Glutamate enrichment as new diagnostic opportunity in breast cancer

A critical appraisal of the role of metabolomics in breast cancer research and diagnostics

Breast cancer (BC) remains the most prevalent cancer among women worldwide, despite significant advancements in its prevention and treatment. The escalating incidence of BC globally necessitates continued research into novel diagnostic and therapeutic strategies. Metabolomics, a burgeoning field, offers a comprehensive analysis of all metabolites within a cell, tissue, system, or organism, providing crucial insights into the dynamic changes occurring during cancer development and progression. This review focuses on the metabolic alterations associated with BC, highlighting the potential of metabolomics in identifying biomarkers for early detection, diagnosis, treatment and prognosis. Metabolomics studies have revealed distinct metabolic signatures in BC, including alterations in lipid metabolism, amino acid metabolism, and energy metabolism. These metabolic changes not only support the rapid proliferation of cancer cells but also influence the tumour microenvironment and therapeutic response. Furthermore, metabolomics holds great promise in personalized medicine, facilitating the development of tailored treatment strategies based on an individual's metabolic profile. By providing a holistic view of the metabolic changes in BC, metabolomics has the potential to revolutionize our understanding of the disease and improve patient outcomes.

Replenishment of TCA cycle intermediates and long-noncoding RNAs regulation in breast cancer

The tricarboxylic acid (TCA) cycle is an essential interface that coordinates cellular metabolism and is as a primary route determining the fate of a variety of fuel sources, including glucose, fatty acid and glutamate. The crosstalk of nutrients replenished TCA cycle regulates breast cancer (BC) progression by changing substrate levels-induced epigenetic alterations, especially the methylation, acetylation, succinylation and lactylation. Long non-coding RNAs (lncRNA) have dual roles in inhibiting or promoting energy reprogramming, and so altering the metabolic flux of fuel sources to the TCA cycle, which may regulate epigenetic modifications at the cellular level of BC. This narrative review discussed the central role of the TCA cycle in interconnecting numerous fuels and the induced epigenetic modifications, and the underlying regulatory mechanisms of lncRNAs in BC.

The pan-cancer landscape of glutamate and glutamine metabolism: A comprehensive bioinformatic analysis across 32 solid cancer types

Glutamine metabolism is a hallmark of cancer metabolism, which matters in the progression of the tumor. This synthetic study conducted a large-scale systematic analysis at the pan-cancer level on the glutamate and glutamine metabolism (GGM) across 32 solid tumors from the TCGA database. The glutamine metabolism activity was quantified through a scoring system. This study revealed that the GGM score in tumor tissues was up-regulated in 13 cancer types (BCLA, BRCA, COAD, KICH, KIRP, LUAD, LUSC, PAAD, PRAD, READ, STAD, THYM, UCEC) and down-regulated in 4 cancer types (CHOL, GBM, LIHC, THCA), exhibiting tissue specificity. The mRNA expression levels of glutamine metabolism-related genes were relatively high, and GLUL exhibited the highest expression level. The expression levels were up-regulated with copy number amplification. ALDH18A1, PYCR1, and PYCR2 show a significant upregulation in protein levels in cancer tissues compared to normal tissues, making them potential pan-cancer therapeutic targets. For the TME related to glutamine metabolism, the GGM score exhibited significant immune and stromal environment inhibitory effects in all involved tumors. Up-regulated GGM score indicated the widespread promotion of drug resistance at the pan-cancer level. GGM score and glutamine metabolism-related genes signature tended to be risk factors for the overall survival of cancer patients.

Redox and metabolic reprogramming in breast cancer and cancer-associated adipose tissue

Redox and metabolic processes are tightly coupled in both physiological and pathological conditions. In cancer, their integration occurs at multiple levels and is characterized by synchronized reprogramming both in the tumor tissue and its specific but heterogeneous microenvironment. In breast cancer, the principal microenvironment is the cancer-associated adipose tissue (CAAT). Understanding how the redox-metabolic reprogramming becomes coordinated in human breast cancer is imperative both for cancer prevention and for the establishment of new therapeutic approaches. This review aims to provide an overview of the current knowledge of the redox profiles and regulation of intermediary metabolism in breast cancer while considering the tumor and CAAT of breast cancer as a unique Warburg's pseudo-organ. As cancer is now recognized as a systemic metabolic disease, we have paid particular attention to the cell-specific redox-metabolic reprogramming and the roles of estrogen receptors and circadian rhythms, as well as their crosstalk in the development, growth, progression, and prognosis of breast cancer.

Fluorescent-Based Neurotransmitter Sensors: Present and Future Perspectives

Neurotransmitters (NTs) are endogenous low-molecular-weight chemical compounds that transmit synaptic signals in the central nervous system. These NTs play a crucial role in facilitating signal communication, motor control, and processes related to memory and learning. Abnormalities in the levels of NTs lead to chronic mental health disorders and heart diseases. Therefore, detecting imbalances in the levels of NTs is important for diagnosing early stages of diseases associated with NTs. Sensing technologies detect NTs rapidly, specifically, and selectively, overcoming the limitations of conventional diagnostic methods. In this review, we focus on the fluorescence-based biosensors that use nanomaterials such as metal clusters, carbon dots, and quantum dots. Additionally, we review biomaterial-based, including aptamer- and enzyme-based, and genetically encoded biosensors. Furthermore, we elaborate on the fluorescence mechanisms, including fluorescence resonance energy transfer, photon-induced electron transfer, intramolecular charge transfer, and excited-state intramolecular proton transfer, in the context of their applications for the detection of NTs. We also discuss the significance of NTs in human physiological functions, address the current challenges in designing fluorescence-based biosensors for the detection of NTs, and explore their future development.

Sijunzi Tang improves gefitinib resistance by regulating glutamine metabolism

Lung cancer is a major health concern and significant barrier to human well-being and social development. Although targeted therapy has shown remarkable progress in the treatment of lung cancer, the emergence of drug resistance has limited its clinical efficacy. Sijunzi Tang (SJZ) is a classical Chinese herbal formula known for tonifying qi and nourishing the lungs, has been recognized for its potential in lung cancer management. However, the underlying mechanism of its combined use with anti-cancer drugs remains unclear. Here, we investigated the anti-lung cancer efficacy and underlying mechanisms of the combination of gefitinib and SJZ in gefitinib-resistant human lung adenocarcinoma cells (PC-9/GR). We conducted in vitro and in vivo experiments using histopathology and targeted metabolomics approaches. Our results demonstrated that the combination of SJZ and gefitinib exhibited synergistic effects on tumor growth inhibition in PC-9/GR-bearing nude mice. Notably, the co-administration of SJZ and gefitinib synergistically promoted tumor cell apoptosis, potentially through the regulation of BAX and BCL-2 expression. Immunohistochemistry and western blot analysis found down-regulation of GLS, GS, and SLC1A5 expression in the co-administration group compared to the control and the individual treatment groups. Targeted metabolomics revealed significant alterations in the plasma glutamine metabolic markers glutamine, alanine, succinate, glutamate, and pyruvate. Of the glutamine metabolism markers measured in tumor tissues, glutamine and pyruvate demonstrated significant differences across the treatment groups. These findings suggest that administration of SJZ improves gefitinib resistance in the treatment of lung cancer without toxic effects. Moreover, SJZ may affect glutamine metabolism by regulating key targets involved in glutamine metabolism (SLC1A5, GLS, and GS) and modulating the levels of related metabolic markers, ultimately reducing gefitinib resistance.

The Role of Amino Acids in the Diagnosis, Risk Assessment, and Treatment of Breast Cancer: A Review

This review summarizes the role of amino acids in the diagnosis, risk assessment, imaging, and treatment of breast cancer. It was shown that the content of individual amino acids changes in breast cancer by an average of 10-15% compared with healthy controls. For some amino acids (Thr, Arg, Met, and Ser), an increase in concentration is more often observed in breast cancer, and for others, a decrease is observed (Asp, Pro, Trp, and His). The accuracy of diagnostics using individual amino acids is low and increases when a number of amino acids are combined with each other or with other metabolites. Gln/Glu, Asp, Arg, Leu/Ile, Lys, and Orn have the greatest significance in assessing the risk of breast cancer. The variability in the amino acid composition of biological fluids was shown to depend on the breast cancer phenotype, as well as the age, race, and menopausal status of patients. In general, the analysis of changes in the amino acid metabolism in breast cancer is a promising strategy not only for diagnosis, but also for developing new therapeutic agents, monitoring the treatment process, correcting complications after treatment, and evaluating survival rates.

An omics data analysis method based on feature linear relationship and graph convolutional network

Biological networks are known to be highly modular, and the dysfunction of network modules may cause diseases. Defining the key modules from the omics data and establishing the classification model is helpful in promoting the research of disease diagnosis and prognosis. However, for applying modules in downstream analysis such as disease states discrimination, most methods only utilize the node information, and ignore the node interactions or topological information, which may lead to false positives and limit the model performance. In this study, we propose an omics data analysis method based on feature linear relationship and graph convolutional network (LCNet). In LCNet, we adopt a way of applying the difference of feature linear relationships during disease development to characterize physiological and pathological changes and construct the differential linear relation network, which is simple and interpretable from the perspective of feature linear relationship. A greedy strategy is developed for searching the highly interactive modules with a strong discrimination ability. To fully utilize the information of the detected modules, the personalized sub-graphs for each sample based on the modules are defined, and the graph convolutional network (GCN) classifiers are trained to predict the sample labels. The experimental results on public datasets show the superiority of LCNet in classification performance. For Breast Cancer metabolic data, the identified metabolites by LCNet involve important pathways. Thus, LCNet can identify the module biomarkers by feature linear relationship and a greedy strategy, and label samples by personalized sub-graphs and GCN. It provides a new manner of utilizing node (molecule) information and topological information in the defined modules for better disease classification.

GLS as a diagnostic biomarker in breast cancer: in-silico, in-situ, and in-vitro insights

Background

Recently, a novel programmed cell death mechanism, Cuproptosis, has been discovered and found to play an important role in the development and progression of diverse tumors. In the present study, we comprehensively investigated the core gene of this mechanism, GLS, in breast cancer.

Materials and methods

Bulk RNA sequencing data were curated from the TCGA repository to investigate the aberrant expression of GLS over diverse cancer types. Then, we examined its efficacy as a diagnostic biomarker in breast cancer by Area Under Curve (AUC) of the Receiver Operative Characteristic (ROC) curve. Furthermore, by applying siRNA technique, we knocked down the GLS expression level in cancerous cell lines, measuring the corresponding effects on cell proliferation and metastasis. Afterward, we explored the potential implications of GLS expression in the tumor immune microenvironment quantitatively by using several R packages and algorithms, including ESTIMATE, CIBERSORT, etc.

Results

Pan-cancer analysis suggested that GLS was aberrantly over-expressed in many cancer types, with breast cancer being typical. More in-depth analyses revealed the expression of GLS exerted a high ROC-AUC value in breast cancer diagnosis. Through the knock-down of GLS expression, it was found that GLS expression was strongly relevant to the growth and metastasis of tumor. Furthermore, it was also found to be correlated with the immune tumor microenvironment.

Conclusion

We highlighted that GLS expression might be applicable as a diagnostic biomarker in breast cancer and possess significant implications in the growth and metastasis of tumor and the immune tumor microenvironment, sharing new insights into ontological and personalized medicine.

The tumor-nerve circuit in breast cancer

It is well established that innervation is one of the updated hallmarks of cancer and that psychological stress promotes the initiation and progression of cancer. The breast tumor environment includes not only fibroblasts, adipocytes, endothelial cells, and lymphocytes but also neurons, which is increasingly discovered important in breast cancer progression. Peripheral nerves, especially sympathetic, parasympathetic, and sensory nerves, have been reported to play important but different roles in breast cancer. However, their roles in the breast cancer progression and treatment are still controversial. In addition, the brain is one of the favorite sites of breast cancer metastasis. In this review, we first summarize the innervation of breast cancer and its mechanism in regulating cancer growth and metastasis. Next, we summarize the neural-related molecular markers in breast cancer diagnosis and treatment. In addition, we review drugs and emerging technologies used to block the interactions between nerves and breast cancer. Finally, we discuss future research directions in this field. In conclusion, the further research in breast cancer and its interactions with innervated neurons or neurotransmitters is promising in the clinical management of breast cancer.

Targeting Mitochondria with ClpP Agonists as a Novel Therapeutic Opportunity in Breast Cancer

Breast cancer is the most frequently diagnosed malignancy worldwide and the leading cause of cancer mortality in women. Despite the recent development of new therapeutics including targeted therapies and immunotherapy, triple-negative breast cancer remains an aggressive form of breast cancer, and thus improved treatments are needed. In recent decades, it has become increasingly clear that breast cancers harbor metabolic plasticity that is controlled by mitochondria. A myriad of studies provide evidence that mitochondria are essential to breast cancer progression. Mitochondria in breast cancers are widely reprogrammed to enhance energy production and biosynthesis of macromolecules required for tumor growth. In this review, we will discuss the current understanding of mitochondrial roles in breast cancers and elucidate why mitochondria are a rational therapeutic target. We will then outline the status of the use of mitochondria-targeting drugs in breast cancers, and highlight ClpP agonists as emerging mitochondria-targeting drugs with a unique mechanism of action. We also illustrate possible drug combination strategies and challenges in the future breast cancer clinic.

Serum nuclear magnetic resonance metabolomics analysis of human metastatic colorectal cancer: Biomarkers and pathway analysis

We describe the use of nuclear magnetic resonance metabolomics to analyze blood serum samples from healthy individuals (n = 26) and those with metastatic colorectal cancer (CRC; n = 57). The assessment, employing both linear and nonlinear multivariate data analysis techniques, revealed specific metabolite changes associated with metastatic CRC, including increased levels of lactate, glutamate, and pyruvate, and decreased levels of certain amino acids and total fatty acids. Biomarker ratios such as glutamate-to-glutamine and pyruvate-to-alanine were also found to be related to CRC. The study also found that glutamate was linked to progression-free survival and that both glutamate and 3-hydroxybutyrate were risk factors for metastatic CRC. Additionally, gas chromatography coupled to flame-ionization detection was utilized to analyze the fatty acid profile and pathway analysis was performed on the profiled metabolites to understand the metabolic processes involved in CRC. A correlation was also found between the presence of certain metabolites in the blood of CRC patients and certain clinical features.

Metabolomic profiling of overnight peritoneal dialysis effluents predicts the peritoneal equilibration test type

This study primarily aimed to evaluate whether peritoneal equilibration test (PET) results can be predicted through the metabolomic analysis of overnight peritoneal dialysis (PD) effluents. From a total of 125 patients, overnight PD effluents on the day of the first PET after PD initiation were analyzed. A modified 4.25% dextrose PET was performed, and the PET type was categorized according to the dialysate-to-plasma creatinine ratio at the 4-h dwell time during the PET as follows: high, high average, low average, or low transporter. Nuclear magnetic resonance (NMR)-based metabolomics was used to analyze the effluents and identify the metabolites. The predictive performances derived from the orthogonal projection to latent structure discriminant analysis (OPLS-DA) modeling of the NMR spectrum were estimated by calculating the area under the curve (AUC) using receiver operating characteristic curve analysis. The OPLS-DA score plot indicated significant metabolite differences between high and low PET types. The relative concentrations of alanine and creatinine were greater in the high transporter type than in the low transporter type. The relative concentrations of glucose and lactate were greater in the low transporter type than in the high transporter type. The AUC of a composite of four metabolites was 0.975 in distinguish between high and low PET types. Measured PET results correlated well with the total NMR metabolic profile of overnight PD effluents.

Nonenzymatic Electrochemical Glutamate Sensor Using Copper Oxide Nanomaterials and Multiwall Carbon Nanotubes

Glutamate is an important neurotransmitter due to its critical role in physiological and pathological processes. While enzymatic electrochemical sensors can selectively detect glutamate, enzymes cause instability of the sensors, thus necessitating the development of enzyme-free glutamate sensors. In this paper, we developed an ultrahigh sensitive nonenzymatic electrochemical glutamate sensor by synthesizing copper oxide (CuO) nanostructures and physically mixing them with multiwall carbon nanotubes (MWCNTs) onto a screen-printed carbon electrode. We comprehensively investigated the sensing mechanism of glutamate; the optimized sensor showed irreversible oxidation of glutamate involving one electron and one proton, and a linear response from 20 μM to 200 μM at pH 7. The limit of detection and sensitivity of the sensor were about 17.5 μM and 8500 μA·mM^-1·cm^-2, respectively. The enhanced sensing performance is attributed to the synergetic electrochemical activities of CuO nanostructures and MWCNTs. The sensor detected glutamate in whole blood and urine and had minimal interference with common interferents, suggesting its potential for healthcare applications.

Energy metabolism pathways in breast cancer progression: The reprogramming, crosstalk, and potential therapeutic targets

Breast cancer (BC) is a malignant tumor that seriously endangers health in women. BC, like other cancers, is accompanied by metabolic reprogramming. Among energy metabolism-related pathways, BC exhibits enhanced glycolysis, tricarboxylic acid (TCA) cycle, pentose phosphate pathway (PPP), glutamate metabolism, and fatty acid metabolism activities. These pathways facilitate the proliferation, growth and migration of BC cells. The progression of BC is closely related to the alterations in the activity or expression level of several metabolic enzymes, which are regulated by the intrinsic factors such as the key signaling and transcription factors. The metabolic reprogramming in the progression of BC is attributed to the aberrant expression of the signaling and transcription factors associated with the energy metabolism pathways. Understanding the metabolic mechanisms underlying the development of BC will provide a druggable potential for BC treatment and drug discovery.

Advances in understanding cancer-associated neurogenesis and its implications on the neuroimmune axis in cancer

Nerves and immunologic mediators play pivotal roles in body homeostasis by interacting with each other through diverse mechanisms. The spread of nerves in the tumor microenvironment increases tumor cell proliferation and disease progression, and this correlates with poor patient outcomes. The effects of sympathetic and parasympathetic nerves on cancer regulation are being investigated. Recent findings demonstrate the possibility of developing therapeutic strategies that target the tumor microenvironment and its components such as immune cells, neurotransmitters, and extracellular vesicles. Therefore, examining and understanding the mechanisms and pathways associated with the sympathetic and parasympathetic nervous systems, neurotransmitters, cancer-derived mediators and their interactions with the immune system in the tumor microenvironment may lead to the development of new cancer treatments. This review discusses the effects of nerve cells, immune cells, and cancer cells have on each other that regulate neurogenesis, cancer progression, and dissemination.

Multi-Omics Analysis Revealed a Significant Alteration of Critical Metabolic Pathways Due to Sorafenib-Resistance in Hep3B Cell Lines

Hepatocellular carcinoma (HCC) is the second prominent cause of cancer-associated death worldwide. Usually, HCC is diagnosed in advanced stages, wherein sorafenib, a multiple target tyrosine kinase inhibitor, is used as the first line of treatment. Unfortunately, resistance to sorafenib is usually encountered within six months of treatment. Therefore, there is a critical need to identify the underlying reasons for drug resistance. In the present study, we investigated the proteomic and metabolomics alterations accompanying sorafenib resistance in hepatocellular carcinoma Hep3B cells by employing ultra-high-performance liquid chromatography quadrupole time of flight mass spectrometry (UHPLC-QTOF-MS). The Bruker Human Metabolome Database (HMDB) library was used to identify the differentially abundant metabolites through MetaboScape 4.0 software (Bruker). For protein annotation and identification, the Uniprot proteome for Homo sapiens (Human) database was utilized through MaxQuant. The results revealed that 27 metabolites and 18 proteins were significantly dysregulated due to sorafenib resistance in Hep3B cells compared to the parental phenotype. D-alanine, L-proline, o-tyrosine, succinic acid and phosphatidylcholine (PC, 16:0/16:0) were among the significantly altered metabolites. Ubiquitin carboxyl-terminal hydrolase isozyme L1, mitochondrial superoxide dismutase, UDP-glucose-6-dehydrogenase, sorbitol dehydrogenase and calpain small subunit 1 were among the significantly altered proteins. The findings revealed that resistant Hep3B cells demonstrated significant alterations in amino acid and nucleotide metabolic pathways, energy production pathways and other pathways related to cancer aggressiveness, such as migration, proliferation and drug-resistance. Joint pathway enrichment analysis unveiled unique pathways, including the antifolate resistance pathway and other important pathways that maintain cancer cells' survival, growth, and proliferation. Collectively, the results identified potential biomarkers for sorafenib-resistant HCC and gave insights into their role in chemotherapeutic drug resistance, cancer initiation, progression and aggressiveness, which may contribute to better prognosis and chemotherapeutic outcomes.

Emerging Roles of Ceramides in Breast Cancer Biology and Therapy

One of the classic hallmarks of cancer is the imbalance between elevated cell proliferation and reduced cell death. Ceramide, a bioactive sphingolipid that can regulate this balance, has long been implicated in cancer. While the effects of ceramide on cell death and therapeutic efficacy are well established, emerging evidence indicates that ceramide turnover to downstream sphingolipids, such as sphingomyelin, hexosylceramides, sphingosine-1-phosphate, and ceramide-1-phosphate, is equally important in driving pro-tumorigenic phenotypes, such as proliferation, survival, migration, stemness, and therapy resistance. The complex and dynamic sphingolipid network has been extensively studied in several cancers, including breast cancer, to find key sphingolipidomic alterations that can be exploited to develop new therapeutic strategies to improve patient outcomes. Here, we review how the current literature shapes our understanding of how ceramide synthesis and turnover are altered in breast cancer and how these changes offer potential strategies to improve breast cancer therapy.

Cellular reprogramming, chemoresistance, and dietary interventions in breast cancer

Breast cancer (BC) diagnosis has been associated with significant risk factors, including family history, late menopause, obesity, poor eating habits, and alcoholism. Despite the advances in the last decades regarding cancer treatment, some obstacles still hinder the effectiveness of therapy. For example, chemotherapy resistance is common in locally advanced or metastatic cancer, reducing treatment options and contributing to mortality. In this review, we provide an overview of BC metabolic changes, including the impact of restrictive diets associated with chemoresistance, the therapeutic potential of the diet on tumor progression, pathways related to metabolic health in oncology, and perspectives on the future in the area of oncological nutrition.

Glutamine addiction promotes glucose oxidation in triple-negative breast cancer

Glutamine is a conditionally essential nutrient for many cancer cells, but it remains unclear how consuming glutamine in excess of growth requirements confers greater fitness to glutamine-addicted cancers. By contrasting two breast cancer subtypes with distinct glutamine dependencies, we show that glutamine-indispensable triple-negative breast cancer (TNBC) cells rely on a non-canonical glutamine-to-glutamate overflow, with glutamine carbon routed once through the TCA cycle. Importantly, this single-pass glutaminolysis increases TCA cycle fluxes and replenishes TCA cycle intermediates in TNBC cells, a process that achieves net oxidation of glucose but not glutamine. The coupling of glucose and glutamine catabolism appears hard-wired via a distinct TNBC gene expression profile biased to strip and then sequester glutamine nitrogen, but hampers the ability of TNBC cells to oxidise glucose when glutamine is limiting. Our results provide a new understanding of how metabolically rigid TNBC cells are sensitive to glutamine deprivation and a way to select vulnerable TNBC subtypes that may be responsive to metabolic-targeted therapies.

Metabolomics of Breast Cancer: A Review

Breast cancer is the most commonly diagnosed cancer in women worldwide. Major advances have been made towards breast cancer prevention and treatment. Unfortunately, the incidence of breast cancer is still increasing globally. Metabolomics is the field of science which studies all the metabolites in a cell, tissue, system, or organism. Metabolomics can provide information on dynamic changes occurring during cancer development and progression. The metabolites identified using cutting-edge metabolomics techniques will result in the identification of biomarkers for the early detection, diagnosis, and treatment of cancers. This review briefly introduces the metabolic changes in cancer with particular focus on breast cancer.

nNav1.5 expression is associated with glutamate level in breast cancer cells

Background

Glutamate and voltage-gated sodium channels, both have been the target of intense investigation for its involvement in carcinogenesis and progression of malignant disease. Breast cancer with increased level of glutamate often metastasize to other organs (especially bone), whilst re-expression of ‘neonatal’ Nav1.5, nNav1.5 in breast cancer is known to promote cell invasion in vitro, metastasis in vivo and positive lymph node metastasis in patients.

Methods

In this study, the role of nNav1.5 in regulating glutamate level in human breast cancer cells was examined using pharmacological approach (VGSCs specific blocker, TTX, glutamate release inhibitor, riluzole and siRNA-nNav1.5). Effect of these agents were evaluated based on endogenous and exogenous glutamate concentration using glutamate fluorometric assay, mRNA expression of nNav1.5 using qPCR and finally, invasion using 3D culture assay.

Results

Endogenous and exogenous glutamate levels were significantly higher in aggressive human breast cancer cells, MDA-MB-231 cells compared to less aggressive human breast cancer cells, MCF-7 and non-cancerous human breast epithelial cells, MCF-10A. Treatment with TTX to MDA-MB-231 cells resulted in significant reduction of endogenous and exogenous glutamate levels corresponded with significant suppression of cell invasion. Subsequently, downregulation of nNav1.5 gene was observed in TTX-treated cells.

Conclusions

An interesting link between nNav1.5 expression and glutamate level in aggressive breast cancer cells was detected and requires further investigation.

How previous treatment changes the metabolomic profile in patients with metastatic breast cancer

Purpose

Metabolites are in the spotlight of attention as promising novel breast cancer biomarkers. However, no study has been conducted concerning changes in the metabolomics profile of metastatic breast cancer patients according to previous therapy.

Methods

We performed a retrospective, single-center, nonrandomized, partially blinded, treatment-based study. Metastatic breast cancer (MBC) patients were enrolled between 03/2010 and 09/2016 at the beginning of a new systemic therapy. The endogenous metabolites in the plasma samples were analyzed using the AbsoluteIDQ^® p180 Kit (Biocrates Life Sciences AG, Innsbruck) a targeted, quality and quantitative-controlled metabolomics approach. The statistical analysis was performed using R package, version 3.3.1. ANOVA was used to statistically assess age differences within groups. Furthermore, we analyzed the CTC status of the patients using the CellSearch^™ assay.

Results

We included 178 patients in our study. Upon dividing the study population according to therapy before study inclusion, we found the following: 4 patients had received no therapy, 165 chemotherapy, and 135 anti-hormonal therapy, 30 with anti-Her2 therapy and 38 had received treatment with bevacizumab. Two metabolites were found to be significantly different, depending on the further therapy of the patients: methionine and serine. Whereas methionine levels were higher in the blood of patients who received an anti-Her2-therapy, serine was lower in patients with endocrine therapy only.

Conclusion

We identified two metabolites for which concentrations differed significantly depending on previous therapies, which could help to choose the next therapy in patients who have already received numerous different treatments.

Metabolic Adaptations in an Endocrine-Related Breast Cancer Mouse Model Unveil Potential Markers of Tumor Response to Hormonal Therapy

Breast cancer (BC) is the most common type of cancer in women and, in most cases, it is hormone-dependent (HD), thus relying on ovarian hormone activation of intracellular receptors to stimulate tumor growth. Endocrine therapy (ET) aimed at preventing hormone receptor activation is the primary treatment strategy, however, about half of the patients, develop resistance in time. This involves the development of hormone independent tumors that initially are ET-responsive (HI), which may subsequently become resistant (HIR). The mechanisms that promote the conversion of HI to HIR tumors are varied and not completely understood. The aim of this work was to characterize the metabolic adaptations accompanying this conversion through the analysis of the polar metabolomes of tumor tissue and non-compromised mammary gland from mice implanted subcutaneously with HD, HI and HIR tumors from a medroxyprogesterone acetate (MPA)-induced BC mouse model. This was carried out by nuclear magnetic resonance (NMR) spectroscopy of tissue polar extracts and data mining through multivariate and univariate statistical analysis. Initial results unveiled marked changes between global tumor profiles and non-compromised mammary gland tissues, as expected. More importantly, specific metabolic signatures were found to accompany progression from HD, through HI and to HIR tumors, impacting on amino acids, nucleotides, membrane percursors and metabolites related to oxidative stress protection mechanisms. For each transition, sets of polar metabolites are advanced as potential markers of progression, including acquisition of resistance to ET. Putative biochemical interpretation of such signatures are proposed and discussed.

Ligand-Gated Ion Channels as Targets for Treatment and Management of Cancers

Ligand-gated ion channels are an ionotropic receptor subtype characterized by the binding of an extracellular ligand, followed by the transient passage of ions through a transmembrane pore. Ligand-gated ion channels are commonly subcategorized into three superfamilies: purinoreceptors, glutamate receptors, and Cys-loop receptors. This classification is based on the differing topographical morphology of the receptors, which in turn confers functional differences. Ligand-gated ion channels have a diverse spatial and temporal expression which implicate them in key cellular processes. Given that the transcellular electrochemical gradient is finely tuned in eukaryotic cells, any disruption in this homeostasis can contribute to aberrancies, including altering the activity of pro-tumorigenic molecular pathways, such as the MAPK/ERK, RAS, and mTOR pathways. Ligand-gated ion channels therefore serve as a potential targetable system for cancer therapeutics. In this review, we analyze the role that each of the three ligand-gated ion channel superfamilies has concerning tumor proliferation and as a target for the treatment of cancer symptomatology.

A micropeptide XBP1SBM encoded by lncRNA promotes angiogenesis and metastasis of TNBC via XBP1s pathway

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer (BC) with a poor prognosis. To date, the mechanism of TNBC's aggressive phenotype is still unclear. Based on metabolome analysis, we found that glutamine (Gln) metabolism plays a key role in the difference between TNBC and non-TNBC. We identified a 21-amino-acid survival-associated micropeptide XBP1SBM, encoded by the lncRNA MLLT4-AS1, which was upregulated in TNBC tissues and Gln-deprived TNBC cell lines. We showed that XBP1SBM expression was upregulated by Gln-deprivation-induced XBP1s transcriptional promotion, and in turn retained XBP1s in the nuclear to enhance the expression of VEGF. Using human endothelial cells, mouse xenograft models and mouse spontaneous BC models, we found that XBP1SBM improved Gln levels and promoted angiogenesis and metastasis in TNBC. Our study showed that a TNBC-specific nutrient deficiency adaption results in aggressive TNBC, and this mechanism provides a novel potential prognostic biomarker and therapeutic target in TNBC.

PINK1 drives production of mtDNA-containing extracellular vesicles to promote invasiveness

The cystine-glutamate antiporter, xCT, supports a glutathione synthesis program enabling cancer cells to cope with metabolically stressful microenvironments. Up-regulated xCT, in combination with glutaminolysis, leads to increased extracellular glutamate, which promotes invasive behavior by activating metabotropic glutamate receptor 3 (mGluR3). Here we show that activation of mGluR3 in breast cancer cells activates Rab27-dependent release of extracellular vesicles (EVs), which can transfer invasive characteristics to "recipient" tumor cells. These EVs contain mitochondrial DNA (mtDNA), which is packaged via a PINK1-dependent mechanism. We highlight mtDNA as a key EV cargo necessary and sufficient for intercellular transfer of invasive behavior by activating Toll-like receptor 9 in recipient cells, and this involves increased endosomal trafficking of pro-invasive receptors. We propose that an EV-mediated mechanism, through which altered cellular metabolism in one cell influences endosomal trafficking in other cells, is key to generation and dissemination of pro-invasive microenvironments during mammary carcinoma progression.

Breast Cancer Cell Subtypes Display Different Metabolic Phenotypes That Correlate with Their Clinical Classification

Simple Summary

Recent studies on cancer cell metabolism have achieved notable breakthroughs that have led to a new scientific paradigm. How cancer cell metabolic reprogramming is orchestrated and the decisive role of this reprogramming in the oncogenic process and tumor adaptative evolution has been characterized at the molecular level. Despite this knowledge, it is essential to understand how cancer cells can metabolically respond as a living whole to ensure their survival and adaptation potential. In this work, we investigated whether different cancers and different subtypes display different metabolic phenotypes with a focus on breast cancer cell models representative of each clinical subtype. The potential results might have significant translational implications for diagnostic, prognostic and therapeutic applications.

Abstract

Metabolic reprogramming of cancer cells represents an orchestrated network of evolving molecular and functional adaptations during oncogenic progression. In particular, how metabolic reprogramming is orchestrated in breast cancer and its decisive role in the oncogenic process and tumor evolving adaptations are well consolidated at the molecular level. Nevertheless, potential correlations between functional metabolic features and breast cancer clinical classification still represent issues that have not been fully studied to date. Accordingly, we aimed to investigate whether breast cancer cell models representative of each clinical subtype might display different metabolic phenotypes that correlate with current clinical classifications. In the present work, functional metabolic profiling was performed for breast cancer cell models representative of each clinical subtype based on the combination of enzyme inhibitors for key metabolic pathways, and isotope-labeled tracing dynamic analysis. The results indicated the main metabolic phenotypes, so-called ‘metabophenotypes’, in terms of their dependency on glycolytic metabolism or their reliance on mitochondrial oxidative metabolism. The results showed that breast cancer cell subtypes display different metabophenotypes. Importantly, these metabophenotypes are clearly correlated with the current clinical classifications.

Prognostic value of glutaminase 1 in breast cancer depends on H3K27me3 expression and menopausal status

Glutaminase 1 (GLS) is a therapeutic target for breast cancer; although GLS inhibitors have been developed, only a few subjects responded well to the therapy. Considering that the expression of histone H3 lysine 27 trimethylation (H3K27me3) and menopausal status was closely linked to GLS, we examined the effects of H3K27me3 and menopausal status on GLS to breast cancer prognosis. Data for 962 women diagnosed with primary invasive breast cancer were analyzed. H3K27me3 and GLS expression in tumors were evaluated with tissue microarrays by immunohistochemistry. Hazard ratios (HRs) and their 95% confidence intervals (CIs) for overall survival and progression-free survival were estimated using Cox regression models. Statistical interaction was assessed on multiplicative scale. There was a beneficial prognostic effect of GLS expression on overall survival for those with low H3K27me3 level (HR = 0.50, 95% CI: 0.20-1.28) but an adverse prognostic effect for those with high H3K27me3 level (HR = 3.90, 95% CI: 1.29-11.78) among premenopausal women, and the statistical interaction was significant (P_interaction = 0.003). Similar pattern was further observed for progression-free survival (HR = 0.44, 95% CI: 0.20-0.95 for low H3K27me3 level, HR = 1.35, 95% CI: 0.74-2.48 for high H3K27me3 level, P_interaction = 0.024). The statistical interaction did not occur among postmenopausal women. Our study showed that the prognostic effects of GLS on breast cancer correlated to the expression level of H3K27me3 and menopausal status, which would help optimize the medication strategies of GLS inhibitors.

SNAP25 Inhibits Glioma Progression by Regulating Synapse Plasticity via GLS-Mediated Glutaminolysis

Background

Neuronal activity regulated by synaptic communication exerts an important role in tumorigenesis and progression in brain tumors. Genes for soluble N-ethylmaleimide-sensitive factor attachment protein receptors (SNAREs) annotated with the function ‘vesicle’ about synaptic connectivity were identified, and synaptosomal-associated protein 25 (SNAP25), one of those proteins, was found to have discrepant expression levels in neuropathies. However, the specific mechanism and prognostic value of SNAP25 during glioma progression remain unclear.

Methods

Using RNA sequencing data from The Cancer Genome Atlas (TCGA) database, the differential synaptosis-related genes between low grade glioma (LGG) and glioblastoma (GBM) were identified as highly correlated. Cox proportional hazards regression analysis and survival analysis were used to differentiate the outcome of low- and high-risk patients, and the Chinese Glioma Genome Atlas (CGGA) cohort was used for validation of the data set. RT-qPCR, western blot, and immunohistochemistry assays were performed to examine the expression level of SNAP25 in glioma cells and samples. Functional assays were performed to identify the effects of SNAP25 knockdown and overexpression on cell viability, migration, and invasion. Liquid chromatography-high resolution mass spectrometry (LC-MS)-based metabolomics approach was presented for identifying crucial metabolic disturbances in glioma cells. In situ mouse xenograft model was used to investigate the role of SNAP25 in vivo. Then, an immunofluorescence assay of the xenograft tissue was applied to evaluate the expression of the neuronal dendron formation marker-Microtubule Associated Protein 2 (MAP2).

Results

SNAP25 was decreased in level of expression in glioma tissues and cell lines, and low-level SNAP25 indicated an unfavorable prognosis of glioma patients. SNAP25 inhibited cell proliferation, migration, invasion and fostered glutamine metabolism of glioma cells, exerting a tumor suppressor role. Overexpressed SNAP25 exerted a lower expression level of MAP2, indicating poor neuronal plasticity and connectivity. SNAP25 could regulate glutaminase (GLS)-mediated glutaminolysis, and GLS knockdown could rescue the anti-tumor effect of SNAP25 in glioma cells. Moreover, upregulated SNAP25 also decreased tumor volume and prolonged the overall survival (OS) of the xenograft mouse.

Conclusion

SNAP25, a tumor suppressor inhibited carcinogenesis of glioma via limiting glutamate metabolism by regulating GLS expression, as well as inhibiting dendritic formation, which could be considered as a novel molecular therapeutic target for glioma.

Metabolomics in cancer research and emerging applications in clinical oncology

Cancer has myriad effects on metabolism that include both rewiring of intracellular metabolism to enable cancer cells to proliferate inappropriately and adapt to the tumor microenvironment, and changes in normal tissue metabolism. With the recognition that fluorodeoxyglucose-positron emission tomography imaging is an important tool for the management of many cancers, other metabolites in biological samples have been in the spotlight for cancer diagnosis, monitoring, and therapy. Metabolomics is the global analysis of small molecule metabolites that like other -omics technologies can provide critical information about the cancer state that are otherwise not apparent. Here, the authors review how cancer and cancer therapies interact with metabolism at the cellular and systemic levels. An overview of metabolomics is provided with a focus on currently available technologies and how they have been applied in the clinical and translational research setting. The authors also discuss how metabolomics could be further leveraged in the future to improve the management of patients with cancer.

Revealing the Potential Application of EC-Synthetic Retinoid Analogues in Anticancer Therapy

(1) Background and Aim: All-trans retinoic acid (ATRA) induces differentiation and inhibits growth of many cancer cells. However, resistance develops rapidly prompting the urgent need for new synthetic and potent derivatives. EC19 and EC23 are two synthetic retinoids with potent stem cell neuro-differentiation activity. Here, these compounds were screened for their in vitro antiproliferative and cytotoxic activity using an array of different cancer cell lines. (2) Methods: MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay, AV/PI (annexin V-fluorescein isothiocyanate (FITC)/propidium iodide (PI)), cell cycle analysis, immunocytochemistry, gene expression analysis, Western blotting, measurement of glutamate and total antioxidant concentrations were recruited. (3) Results: HepG2, Caco-2, and MCF-7 were the most sensitive cell lines; HepG2 (ATRA; 36.2, EC19; 42.2 and EC23; 0.74 µM), Caco-2 (ATRA; 58.0, EC19; 10.8 and EC23; 14.7 µM) and MCF-7 (ATRA; 99.0, EC19; 9.4 and EC23; 5.56 µM). Caco-2 cells were selected for further biochemical investigations. Isobologram analysis revealed the combined synergistic effects with 5-fluorouracil with substantial reduction in IC50. All retinoids induced apoptosis but EC19 had higher potency, with significant cell cycle arrest at subG0-G1, -S and G2/M phases, than ATRA and EC23. Moreover, EC19 reduced cellular metastasis in a transwell invasion assay due to overexpression of E-cadherin, retinoic acid-induced 2 (RAI2) and Werner (WRN) genes. (4) Conclusion: The present study suggests that EC-synthetic retinoids, particularly EC19, can be effective, alone or in combinations, for potential anticancer activity to colorectal cancer. Further in vivo studies are recommended to pave the way for clinical applications.

The Metabolic Mechanisms of Breast Cancer Metastasis

Breast cancer is one of the most common malignancy among women worldwide. Metastasis is mainly responsible for treatment failure and is the cause of most breast cancer deaths. The role of metabolism in the progression and metastasis of breast cancer is gradually being emphasized. However, the regulatory mechanisms that conduce to cancer metastasis by metabolic reprogramming in breast cancer have not been expounded. Breast cancer cells exhibit different metabolic phenotypes depending on their molecular subtypes and metastatic sites. Both intrinsic factors, such as MYC amplification, PIK3CA, and TP53 mutations, and extrinsic factors, such as hypoxia, oxidative stress, and acidosis, contribute to different metabolic reprogramming phenotypes in metastatic breast cancers. Understanding the metabolic mechanisms underlying breast cancer metastasis will provide important clues to develop novel therapeutic approaches for treatment of metastatic breast cancer.

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.

Targeting Cell Metabolism as Cancer Therapy

Significance: Cancer cells exhibit altered metabolic pathways to keep up with biosynthetic and reduction-oxidation needs during tumor proliferation and metastasis. The common induction of metabolic pathways during cancer progression, regardless of cancer histio- or genotype, makes cancer metabolism an attractive target for therapeutic exploitation. Recent Advances: Emerging data suggest that these altered pathways may even result in resistance to anticancer therapies. Identifying specific metabolic dependencies that are unique to cancer cells has proved challenging in this field, limiting the therapeutic window for many candidate drug approaches. Critical Issues: Cancer cells display significant metabolic flexibility in nutrient-limited environments, hampering the longevity of suppressing cancer metabolism through any singular approach. Combinatorial "synthetic lethal" approaches may have a better chance for success and promising strategies are reviewed here. The dynamism of the immune system adds a level of complexity, as various immune populations in the tumor microenvironment often share metabolic pathways with cancer, with successive alterations during immune activation and quiescence. Decoding the reprogramming of metabolic pathways within cancer cells and stem cells, as well as examining metabolic symbiosis between components of the tumor microenvironment, would be essential to further meaningful drug development within the tumor's metabolic ecosystem. Future Directions: In this article, we examine evidence for the therapeutic potential of targeting metabolic alterations in cancer, and we discuss the drawbacks and successes that have stimulated this field.

Effect of Estrogen Receptor Status on Circulatory Immune and Metabolomics Profiles of HER2-Positive Breast Cancer Patients Enrolled for Neoadjuvant Targeted Chemotherapy

HER2-positive breast cancer (BC) represents a heterogeneous cancer disease. In an attempt to identify new stratification models useful for prognosis and therapeutic strategy, we investigated the influence of estrogen receptor (ER) status on the host immune and metabolomics profile of HER2-positive BC patients enrolled for neoadjuvant targeted chemotherapy (NATC). The study enrolled 43 HER2-positive BC patients eligible for NATC based on the trastuzumab-paclitaxel combination. Baseline circulatory cytokines and ¹H NMR plasma metabolomics profiles were investigated. Differences in the immune cytokines and metabolomics profile as a function of the ER status, and their association with clinical outcomes were studied by multivariate and univariate analysis. Baseline metabolomics profiles were found to discriminate HER2-positive ER(+) from ER(−) BC patients. Within the ER(+) group an immune-metabolomics model, based on TNF-α and valine, predicted pathological complete response to NATC with 90.9% accuracy (AUROC = 0.92, p = 0.004). Moreover, metabolomics information integrated with IL-2 and IL-10 cytokine levels were prognostic of relapse with an accuracy of 95.5%. The results indicate that in HER2-positive BC patients the ER status influences the host circulatory immune-metabolomics profile. The baseline immune-metabolomics assessment in combination with ER status could represent an independent stratification tool able to predict NATC response and disease relapse of HER2-positive patients.

Plasma metabolites as possible biomarkers for diagnosis of breast cancer

Metabolomic approaches have been used to identify new diagnostic biomarkers for various types of cancers, including breast cancer. In this study, we aimed to identify potential biomarkers of breast cancer using plasma metabolic profiling. Furthermore, we analyzed whether these biomarkers had relationships with clinicopathological characteristics of breast cancer. Our study used two liquid chromatography-mass spectrometry sets: a discovery set (40 breast cancer patients and 30 healthy controls) and a validation set (30 breast cancer patients and 16 healthy controls). All breast cancer patients were randomly selected from among stage I–III patients who underwent surgery between 2011 and 2016. First, metabolites distinguishing cancer patients from healthy controls were identified in the discovery set. Then, consistent and reproducible metabolites were evaluated in terms of their utility as possible biomarkers of breast cancer. Receiver operating characteristic (ROC) analysis was applied to the discovery set, and ROC cut-off values for the identified metabolites derived therein were applied to the validation set to determine their diagnostic performance. Ultimately, four candidate biomarkers (L-octanoylcarnitine, 5-oxoproline, hypoxanthine, and docosahexaenoic acid) were identified. L-octanoylcarnitine showed the best diagnostic performance, with a 100.0% positive predictive value. Also, L-octanoylcarnitine levels differed according to tumor size and hormone receptor expression. The plasma metabolites identified in this study show potential as biomarkers allowing early diagnosis of breast cancer. However, the diagnostic performance of the metabolites needs to be confirmed in further studies with larger sample sizes.

Glutamate in cancers: from metabolism to signaling

Glutamine and glutamate are major bioenergy substrates for normal and cancer cell growth. Cancer cells need more biofuel than normal tissues for energy supply, anti-oxidation activity and biomass production. Genes related to metabolic chains in many cancers are somehow mutated, which makes cancer cells more glutamate dependent. Meanwhile, glutamate is an excitatory neurotransmitter for conducting signals through binding with different types of receptors in central neuron system. Interestingly, increasing evidences have shown involvement of glutamate signaling, guided through their receptors, in human malignancy. Dysregulation of glutamate transporters, such as excitatory amino acid transporter and cystine/glutamate antiporter system, also generates excessive extracellular glutamate, which in turn, activates glutamate receptors on cancer cells and results in malignant growth. These features make glutamate an attractive target for anti-cancer drug development with some glutamate targeted but blood brain barrier impermeable anti-psychosis drugs under consideration. We discussed the relevant progressions and drawbacks in this field herein.

Accelerated cancer aggressiveness by viral oncomodulation: New targets and newer natural treatments for cancer control and treatment

An infectious etiology for a number of cancers has been entertained for over 100 years and modern studies have confirmed that a number of viruses are linked to cancer induction. While a large number of viruses have been demonstrated in a number of types of cancers, most such findings have been dismissed in the past as opportunistic infections, especially with persistent viruses with high rates of infectivity of the world’s populations. More recent studies have clearly shown that while not definitely causing these cancers, these viruses appear capable of affecting the biology of these tumors in such a way as to make them more aggressive and more resistant to conventional treatments. The term oncomodulatory viruses has been used to describe this phenomenon. A number of recent studies have shown a growing number of ways these oncomodulatory viruses can alter the pathology of these tumors by affecting cell-signaling, cell metabolism, apoptosis mechanisms, cell-cell communication, inflammation, antitumor immunity suppression, and angiogenesis. We are also learning that much of the behavior of tumors depends on cancer stem cells and stromal cells within the tumor microenvironment, which participate in extensive, dynamic crosstalk known to affect tumor behavior. Cancer stem cells have been found to be particularly susceptible to infection by human cytomegalovirus. In a number of studies, it has been shown that while only a select number of cells are actually infected with the virus, numerous viral proteins are released into cancer and stromal cells in the microenvironment and these viral proteins are known to affect tumor behavior and aggressiveness.

Effect of glutaminase inhibition on cancer-induced bone pain

Purpose

The complex nature of cancer-induced bone pain (CIBP) has led to investigation into cancer-targeted therapies. This has involved targeting glutamate release from the tumor, secreted as a byproduct of antioxidant responses and metabolic disruption. Cancer cells undergo many metabolic changes that result in increased glutamine metabolism and subsequently the production of glutamate. Glutaminase (GLS) is the enzyme that mediates the conversion of glutamine to glutamate and has been shown to be upregulated in many cancer types including malignancies of the breast. This enzyme, therefore, represents another potential therapeutic target for CIBP, one that lies upstream of glutamate secretion.

Methods

A recently developed inhibitor of GLS, CB-839, was tested in an animal model of CIBP induced by intrafemoral MDA-MB-231 xenografts. CIBP behaviors were assessed using Dynamic Weight Bearing and Dynamic Plantar Aesthesiometer readings of mechanical hyperalgesia and allodynia.

Results

CB-839 failed to modulate any of the associated nociceptive behaviors induced by intrafemoral MDA-MB-231 tumor growth. Further investigation in vitro revealed the sensitivity of the drug is dependent on the metabolic flexibility of the cell line being tested which can be modulated by cell culture environment.

Conclusion

Adaptation to metabolic disturbances may explain the failure of CB-839 to exhibit any significant effects in vivo and the metabolic flexibility of the cell line tested should be considered for future investigations studying the metabolic effects of glutaminase inhibition.

Prioritization of metabolic genes as novel therapeutic targets in estrogen-receptor negative breast tumors using multi-omics data and text mining

Estrogen-receptor negative (ERneg) breast cancer is an aggressive breast cancer subtype in the need for new therapeutic options. We have analyzed metabolomics, proteomics and transcriptomics data for a cohort of 276 breast tumors (MetaCancer study) and nine public transcriptomics datasets using univariate statistics, meta-analysis, Reactome pathway analysis, biochemical network mapping and text mining of metabolic genes. In the MetaCancer cohort, a total of 29% metabolites, 21% proteins and 33% transcripts were significantly different (raw p <0.05) between ERneg and ERpos breast tumors. In the nine public transcriptomics datasets, on average 23% of all genes were significantly different (raw p <0.05). Specifically, up to 60% of the metabolic genes were significantly different (meta-analysis raw p <0.05) across the transcriptomics datasets. Reactome pathway analysis of all omics showed that energy metabolism, and biosynthesis of nucleotides, amino acids, and lipids were associated with ERneg status. Text mining revealed that several significant metabolic genes and enzymes have been rarely reported to date, including PFKP, GART, PLOD1, ASS1, NUDT12, FAR1, PDE7A, FAHD1, ITPK1, SORD, HACD3, CDS2 and PDSS1. Metabolic processes associated with ERneg tumors were identified by multi-omics integration analysis of metabolomics, proteomics and transcriptomics data. Overall results suggested that TCA anaplerosis, proline biosynthesis, synthesis of complex lipids and mechanisms for recycling substrates were activated in ERneg tumors. Under-reported genes were revealed by text mining which may serve as novel candidates for drug targets in cancer therapies. The workflow presented here can also be used for other tumor types.

Volatomic pattern of breast cancer and cancer-free tissues as a powerful strategy to identify potential biomarkers

Breast cancer (BC), ranked as the fifth amongst all cancers, remains at the top of women's cancers worldwide followed by colorectal, lung, cervix, and stomach cancers. The main handicap of most of the screening/diagnostic methods is based on their low sensitivity and specificity and the invasive behavior of most sampling procedures. The aim of this study was to establish the volatomic pattern of BC and cancer-free (CF) tissues (n = 30) from the same patients, as a powerful tool to identify a set of volatile organic metabolite (VOM) potential BC biomarkers which might be used together or complement with the traditional BC diagnostics strategies, through the integration of chromatographic data, obtained by solid-phase microextraction followed by gas chromatography-mass spectrometry (SPME/GC-qMS), with chemometric tools. A total of four metabolites: limonene, decanoic acid, acetic acid and furfural presented the highest contribution towards discrimination of BC and CF tissues (VIP > 1, p < 0.05). The discrimination efficiency and accuracy of BC tissue metabolites was ascertained by ROC curve analysis that allowed the identification of some metabolites with high sensitivity and specificity. The results obtained with this approach suggest the possibility of identifying endogenous metabolites as a platform to find potential BC biomarkers and pave the way to investigate the related metabolomic pathways in order to improve BC diagnostic tools. Moreover, deeper investigations could unravel novel mechanistic insights into the disease pathophysiology.

Breast Cancer Metabolomics: From Analytical Platforms to Multivariate Data Analysis. A Review

Cancer is a major health issue worldwide for many years and has been increasing significantly. Among the different types of cancer, breast cancer (BC) remains the leading cause of cancer-related deaths in women being a disease caused by a combination of genetic and environmental factors. Nowadays, the available diagnostic tools have aided in the early detection of BC leading to the improvement of survival rates. However, better detection tools for diagnosis and disease monitoring are still required. In this sense, metabolomic NMR, LC-MS and GC-MS-based approaches have gained attention in this field constituting powerful tools for the identification of potential biomarkers in a variety of clinical fields. In this review we will present the current analytical platforms and their applications to identify metabolites with potential for BC biomarkers based on the main advantages and advances in metabolomics research. Additionally, chemometric methods used in metabolomics will be highlighted.

Glutamine to proline conversion is associated with response to glutaminase inhibition in breast cancer

INTRODUCTION

Glutaminase inhibitors target cancer cells by blocking the conversion of glutamine to glutamate, thereby potentially interfering with anaplerosis and synthesis of amino acids and glutathione. The drug CB-839 has shown promising effects in preclinical experiments and is currently undergoing clinical trials in several human malignancies, including triple-negative breast cancer (TNBC). However, response to glutaminase inhibitors is variable and there is a need for identification of predictive response biomarkers. The aim of this study was to determine how glutamine is utilized in two patient-derived xenograft (PDX) models of breast cancer representing luminal-like/ER+ (MAS98.06) and basal-like/triple-negative (MAS98.12) breast cancer and to explore the metabolic effects of CB-839 treatment.

EXPERIMENTAL

MAS98.06 and MAS98.12 PDX mice received CB-839 (200 mg/kg) or drug vehicle two times daily p.o. for up to 28 days (n = 5 per group), and the effect on tumor growth was evaluated. Expression of 60 genes and seven glutaminolysis key enzymes were determined using gene expression microarray analysis and immunohistochemistry (IHC), respectively, in untreated tumors. Uptake and conversion of glutamine were determined in the PDX models using HR MAS MRS after i.v. infusion of [5-¹³C] glutamine when the models had received CB-839 (200 mg/kg) or vehicle for 2 days (n = 5 per group).

RESULTS

Tumor growth measurements showed that CB-839 significantly inhibited tumor growth in MAS98.06 tumors, but not in MAS98.12 tumors. Gene expression and IHC analysis indicated a higher proline synthesis from glutamine in untreated MAS98.06 tumors. This was confirmed by HR MAS MRS of untreated tumors demonstrating that MAS98.06 used glutamine to produce proline, glutamate, and alanine, and MAS98.12 to produce glutamate and lactate. In both models, treatment with CB-839 resulted in accumulation of glutamine. In addition, CB-839 caused depletion of alanine, proline, and glutamate ([1-13C] glutamate) in the MAS98.06 model.

CONCLUSION

Our findings indicate that TNBCs may not be universally sensitive to glutaminase inhibitors. The major difference in the metabolic fate of glutamine between responding MAS98.06 xenografts and non-responding MAS98.12 xenografts is the utilization of glutamine for production of proline. We therefore suggest that addiction to proline synthesis from glutamine is associated with response to CB-839 in breast cancer. The effect of glutaminase inhibition in two breast cancer patient-derived xenograft (PDX) models. ¹³C HR MAS MRS analysis of tumor tissue from CB-839-treated and untreated models receiving ¹³C-labeled glutamine ([5-¹³C] Gln) shows that the glutaminase inhibitor CB-839 is causing an accumulation of glutamine (arrow up) in two PDX models representing luminal-like breast cancer (MAS98.06) and basal-like breast cancer (MAS98.12). In MAS98.06 tumors, CB-839 is in addition causing depletion of proline ([5-¹³C] Pro), alanine ([1-¹³C] Ala), and glutamate ([1-¹³C] Glu), which could explain why CB-839 causes tumor growth inhibition in MAS98.06 tumors, but not in MAS98.12 tumors.

Current Status and Future Prospects of Clinically Exploiting Cancer-specific Metabolism-Why Is Tumor Metabolism Not More Extensively Translated into Clinical Targets and Biomarkers?

Tumor cells exhibit a specialized metabolism supporting their superior ability for rapid proliferation, migration, and apoptotic evasion. It is reasonable to assume that the specific metabolic needs of the tumor cells can offer an array of therapeutic windows as pharmacological disturbance may derail the biochemical mechanisms necessary for maintaining the tumor characteristics, while being less important for normally proliferating cells. In addition, the specialized metabolism may leave a unique metabolic signature which could be used clinically for diagnostic or prognostic purposes. Quantitative global metabolic profiling (metabolomics) has evolved over the last two decades. However, despite the technology’s present ability to measure 1000s of endogenous metabolites in various clinical or biological specimens, there are essentially no examples of metabolomics investigations being translated into actual utility in the cancer clinic. This review investigates the current efforts of using metabolomics as a tool for translation of tumor metabolism into the clinic and further seeks to outline paths for increasing the momentum of using tumor metabolism as a biomarker and drug target opportunity.

Elucidating cancer metabolic plasticity by coupling gene regulation with metabolic pathways

Metabolic plasticity enables cancer cells to switch their metabolism phenotypes between glycolysis and oxidative phosphorylation (OXPHOS) during tumorigenesis and metastasis. However, it is still largely unknown how cancer cells orchestrate gene regulation to balance their glycolysis and OXPHOS activities. Previously, by modeling the gene regulation of cancer metabolism we have reported that cancer cells can acquire a stable hybrid metabolic state in which both glycolysis and OXPHOS can be used. Here, to comprehensively characterize cancer metabolic activity, we establish a theoretical framework by coupling gene regulation with metabolic pathways. Our modeling results demonstrate a direct association between the activities of AMPK and HIF-1, master regulators of OXPHOS and glycolysis, respectively, with the activities of three major metabolic pathways: glucose oxidation, glycolysis, and fatty acid oxidation. Our model further characterizes the hybrid metabolic state and a metabolically inactive state where cells have low activity of both glycolysis and OXPHOS. We verify the model prediction using metabolomics and transcriptomics data from paired tumor and adjacent benign tissue samples from a cohort of breast cancer patients and RNA-sequencing data from The Cancer Genome Atlas. We further validate the model prediction by in vitro studies of aggressive triple-negative breast cancer (TNBC) cells. The experimental results confirm that TNBC cells can maintain a hybrid metabolic phenotype and targeting both glycolysis and OXPHOS is necessary to eliminate their metabolic plasticity. In summary, our work serves as a platform to symmetrically study how tuning gene activity modulates metabolic pathway activity, and vice versa.

Functional Proteomics of Breast Cancer Metabolism Identifies GLUL as Responder during Hypoxic Adaptation

Hypoxia as well as metabolism are central hallmarks of cancer, and hypoxia-inducible factors (HIFs) and metabolic effectors are crucial elements in oxygen-compromised tumor environments. Knowledge of changes in the expression of metabolic proteins in response to HIF function could provide mechanistic insights into adaptation to hypoxic stress, tumorigenesis, and disease progression. We analyzed time-resolved alterations in metabolism-associated protein levels in response to different oxygen potentials across breast cancer cell lines. Effects on the cellular metabolism of both HIF-dependent and -independent processes were analyzed by reverse-phase protein array profiling and a custom statistical model. We revealed a strong induction of glucose transporter 1 (GLUT1) and lactate dehydrogenase A (LDHA) as well as reduced glutamate-ammonia ligase (GLUL) protein levels across all cell lines tested as consistent changes upon hypoxia induction. Low GLUL protein levels were correlated with aggressive molecular subtypes in breast cancer patient data sets and also with hypoxic tumor regions in a xenograft mouse tumor model. Moreover, low GLUL expression was associated with poor survival in breast cancer patients and with high HIF-1α-expressing patient subgroups. Our data reveal time-resolved changes in the regulation of metabolic proteins under oxygen-deprived conditions and elucidate GLUL as a strong responder to HIFs and the hypoxic environment.