Hybrid mathematical modeling decodes the complexity of sphingolipid pathway to predict chemosensitivity

Abstract

Sphingolipid (SL) signaling pathway is a complex biological system able to integrate different types of cellular stress signals related to induction of cell death pathways with special interest in cancer. This makes of the SL pathway a promising sensor of chemosensitivity and a target hub to overcome resistance. However, it is unclear how chemotherapeutic drugs can disturb the SL pathway and how the SL content modulates cellular fate. A hybrid mathematical model was proposed in order to integrate i) the metabolism of SL analogue (SM-BODIPY) modeled by an ordinary differential equation (ODE) approach, ii) a Gaussian mixture model (GMM) of the fluorescence features to identify how the SL pathway senses the effect of chemotherapeutic drugs and iii) a fuzzy logic model (FLM) to associate SL composition with cell viability by semi-quantitative rules. Altogether, this hybrid model approach was able to predict the cell viability of double experimental perturbations with chemotherapy, indicating that the SL pathway is a promising sensor to design strategies to overcome drug resistance in cancer.