A Rare-Cell Detector for Cancer Krivacic, Robert T.; Ladanyi, Andras; Curry, Douglas N. ...
Proceedings of the National Academy of Sciences - PNAS,
07/2004, Letnik:
101, Številka:
29
Journal Article
Recenzirano
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Although a reliable method for detection of cancer cells in blood would be an important tool for diagnosis and monitoring of solid tumors in early stages, current technologies cannot reliably detect ...the extremely low concentrations of these rare cells. The preferred method of detection, automated digital microscopy (ADM), is too slow to scan the large substrate areas. Here we report an approach that uses fiber-optic array scanning technology (FAST), which applies laser-printing techniques to the rare-cell detection problem. With FAST cytometry, laser-printing optics are used to excite 300,000 cells per sec, and emission is collected in an extremely wide field of view, enabling a 500-fold speed-up over ADM with comparable sensitivity and superior specificity. The combination of FAST enrichment and ADM imaging has the performance required for reliable detection of early-stage cancer in blood.
Purpose: The purpose of this study was to assess the feasibility of using rare event imaging system (REIS)-assisted analysis to detect
occult tumor cells (OTCs) in peripheral blood (PB). The study ...also sought to determine whether REIS-assisted OTC detection
presents a clinically viable alternative to manual microscopic detection to establish the true significance of OTC from solid
epithelial tumors.
Experimental Design: We recently demonstrated proof of concept using a fluorescence-based automated microscope system, REIS, for OTC detection
from the PB. For this study, the prototype of the system was adopted for high-throughput and high-content cellular analysis.
Results: The performance of the improved REIS was examined using normal blood ( n = 10), normal blood added to cancer cells ( n = 20), and blood samples obtained from cancer patients ( n = 80). Data from the screening of 80 clinical slides from breast and lung cancer patients, by manual microscopy and by the
REIS, revealed that as many as 14 of 35 positive slides (40%) were missed by manual screening but positively identified by
REIS. In addition, REIS-assisted scanning reliably and reproducibly quantified the total number of cells analyzed in the assay
and categorized positive cells based on their marker expression profile.
Conclusions: REIS-assisted analysis provides excellent sensitivity and reproducibility for OTC detection. This approach may enable an
improved method for screening of PB samples and for obtaining novel information about disease staging and about risk evaluation
in cancer patients.