Towards a fast, efficient
assay for isolating circulating
tumor cells
July 30, 2009
PI: Professor David Eddington
Grad Student: Cari Launiere
Me: Joey Labuz
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 SEM of Si posts with captured
pressure source cancer cell (colored red for visibility)
mL-scale volumes (S Nagrath, et al. 2007)
CTC-chip assay (cont.)
Pros Cons
Simpler than other Complex fabrication
methods process (DRIE)
(immunomagnetic Max flow of ~1 mL/hr
beads) 1-2 hours to run sample
No pre-processing of We can do ~6x faster
blood necessary High cost
High sensitivity (99.1%) Low efficiency (~60%)
Improved purity (over Low purity (~50%)
two times better)
Photo/Soft
Lithography
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 Catch bonds’ strength increases as
tensile force, until a maximum, where
Chinese finger trap of the force begins to overcome the
proteins 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
Channel Groove
Flow Transverse Flow
Slide with
protein coat (NS Lynn and DS Dandy, 2007)
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 Cell area histogram: All cells with areas
cells greater than the mean + standard
deviation are considered clumps
Imaging Solution – Clumped Cells
Validate method by
Image 1
using hand counts
Image 1
By hand: 97
Using program: 98
Error: 1 %
Image 2
By hand: 841 Image 2
Using program: 831
Error: 1.2 %
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 Anti-CAV1 helped
and MDA-MB-231 facilitate stationary
cells, respectively capture
Cells roll on E- Cells detach upon
selectin as expected entering mixer
Observed under the Could be due to overly
microscope at 0.1 turbulent flow
mL/min Or due to poor protein
Anti-EpCAM helped coating – adjust
maintain new capture 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
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.. 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.