Metabolic control analysis as a strategy to identify therapeutic targets, the case of cancer glycolysis
Abstract
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.
... Since lactate dehydrogenase is essential for the Warburg effect (see below), it has also been explored as a therapeutic target with molecules such as GSK 2837808A [52,53]. Further, kinetic modeling and metabolic control analysis identified hexose-6-phosphate isomerase as a possible target in cancer [54]. This enzyme exerts high control in cancer glycolytic flux but not in normal cells. ...
... Consequently, in cells where glycolysis is essential as a source of energy and metabolites, this condition could seriously threaten the survival of such cells. Moreover, increased DHAP also inhibits hexose-6phosphate isomerase [82], which in turn highly affects the glycolytic flux in cancer cells [54]. Therefore, based on the above arguments, HsTIM must be considered an attractive target for designing anticancer molecules [56]. ...
Cancer involves a series of diseases where cellular growth is not controlled. Cancer is a leading cause of death worldwide, and the burden of cancer incidence and mortality is rapidly growing, mainly in developing countries. Many drugs are currently used, from chemotherapeutic agents to immunotherapy, among others, along with organ transplantation. Treatments can cause severe side effects, including remission and progression of the disease with serious consequences. Increased glycolytic activity is characteristic of cancer cells. Triosephosphate isomerase is essential for net ATP production in the glycolytic pathway. Notably, some post-translational events have been described that occur in human triosephosphate isomerase in which functional and structural alterations are provoked. This is considered a window of opportunity, given the differences that may exist between cancer cells and their counterpart in normal cells concerning the glycolytic enzymes. Here, we provide elements that bring out the potential of triosephosphate isomerase, under post-translational modifications, to be considered an efficacious target for treating cancer.
... They used the inhibitor titration method with two different inhibitors, one of which acts on both enzymes and they show a method to obtain both control coefficients in these circumstances. Their results agree with those of Marín-Hernández and Saavedra (2023) in showing a negligible degree of control by glyceraldehyde-3-phosphate dehydrogenase and significant control by hexokinase. Both papers point out the difficulty of using hexokinase as a drug target given its comparable degree of control in some normal tissues. ...
Heterogeneity describes the differences among cancer cells within and between tumors. It refers to cancer cells describing variations in morphology, transcriptional profiles, metabolism, and metastatic potential. More recently, the field has included the characterization of the tumor immune microenvironment and the depiction of the dynamics underlying the cellular interactions promoting the tumor ecosystem evolution. Heterogeneity has been found in most tumors representing one of the most challenging behaviors in cancer ecosystems. As one of the critical factors impairing the long-term efficacy of solid tumor therapy, heterogeneity leads to tumor resistance, more aggressive metastasizing, and recurrence. We review the role of the main models and the emerging single-cell and spatial genomic technologies in our understanding of tumor heterogeneity, its contribution to lethal cancer outcomes, and the physiological challenges to consider in designing cancer therapies. We highlight how tumor cells dynamically evolve because of the interactions within the tumor immune microenvironment and how to leverage this to unleash immune recognition through immunotherapy. A multidisciplinary approach grounded in novel bioinformatic and computational tools will allow reaching the integrated, multilayered knowledge of tumor heterogeneity required to implement personalized, more efficient therapies urgently required for cancer patients.
Advances in cancer biology over the past decades have revealed that metabolic adaptation of cancer cells is an essential aspect of tumorigenesis. However, recent insights into tumour metabolism in vivo have revealed dissimilarities with results obtained in vitro. This is partly due to the reductionism of in vitro cancer models that struggle to reproduce the complexity of tumour tissues. This review describes some of the discrepancies in cancer cell metabolism between in vitro and in vivo conditions, and presents current methodological approaches and tools used to bridge the gap with the clinically relevant microenvironment. As such, these approaches should generate new knowledge that could be more effectively translated into therapeutic opportunities.
Bisphenol A (BPA) and bisphenol S (BPS) are used in the production of plastics. These endocrine disruptors can be released into the environment and food, resulting in the continuous exposure of humans to bisphenols (BPs). The bladder urothelium is chronically exposed to BPA and BPS due to their presence in human urine samples. BPA and BPS exposure has been linked to cancer progression, especially for hormone-dependent cancers. However, the bladder is not recognized as a hormone-dependent tissue. Still, the presence of hormone receptors on the urothelium and their role in bladder cancer initiation and progression suggest that BPs could impact bladder cancer development. The effects of chronic exposure to BPA and BPS for 72 h on the bioenergetics (glycolysis and mitochondrial respiration), proliferation and migration of normal urothelial cells and non-invasive and invasive bladder cancer cells were evaluated. The results demonstrate that chronic exposure to BPs decreased urothelial cells’ energy metabolism and properties while increasing them for bladder cancer cells. These findings suggest that exposure to BPA and BPS could promote bladder cancer development with a potential clinical impact on bladder cancer progression. Further studies using 3D models would help to understand the clinical consequences of this exposure.
Background
pO2 and pH are physiological parameters relevant for different processes in health and disease, including wound healing and cancer progression. Head and neck squamous cell carcinomas (HNSCC) and oesophageal squamous cell carcinomas (ESCC) have a high rate of local recurrence that is partly related to treatment-resistant residual tumour cells. Hence, novel diagnostic tools are required to visualise potential residual tumour cells and thereby improve treatment outcome for HNSCC and ESCC patients. We developed a device to spatiotemporally measure oxygen consumption rates (OCR) and extracellular acidification rates (ECAR) to distinguish HNSCC and ESCC cells from healthy cells in vitro, exploiting general metabolic differences between cancer cells and healthy cells.
Methods
OCR and ECAR were measured via a newly developed device named STO2p-Q (SpatioTemporal O2 and pH Quantification) using the VisiSens technology based on ratiometric fluorescence imaging, facilitating spatiotemporal resolution. Results were confirmed using extracellular flux analyses (Seahorse technology).
Results
STO2p-Q is described and used to measure OCR and ECAR in HNSCC and ESCC cell lines and normal fibroblast and epithelial cells as components of the tumour microenvironment. OCR measurements showed differences amongst HNSCC and ESCC cell lines and between HNSCC/ESCC and normal cells, which on average had lower OCR than HNSCC/ESCC cells. Both OCR and ECAR measurements were independently verified using the Seahorse technology. Additionally, using STO2p-Q, HNSCC/ESCC, and normal cells could be spatially resolved with a resolution in the low millimetre range.
Conclusions
We developed a method to spatiotemporally measure OCR and ECAR of cells, which has many potential in vitro applications and lays the foundation for the development of novel diagnostic tools for the detection of cancerous tissue in HNSCC and ESCC patients in vivo.
Simple Summary
The role of lactate in cancer described by Otto Warburg in 1927 states that cancer cells uptake high amount of glucose with a marked increase in lactate production, this is known as the “Warburg effect”. Since then lactate turn out to be a major signaling molecule in cancer progression. Its release from tumor cells is accompanied by acidification ranging from 6.3 to 6.9 in the tumor microenvironment (TME) which favors processes such as tumor promotion, angiogenesis, metastasis, tumor resistance and more importantly, immunosuppression which has been associated with a poor outcome. The goal of this review is to examine and discuss in deep detail the recent studies that address the role of lactate in all these cancerous processes. Lastly, we explore the efforts to target the lactate production and its transport as a promising approach for cancer therapeutics.
Abstract
Cancer is a complex disease that includes the reprogramming of metabolic pathways by malignant proliferating cells, including those affecting the tumor microenvironment (TME). The “TME concept” was introduced in recognition of the roles played by factors other than tumor cells in cancer progression. In response to the hypoxic or semi-hypoxic characteristic of the TME, cancer cells generate a large amount of lactate via the metabolism of glucose and glutamine. Export of this newly generated lactate by the tumor cells together with H+ prevents intracellular acidification but acidifies the TME. In recent years, the importance of lactate and acidosis in carcinogenesis has gained increasing attention, including the role of lactate as a tumor-promoting metabolite. Here we review the existing literature on lactate metabolism in tumor cells and the ability of extracellular lactate to direct the metabolic reprogramming of those cells. Studies demonstrating the roles of lactate in biological processes that drive or sustain carcinogenesis (tumor promotion, angiogenesis, metastasis and tumor resistance) and lactate’s role as an immunosuppressor that contributes to tumor evasion are also considered. Finally, we consider recent therapeutic efforts using available drugs directed at and interfering with lactate production and transport in cancer treatment.
Interaction among different pathways, such as metabolic, signaling and gene regulatory networks, of cellular system is responsible to maintain homeostasis in a mammalian cell. Malfunctioning of this cooperation may lead to many complex diseases, such as cancer and type 2 diabetes. Timescale differences among these pathways make their integration a daunting task. Metabolic, signaling and gene regulatory networks have three different timescales, such as, ultrafast, fast and slow respectively.
The article deals with this problem by developing a support vector regression (SVR) based three timescale model with the application of genetic algorithm based nonlinear controller. The proposed model can successfully capture the nonlinear transient dynamics and regulations of such integrated biochemical pathway under consideration. Besides, the model is quite capable of predicting the effects of certain drug targets for many types of complex diseases. Here, energy and cell proliferation management of mammalian cancer cells have been explored and analyzed with the help of the proposed novel approach. Previous investigations including in silico/in vivo/in vitro experiments have validated the results (the regulations of glucose transporter 1 (glut1), hexokinase (HK), and hypoxia-inducible factor-1α (HIF-1α) among others, and the switching of pyruvate kinase (M2 isoform) between dimer and tetramer) generated by this model proving its effectiveness. Subsequently, the model predicts the effects of six selected drug targets, such as, the deactivation of transketolase and glucose-6-phosphate isomerase among others, in the case of mammalian malignant cells in terms of growth, proliferation, fermentation, and energy supply in the form of adenosine triphosphate (ATP).
Inhibiting glycolysis remains an aspirational approach for the treatment of cancer. We have previously identified a subset of cancers harbouring homozygous deletion of the glycolytic enzyme enolase (ENO1) that have exceptional sensitivity to inhibition of its redundant paralogue, ENO2, through a therapeutic strategy known as collateral lethality. Here, we show that a small-molecule enolase inhibitor, POMHEX, can selectively kill ENO1-deleted glioma cells at low-nanomolar concentrations and eradicate intracranial orthotopic ENO1-deleted tumours in mice at doses well-tolerated in non-human primates. Our data provide an in vivo proof of principle of the power of collateral lethality in precision oncology and demonstrate the utility of POMHEX for glycolysis inhibition with potential use across a range of therapeutic settings.
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.
For identification of suitable therapeutic targets (enzymes/transporters) in intermediary metabolism of pathological and parasitic cells, the capacity of the target to govern the metabolic pathway flux should be considered. Metabolic Control Analysis (MCA) is a biochemical framework that enables one to quantitate the degree of control that the activity of a target i (ai) exerts on the pathway flux (J), defined as flux control coefficient (CJai). Different experimental strategies are being used to determine the CJai of individual pathway steps, and consequently, the distribution of control in the metabolic pathway. By applying MCA, the components with the highest control on flux can be identified, which are the targets with the highest therapeutic potential. In this chapter, we will review the MCA theoretical principles and experimental approaches to determine the CJai in a range of metabolic pathways such as central carbon and antioxidant metabolism, with potential application to other pathways of diverse human diseases.KeywordsDrug targetMetabolic control analysisFlux control coefficientIntermediary metabolismPathway modeling