An automated high-throughput counting method for screening circulating tumor cells in peripheral blood

Abstract

Enumeration of circulating tumor cells (CTCs) has proved valuable for early detection and prognosis in cancer treatment. This paper describes an automated high-throughput counting method for CTCs based on microfluidics and line-confocal microscopy. Peripheral blood was directly labeled with multiple antibodies, each conjugated with a different fluorophore, pneumatically pumped through a microfluidic channel, and interrogated by a line-confocal microscope. On the basis of the fluorescence signals and labeling schemes, the count of CTCs was automatically reported. Due to the high flow rate, 1 mL of whole blood can be analyzed in less than 30 min. We applied this method in analyzing CTCs from 90 stage IV breast cancer patient samples and performed a side-by-side comparison with the results of the CellSearch assay, which is the only method approved by the U.S. Food and Drug Administration at present for enumeration of CTCs. This method has a recovery rate for cultured breast cancer cells of 94% (n = 9), with an average of 1.2 counts/mL of background level of detected CTCs from healthy donors. It detected CTCs from breast cancer patients ranging from 15 to 3375 counts/7.5 mL. Using this method, we also demonstrate the ability to enumerate CTCs from breast cancer patients that were positive for Her2 or CD44(+)/CD24(-), which is a putative cancer stem cell marker. This automated method can enumerate CTCs from peripheral blood with high throughput and sensitivity. It could potentially benefit the clinical diagnosis and prognosis of cancer.

Figure 1

Schematic and data illustrating the flow-detection platform. a) Depiction of the microfluidics and optics. b) CTC detection and identification scheme using APD signals. A typical CTC event at 183 ms is positive for EpCAM (Yellow signal) and cytokeratin (Red signal), but negative for CD45 (Green signal). c) A cultured MCF-7 cell imaged in the microfluidic channel filled with whole blood. The top panel shows a bright field image of the blood in the microchannel. The white dashed circle shows the location of the MCF-7 cell that is not visible beneath the many blood cells. The blue dashed lines show the location of the microchannel walls. Fluorescence images of the same location show the MCF-7 cell labeled with both anti-EpCAM and anti-Cytokeratin.

Figure 2

The distribution of signal-to-noise ratio (S/N) of a breast-cancer sample analyzed by the EpCAM/cytokeratin/CD45 method. All the data points were two-color events (EpCAM+/Cytokeratin+/CD45-), which were considered to be CTCs.

Figure 3

False positive and recovery performance. a) On average 1.2 cells were found per mL of healthy donor blood with 60% of the samples reporting zero cells. b) MCF-7 cells with known numbers were spiked into a healthy donor’s blood, which was then labeled with PE-anti-EpCAM, Alexa647-anti-cytokeratin, and FITC-anti-CD45. Enumeration results showed an average 94% recovery.

Figure 4

Clinical results from the CTC flow counting system and CellSearch. Our method found a median of 90 CTCs per 7.5 mL of blood compared to a median of zero for the CellSearch system. The black dashed line is a simple threshold (38 counts/7.5 mL) set based on the range of detected CTCs in healthy donors. The magenta dashed line is the threshold (33 counts/7.5 mL) set using the mean background level plus two times of its standard deviation. The blue dashed line is the threshold (63 counts/7.5 mL) determined by Z-test with a 95% confidence level.

Figure 5

Comparison of the CTC enumeration results from the same set of patients using eDAR and flow detection system. The left part is the box plots that show the smallest observation, lower quartile, median, upper quartile, and the largest observation of the two data sets (eDAR vs Flow count), respectively. The right part shows the histograms of the two data sets.