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Jul 1, 2014 (Vol. 34, No. 13)

Detecting Circulating Tumor Cells

Live-Cell RNA Detection Enables Novel Method for CTC Identification

  • Circulating tumor cells (CTCs) are released into the bloodstream from primary and metastatic cancers and could potentially help with early cancer detection. However, CTCs are present at concentrations as low as less than one CTC per million white blood cells (WBCs). It is therefore critical that CTC detection strategies offer high sensitivity and efficiency, while minimizing the number of WBCs mistaken as CTCs to ensure specificity.

    In this study, an ImageStream®X Mark II imaging flow cytometer (Amnis) was employed along with SmartFlare™ fluorescent RNA detection probes (EMD Millipore) to collect imagery from large numbers of WBCs that were spiked with live SKBR-3 human breast cancer cells. Post spiking, the cell population was labeled with detection probes targeting EPCAM and Her-2 mRNAs, common markers for breast cancer cells. By combining the probes with the use of an imaging flow cytometer, the CTCs could be identified and counted in an objective and statistically significant manner.

  • Materials and Methods

    Whole blood was obtained from healthy volunteers and placed in tubes containing EDTA. Red blood cells (RBC) were then lysed using RBC lysis buffer and the pellet was suspended in wash buffer (phosphate-buffered saline [PBS] with 2% fetal bovine serum [FBS]). SKBR-3 cells were cultured in flasks with Dulbecco’s modified Eagle medium (DMEM) supplemented with 10% FBS before subsequent harvesting using trypsin.

    Cell count was determined for WBCs and SKBR-3 cells using a Scepter™ handheld cell counter (EMD Millipore). The WBCs were plated in a 24-well plate and SKBR-3 cells were spiked into the WBC sample such that the final ratio of SKBR-3 cells to WBCs was 1:100,000.

    EPCAM Cy-5 and Her-2 Cy-3 SmartFlare probes were then added to individual wells at a concentration of 25 pM. The probes enable target RNA levels to be determined in live, individual cells while leaving those cells intact for further analysis. The technology uses gold nanoparticles bound to sequence-specific oligonucleotide probes; in the presence of their targets, the probes fluoresce, allowing the cells to be imaged and the RNA quantified using flow cytometry. The probes enter and exit the cell through natural endocytosis and exocytosis without adverse effects, making them a valuable tool for studying CTCs within peripheral blood mononuclear cells (PBMCs).

    SmartFlare uptake control, which has a constitutively fluorescent fluorophore, was used as the positive control probe. SmartFlare scramble control, which targets nonsense mRNA sequences not present in cells, was used as the negative control. Cells were incubated with the probes for 16 hours.

    After incubation, cells were harvested, centrifuged, and resuspended in 50 uL of wash buffer. Analysis was performed on the ImageStreamX Mark II flow cytometer, which has the capacity to acquire multispectral images of large numbers of cells. Image analysis was performed using the image-based algorithms available in IDEAS 6.0 image analysis software.

  • CTC Quantification

    Click Image To Enlarge +
    Figure 1. BDI plots for each SmartFlare target. Cells with BDI higher than the mean BDI of scramble control were selected by setting a gate to identify signal above the background signal of the SmartFlare probe.

    A gating strategy was used to detect and quantify CTCs. First, the background bright detail intensity (BDI) was determined. The BDI algorithm sums the fluorescence of bright spots having radii of three pixels or less within the cell imagery. This calculation discriminates against uniformly distributed autofluorescence and nonspecific background signal.

    The average BDI of the scramble control cells was calculated to determine the background BDI of the SmartFlare probe. Next, a BDI plot was made for each mRNA target. Cells displaying a BDI above background levels were selected by setting a gate to select for signals above the probe’s background signal (Figure 1).

  • Click Image To Enlarge +
    Figure 2. Plot of Raw Min Pixel vs. Area of the SmartFlare probe, made from the high-BDI cells to aid in the exclusion of WBCs while identifying the target SKBR-3 cells.

    Following selection of the high BDI cells, the target SKBR-3 cells had to be identified—while excluding the normal white blood cells. To accomplish this, we plotted Raw Min Pixel vs. Area (Figure 2). Raw Min Pixel is a signal strength-based parameter that measures the smallest pixel value in an image. Area is a size-based feature that quantifies the area of a mask in square microns. The SKBR-3 cells are bigger in size than WBCs and labeled with detection probes. Therefore, they should have higher Raw Min Pixel and Area values than WBCs.

    The final step was to zero in on the SKBR-3 cells spiked within WBCs. We took the SKBR-3 cells region from the Raw Min Pixel vs. Area graph, and plotted Circularity vs. Symmetry 4 for each detection probe (Figure 3). Circularity is a shape-based parameter that measures the degree of a mask’s deviation from a circle. A perfect circle will have less deviation and hence a high circularity score.

    Symmetry 4 is also a shape-based parameter, which measures the tendency of an object to have a fourfold axis of symmetry and therefore four lobes. Using these shape-based parameters, the IDEAS 6.0 image analysis software is able to distinguish between circular, one-lobed SKBR-3 cells and clumps of dead WBCs stuck together, which have a low circularity score and high Symmetry 4 value.

    Using these gating methods, we were able to detect 11 Her-2-positive CTCs and 15 EPCAM-positive CTCs, out of 21 SKBR-3 cells expected. The 11 Her-2-positive CTCs represented 0.004% of the total cells collected on the imaging flow cytometer. The 15 EPCAM-positive CTCs represented 0.003% of the total cells collected on the instrument; though equal numbers of cells were spiked in both samples, more cells were acquired in the EPCAM sample, resulting in the lower percentage.

  • Conclusion

    Click Image To Enlarge +
    Figure 3. To further identify the target cells, a plot of Circularity vs. Symmetry 4 for each SmartFlare probe was generated.

    Image-based analysis provides both qualitative and quantitative morphologic information useful for discriminating CTCs from residual WBCs. An imaging flow cytometer and SmartFlare RNA detection probes provided the ability to accurately identify and enumerate one SKBR-3 cell in 100,000 WBCs.

    CTCs are a promising new area in cancer research, offering the potential to help with early detection and patient diagnosis. The ability to enumerate the CTCs in live cells without perturbing them also allows for the collection and additional analysis of those cells to further understand the complex biology of CTCs. Efforts to improve the accuracy and sensitivity of CTC identification are critical to driving the use of these cells.



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