Hybrid mathematical modeling decodes the complexity of sphingolipid pathway to predict chemosensitivity
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Molina Mora, José Arturo
Quirós Barrantes, Steve
Kop Montero, Mariana
Mora Rodríguez, Rodrigo Antonio
Crespo Mariño, Juan Luis
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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.
Description
Forma parte de los trabajos presentado en el International Conference and Workshop on Bioinspired Intelligence (IWOBI). IEEE, Estados Unidos. Julio de 2017.
Keywords
Fuzzy logic, Cancer, GMM, EDO, Sphingolipids
Citation
https://ieeexplore.ieee.org/document/7985532