Sphingolipid pathway as a biosensor of cancer chemosensitivity: a proof of principle

 

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Bibliographic Details
Authors: Molina Mora, José Arturo, Mesén Porras, Susana, Quirós Fernández, Isaac, Kop Montero, Mariana, Rojas Céspedes, Andrea, Quirós Barrantes, Steve, Siles Canales, Francisco, Mora Rodríguez, Rodrigo Antonio
Format: artículo original
Publication Date:2022
Description:Cancer is a complex genetic disease with reduced treatment alternatives due to tumor heterogeneity and drug multiresistance emergence. The sphingolipid (SL) metabolic pathway integrates different responses of cellular stress signals and defines cell survival. Therefore, we suggest studying the perturbations on the sphingolipid pathway (SLP) caused by chemotherapeutic drugs using a systems biology approach to evaluate its functionality as a drug response sensor. We used a sphingomyelin-BODIPY (SM-BOD) sensor to study SL metabolism by flow cytometry and live cell imaging in different cancer models. To decode pathway complexity, we implemented Gussian mixture models, ordinary differential equations models, unsupervised classification algorithms and a fuzzy logic approach to assess its utility as a chemotherapy response sensor. Our results show that chemotherapeutic drugs perturb the SLP in different ways in a cell line-specific manner. In addition, we found that few SM-BOD fluorescence features predict chemosensitivity with high accuracy. Finally, we found that the relative species composition of SL appears to contribute to the resulting cytotoxicity of many treatments. This report offers a conceptual and mathematical framework for developing personalized mathematical models to predict and improve cancer therapy.
Country:Kérwá
Institution:Universidad de Costa Rica
Repositorio:Kérwá
Language:Inglés
OAI Identifier:oai:kerwa.ucr.ac.cr:10669/87823
Online Access:https://www.revistas.una.ac.cr/index.php/uniciencia/article/view/16127
https://hdl.handle.net/10669/87823
Keyword:CANCER
Tumor chemosensitivity
Sphingolipids
Systems biology
Chemotherapy
Fuzzy logic