During the past five years, we have identified two mathematical equations that quantitatively account for the genome-wide RNA level data measured from (i) budding yeast undergoing nutritional stress and (ii) the breast cancer tissues of 20 patients before and after treating with anticancer drug, doxorubicin [1, 2, 3]. The Poisson distribution formula was found to fit the probability of observing either the beneficial or the harmful RNA expression patterns exhibited by 988 genes in a given number of breast cancer patients, from which a quantitative measure of the efficacy of doxorubicin, referred to as the “micro-therapeutic index (mTI)”, could be calculated, i.e., mTI = 2.5. The same RNA level data set was found to fit another mathematical equation called BRE (blackbody radiation-like equation) that was derived from the blackbody radiation formula discovered by M. Planck in 1900 : y = (a/(Ax + B)^5)/(e^(b/(Ax + B)) -1 ), where y = the probability of observing RNA levels within a given range, x = the ranges of RNA levels. Using the Solver program, we determined the numerical values of the parameters, a, b, A and B, that best fit BRE to the RNA level data. These parameter values were found to different between the RNA data measured before (BE) and after (AF) the drug treatment. This finding supports the notion that BRE can be used as a quantitative method to characterize the effects of drugs on genome-wide RNA metabolism in both normal and diseased cells, thus providing a novel strategy for drug discovery. |
