Different fatty acid metabolism effects of (−)-epigallocatechin-3-gallate and C75 in adenocarcinoma lung cancer

Background Fatty acid synthase (FASN) is overexpressed and hyperactivated in several human carcinomas, including lung cancer. We characterize and compare the anti-cancer effects of the FASN inhibitors C75 and (−)-epigallocatechin-3-gallate (EGCG) in a lung cancer model. Methods We evaluated in vitro the effects of C75 and EGCG on fatty acid metabolism (FASN and CPT enzymes), cellular proliferation, apoptosis and cell signaling (EGFR, ERK1/2, AKT and mTOR) in human A549 lung carcinoma cells. In vivo, we evaluated their anti-tumour activity and their effect on body weight in a mice model of human adenocarcinoma xenograft. Results C75 and EGCG had comparable effects in blocking FASN activity (96,9% and 89,3% of inhibition, respectively). In contrast, EGCG had either no significant effect in CPT activity, the rate-limiting enzyme of fatty acid β-oxidation, while C75 stimulated CPT up to 130%. Treating lung cancer cells with EGCG or C75 induced apoptosis and affected EGFR-signaling. While EGCG abolished p-EGFR, p-AKT, p-ERK1/2 and p-mTOR, C75 was less active in decreasing the levels of EGFR and p-AKT. In vivo, EGCG and C75 blocked the growth of lung cancer xenografts but C75 treatment, not EGCG, caused a marked animal weight loss. Conclusions In lung cancer, inhibition of FASN using EGCG can be achieved without parallel stimulation of fatty acid oxidation and this effect is related mainly to EGFR signaling pathway. EGCG reduce the growth of adenocarcinoma human lung cancer xenografts without inducing body weight loss. Taken together, EGCG may be a candidate for future pre-clinical development

A novel inhibitor of fatty acid synthase shows activity against HER2+ breast cancer xenografts and is active in anti-HER2 drug-resistant cell lines

Introduction: Inhibiting the enzyme Fatty Acid Synthase (FASN) leads to apoptosis of breast carcinoma cells, and this is linked to human epidermal growth factor receptor 2 (HER2) signaling pathways in models of simultaneous expression of FASN and HER2. Methods: In a xenograft model of breast carcinoma cells that are FASN+ and HER2+, we have characterised the anticancer activity and the toxicity profile of G28UCM, the lead compound of a novel family of synthetic FASN inhibitors. In vitro, we analysed the cellular and molecular interactions of combining G28UCM with anti-HER drugs. Finally, we tested the cytotoxic ability of G28UCM on breast cancer cells resistant to trastuzumab or lapatinib, that we developed in our laboratory. Results: In vivo, G28UCM reduced the size of 5 out of 14 established xenografts. In the responding tumours, we observed inhibition of FASN activity, cleavage of poly-ADPribose polymerase (PARP) and a decrease of p-HER2, p- protein kinase B (AKT) and p-ERK1/2, which were not observed in the nonresponding tumours. In the G28UCM-treated animals, no significant toxicities occurred, and weight loss was not observed. In vitro, G28UCM showed marked synergistic interactions with trastuzumab, lapatinib, erlotinib or gefitinib (but not with cetuximab), which correlated with increases in apoptosis and with decreases in the activation of HER2, extracellular signal-regulated kinase (ERK)1/2 and AKT. In trastuzumab-resistant and in lapatinib-resistant breast cancer cells, in which trastuzumab and lapatinib were not effective, G28UCM retained the anticancer activity observed in the parental cells. Conclusions: G28UCM inhibits fatty acid synthase (FASN) activity and the growth of breast carcinoma xenografts in vivo, and is active in cells with acquired resistance to anti-HER2 drugs, which make it a candidate for further pre-clinical development

Metabolic intervention on lipid synthesis converging pathways abrogates prostate cancer growth.

One of the most conserved features of all cancers is a profound reprogramming of cellular metabolism, favoring biosynthetic processes and limiting catalytic processes. With the acquired knowledge of some of these important changes, we have designed a combination therapy in order to force cancer cells to use a particular metabolic pathway that ultimately results in the accumulation of toxic products. This innovative approach consists of blocking lipid synthesis, at the same time that we force the cell, through the inhibition of AMP-activated kinase, to accumulate toxic intermediates, such as malonyl-coenzyme A (malonyl-CoA) or nicotinamide adenine dinucleotide phosphate. This results in excess of oxidative stress and cancer cell death. Our new therapeutic strategy, based on the manipulation of metabolic pathways, will certainly set up the basis for new upcoming studies defining a new paradigm of cancer treatment

Parameter Trajectory Analysis to Identify Treatment Effects of Pharmacological Interventions

<p>The field of medical systems biology aims to advance understanding of molecular mechanisms that drive disease progression and to translate this knowledge into therapies to effectively treat diseases. A challenging task is the investigation of long-term effects of a (pharmacological) treatment, to establish its applicability and to identify potential side effects. We present a new modeling approach, called Analysis of Dynamic Adaptations in Parameter Trajectories (ADAPT), to analyze the long-term effects of a pharmacological intervention. A concept of time-dependent evolution of model parameters is introduced to study the dynamics of molecular adaptations. The progression of these adaptations is predicted by identifying necessary dynamic changes in the model parameters to describe the transition between experimental data obtained during different stages of the treatment. The trajectories provide insight in the affected underlying biological systems and identify the molecular events that should be studied in more detail to unravel the mechanistic basis of treatment outcome. Modulating effects caused by interactions with the proteome and transcriptome levels, which are often less well understood, can be captured by the time-dependent descriptions of the parameters. ADAPT was employed to identify metabolic adaptations induced upon pharmacological activation of the liver X receptor (LXR), a potential drug target to treat or prevent atherosclerosis. The trajectories were investigated to study the cascade of adaptations. This provided a counter-intuitive insight concerning the function of scavenger receptor class B1 (SR-B1), a receptor that facilitates the hepatic uptake of cholesterol. Although activation of LXR promotes cholesterol efflux and -excretion, our computational analysis showed that the hepatic capacity to clear cholesterol was reduced upon prolonged treatment. This prediction was confirmed experimentally by immunoblotting measurements of SR-B1 in hepatic membranes. Next to the identification of potential unwanted side effects, we demonstrate how ADAPT can be used to design new target interventions to prevent these.</p>