Selection of Unique Molecules for Cancer Treatment by Distance-Based Method: Hypericin Effect on Respiratory Chain

Abstract

The heterogeneous composition of tumors presents a significant obstacle to the selection of a single molecule as a potential universal inhibitor of tumor growth. Lipid signaling and cellular metabolism have become the main targets of anticancer treatment in recent years. The protein kinase C (PKC) regulators Gö6976, rottlerin, hypericin, and phorbol myristyl acetate have been identified as agents affecting cellular metabolism. Measurable parameters describing metabolism, endocytosis, and respiration were subjected to a distance-based computational procedure for higher dimensions to complement and extend the knowledge gained from experimental data. The mutual distances of the parameters of the substances applied to the cancer cells in the presence and absence of lipids were calculated within the Lp spaces. The distance-based methods and comparisons of the generalized distances suggested to us the exceptional role of hypericin in heterogeneous systems. Furthermore, our results are confirmed by Western blotting of the levels of respiratory chain proteins and enzymes active in oxidative stress defense in cancer cell monolayers and spheroids. PKCα and PKCδ have been studied for lipid-activated cell signaling. In this study, we attempt to apply the concept of parametric distance in cell signal transduction and activation where the above methods have not yet been used.