Glutamine Metabolism in Cancer

Defining metabolic flexibility in hair follicle stem cell induced squamous cell carcinoma

We previously showed that inhibition of glycolysis in cutaneous squamous cell carcinoma (SCC)-initiating cells had no effect on tumorigenesis, despite the perceived requirement of the Warburg effect, which was thought to drive carcinogenesis. Instead, these SCCs were metabolically flexible and sustained growth through glutaminolysis, another metabolic process frequently implicated to fuel tumorigenesis in various cancers. Here, we focused on glutaminolysis and genetically blocked this process through glutaminase (GLS) deletion in SCC cells of origin. Genetic deletion of GLS had little effect on tumorigenesis due to the up-regulated lactate consumption and utilization for the TCA cycle, providing further evidence of metabolic flexibility. We went on to show that posttranscriptional regulation of nutrient transporters appears to mediate metabolic flexibility in this SCC model. To define the limits of this flexibility, we genetically blocked both glycolysis and glutaminolysis simultaneously and found the abrogation of both of these carbon utilization pathways was enough to prevent both papilloma and frank carcinoma.

Altered metabolism in cancer: insights into energy pathways and therapeutic targets

Cancer cells undergo significant metabolic reprogramming to support their rapid growth and survival. This study examines important metabolic pathways like glycolysis, oxidative phosphorylation, glutaminolysis, and lipid metabolism, focusing on how they are regulated and their contributions to the development of tumors. The interplay between oncogenes, tumor suppressors, epigenetic modifications, and the tumor microenvironment in modulating these pathways is examined. Furthermore, we discuss the therapeutic potential of targeting cancer metabolism, presenting inhibitors of glycolysis, glutaminolysis, the TCA cycle, fatty acid oxidation, LDH, and glucose transport, alongside emerging strategies targeting oxidative phosphorylation and lipid synthesis. Despite the promise, challenges such as metabolic plasticity and the need for combination therapies and robust biomarkers persist, underscoring the necessity for continued research in this dynamic field.

Prostate Cancer's Silent Partners: Fibroblasts and Their Influence on Glutamine Metabolism Manipulation

Cancer-associated fibroblast (CAF)s in the tumour microenvironment (TME) modulate the extracellular matrix, interact with cancer cells, and facilitate communication with infiltrating leukocytes, significantly contributing to cancer progression and therapeutic response. In prostate cancer (PCa), CAFs promote malignancy through metabolic rewiring, cancer stem cell regulation, and therapy resistance. Pre-clinical studies indicate that targeting amino acid metabolism, particularly glutamine (Gln) metabolism, reduces cancer proliferation and stemness. However, most studies lack the context of CAF-cancer interaction, focusing on monocultures. This study assesses the influence of CAFs on PCa growth by manipulating Gln metabolism using colour-labelled PCa cell lines (red) and fibroblast (green) in a co-culture system to evaluate CAFs' effects on PCa cell proliferation and clonogenic potential. CAFs increased the proliferation of hormone-sensitive LNCaP cells, whereas the castration-resistant C4-2 cells were unaffected. However, clonogenic growth increased in both cell lines. Gln deprivation and GLS1 inhibition experiments revealed that the increased growth rate of LNCAP cells was associated with increased dependence on Gln, which was confirmed by proteomic analyses. Tissue analysis of PCa patients revealed elevated GLS1 levels in both the PCa epithelium and stroma, suggesting that GLS1 is a therapeutic target. Moreover, the median overall survival analysis of GLS1 expression in the PCa epithelium and stroma identified a "high-risk" patient group that may benefit from GLS1-targeted therapies. Therefore, GLS1 targeting appears promising in castration-resistant PCa patients with high GLS1 epithelium and low GLS1 stromal expression.

Circ-PITX1 promotes non-small-cell lung cancer progression through regulating ETS1 expression via miR-615-5p

BACKGROUND

Circular RNAs (circRNAs), produced by reverse splicing, act as important players in human cancers. We aimed to assess the biological functions of circRNA pituitary homeobox 1 (circ-PITX1) in non-small-cell lung cancer (NSCLC).

METHODS

qRT-PCR was employed to determine RNA expression. Biological behaviors of NSCLC cells were assessed by CCK-8, colony formation, EdU assay, flow cytometry, wound healing, and transwell assays. Glutamine catabolism was examined via the measurement of glutamine consumption, α-ketoglutarate levels, as well as ATP levels. Protein levels were detected by western blot assays. Dual-luciferase reporter assay and RNA immunoprecipitation (RIP) assay were performed to reveal the mechanism responsible for circ-PITX1 regulating NSCLC cell malignancy. The murine xenograft model was established to investigate circ-PITX1's effect on tumor formation.

RESULTS

Circ-PITX1 was overexpressed in NSCLC tissue samples and cells. Its low expression repressed NSCLC cell proliferation and motility. Moreover, our data revealed its downregulation inhibited glutamine catabolism and tumor formation and promoted cell apoptosis. In addition, circ-PITX1 bound to miR-615-5p, and its inhibitory effect on tumor cellular behaviors could be reversed after decreasing miR-615-5p expression. The miRNA targeted E26 transformation specific-1 (ETS1), whose upregulation abolished miR-615-5p overexpression-induced effects in NSCLC cells. Furthermore, circ-PITX1 positively modulated ETS1 production through interaction with miR-615-5p.

CONCLUSION

Circ-PITX1 facilitated NSCLC progression via modulating miR-615-5p/ETS1 pathway.

Glutaminase - A potential target for cancer treatment

The overexpression of glutaminase is reported to influence cancer growth and metastasis through glutaminolysis. Upregulation of glutamine catabolism is recently recognized as a critical feature of cancer, and cancer cells are observed to reprogram glutamine metabolism to maintain its survival and proliferation. Special focus is given on the glutaminase isoform, GLS1 (kidney type glutaminase), as the other isoform GLS2 (Liver type glutaminase) acts as a tumour suppressor in some conditions. Glutaminolysis linked with autophagy, which is mediated via mTORC1, also serves as a promising target for cancer therapy. Glutamine also plays a vital role in maintaining redox homeostasis. Inhibition of glutaminase aggravates oxidative stress by reducing glutathione level, thus leading to apoptotic-mediated cell death in cancer cells Therefore, inhibiting the glutaminase activity using glutaminase inhibitors such as BPTES, DON, JHU-083, CB-839, compound 968, etc. may answer many intriguing questions behind the uncontrolled proliferation of cancer cells and serve as a prophylactic treatment for cancer. Earlier reports neither discuss nor provide perspectives on exact signaling gene or pathway. Hence, the present review highlights the plausible role of glutaminase in cancer and the current therapeutic approaches and clinical trials to target and inhibit glutaminase enzymes for better cancer treatment.

Glutamine transporter SLC38A3 promotes breast cancer metastasis via Gsk3β/β-catenin/EMT pathway

Breast cancer is the leading cancer-related cause of death in women. Here we show that solute carrier family 38-member 3 (SLC38A3) is overexpressed in breast cancer, particularly in triple-negative breast cancer (TNBC) cells and tissues. Our study reveals that SLC38A3 regulates cellular glutamine, glutamate, asparagine, aspartate, alanine, and glutathione (GSH) levels in breast cancer cells. Our data demonstrate that SLC38A3 enhances cell viability, cell migration and invasion in vitro, and promotes tumor growth and metastasis in vivo, while reducing apoptosis and oxidative stress. Mechanistically, we show that SLC38A3 suppresses the activity of glycogen synthase kinase 3-β (Gsk3β), a negative regulator of β-catenin, and increases protein levels of β-catenin, leading to the upregulation of epithelial-to-mesenchymal-transition (EMT)-inducing transcription factors and EMT markers in breast cancer. In summary, we show that SLC38A3 is overexpressed in breast cancer and promotes breast cancer metastasis via the GSK3β/β-catenin/EMT pathway, presenting a novel therapeutic target to explore for breast cancer.

Development of a prognostic model for muscle-invasive bladder cancer using glutamine metabolism

BACKGROUND

Muscle-invasive bladder cancer (MIBC) is distinguished by its pronounced invasiveness and unfavorable prognosis. Immunotherapy and targeted therapy have emerged as key treatment options for various types of cancer. Altered metabolism is a defining characteristic of cancer cells, and there is mounting evidence suggesting the important role of glutamine metabolism (GM) in tumor metabolism. Nevertheless, the relationship between GM and clinical outcomes, immune microenvironment, and immunotherapy in MIBC remains unknown.

METHODS

This study employed Mendelian randomization to explore the causal relationship between blood metabolites and bladder tumors. We systematically evaluated 373 glutamine metabolism-related genes and identified prognostic-related genes, leading to the construction of a glutamine-associated prognostic model. Further analysis confirmed the correlation between high and low-risk groups with the tumor microenvironment, immune cell infiltration, and tumor mutation burden. Subsequently, we assessed the relationship between the risk score and the sensitivity to various immunotherapies and anticancer drugs.

RESULTS

We identified 14 blood metabolites at the molecular level that have a causal relationship with bladder tumors. At the gene level, the study discussed differentially expressed GM genes in MIBC. First, we established a risk model predicting overall survival (OS) based on GM genes, confirming its reliable predictive ability in MIBC patients and validated it in a GEO cohort. Additionally, a reliable column line chart was created. Secondly, two distinct molecular subtypes were identified, and the associations between different risk groups and tumor microenvironment and immune infiltration were observed. In addition, the predicted risk values correlated with responses to a broad range of pharmaceutical agents.

CONCLUSION

In summary, we confirmed the causal relationship between blood metabolites and bladder tumors. Furthermore, a risk scoring model related to glutamine metabolism consisting of 9 genes was developed. This model could potentially serve as a useful tool for predicting prognosis and guiding the treatment of MIBC patients.

Glutamine metabolism-related genes and immunotherapy in nonspecific orbital inflammation were validated using bioinformatics and machine learning

BACKGROUND

Nonspecific orbital inflammation (NSOI) is an idiopathic, persistent, and proliferative inflammatory condition affecting the orbit, characterized by polymorphous lymphoid infiltration. Its pathogenesis and progression have been linked to imbalances in tumor metabolic pathways, with glutamine (Gln) metabolism emerging as a critical aspect in cancer. Metabolic reprogramming is known to influence clinical outcomes in various malignancies. However, comprehensive research on glutamine metabolism's significance in NSOI is lacking.

METHODS

This study conducted a bioinformatics analysis to identify and validate potential glutamine-related molecules (GlnMgs) associated with NSOI. The discovery of GlnMgs involved the intersection of differential expression analysis with a set of 42 candidate GlnMgs. The biological functions and pathways of the identified GlnMgs were analyzed using GSEA and GSVA. Lasso regression and SVM-RFE methods identified hub genes and assessed the diagnostic efficacy of fourteen GlnMgs in NSOI. The correlation between hub GlnMgs and clinical characteristics was also examined. The expression levels of the fourteen GlnMgs were validated using datasets GSE58331 and GSE105149.

RESULTS

Fourteen GlnMgs related to NSOI were identified, including FTCD, CPS1, CTPS1, NAGS, DDAH2, PHGDH, GGT1, GCLM, GLUD1, ART4, AADAT, ASNSD1, SLC38A1, and GFPT2. Biological function analysis indicated their involvement in responses to extracellular stimulus, mitochondrial matrix, and lipid transport. The diagnostic performance of these GlnMgs in distinguishing NSOI showed promising results.

CONCLUSIONS

This study successfully identified fourteen GlnMgs associated with NSOI, providing insights into potential novel biomarkers for NSOI and avenues for monitoring disease progression.

Amino acids and cancer: potential for therapies?

PURPOSE OF REVIEW

Cancer patients may have a variety of disorders associated with systemic inflammation caused by disease progression. Consequently, we have protein hypercatabolism. In view of this, protein and amino acid adequacy should be considered in relation to nutritional behavior. Therefore, this review aims to evaluate the influence of protein and amino acids in the nutritional therapy of cancer.

RECENT FINDINGS

Diets with adequate protein levels appear to be beneficial in the treatment of cancer; guidelines suggest consumption of greater than 1.0-1.5 g/kg body weight/day. In patients diagnosed with malnutrition, sarcopenia, or cachexia, it is recommended to use the maximum amount of protein (1.5 g/kg of weight/day) to adapt the diet. In addition, based on the evidence found, there is no consensus on the dose and effects in cancer patients of amino acids such as branched-chain amino acids, glutamine, arginine, and creatine.

SUMMARY

When evaluating the components of the diet of cancer patients, the protein recommendation should be greater than 1.0-1.5 g/kg of weight/day, with a distribution between animal and vegetable proteins. We found little evidence demonstrating clinical benefits regarding individual or combined amino acid supplementation. Still, it is unclear how the use, dose, and specificity for different types of cancer should be prescribed or at what stage of treatment amino acids should be prescribed.

SLC38A5 promotes glutamine metabolism and inhibits cisplatin chemosensitivity in breast cancer

BACKGROUND

Solute carrier family 38 member 5 (SLC38A5), as an amino acid transporter, play a vital role in cellular biological processes. In this study, we analyzed the function of SLC38A5 and its potential mechanism in breast cancer (BC) progression.

METHODS

The expression of SLC38A5 in cancer and adjacent-normal tissues was analyzed by qRT-PCR and Western blot, and its correlation with patient prognosis was analyzed. The immunohistochemical staining of cancer tissues and adjacent-normal tissues was performed on SLC38A5-positive specimens. BC mice were successfully applied to examine the role of SLC38A5 on tumor proliferation using the CCK-8 assay. In BC cells and mouse tumor tissues, SLC38A5 and PCNA expression were determined by Western blotting.

RESULTS

The study found that SLC38A5 was highly expressed in BC patients and associated with a poor survival. SLC38A5 silencing inhibited BC cell viability and glutamine uptake. In addition, SLC38A5 overexpression promoted BC cell viability via the glutamine metabolism. SLC38A5 inhibited cisplatin chemosensitivity in BC cells. Importantly, SLC38A5 silencing inhibited tumor growth in vivo.

CONCLUSION

Our findings suggest that SLC38A5 enhances BC cell viability by glutamine metabolism, inhibits the chemical sensitivity of cisplatin in BC cells, and promotes tumor growth, emphasizing the clinical relevance of SLC38A5 in BC management as a novel potential therapeutic target.

Genetic estimation of correlations between circulating glutamine and cancer

The controversy regarding the causal relationship between circulating glutamine and cancer risk remains unresolved. Here, we aim to assess the causal impact of glutamine on the risk of six prevalent cancer types and their respective subtypes including breast, lung, ovarian, thyroid, prostate, and endometrial cancers. A Mendelian randomization (MR) analysis was conducted to evaluate the causal effect of circulating glutamine on cancers risk. Data on circulating glutamine were extracted from the UK Biobank (UKB), comprising 114,750 European patients. To ensure the validity of our findings, we employed several analytical approaches, such as inverse variance weighting, weighted median, weighted mode test, MR-Egger regression, and MR-PRESSO method. Both univariable and multivariable MR analyses were conducted. Additionally, we employed a large-scale summary-level study on circulating glutamine involving 24,925 European participants for validation purposes. Our MR analysis reveals a causal association between circulating glutamine and thyroid cancer in both the UKB cohort (IVW: OR = 0.667, 95% CI [0.541-0.822], P = 1.52×10-4) and the validated cohort (IVW: OR = 0.577, 95% CI [0.421-0.790], P = 6.14×10-4). Sensitivity analysis, including multivariable MR analyses, consistently supports this finding (P < 0.05), affirming the reliability and robustness of our study. Our findings indicate an inverse correlation between circulating glutamine and the incidence of thyroid cancer in European populations. However, further research encompassing diverse ancestries is necessary to validate this causal relationship.

Targeting Glucose Metabolism in Cancer Cells as an Approach to Overcoming Drug Resistance

The "Warburg effect" consists of a metabolic shift in energy production from oxidative phosphorylation to glycolysis. The continuous activation of glycolysis in cancer cells causes rapid energy production and an increase in lactate, leading to the acidification of the tumour microenvironment, chemo- and radioresistance, as well as poor patient survival. Nevertheless, the mitochondrial metabolism can be also involved in aggressive cancer characteristics. The metabolic differences between cancer and normal tissues can be considered the Achilles heel of cancer, offering a strategy for new therapies. One of the main causes of treatment resistance consists of the increased expression of efflux pumps, and multidrug resistance (MDR) proteins, which are able to export chemotherapeutics out of the cell. Cells expressing MDR proteins require ATP to mediate the efflux of their drug substrates. Thus, inhibition of the main energy-producing pathways in cancer cells, not only induces cancer cell death per se, but also overcomes multidrug resistance. Given that most anticancer drugs do not have the ability to distinguish normal cells from cancer cells, a number of drug delivery systems have been developed. These nanodrug delivery systems provide flexible and effective methods to overcome MDR by facilitating cellular uptake, increasing drug accumulation, reducing drug efflux, improving targeted drug delivery, co-administering synergistic agents, and increasing the half-life of drugs in circulation.

S-Nitrosylation at the intersection of metabolism and autophagy: Implications for cancer

Metabolic plasticity, which determines tumour growth and metastasis, is now understood to be a flexible and context-specific process in cancer metabolism. One of the major pathways contributing to metabolic adaptations in eucaryotic cells is autophagy, a cellular degradation and recycling process that is activated during periods of starvation or stress to maintain metabolite and biosynthetic intermediate levels. Consequently, there is a close association between the metabolic adaptive capacity of tumour cells and autophagy-related pathways in cancer. Additionally, nitric oxide regulates protein function and signalling through S-nitrosylation, a post-translational modification that can also impact metabolism and autophagy. The primary objective of this review is to provide an up-to-date overview of the role of S-nitrosylation at the intersection of metabolism and autophagy in cancer. First, we will outline the involvement of S-nitrosylation in the metabolic adaptations that occur in tumours. Then, we will discuss the multifaceted role of autophagy in cancer, the interplay between metabolism and autophagy during tumour progression, and the contribution of S-nitrosylation to autophagic dysregulation in cancer. Finally, we will present insights into relevant therapeutic aspects and discuss prospects for the future.

Defining metabolic flexibility in hair follicle stem cell induced squamous cell carcinoma

Among the numerous changes associated with the transformation to cancer, cellular metabolism is one of the first discovered and most prominent[1, 2]. However, despite the knowledge that nearly every cancer is associated with the strong upregulation of various metabolic pathways, there has yet to be much clinical progress on the treatment of cancer by targeting a single metabolic enzyme directly[3-6]. We previously showed that inhibition of glycolysis through lactate dehydrogenase (LDHA) deletion in cancer cells of origin had no effect on the initiation or progression of cutaneous squamous cell carcinoma[7], suggesting that these cancers are metabolically flexible enough to produce the necessary metabolites required for sustained growth in the absence of glycolysis. Here we focused on glutaminolysis, another metabolic pathway frequently implicated as important for tumorigenesis in correlative studies. We genetically blocked glutaminolysis through glutaminase (GLS) deletion in cancer cells of origin, and found that this had little effect on tumorigenesis, similar to what we previously showed for blocking glycolysis. Tumors with genetic deletion of glutaminolysis instead upregulated lactate consumption and utilization for the TCA cycle, providing further evidence of metabolic flexibility. We also found that the metabolic flexibility observed upon inhibition of glycolysis or glutaminolysis is due to post-transcriptional changes in the levels of plasma membrane lactate and glutamine transporters. To define the limits of metabolic flexibility in cancer initiating hair follicle stem cells, we genetically blocked both glycolysis and glutaminolysis simultaneously and found that frank carcinoma was not compatible with abrogation of both of these carbon utilization pathways. These data point towards metabolic flexibility mediated by regulation of nutrient consumption, and suggest that treatment of cancer through metabolic manipulation will require multiple interventions on distinct pathways.

Bioinformatics and machine learning were used to validate glutamine metabolism-related genes and immunotherapy in osteoporosis patients

BACKGROUND

Osteoporosis (OP), often referred to as the "silent disease of the twenty-first century," poses a significant public health concern due to its severity, chronic nature, and progressive course, predominantly affecting postmenopausal women and elderly individuals. The pathogenesis and progression of this disease have been associated with dysregulation in tumor metabolic pathways. Notably, the metabolic utilization of glutamine has emerged as a critical player in cancer biology. While metabolic reprogramming has been extensively studied in various malignancies and linked to clinical outcomes, its comprehensive investigation within the context of OP remains lacking.

METHODS

This study aimed to identify and validate potential glutamine metabolism genes (GlnMgs) associated with OP through comprehensive bioinformatics analysis. The identification of GlnMgs was achieved by integrating the weighted gene co-expression network analysis and a set of 28 candidate GlnMgs. Subsequently, the putative biological functions and pathways associated with GlnMgs were elucidated using gene set variation analysis. The LASSO method was employed to identify key hub genes, and the diagnostic efficacy of five selected GlnMgs in OP detection was assessed. Additionally, the relationship between hub GlnMgs and clinical characteristics was investigated. Finally, the expression levels of the five GlnMgs were validated using independent datasets (GSE2208, GSE7158, GSE56815, and GSE35956).

RESULTS

Five GlnMgs, namely IGKC, TMEM187, RPS11, IGLL3P, and GOLGA8N, were identified in this study. To gain insights into their biological functions, particular emphasis was placed on synaptic transmission GABAergic, inward rectifier potassium channel activity, and the cytoplasmic side of the lysosomal membrane. Furthermore, the diagnostic potential of these five GlnMgs in distinguishing individuals with OP yielded promising results, indicating their efficacy as discriminative markers for OP.

CONCLUSIONS

This study discovered five GlnMgs that are linked to OP. They shed light on potential new biomarkers for OP and tracking its progression.

Glutamine metabolism in diseases associated with mitochondrial dysfunction

Mitochondrial dysfunction can arise from genetic defects or environmental exposures and impact a wide range of biological processes. Among these are metabolic pathways involved in glutamine catabolism, anabolism, and glutamine-glutamate cycling. In recent years, altered glutamine metabolism has been found to play important roles in the pathologic consequences of mitochondrial dysfunction. Glutamine is a pleiotropic molecule, not only providing an alternate carbon source to glucose in certain conditions, but also playing unique roles in cellular communication in neurons and astrocytes. Glutamine consumption and catabolic flux can be significantly altered in settings of genetic mitochondrial defects or exposure to mitochondrial toxins, and alterations to glutamine metabolism appears to play a particularly significant role in neurodegenerative diseases. These include primary mitochondrial diseases like Leigh syndrome (subacute necrotizing encephalopathy) and MELAS (mitochondrial myopathy with encephalopathy, lactic acidosis, and stroke-like episodes), as well as complex age-related neurodegenerative disorders such as Alzheimer's and Parkinson's diseases. Pharmacologic interventions targeting glutamine metabolizing and catabolizing pathways appear to provide some benefits in cell and animal models of these diseases, indicating glutamine metabolism may be a clinically relevant target. In this review, we discuss glutamine metabolism, mitochondrial disease, the impact of mitochondrial dysfunction on glutamine metabolic processes, glutamine in neurodegeneration, and candidate targets for therapeutic intervention.

SIRT5 Activation and Inorganic Phosphate Binding Reduce Cancer Cell Vitality by Modulating Autophagy/Mitophagy and ROS

Cancer cells show increased glutamine consumption. The glutaminase (GLS) enzyme controls a limiting step in glutamine catabolism. Breast tumors, especially the triple-negative subtype, have a high expression of GLS. Our recent study demonstrated that GLS activity and ammonia production are inhibited by sirtuin 5 (SIRT5). We developed MC3138, a selective SIRT5 activator. Treatment with MC3138 mimicked the deacetylation effect mediated by SIRT5 overexpression. Moreover, GLS activity was regulated by inorganic phosphate (Pi). Considering the interconnected roles of GLS, SIRT5 and Pi in cancer growth, our hypothesis is that activation of SIRT5 and reduction in Pi could represent a valid antitumoral strategy. Treating cells with MC3138 and lanthanum acetate, a Pi chelator, decreased cell viability and clonogenicity. We also observed a modulation of MAP1LC3B and ULK1 with MC3138 and lanthanum acetate. Interestingly, inhibition of the mitophagy marker BNIP3 was observed only in the presence of MC3138. Autophagy and mitophagy modulation were accompanied by an increase in cytosolic and mitochondrial reactive oxygen species (ROS). In conclusion, our results show how SIRT5 activation and/or Pi binding can represent a valid strategy to inhibit cell proliferation by reducing glutamine metabolism and mitophagy, leading to a deleterious accumulation of ROS.

Metabolic Heterogeneity, Plasticity, and Adaptation to "Glutamine Addiction" in Cancer Cells: The Role of Glutaminase and the GTωA [Glutamine Transaminase-ω-Amidase (Glutaminase II)] Pathway

Many cancers utilize l-glutamine as a major energy source. Often cited in the literature as "l-glutamine addiction", this well-characterized pathway involves hydrolysis of l-glutamine by a glutaminase to l-glutamate, followed by oxidative deamination, or transamination, to α-ketoglutarate, which enters the tricarboxylic acid cycle. However, mammalian tissues/cancers possess a rarely mentioned, alternative pathway (the glutaminase II pathway): l-glutamine is transaminated to α-ketoglutaramate (KGM), followed by ω-amidase (ωA)-catalyzed hydrolysis of KGM to α-ketoglutarate. The name glutaminase II may be confused with the glutaminase 2 (GLS2) isozyme. Thus, we recently renamed the glutaminase II pathway the "glutamine transaminase-ω-amidase (GTωA)" pathway. Herein, we summarize the metabolic importance of the GTωA pathway, including its role in closing the methionine salvage pathway, and as a source of anaplerotic α-ketoglutarate. An advantage of the GTωA pathway is that there is no net change in redox status, permitting α-ketoglutarate production during hypoxia, diminishing cellular energy demands. We suggest that the ability to coordinate control of both pathways bestows a metabolic advantage to cancer cells. Finally, we discuss possible benefits of GTωA pathway inhibitors, not only as aids to studying the normal biological roles of the pathway but also as possible useful anticancer agents.

Glutamine metabolism genes prognostic signature for stomach adenocarcinoma and immune infiltration: potential biomarkers for predicting overall survival

Background

Stomach adenocarcinoma (STAD), caused by mutations in stomach cells, is characterized by poor overall survival. Chemotherapy is commonly administered for stomach cancer patients following surgical resection. An imbalance in tumor metabolic pathways is connected to tumor genesis and growth. It has been discovered that glutamine (Gln) metabolism plays a crucial role in cancer. Metabolic reprogramming is associated with clinical prognosis in various cancers. However, the role of glutamine metabolism genes (GlnMgs) in the fight against STAD remains poorly understood.

Methods

GlnMgs were determined in STAD samples from the TCGA and GEO datasets. The TCGA and GEO databases provide information on stemness indices (mRNAsi), gene mutations, copy number variations (CNV), tumor mutation burden (TMB), and clinical characteristics. Lasso regression was performed to build the prediction model. The relationship between gene expression and Gln metabolism was investigated using co-expression analysis.

Results

GlnMgs, found to be overexpressed in the high-risk group even in the absence of any symptomatology, demonstrated strong predictive potential for STAD outcomes. GSEA highlighted immunological and tumor-related pathways in the high-risk group. Immune function and m6a gene expression differed significantly between the low- and high-risk groups. AFP, CST6, CGB5, and ELANE may be linked to the oncology process in STAD patients. The prognostic model, CNVs, single nucleotide polymorphism (SNP), and medication sensitivity all revealed a strong link to the gene.

Conclusion

GlnMgs are connected to the genesis and development of STAD. These corresponding prognostic models aid in predicting the prognosis of STAD GlnMgs and immune cell infiltration in the tumor microenvironment (TME) may be possible therapeutic targets in STAD. Furthermore, the glutamine metabolism gene signature presents a credible alternative for predicting STAD outcomes, suggesting that these GlnMgs could open a new field of study for STAD-focused therapy Additional trials are needed to validate the results of the current study.

A novel Alzheimer's disease prognostic signature: identification and analysis of glutamine metabolism genes in immunogenicity and immunotherapy efficacy

Alzheimer's disease (AD) is characterized as a distinct onset and progression of cognitive and functional decline associated with age, as well as a specific neuropathology. It has been discovered that glutamine (Gln) metabolism plays a crucial role in cancer. However, a full investigation of its role in Alzheimer's disease is still missing. This study intended to find and confirm potential Gln-related genes associated with AD using bioinformatics analysis. The discovery of GlnMgs was made possible by the intersection of the WGCNA test and 26 Gln-metabolism genes (GlnMgs). GlnMgs' putative biological functions and pathways were identified using GSVA. The LASSO method was then used to identify the hub genes as well as the diagnostic efficiency of the four GlnMgs in identifying AD. The association between hub GlnMgs and clinical characteristics was also studied. Finally, the GSE63060 was utilized to confirm the levels of expression of the four GlnMgs. Four GlnMgs were discovered (ATP5H, NDUFAB1, PFN2, and SPHKAP). For biological function analysis, cell fate specification, atrioventricular canal development, and neuron fate specification were emphasized. The diagnostic ability of the four GlnMgs in differentiating AD exhibited a good value. This study discovered four GlnMgs that are linked to AD. They shed light on potential new biomarkers for AD and tracking its progression.

NMDA Receptor and Its Emerging Role in Cancer

Glutamate is a key player in excitatory neurotransmission in the central nervous system (CNS). The N-methyl-D-aspartate receptor (NMDAR) is a glutamate-gated ion channel which presents several unique features and is involved in various physiological and pathological neuronal processes. Thanks to great efforts in neuroscience, its structure and the molecular mechanisms controlling its localization and functional regulation in neuronal cells are well known. The signaling mediated by NMDAR in neurons is very complex as it depends on its localization, composition, Ca²⁺ influx, and ion flow-independent conformational changes. Moreover, NMDA receptors are highly diffusive in the plasma membrane of neurons, where they form heterocomplexes with other membrane receptors and scaffold proteins which determine the receptor function and activation of downstream signaling. Interestingly, a recent paper demonstrates that NMDAR signaling is involved in epithelial cell competition, an evolutionary conserved cell fitness process influencing cancer initiation and progress. The idea that NMDAR signaling is limited to CNS has been challenged in the past two decades. A large body of evidence suggests that NMDAR is expressed in cancer cells outside the CNS and can respond to the autocrine/paracrine release of glutamate. In this review, we survey research on NMDAR signaling and regulation in neurons that can help illuminate its role in tumor biology. Finally, we will discuss existing data on the role of the glutamine/glutamate metabolism, the anticancer action of NMDAR antagonists in experimental models, NMDAR synaptic signaling in tumors, and clinical evidence in human cancer.

Role of Metabolism and Metabolic Pathways in Prostate Cancer

Prostate cancer (PCa) is the common cause of death in men. The pathophysiological factors contributing to PCa are not well known. PCa cells gain a protective mechanism via abnormal lipid signaling and metabolism. PCa cells modify their metabolism in response to an excessive intake of nutrients to facilitate advancement. Metabolic syndrome (MetS) is inextricably linked to the carcinogenic progression of PCa, which heightens the severity of the disease. It is hypothesized that changes in the metabolism of the mitochondria contribute to the onset of PCa. The studies of particular alterations in the progress of PCa are best accomplished by examining the metabolome of prostate tissue. Due to the inconsistent findings written initially, additional epidemiological research is required to identify whether or not MetS is an aspect of PCa. There is a correlation between several risk factors and the progression of PCa, one of which is MetS. The metabolic symbiosis between PCa cells and the tumor milieu and how this type of crosstalk may aid in the development of PCa is portrayed in this work. This review focuses on in-depth analysis and evaluation of the metabolic changes that occur within PCa, and also aims to assess the effect of metabolic abnormalities on the aggressiveness status and metabolism of PCa.

Metabolic reservoir cycles in cancer

Cancer cells possess various biological processes to ensure survival and proliferation even under unfavorable conditions such as hypoxia, nutrient deprivation, and oxidative stress. One of the defining hallmarks of cancer cells is their ability to reprogram their metabolism to suit their needs. Building on over a decade of research in the field of cancer metabolism, numerous unique metabolic capabilities are still being discovered in the present day. One recent discovery in the field of cancer metabolism that was hitherto unexpected is the ability of cancer cells to store vital metabolites in forms that can be readily converted to glucose and glutamine for later use. We called these forms "metabolic reservoirs." While many studies have been conducted on storage molecules such as glycogen, triglyceride, and phosphocreatine (PCr), few have explored the concept of "metabolic reservoirs" for cancer as a whole. In this review, we will provide an overview of this concept, the previously known reservoirs including glycogen, triglyceride, and PCr, and the new discoveries made including the newly discovered reservoirs such as N-acetyl-aspartyl-glutamate (NAAG), lactate, and γ- aminobutyric acid (GABA). We will also discuss whether disrupting these reservoir cycles may be a new avenue for cancer treatment.

Metabolic changes during prostate cancer development and progression

Metabolic reprogramming has been recognised as a hallmark in solid tumours. Malignant modification of the tumour's bioenergetics provides energy for tumour growth and progression. Otto Warburg first reported these metabolic and biochemical changes in 1927. In prostate cancer (PCa) epithelial cells, the tumour metabolism also changes during development and progress. These alterations are partly driven by the androgen receptor, the key regulator in PCa development, progress, and survival. In contrast to other epithelial cells of different entities, glycolytic metabolism in prostate cells sustains physiological citrate secretion in the normal prostatic epithelium. In the early stages of PCa, citrate is utilised to power oxidative phosphorylation and fuel lipogenesis, enabling tumour growth and progression. In advanced and incurable castration-resistant PCa, a metabolic shift towards choline, amino acid, and glycolytic metabolism fueling tumour growth and progression has been described. Therefore, even if the metabolic changes are not fully understood, the altered metabolism during tumour progression may provide opportunities for novel therapeutic strategies, especially in advanced PCa stages. This review focuses on the main differences in PCa's metabolism during tumourigenesis and progression highlighting glutamine's role in PCa.

A Novel Small-Molecule Inhibitor of SREBP-1 Based on Natural Product Monomers Upregulates the Sensitivity of Lung Squamous Cell Carcinoma Cells to Antitumor Drugs

The transcription factor, sterol regulatory element binding protein 1 (SREBP-1), plays important roles in modulating the proliferation, metastasis, or resistance to antitumor agents by promoting cellular lipid metabolism and related cellular glucose-uptake/Warburg Effect. However, the underlying mechanism of SREBP-1 regulating the proliferation or drug-resistance in lung squamous cell carcinoma (LUSC) and the therapeutic strategies targeted to SREBP-1 in LUSC remain unclear. In this study, SREBP-1 was highly expressed in LUSC tissues, compared with the paired non-tumor tissues (the para-tumor tissues). A novel small-molecule inhibitor of SREBP-1, MSI-1 (Ma’s inhibitor of SREBP-1), based on natural product monomers, was identified by screening the database of natural products. Treatment with MSI-1 suppressed the activation of SREBP-1-related pathways and the Warburg effect of LUSC cells, as indicated by decreased glucose uptake or glycolysis. Moreover, treatment of MSI-1 enhanced the sensitivity of LUSC cells to antitumor agents. The specificity of MSI-1 on SREBP-1 was confirmed by molecular docking and point-mutation of SPEBP-1. Therefore, MSI-1 improved our understanding of SREBP-1 and provided additional options for the treatment of LUSC.

Targeting Ribosome Biogenesis in Cancer: Lessons Learned and Way Forward

Simple Summary

Cells need to produce ribosomes to sustain continuous proliferation and expand in numbers, a feature that is even more prominent in uncontrollably proliferating cancer cells. Certain cancer cell types are expected to depend more on ribosome biogenesis based on their genetic background, and this potential vulnerability can be exploited in designing effective, targeted cancer therapies. This review provides information on anti-cancer molecules that target the ribosome biogenesis machinery and indicates avenues for future research.

Abstract

Rapid growth and unrestrained proliferation is a hallmark of many cancers. To accomplish this, cancer cells re-wire and increase their biosynthetic and metabolic activities, including ribosome biogenesis (RiBi), a complex, highly energy-consuming process. Several chemotherapeutic agents used in the clinic impair this process by interfering with the transcription of ribosomal RNA (rRNA) in the nucleolus through the blockade of RNA polymerase I or by limiting the nucleotide building blocks of RNA, thereby ultimately preventing the synthesis of new ribosomes. Perturbations in RiBi activate nucleolar stress response pathways, including those controlled by p53. While compounds such as actinomycin D and oxaliplatin effectively disrupt RiBi, there is an ongoing effort to improve the specificity further and find new potent RiBi-targeting compounds with improved pharmacological characteristics. A few recently identified inhibitors have also become popular as research tools, facilitating our advances in understanding RiBi. Here we provide a comprehensive overview of the various compounds targeting RiBi, their mechanism of action, and potential use in cancer therapy. We discuss screening strategies, drug repurposing, and common problems with compound specificity and mechanisms of action. Finally, emerging paths to discovery and avenues for the development of potential biomarkers predictive of therapeutic outcomes across cancer subtypes are also presented.

Comment on 'Long noncoding RNA UCA1 promotes glutamine-driven anaplerosis of bladder cancer by interacting with hnRNP I/L to upregulate GPT2 expression' by Chen et al.'"

Bladder cancer is prevalent cancer worldwide with poor outcomes for patients with high-grade disease. Emerging evidence shows that alteration of metabolic status drives tumorigenesis in bladder cancer. As long noncoding RNA urothelial cancer associated 1 (UCA1) is known to play an essential role in cancer metabolisms, such as glycolysis and glutaminolysis. Chen et al. report the novel function of UCA1 in glutamine metabolism through interacting with heterogeneous nuclear ribonucleoproteins (hnRNPs) I and L (hnRNP I/L). This study reveals that UCA1 promotes glutamic pyruvate transaminase 2 (GPT2) expression at the transcription level in mechanistic studies. Inhibition of either UCA1, hnRNPI/L, or GPT2 significantly reduces bladder cancer tumor growth in the mice model. This work explores a new mechanism for glutamine metabolism and the novel therapeutic target of the UCA1-hnRNPI/L-GPT2 axis across malignancies.

Glutamine Imaging: A New Avenue for Glioma Management

The glutamine pathway is emerging as an important marker of cancer prognosis and a target for new treatments. In gliomas, the most common type of brain tumors, metabolic reprogramming leads to abnormal consumption of glutamine as an energy source, and increased glutamine concentrations are associated with treatment resistance and proliferation. A key challenge in the development of glutamine-based biomarkers and therapies is the limited number of in vivo tools to noninvasively assess local glutamine metabolism and monitor its changes. In this review, we describe the importance of glutamine metabolism in gliomas and review the current landscape of translational and emerging imaging techniques to measure glutamine in the brain. These techniques include MRS, PET, SPECT, and preclinical methods such as fluorescence and mass spectrometry imaging. Finally, we discuss the roadblocks that must be overcome before incorporating glutamine into a personalized approach for glioma management.

Nuclear Receptor-Mediated Metabolic Reprogramming and the Impact on HR+ Breast Cancer

Simple Summary

Breast cancer is the most commonly diagnosed and second leading cause of cancer-related deaths in women in the United States, with hormone receptor positive (HR+) tumors representing more than two-thirds of new cases. Recent evidence has indicated that dysregulation of multiple metabolic programs, which can be driven through nuclear receptor activity, is essential for tumor genesis, progression, therapeutic resistance and metastasis. This study will review the current advances in our understanding of the impact and implication of altered metabolic processes driven by nuclear receptors, including hormone-dependent signaling, on HR+ breast cancer.

Abstract

Metabolic reprogramming enables cancer cells to adapt to the changing microenvironment in order to maintain metabolic energy and to provide the necessary biological macromolecules required for cell growth and tumor progression. While changes in tumor metabolism have been long recognized as a hallmark of cancer, recent advances have begun to delineate the mechanisms that modulate metabolic pathways and the consequence of altered signaling on tumorigenesis. This is particularly evident in hormone receptor positive (HR+) breast cancers which account for approximately 70% of breast cancer cases. Emerging evidence indicates that HR+ breast tumors are dependent on multiple metabolic processes for tumor progression, metastasis, and therapeutic resistance and that changes in metabolic programs are driven, in part, by a number of key nuclear receptors including hormone-dependent signaling. In this review, we discuss the mechanisms and impact of hormone receptor mediated metabolic reprogramming on HR+ breast cancer genesis and progression as well as the therapeutic implications of these metabolic processes in this disease.

The Heterogeneity of Liver Cancer Metabolism

Primary liver cancer is the fourth leading cause of cancer death around the world. Histologically, it can be divided into two major groups, hepatocellular carcinoma (75% of all liver cancer) and intrahepatic cholangiocarcinoma (15% of all liver cancer) [1, 2]. Primary liver cancer usually happens in liver disease or cirrhosis patients [1], and the risk factors for developing HCC depend on the etiology [3] and the country of provenance [1]. There is an urgent need for an accurate diagnostic test given the high proportion of false positives and false negatives for alpha-fetoprotein (AFP), a common HCC biomarker [4]. Due to often being diagnosed in advanced stages, HCCrelated deaths per year have doubled since 1999 [3]. With the use of metabolomics technologies [5], the aberrant metabolism characteristics of cancer tissues can be discovered and exploited for the new biomarkers and new therapies to treat HCC [6, 7].

The Intricate Metabolism of Pancreatic Cancers

Currently, approximately 95% of pancreatic cancers are pancreatic ductal adenocarcinomas (PDAC), which are the most aggressive form and the fourth leading cause of cancer death with extremely poor prognosis [1]. Poor prognosis is primarily attributed to the late diagnosis of the disease when patients are no longer candidates for surgical resection [2]. Cancer cells are dependent on the oncogenes that allow them to proliferate limitlessly. Thus, targeting the expression of known oncogenes in pancreatic cancer has been shown to lead to more effective treatment [3]. This chapter discusses the complexity of metabolic features in pancreatic cancers. In order to comprehend the heterogeneous nature of cancer metabolism fully, we need to take into account the close relationship between cancer metabolism and genetics. Gene expression varies tremendously, not only among different types of cancers but also within the same type of cancer among different patients. Cancer metabolism heterogeneity is often prompted and perpetuated not only by mutations in oncogenes and tumor-suppressor genes but also by the innate diversity of the tumor microenvironment. Much effort has been focused on elucidating the genetic alterations that correlate with disease progression and treatment response [4, 5]. However, the precise mechanisms by which tumor metabolism contributes to cancer growth, survival, mobility, and aggressiveness represent a functional readout of tumor progression (Fig. 1).

Uncovering Metabolic Reservoir Cycles in MYC-Transformed Lymphoma B cells Using Stable Isotope Resolved Metabolomics

The use of metabolomics technologies and stable isotope labeling recently enabled us to discover an unexpected role of N-acetyl-aspartyl-glutamate (NAAG): NAAG is a glutamate reservoir for cancer cells. In the current study, we first found that glucose carbon contributes to the formation of NAAG and its precursors via glycolysis, demonstrating the existence of a glucose-NAAG-glutamate cycle in cancer cells. Second, we found that glucose carbon and, unexpectedly, glutamine carbon contribute to the formation of lactate via glutaminolysis. Importantly, lactate carbon can be incorporated into glucose via gluconeogenesis, demonstrating the existence of a glutamine-lactate-glucose cycle. While a glucose-lactate-glucose cycle was expected, the finding of a glutamine-lactate-glucose cycle was unforeseen. And third, we discovered that glutamine carbon is incorporated into γ-aminobutyric acid (GABA), revealing a glutamate-GABA-succinate cycle. Thus, NAAG, lactate, and GABA can play important roles as storage molecules for glutamate, glucose, and succinate carbon in oncogenic MYC-transformed P493 lymphoma B cells (MYC-ON cells) but not in non-oncogenic MYC-OFF cells. Altogether, examining the isotopic labeling patterns of metabolites derived from labeled ¹³C₆-glucose or ¹³C₅¹⁵N₂-glutamine helped reveal the presence of what we have named "metabolic reservoir cycles" in oncogenic cells.

The Multifaceted Glioblastoma: From Genomic Alterations to Metabolic Adaptations

Glioblastoma multiforme (GBM) develops on glial cells and is the most common as well as the deadliest form of brain cancer. As in other cancers, distinct combinations of genetic alterations in GBM subtypes induce a diversity of metabolic phenotypes, which explains the variability of GBM sensitivity to current therapies targeting its reprogrammed metabolism. Therefore, it is becoming imperative for cancer researchers to account for the temporal and spatial heterogeneity within this cancer type before making generalized conclusions about a particular treatment's efficacy. Standard therapies for GBM have shown little success as the disease is almost always lethal; however, researchers are making progress and learning how to combine therapeutic strategies most effectively. GBMs can be classified initially into two subsets consisting of primary and secondary GBMs, and this categorization stems from cancer development. GBM is the highest grade of gliomas, which includes glioma I (low proliferative potential), glioma II (low proliferative potential with some capacity for infiltration and recurrence), glioma III (evidence of malignancy), and glioma IV (GBM) (malignant with features of necrosis and microvascular proliferation). Secondary GBM develops from a low-grade glioma to an advanced-stage cancer, while primary GBM provides no signs of progression and is identified as an advanced-stage glioma from the onset. The differences in prognosis and histology correlated with each classification are generally negligible, but the demographics of individuals affected and the accompanying genetic/metabolic properties show distinct differentiation [3].

Cancer Stem Cell Metabolism

Cancer stem cells (CSCs), also known as tumorinitiating cells (TICs), are a group of cells found within cancer cells. Like normal stem cells, CSCs can proliferate, engage in self-renewal, and are often implicated in the recurrence of tumors after therapy [1, 2]. The existence of CSCs in various types of cancer has been proven, such as in acute myeloid leukemia (AML) [3], breast [4], pancreatic [5], and lung cancers [6], to name a few. There are two theories regarding the origin of CSCs. First, CSCs may have arisen from normal stem/progenitor cells that experienced changes in their environment or genetic mutations. On the other hand, CSCs may also have originated from differentiated cells that underwent genetic and/or heterotypic modifications [7]. Either way, CSCs reprogram their metabolism in order to support tumorigenesis.

The Intratumoral Heterogeneity of Cancer Metabolism

Cancer is one of the deadliest diseases in the world, causing over half a million deaths a year in the USA alone. Despite recent advances made in the field of cancer biology and the therapies that have been developed [1, 2], it is clear that more advances are necessary for us to classify cancer as curable. The logical question that arises is simple: Why, despite all the technologies and medical innovations of our time, has a complete cure eluded us? This chapter sheds light on one of cancer's most impactful attributes: its heterogeneity and, more specifically, the intratumoral heterogeneity of cancer metabolism. Simply put, what makes cancer one of the deadliest diseases is its ability to change and adapt. Cancer cells' rapid evolution, coupled with their irrepressible ability to divide, gives most of them the advantage over our immune systems. In this chapter, we delve into the complexities of this adaptability and the vital role that metabolism plays in the rise and progression of this heterogeneity.

Diabetes and Cancer: The Epidemiological and Metabolic Associations

Diabetes mellitus, commonly known as diabetes, and cancer are two of the most common diseases plaguing the world today. According to the Centers for Disease Control and Prevention (CDC), there are currently more than 20 million people with diabetes in the United States [1]. According to the International Agency for Research on Cancer (IARC), there were around 18 million people diagnosed with cancer, with approximately ten million deaths globally in 2018 [2]. Given the prevalence and deadliness of diabetes and cancer, these two diseases have long been the focus of many researchers with the goal of improving treatment outcomes. While diabetes and cancer may seem to be two very different diseases at first glance, they share several similarities, especially regarding their metabolic characteristics. This chapter discusses the similarities and relationships between the metabolism of diabetes, especially type 2 diabetes (T2D), and cancer, including their abnormal glucose and amino acid metabolism, the contribution of hyperglycemia to oncogenic mutation, and the contribution of hyperinsulinemia to cancer progression. Investigating the metabolic interplay between diabetes and cancer in an effort to exploit this connection for cancer treatment has the potential to significantly improve clinical efficacy.

Bridging the Metabolic Parallels Between Neurological Diseases and Cancer

Despite the many recent breakthroughs in cancer research, oncology has traditionally been seen as a distinct field from other diseases. Recently, more attention has been paid to repurposing established therapeutic strategies and targets of other diseases towards cancer treatment, with some of these attempts generating promising outcomes [1, 2]. Recent studies using advanced metabolomics technologies [3] have shown evidence of close metabolic similarities between cancer and neurological diseases. These studies have unveiled several metabolic characteristics shared by these two categories of diseases, including metabolism of glutamine, gamma-aminobutyric acid (GABA), and N-acetyl-aspartyl-glutamate (NAAG) [4-6]. The striking metabolic overlap between cancer and neurological diseases sheds light on novel therapeutic strategies for cancer treatment. For example, 2-(phosphonomethyl) pentanedioic acid (2-PMPA), one of the glutamate carboxypeptidase II (GCP II) inhibitors that prevent the conversion of NAAG to glutamate, has been shown to suppress cancer growth [6, 7]. These promising results have led to an increased interest in integrating this metabolic overlap between cancer and neurological diseases into the study of cancer metabolism. The advantages of studying this metabolic overlap include not only drug repurposing but also translating existing knowledge from neurological diseases to the field of cancer research. This chapter discusses the specific overlapping metabolic features between cancer and neurological diseases, focusing on glutamine, GABA, and NAAG metabolisms. Understanding the interconnections between cancer and neurological diseases will guide researchers and clinicians to find more effective cancer treatments.

Metabolic Intersection of Cancer and Cardiovascular Diseases: Opportunities for Cancer Therapy

According to data from the World Health Organization, cardiovascular diseases and cancer are the two leading causes of mortality in the world [1]. Despite the immense effort to study these diseases and the constant innovation in treatment modalities, the number of deaths associated with cardiovascular diseases and cancer is predicted to increase in the coming decades [1]. From 2008 to 2030, due to population growth and population aging in many parts of the world, the number of deaths caused by cancer globally is projected to increase by 45%, corresponding to an annual increase of around four million people [1]. For cardiovascular diseases, this number is six million people [1]. In the United States, treatments for these two diseases are among the most costly and result in a disproportionate impact on low- and middleincome people. As the fight against these fatal diseases continues, it is crucial that we continue our investigation and broaden our understanding of cancer and cardiovascular diseases to innovate our prognostic and treatment approaches. Even though cardiovascular diseases and cancer are usually studied independently [2-12], there are some striking overlaps between their metabolic behaviors and therapeutic targets, suggesting the potential application of cardiovascular disease treatments for cancer therapy. More specifically, both cancer and many cardiovascular diseases have an upregulated glutaminolysis pathway, resulting in low glutamine and high glutamate circulating levels. Similar treatment modalities, such as glutaminase (GLS) inhibition and glutamine supplementation, have been identified to target glutamine metabolism in both cancer and some cardiovascular diseases. Studies have also found similarities in lipid metabolism, specifically fatty acid oxidation (FAO) and synthesis. Pharmacological inhibition of FAO and fatty acid synthesis have proven effective against many cancer types as well as specific cardiovascular conditions. Many of these treatments have been tested in clinical trials, and some have been medically prescribed to patients to treat certain diseases, such as angina pectoris [13, 14]. Other metabolic pathways, such as tryptophan catabolism and pyruvate metabolism, were also dysregulated in both diseases, making them promising treatment targets. Understanding the overlapping traits exhibited by both cancer metabolism and cardiovascular disease metabolism can give us a more holistic view of how important metabolic dysregulation is in the progression of diseases. Using established links between these illnesses, researchers can take advantage of the discoveries from one field and potentially apply them to the other. In this chapter, we highlight some promising therapeutic discoveries that can support our fight against cancer, based on common metabolic traits displayed in both cancer and cardiovascular diseases.

Non-Hodgkin Lymphoma Metabolism

Non-Hodgkin lymphomas (NHLs) are a heterogeneous group of lymphoid neoplasms with different biological characteristics. About 90% of all lymphomas in the United States originate from B lymphocytes, while the remaining originate from T cells [1]. The treatment of NHLs depends on the neoplastic histology and stage of the tumor, which will indicate whether radiotherapy, chemotherapy, or a combination is the best suitable treatment [2]. The American Cancer Society describes the staging of lymphoma as follows: Stage I is lymphoma in a single node or area. Stage II is when that lymphoma has spread to another node or organ tissue. Stage III is when it has spread to lymph nodes on two sides of the diaphragm. Stage IV is when cancer has significantly spread to organs outside the lymph system. Radiation therapy is the traditional therapeutic route for localized follicular and mucosa-associated lymphomas. Chemotherapy is utilized for the treatment of large-cell lymphomas and high-grade lymphomas [2]. However, the treatment of indolent lymphomas remains problematic as the patients often have metastasis, for which no standard approach exists [2].

Targeting Metabolic Cross Talk Between Cancer Cells and Cancer-Associated Fibroblasts

Although cancer has classically been regarded as a genetic disease of uncontrolled cell growth, the importance of the tumor microenvironment (TME) [1, 2] is continuously emphasized by the accumulating evidence that cancer growth is not simply dependent on the cancer cells themselves [3, 4] but also dependent on angiogenesis [5-8], inflammation [9, 10], and the supporting roles of cancer-associated fibroblasts (CAFs) [11-13]. After the discovery that CAFs are able to remodel the tumor matrix within the TME and provide the nutrients and chemicals to promote cancer cell growth [14], many studies have aimed to uncover the cross talk between cancer cells and CAFs. Moreover, a new paradigm in cancer metabolism shows how cancer cells act like "metabolic parasites" to take up the high-energy metabolites, such as lactate, ketone bodies, free fatty acids, and glutamine from supporting cells, including CAFs and cancer-associated adipocytes (CAAs) [15, 16]. This chapter provides an overview of the metabolic coupling between CAFs and cancer cells to further define the therapeutic options to disrupt the CAF-cancer cell interactions.

Metabolic Relationship Between Cancer-Associated Fibroblasts and Cancer Cells

Cancer-associated fibroblasts (CAFs), a major component of the tumor microenvironment (TME), play an important role in cancer initiation, progression, and metastasis. Recent findings have demonstrated that the TME not only provides physical support for cancer cells but also directs cell-to-cell interactions (in this case, the interaction between cancer cells and CAFs). As cancer progresses, the CAFs also coevolve, transitioning from an inactivated state to an activated state. The elucidation and understanding of the interaction between cancer cells and CAFs will pave the way for new cancer therapies [1-3].

The Heterogeneity of Breast Cancer Metabolism

Despite advances in screening, therapy, and surveillance that have improved patient survival rates, breast cancer is still the most commonly diagnosed cancer and the second leading cause of cancer mortality among women [1]. Breast cancer is a highly heterogeneous disease rooted in a genetic basis, influenced by extrinsic stimuli, and reflected in clinical behavior. The diversity of breast cancer hormone receptor status and the expression of surface molecules have guided therapy decisions for decades; however, subtype-specific treatment often yields diverse responses due to varying tumor evolution and malignant potential. Although the mechanisms behind breast cancer heterogeneity is not well understood, available evidence suggests that studying breast cancer metabolism has the potential to provide valuable insights into the causes of these variations as well as viable targets for intervention.

Metabolism of Immune Cells in the Tumor Microenvironment

The tumor microenvironment (TME) is a complex biological structure surrounding tumor cells and includes blood vessels, immune cells, fibroblasts, adipocytes, and extracellular matrix (ECM) [1, 2]. These heterogeneous surrounding structures provide nutrients, metabolites, and signaling molecules to provide a cancer-friendly environment. The metabolic interplay between immune cells and cancer cells in the TME is a key feature not only for understanding tumor biology but also for discovering cancer cells' vulnerability. As cancer immunotherapy to treat cancer patients and the use of metabolomics technologies become more and more common [3], the importance of the interplay between cancer cells and immune cells in the TME is emerging with respect to not only cell-to-cell interactions but also metabolic pathways. This interaction between immune cells and cancer cells is a complex and dynamic process in which immune cells act as a determinant factor of cancer cells' fate and vice versa. In this chapter, we provide an overview of the metabolic interplay between immune cells and cancer cells and discuss the therapeutic opportunities as a result of this interplay in order to define targets for cancer treatment. It is important to understand and identify therapeutic targets that interrupt this cancerpromoting relationship between cancer cells and the surrounding immune cells, allowing for maximum efficacy of immune checkpoint inhibitors as well as other genetic and cellular therapies.

Different Tumor Microenvironments Lead to Different Metabolic Phenotypes

The beginning of the twenty-first century offered new advances in cancer research, including new knowledge about the tumor microenvironment (TME). Because TMEs provide the niches in which cancer cells, fibroblasts, lymphocytes, and immune cells reside, they play a crucial role in cancer cell development, differentiation, survival, and proliferation. Throughout cancer progression, the TME constantly evolves, causing cancer cells to adapt to the new conditions. The heterogeneity of cancer, evidenced by diverse proliferation rates, cellular structures, metabolisms, and gene expressions, presents challenges for cancer treatment despite the advances in research. This chapter discusses how different TMEs lead to specific metabolic adaptations that drive cancer progression.

The Heterogeneity Metabolism of Renal Cell Carcinomas

According to data from the American Cancer Society, cancer is one of the deadliest health problems globally. Annually, renal cell carcinoma (RCC) causes more than 100,000 deaths worldwide [1-4], posing an urgent need to develop effective treatments to increase patient survival outcomes. New therapies are expected to address a major factor contributing to cancer's resistance to standard therapies: oncogenic heterogeneity. Gene expression can vary tremendously among different types of cancers, different patients of the same tumor type, and even within individual tumors; various metabolic phenotypes can emerge, making singletherapy approaches insufficient. Novel strategies targeting the diverse metabolism of cancers aim to overcome this obstacle. Though some have yielded positive results, it remains a challenge to uncover all of the distinct metabolic profiles of RCC. In the quest to overcome this obstacle, the metabolic oriented research focusing on these cancers has offered freshly new perspectives, which are expected to contribute heavily to the development of new treatments.