A Mechanistic Modeling Framework Reveals the Key Principles Underlying Tumor Metabolism

AbstractWhile aerobic glycolysis, or the Warburg effect, has for a long time been considered a hallmark of tumor metabolism, recent studies have revealed a far more complex picture. Tumor cells exhibit widespread metabolic heterogeneity, utilizing glycolysis, oxidative phosphorylation, or both, and can switch between different metabolic phenotypes. A framework to analyze the observed metabolic heterogeneity and plasticity is, however, lacking. Using a mechanistic model that includes the key metabolic pathways active in tumor cells, we show that the inhibition of phosphofructokinase by excess ATP in the cytoplasm can drive a preference for aerobic glycolysis in fast-proliferating tumor cells. The differing rates of ATP utilization by tumor cells can therefore drive metabolic heterogeneity. Building upon this idea, we couple the metabolic phenotype of tumor cells to their migratory phenotype, and show that our model predictions are in agreement with previous experiments. We report that the reliance of proliferating cells on different anaplerotic pathways depends on the relative availability of glucose and glutamine, and can further drive metabolic heterogeneity. Finally, using treatment of melanoma cells with a BRAF inhibitor as an example, we show that our model can be used to predict the metabolic and gene expression changes in cancer cells in response to drug treatment. By making predictions that are far more generalizable and interpretable as compared to previous tumor metabolism modeling approaches, our framework identifies key principles that govern tumor cell metabolism, and the reported heterogeneity and plasticity. These principles could be key to targeting the metabolic vulnerabilities of cancer.SignificanceThis study presents an interpretable mathematical framework for analyzing the metabolic heterogeneity and plasticity exhibited by tumor cells.

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Using the Mutation-Selection Framework to Characterize Selection on Protein Sequences

Genes ◽

10.3390/genes9080409 ◽

2018 ◽

Vol 9 (8) ◽

pp. 409 ◽

Cited By ~ 4

Author(s):

Ashley Teufel ◽

Andrew Ritchie ◽

Claus Wilke ◽

David Liberles

Keyword(s):

Protein Sequences ◽

Original Model ◽

Mechanistic Modeling ◽

Mathematical Framework ◽

Conditional Probabilities ◽

Modeling Framework ◽

Mutational Pressure ◽

Generative Process ◽

Different Types ◽

Selection Framework

When mutational pressure is weak, the generative process of protein evolution involves explicit probabilities of mutations of different types coupled to their conditional probabilities of fixation dependent on selection. Establishing this mechanistic modeling framework for the detection of selection has been a goal in the field of molecular evolution. Building on a mathematical framework proposed more than a decade ago, numerous methods have been introduced in an attempt to detect and measure selection on protein sequences. In this review, we discuss the structure of the original model, subsequent advances, and the series of assumptions that these models operate under.

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Quercetin Inhibits the Proliferation of Glycolysis-Addicted HCC Cells by Reducing Hexokinase 2 and Akt-mTOR Pathway

Molecules ◽

10.3390/molecules24101993 ◽

2019 ◽

Vol 24 (10) ◽

pp. 1993 ◽

Cited By ~ 9

Author(s):

Hongyan Wu ◽

Lanlan Pan ◽

Cuixiang Gao ◽

Hongtao Xu ◽

Yanping Li ◽

...

Keyword(s):

Tumor Cells ◽

Aerobic Glycolysis ◽

Underlying Mechanism ◽

Mtor Pathway ◽

Metabolic Phenotype ◽

Hexokinase 2 ◽

Continuous Growth ◽

Increased Risk ◽

Hcc Cells

Increased glycolysis in tumor cells is associated with increased risk of tumor progression and mortality. Therefore, disruption of glycolysis, one of the main sources of cellular energy supply, can serve as a target for suppressing tumor growth and progression. Of note, hexokinase-2 (HK2) plays vital roles in glucose metabolism. Moreover, the expression of HK2 alters the metabolic phenotype and supports the continuous growth of tumor cells, making it an attractive target for cancer therapy. Quercetin (QUE), a bioactive flavonoid, has a profound anti-tumor effect on hepatocellular carcinoma (HCC), but the precise underlying mechanism of this effect is unclear. In the present study, we reported that QUE inhibited the proliferation of HCC cells that relied on aerobic glycolysis. We further found that QUE could decrease the protein levels of HK2 and suppress the AKT/mTOR pathway in HCC cells. In addition, QUE significantly restrained the growth of HCC xenografts and decreased HK-2 expression in vivo. Taken together, we have revealed that QUE suppresses the progression of HCC by inhibiting HK2-dependentglycolysis, which may have a promising potential to be an effective treatments for HCC, especially for those patients with high HK2 expression.

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TAMI-19. METABOLIC INTERACTIONS BETWEEN TUMOR CELLS AND THE IMMUNE SYSTEM IN GBM: A POTENTIAL ACHILLES HEEL OF GBM FOR NOVEL THERAPEUTICS

Neuro-Oncology ◽

10.1093/neuonc/noaa215.908 ◽

2020 ◽

Vol 22 (Supplement_2) ◽

pp. ii217-ii217

Author(s):

Guimei Tian ◽

Changlin Yang ◽

Michael Andrews ◽

Aida Karachi ◽

Mariana Dajac ◽

...

Keyword(s):

Immune System ◽

Lipid Metabolism ◽

Tumor Microenvironment ◽

Tumor Cells ◽

Aerobic Glycolysis ◽

Cell Metabolism ◽

Critical Role ◽

Acid Uptake ◽

Metabolic Interactions ◽

Metabolic Heterogeneity

Abstract INTRODUCTION Glioblastoma (GBM) contains cell populations with distinct metabolic requirements, with fast-cycling cells harnessing aerobic glycolysis, and treatment-resistant slow-cycling cells (SCCs) preferentially engaging lipid metabolism. How the different tumor cells interact with immune cells and how this metabolic heterogeneity shapes the immune landscape in GBM has yet to be understood. OBJECTIVES The objectives are to unravel the various molecular signals and metabolic link that underlie the interaction of SCCs with the GBM microenvironment, in particular with the suppressive immune compartment, and to effectively target these interactions for better therapeutics. METHODS Multiple murine glioma cell lines were used to establish metabolic heterogeneity and communications, while various genetic and pharmacological approaches were applied to assess the effect of disrupting the metabolic interplay between SCCs and the immune system. RESULTS We determined that SCCs exhibit distinct metabolic dependencies, involving preferential lipid metabolism supported by enhanced fatty acid uptake. We also found that tumor progression is regulated by the interaction of SCCs with the immune system and established that SCCs recruit immune suppressive M2-like macrophages to the tumor microenvironment, which in turn work against tumor immune rejection by inhibiting T cell anti-tumor activity. The immune microenvironment shaped by SCCs is marked by specific metabolic features enhancing lipid exchange capacities that are exploited by SCCs to support their survival and functions. Importantly, disrupting lipid metabolic exchange sensitized tumors to chemotherapy. CONCLUSION Our results reveal that metabolic interactions between SCCs and tumor-associated macrophages within the GBM microenvironment play a critical role in the development of drug and immune resistant tumors. This study delineates these metabolic communications and assesses the potential therapeutic effect of disrupting these interactions to treat GBM. The insights generated from this project uncover fundamental principles of the emerging connections between the tumor microenvironment, cell metabolism, anti-tumor immunity, and associated therapeutic vulnerabilities.

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TAMI-38. CYSTEINE-PROMOTING COMPOUNDS INDUCE MITOCHONDRIAL TOXICITY IN GLIOBLASTOMA THROUGH ALTERED PYRUVATE AND SERINE METABOLISM

Neuro-Oncology ◽

10.1093/neuonc/noaa215.926 ◽

2020 ◽

Vol 22 (Supplement_2) ◽

pp. ii221-ii221

Author(s):

Evan Noch ◽

Laura Palma ◽

Isaiah Yim ◽

Bhavneet Binder ◽

Elisa Benedetti ◽

...

Keyword(s):

Amino Acid ◽

Cell Growth ◽

Growth Inhibition ◽

Glucose Deprivation ◽

Tumor Metabolism ◽

Metabolic Phenotype ◽

Low Grade ◽

Mitochondrial Toxicity ◽

Human Cancers ◽

Pathway Gene

Abstract Glioblastoma (GBM) remains a poorly treatable disease with high mortality. Tumor metabolism in GBM is a critical mechanism responsible for accelerated growth because of upregulation of glucose, amino acid, and fatty acid utilization. However, little is known about the metabolic alterations that are specific to GBM and that are targetable with FDA-approved compounds. To investigate tumor metabolism signatures unique to GBM, we interrogated the TCGA and a cancer metabolite database for alterations in glucose and amino acid signatures in GBM relative to other human cancers and relative to low-grade glioma. From these analyses, we found that GBM exhibits the highest levels of cysteine and methionine pathway gene expression of 32 human cancers and that GBM exhibits high levels of cysteine-related metabolites compared to low-grade gliomas. To study the role of cysteine in GBM pathogenesis, we treated patient-derived GBM cells with a variety of FDA-approved cyst(e)ine-promoting compounds in vitro, including N-acetylcysteine (NAC) and the cephalosporin antibiotic, Ceftriaxone (CTX), which induces cystine import through System Xc transporter upregulation. Cysteine-promoting compounds, including NAC and CTX, inhibit growth of GBM cells, which is exacerbated by glucose deprivation. This growth inhibition is associated with reduced mitochondrial metabolism, manifest by reduction in ATP, NADPH/NADP+ ratio, mitochondrial membrane potential, and oxygen consumption rate. Metabolic tracing experiments with 13C6-glucose demonstrate that L-serine is rapidly depleted in GBM cells upon treatment with NAC and CTX, and exogenous serine rescues NAC- and CTX-mediated cell growth inhibition. In addition, these compounds reduce GBM mitochondrial pyruvate transport. We show that cysteine-promoting compounds reduce cell growth and induce mitochondrial toxicity in GBM, which may be due to rapid serine depletion and reduced mitochondrial pyruvate transport. This metabolic phenotype is exacerbated by glucose deprivation. This pathway is targetable with FDA-approved cysteine-promoting compounds and could synergize with glucose-lowering treatments, including the ketogenic diet, for GBM.

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Hyperpolarized 13C-glucose magnetic resonance highlights reduced aerobic glycolysis in vivo in infiltrative glioblastoma

Scientific Reports ◽

10.1038/s41598-021-85339-7 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Mor Mishkovsky ◽

Olga Gusyatiner ◽

Bernard Lanz ◽

Cristina Cudalbu ◽

Irene Vassallo ◽

...

Keyword(s):

Magnetic Resonance ◽

Tumor Recurrence ◽

Aerobic Glycolysis ◽

Imaging Techniques ◽

Tumor Type ◽

Hyperpolarized 13C ◽

Metabolic Heterogeneity ◽

Metabolic Information ◽

Opposite Response

AbstractGlioblastoma (GBM) is the most aggressive brain tumor type in adults. GBM is heterogeneous, with a compact core lesion surrounded by an invasive tumor front. This front is highly relevant for tumor recurrence but is generally non-detectable using standard imaging techniques. Recent studies demonstrated distinct metabolic profiles of the invasive phenotype in GBM. Magnetic resonance (MR) of hyperpolarized 13C-labeled probes is a rapidly advancing field that provides real-time metabolic information. Here, we applied hyperpolarized 13C-glucose MR to mouse GBM models. Compared to controls, the amount of lactate produced from hyperpolarized glucose was higher in the compact GBM model, consistent with the accepted “Warburg effect”. However, the opposite response was observed in models reflecting the invasive zone, with less lactate produced than in controls, implying a reduction in aerobic glycolysis. These striking differences could be used to map the metabolic heterogeneity in GBM and to visualize the infiltrative front of GBM.

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Anti-Warburg Effect of Melatonin: A Proposed Mechanism to Explain its Inhibition of Multiple Diseases

International Journal of Molecular Sciences ◽

10.3390/ijms22020764 ◽

2021 ◽

Vol 22 (2) ◽

pp. 764

Author(s):

Russel J. Reiter ◽

Ramaswamy Sharma ◽

Sergio Rosales-Corral

Keyword(s):

Pyruvate Dehydrogenase ◽

Warburg Effect ◽

Coenzyme A ◽

Aerobic Glycolysis ◽

Pyruvate Dehydrogenase Complex ◽

Pyruvate Dehydrogenase Kinase ◽

Metabolic Phenotype ◽

Common Denominator ◽

Acetyl Coenzyme A ◽

Acetyl Coenzyme

Glucose is an essential nutrient for every cell but its metabolic fate depends on cellular phenotype. Normally, the product of cytosolic glycolysis, pyruvate, is transported into mitochondria and irreversibly converted to acetyl coenzyme A by pyruvate dehydrogenase complex (PDC). In some pathological cells, however, pyruvate transport into the mitochondria is blocked due to the inhibition of PDC by pyruvate dehydrogenase kinase. This altered metabolism is referred to as aerobic glycolysis (Warburg effect) and is common in solid tumors and in other pathological cells. Switching from mitochondrial oxidative phosphorylation to aerobic glycolysis provides diseased cells with advantages because of the rapid production of ATP and the activation of pentose phosphate pathway (PPP) which provides nucleotides required for elevated cellular metabolism. Molecules, called glycolytics, inhibit aerobic glycolysis and convert cells to a healthier phenotype. Glycolytics often function by inhibiting hypoxia-inducible factor-1α leading to PDC disinhibition allowing for intramitochondrial conversion of pyruvate into acetyl coenzyme A. Melatonin is a glycolytic which converts diseased cells to the healthier phenotype. Herein we propose that melatonin’s function as a glycolytic explains its actions in inhibiting a variety of diseases. Thus, the common denominator is melatonin’s action in switching the metabolic phenotype of cells.

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The fatty acid receptor CD36 promotes HCC progression through activating Src/PI3K/AKT axis-dependent aerobic glycolysis

Cell Death and Disease ◽

10.1038/s41419-021-03596-w ◽

2021 ◽

Vol 12 (4) ◽

Author(s):

Xiaoqing Luo ◽

Enze Zheng ◽

Li Wei ◽

Han Zeng ◽

Hong Qin ◽

...

Keyword(s):

Fatty Acid ◽

Aerobic Glycolysis ◽

Lactic Acid Production ◽

Metabolic Reprogramming ◽

Metabolic Phenotype ◽

Hepatic Tissue ◽

Promoting Effect ◽

Acid Receptor ◽

Hcc Cells ◽

Fatty Acid Receptor

AbstractMetabolic reprogramming is a new hallmark of cancer but it remains poorly defined in hepatocellular carcinogenesis (HCC). The fatty acid receptor CD36 is associated with both lipid and glucose metabolism in the liver. However, the role of CD36 in metabolic reprogramming in the progression of HCC still remains to be elucidated. In the present study, we found that CD36 is highly expressed in human HCC as compared with non-tumor hepatic tissue. CD36 overexpression promoted the proliferation, migration, invasion, and in vivo tumor growth of HCC cells, whereas silencing CD36 had the opposite effects. By analysis of cell metabolic phenotype, CD36 expression showed a positive association with extracellular acidification rate, a measure of glycolysis, instead of oxygen consumption rate. Further experiments verified that overexpression of CD36 resulted in increased glycolysis flux and lactic acid production. Mechanistically, CD36 induced mTOR-mediated oncogenic glycolysis via activation of Src/PI3K/AKT signaling axis. Pretreatment of HCC cells with PI3K/AKT/mTOR inhibitors largely blocked the tumor-promoting effect of CD36. Our findings suggest that CD36 exerts a stimulatory effect on HCC growth and metastasis, through mediating aerobic glycolysis by the Src/PI3K/AKT/mTOR signaling pathway.

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Inverse mechanistic modeling of transdermal drug delivery for fast identification of optimal model parameters

10.1101/2020.12.11.420836 ◽

2020 ◽

Author(s):

Thijs Defraeye ◽

Flora Bahrami ◽

Rene M Rossi

Keyword(s):

Drug Delivery ◽

Inverse Modeling ◽

Transdermal Drug Delivery ◽

Drug Transport ◽

Mechanistic Model ◽

Mechanistic Modeling ◽

Drug Uptake ◽

Added Value ◽

Model Parameters ◽

Transdermal Drug Delivery Systems

Transdermal drug delivery systems are a key technology to administer drugs with a high first-pass effect in a non-invasive and controlled way. Physics-based modeling and simulation are on their way to become a cornerstone in the engineering of these healthcare devices since it provides a unique complementarity to experimental data and insights. Simulations enable to virtually probe the drug transport inside the skin at each point in time and space. However, the tedious experimental or numerical determination of material properties currently forms a bottleneck in the modeling workflow. We show that multiparameter inverse modeling to determine the drug diffusion and partition coefficients is a fast and reliable alternative. We demonstrate this strategy for transdermal delivery of fentanyl. We found that inverse modeling reduced the normalized root mean square deviation of the measured drug uptake flux from 26 to 9%, when compared to the experimental measurement of all skin properties. We found that this improved agreement with experiments was only possible if the diffusion in the reservoir holding the drug was smaller than the experimentally-measured diffusion coefficients suggested. For indirect inverse modeling, which systematically explores the entire parametric space, 30 000 simulations were required. By relying on direct inverse modeling, we reduced the number of simulations to be performed to only 300, so a factor 100 difference. The modeling approach's added value is that it can be calibrated once in-silico for all model parameters simultaneously by solely relying on a single measurement of the drug uptake flux evolution over time. We showed that this calibrated model could accurately be used to simulate transdermal patches with other drug doses. We showed that inverse modeling is a fast way to build up an accurate mechanistic model for drug delivery. This strategy opens the door to clinically-ready therapy that is tailored to patients.

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Mechanics unlocks the morphogenetic puzzle of interlocking bivalved shells

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1916520116 ◽

2019 ◽

Vol 117 (1) ◽

pp. 43-51 ◽

Cited By ~ 1

Author(s):

Derek E. Moulton ◽

Alain Goriely ◽

Régis Chirat

Keyword(s):

Pattern Formation ◽

Growth Process ◽

Shell Growth ◽

Point Of View ◽

Mathematical Framework ◽

Bivalve Mollusks ◽

Modeling Framework ◽

Mechanistic Basis ◽

Developmental Point ◽

Rigid Shell

Brachiopods and mollusks are 2 shell-bearing phyla that diverged from a common shell-less ancestor more than 540 million years ago. Brachiopods and bivalve mollusks have also convergently evolved a bivalved shell that displays an apparently mundane, yet striking feature from a developmental point of view: When the shell is closed, the 2 valve edges meet each other in a commissure that forms a continuum with no gaps or overlaps despite the fact that each valve, secreted by 2 mantle lobes, may present antisymmetric ornamental patterns of varying regularity and size. Interlocking is maintained throughout the entirety of development, even when the shell edge exhibits significant irregularity due to injury or other environmental influences, which suggests a dynamic physical process of pattern formation that cannot be genetically specified. Here, we derive a mathematical framework, based on the physics of shell growth, to explain how this interlocking pattern is created and regulated by mechanical instabilities. By close consideration of the geometry and mechanics of 2 lobes of the mantle, constrained both by the rigid shell that they secrete and by each other, we uncover the mechanistic basis for the interlocking pattern. Our modeling framework recovers and explains a large diversity of shell forms and highlights how parametric variations in the growth process result in morphological variation. Beyond the basic interlocking mechanism, we also consider the intricate and striking multiscale-patterned edge in certain brachiopods. We show that this pattern can be explained as a secondary instability that matches morphological trends and data.

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