Enzymes of the cytochrome P450 (CYP) family catalyze the metabolism of chemotherapeutic agents and are among the key players in primary and acquired chemoresistance of cancer. The activity of CYP is heterogeneous in tumor tissues, and the quantitative characteristics of this heterogeneity can be used to predict chemoresistance. Cytometry of reaction rate constant (CRRC) is a kinetic approach to assess cell population heterogeneity by measuring rates of processes at the single-cell level via time-lapse imaging. CRRC was shown to be an accurate and robust method for assessing the heterogeneity of drug-extrusion activity catalyzed by ABC transporters, which are also key players in cancer chemoresistance. We hypothesized that CRRC is also a reliable method for assessing the heterogeneity of CYP activity. Here, we evaluated the robustness of assessing the heterogeneity of CYP activity by CRRC with respect to controlled variation in the concentration of a CYP substrate by comparing CRRC with non-kinetic approaches. We found that changing the substrate concentration by 20% resulted only in minimal changes in the position, width, and asymmetry of the peak in the CRRC histogram, while these parameters varied greatly in the non-kinetic histograms. Moreover, the Kolmogorov-Smirnov statistical test showed that the distribution of the cell population in CRRC histograms was not significantly different; the result was opposite for non-kinetic histograms. In conclusion, we were able to demonstrate the robustness of CRRC with respect to changes in substrate concentration when evaluating CYP activity at the single-cell level.
We propose Cytometry of Reaction Rate Constant (CRRC) for accurate analysis of cell-population heterogeneity with respect to a specific molecular reaction. Conceptually, in CRRC, the cells are loaded with a reaction substrate, and its conversion into a product is followed by time-lapse fluorescence microscopy at the single-cell level. A reaction rate constant is determined for every cell by using a known kinetic mechanism of the reaction, and a kinetic histogram “number of cells vs. the rate constant” is built. Finally, this histogram is used to determine parameters of reaction-based cell-population heterogeneity. Here, we studied a reaction of substrate extrusion from cells by ABC transporters. We proved that sizes of subpopulations with different extrusion rates could be accurately determined from the kinetic histogram, and this determination was not significantly affected by change in substrate concentration. We foresee that CRRC will facilitate the development of reliable disease biomarkers based on parameters of reaction-based cell-population heterogeneity.
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