The consequences of enhanced cell-autonomous glucose metabolism

Identification and functional analysis of lactic acid metabolism-related differentially expressed genes in hepatocellular carcinoma

Background: Hepatocellular carcinoma (HCC) is a malignant tumor with high morbidity and mortality rate that seriously threatens human health. We aimed to investigate the expression, prognostic value, and immune cell infiltration of lactic acid metabolism-related genes (LAMRGs) in HCC using bioinformatics. Methods: The HCC database (The Cancer Genome Atlas-Liver Hepatocellular Carcinoma) was downloaded from the Cancer Genome Atlas (TCGA). Differentially expressed genes (DEGs) between normal and tumor groups were identified. The LAMRGs were obtained from literature and GeneCards and MSigDB databases. Lactic acid metabolism-related differentially expressed genes (LAMRDEGs) in HCC were screened from the DEGs and LAMRGs. Functional enrichment analyses of the screened LAMRDEGs were further conducted using Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, and Gene Set Enrichment Analysis (GSEA). The genes were used in multivariate Cox regression and least absolute shrinkage and selection operator (LASSO) analyses to construct a prognostic model. Then, a protein-protein interaction network was constructed using STRING and CTD databases. Furthermore, the CIBERSORTx online database was used to assess the relationship between immune cell infiltration and hub genes. Results: Twenty-eight lactic acid metabolism-related differentially expressed genes (LAMRDEGs) were identified. The GO and KEGG analyses showed that the LAMRDEGs were related to the prognosis of HCC. The GSEA indicated that the LAMRDEGs were significantly enriched in tumor related pathways. In the multivariate Cox regression analysis, 14 key genes (E2F1, SERPINE1, GYS2, SPP1, PCK1, CCNB1, CYP2C9, IGFBP3, KDM8, RCAN1, ALPL, FBP1, NQO1, and LCAT) were found to be independent prognostic factors of HCC. Finally, the LASSO and Cox regression analyses showed that six key genes (SERPINE1, SPP1, CCNB1, CYP2C9, NQO1, and LCAT) were associated with HCC prognosis. Moreover, the correlation analyses revealed that the expression of the six key genes were associated with immune infiltrates of HCC. Conclusion: The LAMRDEGs can predict the prognosis and may be associated with immune cells infiltration in patients with HCC. These genes might be the promising biomarkers for the prognosis and treatment of HCC.

A viral interferon regulatory factor degrades RNA-binding protein hnRNP Q1 to enhance aerobic glycolysis via recruiting E3 ubiquitin ligase KLHL3 and decaying GDPD1 mRNA

Reprogramming of host metabolism is a common strategy of viral evasion of host cells, and is essential for successful viral infection and induction of cancer in the context cancer viruses. Kaposi's sarcoma (KS) is the most common AIDS-associated cancer caused by KS-associated herpesvirus (KSHV) infection. KSHV-encoded viral interferon regulatory factor 1 (vIRF1) regulates multiple signaling pathways and plays an important role in KSHV infection and oncogenesis. However, the role of vIRF1 in KSHV-induced metabolic reprogramming remains elusive. Here we show that vIRF1 increases glucose uptake, ATP production and lactate secretion by downregulating heterogeneous nuclear ribonuclear protein Q1 (hnRNP Q1). Mechanistically, vIRF1 upregulates and recruits E3 ubiquitin ligase Kelch-like 3 (KLHL3) to degrade hnRNP Q1 through a ubiquitin-proteasome pathway. Furthermore, hnRNP Q1 binds to and stabilizes the mRNA of glycerophosphodiester phosphodiesterase domain containing 1 (GDPD1). However, vIRF1 targets hnRNP Q1 for degradation, which destabilizes GDPD1 mRNA, resulting in induction of aerobic glycolysis. These results reveal a novel role of vIRF1 in KSHV metabolic reprogramming, and identifying a potential therapeutic target for KSHV infection and KSHV-induced cancers.

Glucose-Restricted Diet Regulates the Tumor Immune Microenvironment and Prevents Tumor Growth in Lung Adenocarcinoma

Background

Lung cancer is the second common cancer type in western countries and has a high mortality. During the development and progression of the tumor, the nutrients in its environment play a central role. The tumor cells depend crucially on glucose metabolism and uptake. Tumor cell metabolism is dominated by the Warburg effect, where tumor cells produce large amounts of lactate from pyruvate under aerobic conditions. We thus reasoned that, reducing carbohydrates in the diet might support anti-tumoral effects of current immunotherapy and additionally target tumor immune escape.

Objectives

The link between reducing carbohydrates to improve current immunotherapy is not clear. We thus aimed at analyzing the effects of different glucose levels on the tumor development, progression and the anti-tumoral immune response.

Methods

We correlated the clinical parameters of our LUAD cohort with different metabolic markers. Additionally, we performed cell culture experiments with A549 tumor cell line under different glucose levels. Lastly, we investigated the effect of low and high carbohydrate diet in an experimental murine model of lung cancer on the tumor progression and different immune subsets.

Results

Here we found a positive correlation between the body mass index (BMI), blood glucose levels, reduced overall survival (OS) and the expression of Insulin-like growth factor-1 receptor (IGF1R) in the lung tumoral region of patients with lung adenocarcinoma (LUAD). Furthermore, increasing extracellular glucose induced IGF1R expression in A549 LUAD cells. Functional studies in a murine model of LUAD demonstrated that, glucose restricted diet resulted in decreased tumor load in vivo. This finding was associated with increased presence of lung infiltrating cytotoxic CD8+ T effector memory (TEM), tissue resident memory T (TRM) and natural killer cells as well as reduced IGFR mRNA expression, suggesting that glucose restriction regulates lung immunity in the tumor microenvironment.

Conclusions

These results indicate that, glucose restricted diet improves lung immune responses of the host and suppresses tumor growth in experimental lung adenocarcinoma. As glucose levels in LUAD patients were negatively correlated to postoperative survival rates, glucose-restricted diet emerges as therapeutic avenue for patients with LUAD.

Development and Validation of Lactate Metabolism-Related lncRNA Signature as a Prognostic Model for Lung Adenocarcinoma

BACKGROUND

Lung cancer has been a prominent research focus in recent years due to its role in cancer-related fatalities globally, with lung adenocarcinoma (LUAD) being the most prevalent histological form. Nonetheless, no signature of lactate metabolism-related long non-coding RNAs (LMR-lncRNAs) has been developed for patients with LUAD. Accordingly, we aimed to develop a unique LMR-lncRNA signature to determine the prognosis of patients with LUAD.

METHOD

The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were utilized to derive the lncRNA expression patterns. Identification of LMR-lncRNAs was accomplished by analyzing the co-expression patterns between lncRNAs and LMR genes. Subsequently, the association between lncRNA levels and survival outcomes was determined to develop an effective signature. In the TCGA cohort, Cox regression was enlisted to build an innovative signature consisting of three LMR-lncRNAs, which was validated in the GEO validation cohort. GSEA and immune infiltration analysis were conducted to investigate the functional annotation of the signature and the function of each type of immune cell.

RESULTS

Fourteen differentially expressed LMR-lncRNAs were strongly correlated with the prognosis of patients with LUAD and collectively formed a new LMR-lncRNA signature. The patients could be categorized into two cohorts based on their LMR-lncRNA signatures: a low-risk and high-risk group. The overall survival of patients with LUAD in the high-risk group was considerably lower than those in the low-risk group. Using Cox regression, this signature was shown to have substantial potential as an independent prognostic factor, which was further confirmed in the GEO cohort. Moreover, the signature could anticipate survival across different groups based on stage, age, and gender, among other variables. This signature also correlated with immune cell infiltration (including B cells, neutrophils, CD4⁺ T cells, CD8⁺ T cells, etc.) as well as the immune checkpoint blockade target CTLA-4.

CONCLUSION

We developed and verified a new LMR-lncRNA signature useful for anticipating the survival of patients with LUAD. This signature could give potentially critical insight for immunotherapy interventions in patients with LUAD.

The Role of Mitochondrial Dysfunction in Vascular Disease, Tumorigenesis, and Diabetes

Mitochondrial dysfunction is known to be associated with a wide range of human pathologies, such as cancer, metabolic, and cardiovascular diseases. One of the possible ways of mitochondrial involvement in the cellular damage is excessive production of reactive oxygen and nitrogen species (ROS and RNS) that cannot be effectively neutralized by existing antioxidant systems. In mitochondria, ROS and RNS can contribute to protein and mitochondrial DNA (mtDNA) damage causing failure of enzymatic chains and mutations that can impair mitochondrial function. These processes further lead to abnormal cell signaling, premature cell senescence, initiation of inflammation, and apoptosis. Recent studies have identified numerous mtDNA mutations associated with different human pathologies. Some of them result in imbalanced oxidative phosphorylation, while others affect mitochondrial protein synthesis. In this review, we discuss the role of mtDNA mutations in cancer, diabetes, cardiovascular diseases, and atherosclerosis. We provide a list of currently described mtDNA mutations associated with each pathology and discuss the possible future perspective of the research.

Including the mitochondrial metabolism of L-lactate in cancer metabolic reprogramming

Glucose avidity, high glycolysis and L-lactate production, regardless of oxygen availability, are the main traits of cancer metabolic reprogramming. The idea that mitochondria are dysfunctional in cancer, thus causing a glycolysis increase for ATP production and L-lactate accumulation as a dead-end product of glucose catabolism, has oriented cancer research for many years. However, it was shown that mitochondrial metabolism is essential for cancer cell proliferation and tumorigenesis and that L-lactate is a fundamental energy substrate with tumor growth-promoting and signaling capabilities. Nevertheless, the known ability of mitochondria to take up and oxidize L-lactate has remained ignored by cancer research. Beginning with a brief overview of the metabolic changes occurring in cancer, we review the present knowledge of L-lactate formation, transport, and intracellular oxidation and underline the possible role of L-lactate metabolism as energetic, signaling and anabolic support for cancer cell proliferation. These unexplored aspects of cancer biochemistry might be exploited for therapeutic benefit.

New concepts in feedback regulation of glucose metabolism

Glycolysis, the breakdown of glucose, is one of the most conserved and extensively studied biochemical pathways. Designing principles from chemistry and thermodynamics allow for energy production, biosynthesis and cellular communication. However, the kinetics or metabolic flux through the pathway also determines its function. Recently, there have been numerous developments that establish new allosteric interactions of glycolytic enzymes with small molecule metabolites and other mechanisms that may cooperate to allow for addition complex regulation of glycolysis. This review surveys these newfound sources of glycolysis regulation and discusses their possible roles in establishing kinetic design principles of glycolysis.

Simulating Heterogeneous Tumor Cell Populations

Certain tumor phenomena, like metabolic heterogeneity and local stable regions of chronic hypoxia, signify a tumor's resistance to therapy. Although recent research has shed light on the intracellular mechanisms of cancer metabolic reprogramming, little is known about how tumors become metabolically heterogeneous or chronically hypoxic, namely the initial conditions and spatiotemporal dynamics that drive these cell population conditions. To study these aspects, we developed a minimal, spatially-resolved simulation framework for modeling tissue-scale mixed populations of cells based on diffusible particles the cells consume and release, the concentrations of which determine their behavior in arbitrarily complex ways, and on stochastic reproduction. We simulate cell populations that self-sort to facilitate metabolic symbiosis, that grow according to tumor-stroma signaling patterns, and that give rise to stable local regions of chronic hypoxia near blood vessels. We raise two novel questions in the context of these results: (1) How will two metabolically symbiotic cell subpopulations self-sort in the presence of glucose, oxygen, and lactate gradients? We observe a robust pattern of alternating striations. (2) What is the proper time scale to observe stable local regions of chronic hypoxia? We observe the stability is a function of the balance of three factors related to O2-diffusion rate, local vessel release rate, and viable and hypoxic tumor cell consumption rate. We anticipate our simulation framework will help researchers design better experiments and generate novel hypotheses to better understand dynamic, emergent whole-tumor behavior.

The Warburg Effect: How Does it Benefit Cancer Cells?

Cancer cells rewire their metabolism to promote growth, survival, proliferation, and long-term maintenance. The common feature of this altered metabolism is the increased glucose uptake and fermentation of glucose to lactate. This phenomenon is observed even in the presence of completely functioning mitochondria and, together, is known as the 'Warburg Effect'. The Warburg Effect has been documented for over 90 years and extensively studied over the past 10 years, with thousands of papers reporting to have established either its causes or its functions. Despite this intense interest, the function of the Warburg Effect remains unclear. Here, we analyze several proposed explanations for the function of Warburg Effect, emphasize their rationale, and discuss their controversies.

The rate of glycolysis quantitatively mediates specific histone acetylation sites

Background

Glucose metabolism links metabolic status to protein acetylation. However, it remains poorly understood to what extent do features of glucose metabolism contribute to protein acetylation and whether the process can be dynamically and quantitatively regulated by differing rates of glycolysis.

Results

Here, we show that titratable rates of glycolysis with corresponding changes in the levels of glycolytic intermediates result in a graded remodeling of a bulk of the metabolome and resulted in gradual changes in total histone acetylation levels. Dynamic histone acetylation levels were found and most strongly correlated with acetyl coenzyme A (ac-CoA) levels and inversely associated with the ratio of ac-CoA to free CoA. A multiplexed stable isotopic labeling by amino acids in cell culture (SILAC)-based proteomics approach revealed that the levels of half of identified histone acetylation sites as well as other lysine acylation modifications are tuned by the rate of glycolysis demonstrating that glycolytic rate affects specific acylation sites.

Conclusions

We demonstrate that histone acylation is directly sensed by glucose flux in a titratable, dose-dependent manner that is modulated by glycolytic flux and that a possible function of the Warburg Effect, a metabolic state observed in cancers with enhanced glucose metabolism, is to confer specific signaling effects on cells.

Estimating relative changes of metabolic fluxes

Fluxes are the central trait of metabolism and Kinetic Flux Profiling (KFP) is an effective method of measuring them. To generalize its applicability, we present an extension of the method that estimates the relative changes of fluxes using only relative quantitation of ¹³C-labeled metabolites. Such features are directly tailored to the more common experiment that performs only relative quantitation and compares fluxes between two conditions. We call our extension rKFP. Moreover, we examine the effects of common missing data and common modeling assumptions on (r)KFP, and provide practical suggestions. We also investigate the selection of measuring times for (r)KFP and provide a simple recipe. We then apply rKFP to ¹³C-labeled glucose time series data collected from cells under normal and glucose-deprived conditions, estimating the relative flux changes of glycolysis and its branching pathways. We identify an adaptive response in which de novo serine biosynthesis is compromised to maintain the glycolytic flux backbone. Together, these results greatly expand the capabilities of KFP and are suitable for broad biological applications.

Metabolism underlies all biological processes, and its quantitative study is crucial for our understanding. The central trait of metabolism, metabolic fluxes, cannot be directly measured and are estimated usually through modeling. Existing modeling methods, however, are limited by poorly-characterized parameters, crude precision, or labor-intensiveness. Motivated by these limitations, and recognizing a most common goal in the field of comparing the fluxes between two conditions, we develop an extension of an existing method that takes in time-series relative-quantitation data of isotope-labeled metabolites (a kind of data that modern metabolomic technologies readily generate), and outputs the relative changes of fluxes in the metabolic networks of interest. We also carefully examine some issues on model construction and experimental design, and improve the reliability and strength of the method. We apply our method to data collected from cells in normal and glucose-deprived conditions, demonstrate the efficacy of the method and arrive at new biological insight.

Heterogeneity of glycolysis in cancers and therapeutic opportunities

Upregulated glycolysis, both in normoxic and hypoxic environments, is a nearly universal trait of cancer cells. The enormous difference in glucose metabolism offers a target for therapeutic intervention with a potentially low toxicity profile. The past decade has seen a steep rise in the development and clinical assessment of small molecules that target glycolysis. The enzymes in glycolysis have a highly heterogeneous nature that allows for the different bioenergetic, biosynthetic, and signaling demands needed for various tissue functions. In cancers, these properties enable them to respond to the variable requirements of cell survival, proliferation and adaptation to nutrient availability. Heterogeneity in glycolysis occurs through the expression of different isoforms, posttranslational modifications that affect the kinetic and regulatory properties of the enzyme. In this review, we will explore this vast heterogeneity of glycolysis and discuss how this information might be exploited to better target glucose metabolism and offer possibilities for biomarker development.

Nuclear ARRB1 induces pseudohypoxia and cellular metabolism reprogramming in prostate cancer

Tumour cells sustain their high proliferation rate through metabolic reprogramming, whereby cellular metabolism shifts from oxidative phosphorylation to aerobic glycolysis, even under normal oxygen levels. Hypoxia-inducible factor 1A (HIF1A) is a major regulator of this process, but its activation under normoxic conditions, termed pseudohypoxia, is not well documented. Here, using an integrative approach combining the first genome-wide mapping of chromatin binding for an endocytic adaptor, ARRB1, both in vitro and in vivo with gene expression profiling, we demonstrate that nuclear ARRB1 contributes to this metabolic shift in prostate cancer cells via regulation of HIF1A transcriptional activity under normoxic conditions through regulation of succinate dehydrogenase A (SDHA) and fumarate hydratase (FH) expression. ARRB1-induced pseudohypoxia may facilitate adaptation of cancer cells to growth in the harsh conditions that are frequently encountered within solid tumours. Our study is the first example of an endocytic adaptor protein regulating metabolic pathways. It implicates ARRB1 as a potential tumour promoter in prostate cancer and highlights the importance of metabolic alterations in prostate cancer.

Epigenetics and cancer metabolism

Cancer cells adapt their metabolism to support proliferation and survival. A hallmark of cancer, this alteration is characterized by dysfunctional metabolic enzymes, changes in nutrient availability, tumor microenvironment and oncogenic mutations. Metabolic rewiring in cancer is tightly connected to changes at the epigenetic level. Enzymes that mediate epigenetic status of cells catalyze posttranslational modifications of DNA and histones and influence metabolic gene expression. These enzymes require metabolites that are used as cofactors and substrates to carry out reactions. This interaction of epigenetics and metabolism constitutes a new avenue of cancer biology and could lead to new insights for the development of anti-cancer therapeutics.

Serine, glycine and one-carbon units: cancer metabolism in full circle

One-carbon metabolism involving the folate and methionine cycles integrates nutritional status from amino acids, glucose and vitamins, and generates diverse outputs, such as the biosynthesis of lipids, nucleotides and proteins, the maintenance of redox status and the substrates for methylation reactions. Long considered a 'housekeeping' process, this pathway has recently been shown to have additional complexity. Genetic and functional evidence suggests that hyperactivation of this pathway is a driver of oncogenesis and establishes a link to cellular epigenetic status. Given the wealth of clinically available agents that target one-carbon metabolism, these new findings could present opportunities for translation into precision cancer medicine.

Nutrient-dependent/pheromone-controlled adaptive evolution: a model

BACKGROUND

The prenatal migration of gonadotropin-releasing hormone (GnRH) neurosecretory neurons allows nutrients and human pheromones to alter GnRH pulsatility, which modulates the concurrent maturation of the neuroendocrine, reproductive, and central nervous systems, thus influencing the development of ingestive behavior, reproductive sexual behavior, and other behaviors.

METHODS

THIS MODEL DETAILS HOW CHEMICAL ECOLOGY DRIVES ADAPTIVE EVOLUTION VIA: (1) ecological niche construction, (2) social niche construction, (3) neurogenic niche construction, and (4) socio-cognitive niche construction. This model exemplifies the epigenetic effects of olfactory/pheromonal conditioning, which alters genetically predisposed, nutrient-dependent, hormone-driven mammalian behavior and choices for pheromones that control reproduction via their effects on luteinizing hormone (LH) and systems biology.

RESULTS

Nutrients are metabolized to pheromones that condition behavior in the same way that food odors condition behavior associated with food preferences. The epigenetic effects of olfactory/pheromonal input calibrate and standardize molecular mechanisms for genetically predisposed receptor-mediated changes in intracellular signaling and stochastic gene expression in GnRH neurosecretory neurons of brain tissue. For example, glucose and pheromones alter the hypothalamic secretion of GnRH and LH. A form of GnRH associated with sexual orientation in yeasts links control of the feedback loops and developmental processes required for nutrient acquisition, movement, reproduction, and the diversification of species from microbes to man.

CONCLUSION

An environmental drive evolved from that of nutrient ingestion in unicellular organisms to that of pheromone-controlled socialization in insects. In mammals, food odors and pheromones cause changes in hormones such as LH, which has developmental affects on pheromone-controlled sexual behavior in nutrient-dependent reproductively fit individuals across species of vertebrates.