Inhibition of Non-flux-Controlling Enzymes Deters Cancer Glycolysis by Accumulation of Regulatory Metabolites of Controlling Steps

The Hallmarks of Cancer as Eco-Evolutionary Processes

SIGNIFICANCE

Viewing the hallmarks as a sequence of adaptations captures the "why" behind the "how" of the molecular changes driving cancer. This eco-evolutionary view distils the complexity of cancer progression into logical steps, providing a framework for understanding all existing and emerging hallmarks of cancer and developing therapeutic interventions.

Metabolic control analysis as a strategy to identify therapeutic targets, the case of cancer glycolysis

The use of kinetic modeling and metabolic control analysis (MCA) to identify possible therapeutic targets and to investigate the controlling and regulatory mechanisms in cancer glycolysis is here reviewed. The glycolytic pathway has been considered a target to decrease cancer cell growth; however, its occurrence in normal cells makes it difficult to design therapeutic strategies that target this pathway in pathological cells. Notwithstanding, the over-expression of all enzymes and transporters, as well as the expression of isoenzymes with different kinetic and regulatory properties in cancer cells, suggested a different distribution of the control of glycolytic flux than that observed in normal cells. Kinetic models of glycolysis are constructed with enzyme kinetics experimental data, validated with the steady-state metabolite concentrations and glycolytic fluxes; applying MCA, permitted us to identify the steps with the highest control of glycolysis in cancer cells, but low control in normal cells. The cancer glycolysis main controlling steps under several metabolic conditions were: glucose transport, hexokinase and hexose-6-phosphate isomerase (HPI); whereas in normal cells were: the first two and phosphofructokinase-1. HPI is the best therapeutic target because it exerts high control in cancer glycolytic flux, but not in normal cells. Furthermore, kinetic modeling also contributed to identifying new feed-back and feed-forward regulatory loops in cancer cells glycolysis, and to understanding the mode of metabolic action of glycolytic inhibitors. Thus, MCA and metabolic modeling allowed to propose new strategies for inhibiting glycolysis in cancer cells.

Protein acetylation effects on enzyme activity and metabolic pathway fluxes

Acetylation of proteins seems a widespread process found in the three domains of life. Several studies have shown that besides histones, acetylation of lysine residues also occurs in non-nuclear proteins. Hence, it has been suggested that this covalent modification is a mechanism that might regulate diverse metabolic pathways by modulating enzyme activity, stability, and/or subcellular localization or interaction with other proteins. However, protein acetylation levels seem to have low correlation with modification of enzyme activity and pathway fluxes. In addition, the results obtained with mutant enzymes that presumably mimic acetylation have frequently been over-interpreted. Moreover, there is a generalized lack of rigorous enzyme kinetic analysis in parallel to acetylation level determinations. The purpose of this review is to analyze the current findings on the impact of acetylation on metabolic enzymes and its repercussion on metabolic pathways function/regulation.

Dicarbonyl derived post-translational modifications: chemistry bridging biology and aging-related disease

In living systems, nucleophilic amino acid residues are prone to non-enzymatic post-translational modification by electrophiles. α-Dicarbonyl compounds are a special type of electrophiles that can react irreversibly with lysine, arginine, and cysteine residues via complex mechanisms to form post-translational modifications known as advanced glycation end-products (AGEs). Glyoxal, methylglyoxal, and 3-deoxyglucosone are the major endogenous dicarbonyls, with methylglyoxal being the most well-studied. There are several routes that lead to the formation of dicarbonyl compounds, most originating from glucose and glucose metabolism, such as the non-enzymatic decomposition of glycolytic intermediates and fructosyl amines. Although dicarbonyls are removed continuously mainly via the glyoxalase system, several conditions lead to an increase in dicarbonyl concentration and thereby AGE formation. AGEs have been implicated in diabetes and aging-related diseases, and for this reason the elucidation of their structure as well as protein targets is of great interest. Though the dicarbonyls and reactive protein side chains are of relatively simple nature, the structures of the adducts as well as their mechanism of formation are not that trivial. Furthermore, detection of sites of modification can be demanding and current best practices rely on either direct mass spectrometry or various methods of enrichment based on antibodies or click chemistry followed by mass spectrometry. Future research into the structure of these adducts and protein targets of dicarbonyl compounds may improve the understanding of how the mechanisms of diabetes and aging-related physiological damage occur.

Identification of flux checkpoints in a metabolic pathway through white-box, grey-box and black-box modeling approaches

Metabolic pathway modeling plays an increasing role in drug design by allowing better understanding of the underlying regulation and controlling networks in the metabolism of living organisms. However, despite rapid progress in this area, pathway modeling can become a real nightmare for researchers, notably when few experimental data are available or when the pathway is highly complex. Here, three different approaches were developed to model the second part of glycolysis of E. histolytica as an application example, and have succeeded in predicting the final pathway flux: one including detailed kinetic information (white-box), another with an added adjustment term (grey-box) and the last one using an artificial neural network method (black-box). Afterwards, each model was used for metabolic control analysis and flux control coefficient determination. The first two enzymes of this pathway are identified as the key enzymes playing a role in flux control. This study revealed the significance of the three methods for building suitable models adjusted to the available data in the field of metabolic pathway modeling, and could be useful to biologists and modelers.

Kinetic modeling of glucose central metabolism in hepatocytes and hepatoma cells

BACKGROUND

Kinetic modeling and control analysis of a metabolic pathway may identify the steps with the highest control in tumor cells, and low control in normal cells, which can be proposed as the best therapeutic targets.

METHODS

Enzyme kinetic characterization, pathway kinetic modeling and control analysis of the glucose central metabolism were carried out in rat (hepatoma AS-30D) and human (cervix HeLa) cancer cells and normal rat hepatocytes.

RESULTS

The glycogen metabolism enzymes in AS-30D, HeLa cells and hepatocytes showed similar kinetic properties, except for higher AS-30D glycogen phosphorylase (GP) sensitivity to AMP. Pathway modeling indicated that fluxes of glycogen degradation and PPP were mainly controlled by GP and NADPH consumption, respectively, in both hepatocytes and cancer cells. Likewise, hexose-6-phosphate isomerase (HPI) and phosphoglucomutase (PGM) exerted significant control on glycolysis and glycogen synthesis fluxes in cancer cells but not in hepatocytes. Modeling also indicated that glycolytic and glycogen synthesis fluxes could be strongly decreased when HPI and PGM were simultaneously inhibited in AS-30D cells but not in hepatocytes. Experimental assessment of these predictions showed that both the glycolytic and glycogen synthesis fluxes of AS-30D cells, but not of hepatocytes, were inhibited by oxamate, by inducing increased Fru1,6BP levels, a competitive inhibitor of HPI and PGM.

CONCLUSION

HPI and PGM seem suitable targets for decreasing glycolytic and glycogen synthesis fluxes in AS-30D cells but not in hepatocytes.

GENERAL SIGNIFICANCE

The present study identified new therapeutic targets within glucose central metabolism in the analyzed cancer cells, with no effects on non-cancer cells.

The immunologic Warburg effect: Evidence and therapeutic opportunities in autoimmunity

Pro‐inflammatory signals induce metabolic reprogramming in innate and adaptive immune cells of both myeloid and lymphoid lineage, characterized by a shift to aerobic glycolysis akin to the Warburg effect first described in cancer. Blocking the switch to aerobic glycolysis impairs the survival, differentiation, and effector functions of pro‐inflammatory cell types while favoring anti‐inflammatory and regulatory phenotypes. Glycolytic reprogramming may therefore represent a selective vulnerability of inflammatory immune cells, providing an opportunity to modulate immune responses in autoimmune disease without broad toxicity in other tissues of the body. The mechanisms by which aerobic glycolysis and the balance between glycolysis and oxidative phosphorylation regulate immune responses have only begun to be understood, with many additional insights expected in the years to come. Immunometabolic therapies targeting aerobic glycolysis include both pharmacologic inhibitors of key enzymes and glucose‐restricted diets, such as the ketogenic diet. Animal studies support a role for these pharmacologic and dietary therapies for the treatment of autoimmune diseases, and in a few cases proof of concept has been demonstrated in human disease. Nonetheless, much more work is needed to establish the clinical safety and efficacy of these treatments.

This article is categorized under:

Biological Mechanisms > Metabolism

Translational, Genomic, and Systems Medicine > Translational Medicine

Biological Mechanisms > Cell Signaling