The Planck-Shannon plot: A
novel method for discovering "hypermetabolic pathways" as potential
biomarkers for anti-cancer drugs.
Ji, S., Rutgers
University, Piscataway, USA
The
Planckian Distribution Equation (PDE) was derived at Rutgers in 2008 from the
blackbody radiation equation (BRE) discovered by M. Plank in 1900 [1, 2, 3]. PDE replaces the universal constants and
temperature in BRE with free parameters, A, B and C, resulting in y = A/(x +
B)^5/(e^(C/(x + B)) – 1). Two kinds of information can be defined based on PDE
[4]: Plankian information of the first kind (IPF) and Plankian information
of the second kind (IPS). PDE also allows us to calculate the associated
Shannon entropy as H = - \Sigma (pi log2 pi). We have analyzed the mRNA levels of 10 metabolic pathways
measured from human breast tissues using microarrays [5]. These data sets all
fitted PDE, generating 10 each of the I_PS and H values which are plotted in the
upper left panel in Figure 1. A similar
analysis was carried out on a set of 10 arbitrarily selected mRNA data of
unknown biological function (see the upper right panel in Figure 1). Only the
10 sets of mRNA data with known metabolic functions are linearly correlated and
the other 10 sets of unknown mRNA’s are distributed randomly in the
Planck-Shannon space, indicating that the Planck-Shannon plot is able to identify
functionally related set of metabolic pathways.
The lower panels of Figure 1 display
the results of analyzing the 5 sets of the mRNA levels of the hypothetical
protein measured from 5 breast cancer patients. The drug treatment increased
the correlation coefficient of the Planck-Shannon plot from 0.390 to
0.791, indicating that the hypothetical
protein may have been implicated in the doxorubicin-induced increase in the
longevity of the 5 breast cancer patients. Thus,
the hypothetical protein may serve as a biomarker for discovering anti-breast
cancer drugs when its mRNA levels are analyzed utilizing the Planck-Shannon
plot.
No comments:
Post a Comment