We present a method for the comparative analysis of parameter groups according to their correlation to disease. The theoretical basis of the proposed method is Information Theory and Nonparametric Statistics. Normalized mutual information is used as the measure of correlation between parameters, and statistical conclusions are based on ranking. The fluorescence polarization (FP) parameter is considered as the principal diagnostic characteristic. The FP was measured in fluorescein diacetate (FDA)-stained individual peripheral blood mononuclear cells (PBMC), derived from healthy subjects and breast cancer (BC) patients, under different stimulation conditions: by tumor tissue, the mitogen phytohemagglutinin (PHA) or without the stimulants. The FP parameters were grouped according to their correlation with breast cancer. It was established that the greatest difference between cells of BC patients and healthy subjects is found in the PHA test (parameter P1).
Bibliographical noteFunding Information:
This research was supported by The Komen Foundation, The Horowitz Foundation and by US Army Medical Research and Material Command Grant DAMD17-01-1-0131.
- Breast cancer (BC)
- Fluorescence polarization (FP)
- Information Theory
- Mitogenic stimulation
- Nonparametric Statistics
- Peripheral blood mononuclear cells (PBMC)
- Selecting parameter groups