Date Published: September 6, 2011
Publisher: Hindawi Publishing Corporation
Author(s): Nickolaas Maria van Rodijnen, Math Pieters, Sjack Hoop, Marius Nap.
Propidium Iodide is a fluorochrome that is used to measure the DNA content of individual cells, taken from solid tissues, with a flow cytometer. Compensation for spectral cross-over of this fluorochrome still leads to compensation results that are depending on operator experience. We present a data-driven compensation (DDC) algorithm that is designed to automatically compensate combined DNA phenotype flow cytometry acquisitions. The generated compensation values of the DDC algorithm are validated by comparison with manually determined compensation values. The results show that (1) compensation of two-color flow cytometry leads to comparable results using either manual compensation or the DDC method; (2) DDC can calculate sample-specific compensation trace lines; (3) the effects of two different approaches to calculate compensation values can be visualized within one sample. We conclude that the DDC algorithm contributes to the standardization of compensation for spectral cross-over in flow cytometry of solid tissues.
Multiparameter flow cytometry (MP-FCM) of solid tumors is a powerful tool for quantification of antigen expression and DNA content, based on large numbers of individual mammalian cells. However, simultaneous application of different fluorochromes introduces spectral cross-over. Spectral cross-over is the acquisition of fluorochrome intensities from a primary fluorochrome in the detector(s) used to acquire the intensity of secondary fluorochromes. Compensation is the estimation of the amount of fluorochrome intensity that needs to be subtracted from the acquired intensities to correct for spectral cross-over [1–4]. Proper compensation is achieved when the compensated data in the cross-over detector has no bias in the fluorescence distribution that is related to the intensity measured in any other detector . To achieve proper compensation, the amount of spectral cross-over of each fluorochrome in a flow cytometry panel can be estimated with a single stained control (SSC). An SSC consists of a single cell suspension of which the individual cells are labeled with only one fluorochrome. This fluorochrome, of which the intensity is acquired in its primary detector, exhibits spectral cross-over in other secondary detectors. The cross-over of the SSC in each secondary detector is expressed as a percentage of the intensity acquired in the primary detector. This percentage is based on the correlation coefficient between the fluorochrome intensity of a SSC in the primary and secondary detector(s) [1, 3]. The combination of all the percentages cross-over for each SSC, in each secondary detector, is expressed in a compensation matrix. It is common to calculate this compensation matrix once or twice a day and to use it for all following acquisitions.
To test the DDC algorithm we conducted three experiments. In the first experiment we compared the compensation values obtained with DDC to those of manual compensation. All manual compensations were performed individually in the Summit software. We consider the performance of the DDC algorithm comparable with manual compensation when the two sets of compensation values agree. In the second experiment the results of the SLN analysis are calculated. These results are expressed as the percentage of positive counts in the TEST sample. The outcome is compared between the DDC and Summit paths. For these first two experiments a new MATLAB implementation was written for the reanalysis of the cases in the DDC dataset, which used the function FCA_readfcs . The only difference between the automated Matlab implementation and the manual analysis in Summit software is the compensation algorithm. The Matlab implementation of DDC includes the “Trust Region” algorithm [15–17]. This algorithm calculates the optimal fit of the compensation trace line through the CC. Alternatively, the manually determined compensation trace line, using the Summit software, is based on a visually determined optimal fit through all available counts. After compensation is completed, a doublet discrimination step is applied. This doublet discrimination will not influence the first experiment, although it slightly affects the percentage positive counts in the second experiment.
We have evaluated an automated data-driven approach to fluorescence compensation in a two-color setting. All other compensation methods used thus far involve operator interaction and limit a fully automated data analysis. In order to provide confirmation and validation for the proposed methodology, we have used two methods that are commonly used in flow cytometry laboratories as reference, the Summit and the Winlist software. We have compared the outcome of the proposed DDC method against the outcome of these reference methods. The results show that (1) two color flow cytometry compensation and analysis of sentinel lymph nodes in Summit and DDC lead to comparable results, despite that Summit uses different compensation values than DDC does, (2) the effects of different approaches to calculate compensation values based on the CC can be visualized within one sample, (3) DDC is a data-driven method that combines the information of a NC or SSC with a TEST to calculate sample-specific trace lines, which enables the possibility to automatically analyze large datasets of individual cases batchwise. This is where DDC improves current compensation methods.