Molecular characterization of breast cancer cell response to metabolic drugs

Abstract

Metabolic reprogramming is a hallmark of cancer. We and other authors have previously shown that breast cancer subtypes present metabolism differences. In this study, breast cancer cell lines were treated with metformin and rapamycin. The response was heterogeneous across various breast cancer cells, leading to cell cycle disruption in specific conditions. The molecular effects of these treatments were characterized using sublethal doses, SNP genotyping and mass spectrometry-based proteomics. Protein expression was analyzed using probabilistic graphical models, showing that treatments elicit various responses in some biological processes, providing insights into cell responses to metabolism drugs. Moreover, a flux balance analysis approach using protein expression values was applied, showing that predicted growth rates were comparable with cell viability measurements and suggesting an increase in reactive oxygen species response enzymes due to metformin treatment. In addition, a method to assess flux differences in whole pathways was proposed. Our results show that these various approaches provide complementary information, which can be used to suggest hypotheses about the drugs’ mechanisms of action and the response to drugs that target metabolism.

Computational models applied to metabolomics data hints at the relevance of glutamine metabolism in breast cancer

“…As previously described [10,11,14,20], PGMs compatible with high dimensional data were used, using correlation as associative criteria. PGMs were built using metabolomics, gene expression or flux activity data without any a priori information.…”

“…Once the functional structure was defined, functional node activities were calculated in order to make comparisons between groups, as previously described [10,11,14,20]. Briefly, each functional node activity was calculated as the mean of the expression/quantity of genes/ metabolites of each node that are related to the main node function/metabolic pathway.…”

“…GPRs represent the relationships between genes and metabolic reactions and they are included into the model as Boolean expressions. GPRs were solved as described in previous studies [11,14], using a modification of the Barker et al algorithm [29], which were incorporated into the model by a modified E-flux method [14,30]. Briefly, the "OR" operators were solved as the sum and the "AND" operators were solved as the minimum.…”

“…Flux activities were previously proposed as a measurement to compare differences at the metabolic pathway level [14]. Briefly, they were calculated as the sum of the fluxes of the reactions included in each pathway defined in Recon2.…”

“…Flux Balance Analysis (FBA), however, is a method that has been widely used to study biochemical networks [12]. FBA predicts the growth rate or the rate of production of a given metabolite [13], and it has previously been used to characterize breast cancer cell responses against drugs targeting metabolism [14]. In this study, flux activities were proposed as a feasible method to compare flux patterns in metabolic pathways.…”