The different methods (correlation, logistic regression, median and random forest methods) for the selection of informative characteristics of the intensity distribution of fluorescent nuclei on multichannel luminescent images of cancer cells are considered. The input data are the three-channel RGB images. In total, 39 standard characteristics of distributions are studied, including 13 characteristics per each color channel. It is established that the use of 6 features permits to achieve the same classification accuracy as for using 39 features. Moreover, one can use only two features with an insignificant increase in the classification accuracy (by 0.005). It is proposed to use the data of the immunohistochemical analysis of biomarkers in breast cancer cells during the analysis of luminescent images when processing the results in oncocytology.