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Optimization of Immunofluorescent Detection of Bone Marrow Disseminated Tumor Cells
Haley D Axelrod1,2, Kenneth J Pienta1, Kenneth C Valkenburg1
11The James Buchanan Brady Urological Institute, Johns Hopkins University School of Medicine, 600 North Wolfe St., Marburg Building Room 121, Baltimore, MD 21287 USA.
Background:
Cancer metastasis is the primary cause of cancer-related deaths and remains incurable. Current clinical methods for predicting metastatic recurrence are not sensitive enough to detect individual cancer cells in the body; therefore, current efforts are directed toward liquid biopsy-based assays to capture circulating and disseminated tumor cells (CTCs and DTCs) in the blood and bone marrow, respectively. The most promising strategy is fluorescence-based immunostaining using cancer cell-specific markers. However, despite recent efforts to develop robust processing and staining platforms, results from these platforms have been discordant among groups, particularly for DTC detection. While the choice of cancer cell-specific markers is a large factor in this discordance, we have found that marker-independent factors causing false signal are just as critical to consider. Bone marrow is particularly challenging to analyze by immunostaining because endogenous immune cell properties and bone marrow matrix components typically generate false staining. For immunostaining of whole tumor tissue containing ample cancer cells, this background staining can be overcome. Application of fluorescent-based staining for rare cells, however, is easily jeopardized by immune cells and autofluorescence that lead to false signal.
Results:
We have specifically found two types of background staining in bone marrow samples: autofluorescence of the tissue and non-specific binding of secondary antibodies. We systematically optimized a basic immunofluorescence protocol to eliminate this background using cancer cells spiked into human bone marrow. This enhanced the specificity of automated scanning detection software. Our optimized protocol also outperformed a commercial rare cell detection protocol in detecting candidate DTCs from metastatic patient bone marrow.
Conclusions:
Robust optimization to increase the signal-to-noise ratio of immunofluorescent staining of bone marrow is required in order to achieve the necessary sensitivity and specificity for rare cell detection. Background immunofluorescent staining in bone marrow causes uncertainty and inconsistency among investigators, which can be overcome by systematically addressing each contributing source. Our optimized assay eliminates sources of background signal, and is adaptable to automated staining platforms for high throughput analysis.
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