Reproducibility of measurements of potential doubling time of tumour cells in the multicentre National Cancer Institute protocol T92-0045

We compared the flow cytometric measurement and analysis of the potential doubling time (Tpot) between three centres involved in the National Cancer Institute (NCI) protocol T92-0045. The primary purpose was to understand and minimize the variation within the measurement. A total of 102 specimens were selected at random from patients entered into the trial. Samples were prepared, stained, run and analysed in each centre and a single set of data analysed by all three centres. Analysis of the disc data set revealed that the measurement of labelling index (LI) was robust and reproducible. The estimation of duration of S-phase (Ts) was subject to errors of profile interpretation, particularly DNA ploidy status, and analysis. The LI dominated the variation in Tpot such that the level of final agreement, after removal of outliers and ploidy agreement, reached correlation coefficients of 0.9. The sample data showed poor agreement within each of the components of the measurement. There was some improvement when ploidy was in agreement, but correlation coefficients failed to exceed values of 0.5 for Tpot. The data suggest that observer-associated analysis of Ts and tissue processing and tumour heterogeneity were the major causes of variability in the Tpot measurement. The first two aspects can be standardized and minimized, but heterogeneity will remain a problem with biopsy techniques. © 1999 Cancer Research Campaig

Computer-Assisted Microscope Analysis of Feulgen-Stained Nuclei in Gonadotroph Adenomas and Null-Cell Adenomas of the Pituitary Gland.

The current classification of clinically nonfunctioning pituitary adenomas is based on immunocytochemical and ultrastructural studies. However, a number of cases have less distinctive features that cannot be easily conformed with the prevailing morphologic classifications. The diagnostic information contributed by the determination of the nuclear DNA content (DNA ploidy level) and quantitative chromatic pattern description as opposed to the morphofunctional diagnosis in clinically nonfunctioning adenomas was consequently investigated in a series of 71 pituitary adenomas, including 31 null-cell adenomas, 35 gonadotropin adenomas, and 5 nonfunctioning adenomas that were not examined by electron microscopy. DNA ploidy level (8 variables) and quantitative chromatin pattern description (30 variables) were carried out by means of the computer-assisted microscope analysis of 80-1600 Feulgen-stained nuclei analyzed/case. The diagnostic information contributed by the 38 quantitative variables was determined by multifactorial statistical analysis (i.e. Discriminant Analysis). This computer-assisted classification significantly differentiated nulLcell adenomas from gonadotropin adenomas (p = 0.0025). In addition, it was able to differentiate three major subtypes of nonfunctioning adenomas on the basis of their immunohistochemical profiles. These were the immunonegative adenomas, the follicle-stimulating hormone (FSH)-positive adenomas, and the a-subunit (a) and/or luteiwizing hormone (LH)-positive adenomas (p < 0.0001 to p < 0.001). We thus suggest that the cytometric image analysis of Feulgen-stained nuclei can contribute on the discrimination of subtypes of clinically nonfunctioning pituitary adenomas.JOURNAL ARTICLEinfo:eu-repo/semantics/publishe

qFlow Cytometry-Based Receptoromic Screening: A High-Throughput Quantification Approach Informing Biomarker Selection and Nanosensor Development

Nanosensor-based detection of biomarkers can improve medical diagnosis; however, a critical factor in nanosensor development is deciding which biomarker to target, as most diseases present several biomarkers. Biomarker-targeting decisions can be informed via an understanding of biomarker expression. Currently, immunohistochemistry (IHC) is the accepted standard for profiling biomarker expression. While IHC provides a relative mapping of biomarker expression, it does not provide cell-by-cell readouts of biomarker expression or absolute biomarker quantification. Flow cytometry overcomes both these IHC challenges by offering biomarker expression on a cell-by-cell basis, and when combined with calibration standards, providing quantitation of biomarker concentrations: this is known as qFlow cytometry. Here, we outline the key components for applying qFlow cytometry to detect biomarkers within the angiogenic vascular endothelial growth factor receptor family. The key aspects of the qFlow cytometry methodology include: antibody specificity testing, immunofluorescent cell labeling, saturation analysis, fluorescent microsphere calibration, and quantitative analysis of both ensemble and cell-by-cell data. Together, these methods enable high-throughput quantification of biomarker expression