Modeling Cell Reactions to Ionizing Radiation: From a Lesion to a Cancer. Issue 2 (4th April 2019)

• Record Type: Journal Article
• Authors: Dobrzyński, L.; Fornalski, K. W.; Reszczyńska, J.; Janiak, M. K.
• Is Part Of: Dose-response. Volume 17:Issue 2(2019:Apr./Jun.)
• Publication Date: 2019-04-04
• Subjects: ionizing radiation -- low doses -- adaptive response -- modelling -- cancer -- radiation biophysics -- physics of cancer; Dose-response relationship (Biochemistry) -- Periodicals; Drugs -- Dose-response relationship -- Periodicals; Drugs -- Physiological effect -- Periodicals; Hormesis -- Periodicals; Dose-Response Relationship, Drug -- Periodicals; Dose-response relationship (Biochemistry); Drugs -- Dose-response relationship; Drugs -- Physiological effect; Periodicals; 571.634
• DOI: 10.1177/1559325819838434
• Languages: English
• ISSNs: 1559-3258

Abstract

This article focuses on the analytic modeling of responses of cells in the body to ionizing radiation. The related mechanisms are consecutively taken into account and discussed. A model of the dose- and time-dependent adaptive response is considered for 2 exposure categories: acute and protracted. In case of the latter exposure, we demonstrate that the response plateaus are expected under the modelling assumptions made. The expected total number of cancer cells as a function of time turns out to be perfectly described by the Gompertz function. The transition from a collection of cancer cells into a tumor is discussed at length. Special emphasis is put on the fact that characterizing the growth of a tumor (ie, the increasing mass and volume), the use of differential equations cannot properly capture the key dynamics—formation of the tumor must exhibit properties of the phase transition, including self-organization and even self-organized criticality. As an example, a manageable percolation-type phase transition approach is used to address this problem. Nevertheless, general theory of tumor emergence is difficult to work out mathematically because experimental observations are limited to the relatively large tumors. Hence, determination of the conditions around the critical point is uncertain.