Towards a fast, efficientassay for isolating circulating tumor cells

PI: Professor David Eddington

Grad Student: Cari Launiere

Me: Joey Labuz

July 30, 2009

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)

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)

CTC-chip assay (cont.)

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%)

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)

Caveolin-1 Capture

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) Computer generated images of various Cav-1 conformations (Cai, et al)

E-Selectin Binding

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

Catch bonds’ strength increases as tensile force, until a maximum, where the force begins to overcome the bond strength (Thomas W, 2009).

Mixer Optimization

Force cells down to proteins on slide Channel height: 100 µm Groove height: 160 µm Grooves lead to transverse flow

Flow Slide with protein coat

Transverse Flow

(NS Lynn and DS Dandy, 2007)

GrooveChannel

Imaging Problem – Clumped Cells Clumped cells are often

counted as one, instead of several

Watersheding methods inadequate for separating cells and maintaining image quality

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

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

Imaging Problem – Mixer

Mixer pattern diffracts light Creates problems during image processing

Imaging Solution – Mixer

Use subtract function in ImageJ Subtracts grayscale values pixel by pixel Subtract image from control

Control image Image with cells

_

Imaging Solution – Mixer

Preliminary results

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

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

Acknowledgements

Financial support NSF DoD

Cari Launiere Prof. David Eddington REU advisors The BML lab My roommate

ReferencesCai, 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. 2008Monahan, 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.