An experimental-mathematical approach to predict tumor cell growth as a function of glucose availability in breast cancer cell lines.

ABSTRACT: We present the development and validation of a mathematical model that predicts how glucose dynamics influence metabolism and therefore tumor cell growth. Glucose, the starting material for glycolysis, has a fundamental influence on tumor cell growth. We employed time-resolved microscopy to track the temporal change of the number of live and dead tumor cells under different initial glucose concentrations and seeding densities. We then constructed a family of mathematical models (where cell death was accounted for differently in each member of the family) to describe overall tumor cell growth in response to the initial glucose and confluence conditions. The Akaikie Information Criteria was then employed to identify the most parsimonious model. The selected model was then trained on 75% of t

SUBMITTER: Yang J 

PROVIDER: S-EPMC8277046 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature