Monocarboxylate transport inhibition potentiates the cytotoxic effect of 5-fluorouracil in colorectal cancer cells

Cancer cells rely mostly on glycolysis to meet their energetic demands, producing large amounts of lactate that are extruded to the tumour microenvironment by monocarboxylate transporters (MCTs). The role of MCTs in the survival of colorectal cancer (CRC) cells is scarce and poorly understood. In this study, we aimed to better understand this issue and exploit these transporters as novel therapeutic targets alone or in combination with the CRC classical chemotherapeutic drug 5-Fluorouracil. For that purpose, we characterized the effects of MCT activity inhibition in normal and CRC derived cell lines and assessed the effect of MCT inhibition in combination with 5-FU. Here, we demonstrated that MCT inhibition using CHC (a-cyano-4-hydroxycinnamic acid), DIDS (4,4'-diisothiocyanatostilbene-2,2'-disulphonic acid) and quercetin decreased cell viability, disrupted the glycolytic phenotype, inhibited proliferation and enhanced cell death in CRC cells. These results were confirmed by specific inhibition of MCT1/4 by RNA interference. Notably, we showed that 5-FU cytotoxicity was potentiated by lactate transport inhibition in CRC cells, either by activity inhibition or expression silencing. These findings provide novel evidence for the pivotal role of MCTs in CRC maintenance and survival, as well as for the use of these transporters as potential new therapeutic targets in combination with CRC conventional therapy.

Nanotechnological approaches using curcumin and Withania somnifera: neuroprotection and antimicrobial activities

Tese de Doutoramento em Biologia de Plantas

Current Challenges in Modeling Cellular Metabolism

Mathematical and computational models play an essential role in understanding the cellular metabolism. They are used as platforms to integrate current knowledge on a biological system and to systematically test and predict the effect of manipulations to such systems. The recent advances in genome sequencing techniques have facilitated the reconstruction of genome-scale metabolic networks for a wide variety of organisms from microbes to human cells. These models have been successfully used in multiple biotechnological applications. Despite these advancements, modeling cellular metabolism still presents many challenges. The aim of this Research Topic is not only to expose and consolidate the state-of-the-art in metabolic modeling approaches, but also to push this frontier beyond the current edge through the introduction of innovative solutions. The articles presented in this e-book address some of the main challenges in the field, including the integration of different modeling formalisms, the integration of heterogeneous data sources into metabolic models, explicit representation of other biological processes during phenotype simulation, and standardization efforts in the representation of metabolic models and simulation results.