Mathematical (Quantitative) and Cell Linguistic (Qualitative) Evidence for Hypermetabolic Pathways as Potential Drug Targets

Objectives: According to the cell language theory first proposed in 1997, living cells use a molecular language whose structure is similar to (or isomorphic) with the structures of the human language with respect to the 10 out of the 13 design features established by linguists. One of the predictions of the cell language theory is that there should exist in the living cell what is referred to as ‘hypermetabolic pathways’ that correspond to texts in human language deemed essential for reasoning and computing. A mathematical method known as the Planck-Shannon plot is described that can be employed to identify the predicted hypermetabolic pathways that underlie human breast cancer and hence can serve as potential anti-cancer drug targets. Data and analytic method: The gene expression profile data measured with microarrays were provided by Perez- Ortin’s group in Valencia, Spain and Perou and his coworkers at Stanford University. The mRNA data were transformed into histograms which were then fitted to the Planck Distribution Equation (PDE y = ((A / (x + B)5 ) / (eC/ ( x + B) – 1)) , to generate the numerical values for the parameters, A, B and C, that quantitatively characterize the shape of each histogram and hence the information contained in the original mRNA data set. The fitting of mRNA data to PDE was performed by the Sovler program available in Excel. Results: The hypermetabolic pathways, both intra-organismic, and inter-organismic, that are predicted by the cell language theory can be identified with the PDE-based analysis of mRNA data. The intra-organismic hypermetabolic pathway identified with PDE consists of 3 or more traditional metabolic pathways, while the interorganismic hypermetabolic pathway consists of one traditional metabolic pathway whose activity is correlated among 3 or more organisms exhibiting a common phenotype, e.g., breast cancer. Conclusion: Ribonoscopy, defined as the genome-wide study of mRNA levels within an organism or between different organisms, when combined with the quantitative method of analysis afforded by the Planck Distribution Equation (PDE), can identify a novel class of metabolic structures referred to as “intra-organismic hypermetabolic pathways” and “inter-organismic hypermetabolic pathways” that can serve as potential targets of cancer drug therapy.