sinica 24, 1051-1059 (2003). Cancer Facts & Figures 2008. American Cancer Society (2008). Lynn NS and DS Dandy. “Geometrical optimization of helical flow in grooved micromixers” Lab on a Chip. 7: 580-587. 2007. Mohammed, JS, HH Caicedo, et al. “Microfluidic add-on for standard electrophysiology chambers.” Lab on a Chip. 8: 1048-1055. 2008 Monahan, J., Gewirth, A. A. & Nuzzo, R. G. A method for filling complex polymeric microfluidic devices and arrays. Analytical Chemistry 73, 3193-3197 (2001). Nagrath, S, LV Sequist, et. al. “Isolation of rare circulating tumour cells in cancer patients by microchip technology.” Nature. 450: 1235-1239. 2007. Sieuwerts, A. M. et al. Anti-Epithelial Cell Adhesion Molecule Antibodies and the Detection of Circulating Normal-Like Breast Tumor Cells. Journal of the National Cancer Institute 101, 61-66 (2009). Thomas, W. Research Projects: Catch Bonds.<https://faculty.washington.edu/wendyt/research.html>. 2009. Went, P. T. et al. Frequent EpCam protein expression in human carcinomas. Human Pathology 35, 122-128 (2004). Zen K, Liu D-Q, Guo Y-L, Wang C, Shan J, et al. (2008) CD44v4 Is a Major E-Selectin Ligand that Mediates Breast Cancer Cell Transendothelial Migration. PLoS ONE 3(3): e1826.