Probing the metabolic phenotype of breast cancer cells by multiple tracer stable isotope resolved metabolomics

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.

Determination of fatty acid uptake and desaturase activity in mammalian cells by NMR-based stable isotope tracing

BACKGROUND

Mammalian cells both import exogenous fatty acids and synthesize them de novo. Palmitate, the end product of fatty acid synthase (FASN) is a substrate for stearoyl-CoA desaturases (Δ-9 desaturases) that introduce a single double bond into fatty acyl-CoA substrates such as palmitoyl-CoA and stearoyl-CoA. This process is particularly upregulated in lipogenic tissues and cancer cells. Tracer methodology is needed to determine uptake versus de novo synthesis of lipids and subsequent chain elongation and desaturation. Here we describe an NMR method to determine the uptake of 13C-palmitate from the medium into HCT116 human colorectal cancer cells, and the subsequent desaturation and incorporation into complex lipids.

RESULTS

Exogenous 13C16-palmitate was absorbed from the medium by HCT116 cells and incorporated primarily into complex glycerol lipids. Desaturase activity was determined from the quantification of double bonds in acyl chains, which was greatly reduced by ablation of the major desaturase SCD1.

SIGNIFICANCE

The NMR approach requires minimal sample preparation, is non-destructive, and provides direct information about the level of saturation and incorporation of fatty acids into complex lipids.

Pirfenidone inhibits TGF-β1-induced metabolic reprogramming during epithelial-mesenchymal transition in non-small cell lung cancer

Metastasis is an important contributor to increased mortality rates in non-small cell lung cancer (NSCLC). The TGF-β signalling pathway plays a crucial role in facilitating tumour metastasis through epithelial-mesenchymal transition (EMT). Glycolysis, a key metabolic process, is strongly correlated with NSCLC metastasis. Pirfenidone (PFD) has been shown to safely and effectively inhibit TGF-β1 in patients with lung diseases. Furthermore, TGF-β1 and glycolysis demonstrate an interdependent relationship within the tumour microenvironment. Our previous study demonstrated that PFD effectively inhibited glycolysis in NSCLC cells, prompting further investigation into its potential antitumour effects in this context. Therefore, the present study aims to investigate the potential antitumour effect of PFD in NSCLC and explore the relationship among TGF-β1, glycolysis and EMT through further experimentation. The antitumour effects of PFD were evaluated using five different NSCLC cell lines and a xenograft tumour model. Notably, PFD demonstrated a significant antitumour effect specifically in highly glycolytic H1299 cells. To elucidate the underlying mechanism, we compared the efficacy of PFD after pretreatment with either TGF-β1 or a TGF-β receptor inhibitor (LY2109761). The energy metabolomics analysis of tumour tissue demonstrated that PFD, a chemosensitizing agent, reduced lactate and ATP production, thereby inhibiting glycolysis and exerting synergistic antineoplastic effects. Additionally, PFD combined with cisplatin targeted TGF-β1 to inhibit glycolysis during EMT and enhanced the chemosensitization of A549 and H1299 cells. The magnitude of the anticancer effect exhibited by PFD was intricately linked to its metabolic properties.

E. coli Secretome Metabolically Modulates MDA-MB-231 Breast Cancer Cells' Energy Metabolism

Breast cancer (BC) is commonly diagnosed in women. BC cells are associated with altered metabolism, which is essential to support their energetic requirements, cellular proliferation, and continuous survival. The altered metabolism of BC cells is a result of the genetic abnormalities of BC cells. Risk factors can also enhance it, including age, lifestyle, hormone disturbances, etc. Other unknown BC-promoting risk factors are under scientific investigation. One of these investigated factors is the microbiome. However, whether the breast microbiome found in the BC tissue microenvironment can impact BC cells has not been studied. We hypothesized that E. coli, part of a normal breast microbiome with more presence in BC tissue, secretes metabolic molecules that could alter BC cells' metabolism to maintain their survival. Thus, we directly examined the impact of the E. coli secretome on the metabolism of BC cells in vitro. MDA-MB-231 cells, an in vitro model of aggressive triple-negative BC cells, were treated with the E. coli secretome at different time points, followed by untargeted metabolomics analyses via liquid chromatography-mass spectrometry to identify metabolic alterations in the treated BC cell lines. MDA-MB-231 cells that were not treated were used as controls. Moreover, metabolomic analyses were performed on the E. coli secretome to profile the most significant bacterial metabolites affecting the metabolism of the treated BC cell lines. The metabolomics results revealed about 15 metabolites that potentially have indirect roles in cancer metabolism that were secreted from E. coli in the culture media of MDA-MB-231 cells. The cells treated with the E. coli secretome showed 105 dysregulated cellular metabolites compared to controls. The dysregulated cellular metabolites were involved in the metabolism of fructose and mannose, sphingolipids, amino acids, fatty acids, amino sugar, nucleotide sugar, and pyrimidine, which are vital pathways required for the pathogenesis of BC. Our findings are the first to show that the E. coli secretome modulates the BC cells' energy metabolism, highlighting insights into the possibility of altered metabolic events in BC tissue in the actual BC tissue microenvironment that are potentially induced by the local bacteria. Our study provides metabolic data that could be as a basis for future studies searching for the underlying mechanisms mediated by bacteria and their secretome to alter the metabolism of BC cells.

Quantitative NMR Methods in Metabolomics

Nuclear Magnetic Resonance (NMR) spectroscopy is one of the two major analytical platforms in the field of metabolomics, the other being mass spectrometry (MS). NMR is less sensitive than MS and hence it detects a relatively small number of metabolites. However, NMR exhibits numerous unique characteristics including its high reproducibility and non-destructive nature, its ability to identify unknown metabolites definitively, and its capabilities to obtain absolute concentrations of all detected metabolites, sometimes even without an internal standard. These characteristics outweigh the relatively low sensitivity and resolution of NMR in metabolomics applications. Since biological mixtures are highly complex, increased demand for new methods to improve detection, better identify unknown metabolites, and provide more accurate quantitation continues unabated. Technological and methodological advances to date have helped to improve the resolution and sensitivity and detection of a larger number of metabolite signals. Efforts focused on measuring unknown metabolite signals have resulted in the identification and quantitation of an expanded pool of metabolites including labile metabolites such as cellular redox coenzymes, energy coenzymes, and antioxidants. This chapter describes quantitative NMR methods in metabolomics with an emphasis on recent methodological developments, while highlighting the benefits and challenges of NMR-based metabolomics.

Ultrahigh resolution MS1/MS2-based reconstruction of metabolic networks in mammalian cells reveals changes for selenite and arsenite action

Metabolic networks are complex, intersecting, and composed of numerous enzyme-catalyzed biochemical reactions that transfer various molecular moieties among metabolites. Thus, robust reconstruction of metabolic networks requires metabolite moieties to be tracked, which cannot be readily achieved with mass spectrometry (MS) alone. We previously developed an Ion Chromatography-ultrahigh resolution-MS1/data independent-MS2 method to track the simultaneous incorporation of the heavy isotopes 13C and 15N into the moieties of purine/pyrimidine nucleotides in mammalian cells. Ultrahigh resolution-MS1 resolves and counts multiple tracer atoms in intact metabolites, while data independent-tandem MS (MS2) determines isotopic enrichment in their moieties without concern for the numerous mass isotopologue source ions to be fragmented. Together, they enabled rigorous MS-based reconstruction of metabolic networks at specific enzyme levels. We have expanded this approach to trace the labeled atom fate of [13C6]-glucose in 3D A549 spheroids in response to the anticancer agent selenite and that of [13C5,15N2]-glutamine in 2D BEAS-2B cells in response to arsenite transformation. We deduced altered activities of specific enzymes in the Krebs cycle, pentose phosphate pathway, gluconeogenesis, and UDP-GlcNAc synthesis pathways elicited by the stressors. These metabolic details help elucidate the resistance mechanism of 3D versus 2D A549 cultures to selenite and metabolic reprogramming that can mediate the transformation of BEAS-2B cells by arsenite.

Unsupervised Analysis Based on DCE-MRI Radiomics Features Revealed Three Novel Breast Cancer Subtypes with Distinct Clinical Outcomes and Biological Characteristics

Background: This study aimed to reveal the heterogeneity of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of breast cancer (BC) and identify its prognosis values and molecular characteristics. Methods: Two radiogenomics cohorts (n = 246) were collected and tumor regions were segmented semi-automatically. A total of 174 radiomics features were extracted, and the imaging subtypes were identified and validated by unsupervised analysis. A gene-profile-based classifier was developed to predict the imaging subtypes. The prognostic differences and the biological and microenvironment characteristics of subtypes were uncovered by bioinformatics analysis. Results: Three imaging subtypes were identified and showed high reproducibility. The subtypes differed remarkably in tumor sizes and enhancement patterns, exhibiting significantly different disease-free survival (DFS) or overall survival (OS) in the discovery cohort (p = 0.024) and prognosis datasets (p ranged from <0.0001 to 0.0071). Large sizes and rapidly enhanced tumors usually had the worst outcomes. Associations were found between imaging subtypes and the established subtypes or clinical stages (p ranged from <0.001 to 0.011). Imaging subtypes were distinct in cell cycle and extracellular matrix (ECM)-receptor interaction pathways (false discovery rate, FDR < 0.25) and different in cellular fractions, such as cancer-associated fibroblasts (p < 0.05). Conclusions: The imaging subtypes had different clinical outcomes and biological characteristics, which may serve as potential biomarkers.

Delving into the Heterogeneity of Different Breast Cancer Subtypes and the Prognostic Models Utilizing scRNA-Seq and Bulk RNA-Seq

Background: Breast cancer (BC) is the most common malignancy in women with high heterogeneity. The heterogeneity of cancer cells from different BC subtypes has not been thoroughly characterized and there is still no valid biomarker for predicting the prognosis of BC patients in clinical practice. Methods: Cancer cells were identified by calculating single cell copy number variation using the inferCNV algorithm. SCENIC was utilized to infer gene regulatory networks. CellPhoneDB software was used to analyze the intercellular communications in different cell types. Survival analysis, univariate Cox, least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox analysis were used to construct subtype specific prognostic models. Results: Triple-negative breast cancer (TNBC) has a higher proportion of cancer cells than subtypes of HER2+ BC and luminal BC, and the specifically upregulated genes of the TNBC subtype are associated with antioxidant and chemical stress resistance. Key transcription factors (TFs) of tumor cells for three subtypes varied, and most of the TF-target genes are specifically upregulated in corresponding BC subtypes. The intercellular communications mediated by different receptor–ligand pairs lead to an inflammatory response with different degrees in the three BC subtypes. We establish a prognostic model containing 10 genes (risk genes: ATP6AP1, RNF139, BASP1, ESR1 and TSKU; protective genes: RPL31, PAK1, STARD10, TFPI2 and SIAH2) for luminal BC, seven genes (risk genes: ACTR6 and C2orf76; protective genes: DIO2, DCXR, NDUFA8, SULT1A2 and AQP3) for HER2+ BC, and seven genes (risk genes: HPGD, CDC42 and PGK1; protective genes: SMYD3, LMO4, FABP7 and PRKRA) for TNBC. Three prognostic models can distinguish high-risk patients from low-risk patients and accurately predict patient prognosis. Conclusions: Comparative analysis of the three BC subtypes based on cancer cell heterogeneity in this study will be of great clinical significance for the diagnosis, prognosis and targeted therapy for BC patients.

Methodological Developments for Metabolic NMR Spectroscopy from Cultured Cells to Tissue Extracts: Achievements, Progress and Pitfalls

This is a broad overview and critical review of a particular group of closely related ex vivo and in vitro metabolic NMR spectroscopic methods. The scope of interest comprises studies of cultured cells and excised tissue, either intact or after physicochemical extraction of metabolites. Our detailed discussion includes pitfalls that have led to erroneous statements in the published literature, some of which may cause serious problems in metabolic and biological interpretation of results. To cover a wide range of work from relevant research areas, we consider not only the most recent achievements in the field, but also techniques that proved to be valid and successful in the past, although they may not have generated a very significant number of papers more recently. Thus, this comparative review also aims at providing background information useful for judiciously choosing between the metabolic ex vivo/in vitro NMR methods presented. Finally, the methods of interest are discussed in the context of, and in relation to, other metabolic analysis protocols such as HR-MAS and cell perfusion NMR, as well as the mass spectrometry approach.

Classification and biomarker identification of prostate tissue from TRAMP mice with hyperpolarized 13C-SIRA

Hyperpolarized ¹³C isotope resolved spectroscopy boosts NMR signal intensity, which improves signal detection and allows metabolic fluxes to be analyzed. Such hyperpolarized flux data may offer new approaches to tissue classification and biomarker identification that could be translated in vivo. Here we used hyperpolarized stable isotope resolved analysis (SIRA) to measure metabolite specific ¹³C isotopic enrichments in the central carbon metabolism of mouse prostate. Prostate and tumor tissue samples were acquired from transgenic adenocarcinomas of the mouse prostate (TRAMP) mice. Before euthanasia, mice were injected with [U-¹³C]glucose intraperitoneally (i.p.). Polar metabolite extracts were prepared, and hyperpolarized 1D-¹³C NMR spectra were obtained from normal prostate (n = 19) and cancer tissue (n = 19) samples. Binary classification and feature analysis was performed to make a separation model and to investigate differences between samples originating from normal and cancerous prostate tissue, respectively. Hyperpolarized experiments were carried out according to a standardized protocol, which showed a high repeatability (CV = 15%) and an average linewidth in the 1D-¹³C NMR spectra of 2 ± 0.5 Hz. The resolution of the hyperpolarized 1D-¹³C spectra was high with little signal overlap in the carbonyl region and metabolite identification was easily accomplished. A discrimination with 95% success rate could be made between samples originating from TRAMP mice prostate and tumor tissue based on isotopomers from uniquely identified metabolites. Hyperpolarized ¹³C-SIRA allowed detailed metabolic information to be obtained from tissue specimens. The positional information of ¹³C isotopic enrichments lead to easily interpreted features responsible for high predictive classification of tissue types. This analytical approach has matured, and the robust experimental protocols currently available allow systematic tracking of metabolite flux ex vivo.

Metabolomics-Microbiome Crosstalk in the Breast Cancer Microenvironment

Breast cancer, the most frequent cancer diagnosed among females, is associated with a high mortality rate worldwide. Alterations in the microbiota have been linked with breast cancer development, suggesting the possibility of discovering disease biomarkers. Metabolomics has emerged as an advanced promising analytical approach for profiling metabolic features associated with breast cancer subtypes, disease progression, and response to treatment. The microenvironment compromises non-cancerous cells such as fibroblasts and influences cancer progression with apparent phenotypes. This review discusses the role of metabolomics in studying metabolic dysregulation in breast cancer caused by the effect of the tumor microenvironment on multiple cells such as immune cells, fibroblasts, adipocytes, etc. Breast tumor cells have a unique metabolic profile through the elevation of glycolysis and the tricarboxylic acid cycle metabolism. This metabolic profile is highly sensitive to microbiota activity in the breast tissue microenvironment. Metabolomics shows great potential as a tool for monitoring metabolic dysregulation in tissue and associating the findings with microbiome expression.

The Role of Raman Spectroscopy Within Quantitative Metabolomics

Ninety-four years have passed since the discovery of the Raman effect, and there are currently more than 25 different types of Raman-based techniques. The past two decades have witnessed the blossoming of Raman spectroscopy as a powerful physicochemical technique with broad applications within the life sciences. In this review, we critique the use of Raman spectroscopy as a tool for quantitative metabolomics. We overview recent developments of Raman spectroscopy for identification and quantification of disease biomarkers in liquid biopsies, with a focus on the recent advances within surface-enhanced Raman scattering-based methods. Ultimately, we discuss the applications of imaging modalities based on Raman scattering as label-free methods to study the abundance and distribution of biomolecules in cells and tissues, including mammalian, algal, and bacterial cells.

NMR Methods for Determining Lipid Turnover via Stable Isotope Resolved Metabolomics

Lipids comprise diverse classes of compounds that are important for the structure and properties of membranes, as high-energy fuel sources and as signaling molecules. Therefore, the turnover rates of these varied classes of lipids are fundamental to cellular function. However, their enormous chemical diversity and dynamic range in cells makes detailed analysis very complex. Furthermore, although stable isotope tracers enable the determination of synthesis and degradation of complex lipids, the numbers of distinguishable molecules increase enormously, which exacerbates the problem. Although LC-MS-MS (Liquid Chromatography-Tandem Mass Spectrometry) is the standard for lipidomics, NMR can add value in global lipid analysis and isotopomer distributions of intact lipids. Here, we describe new developments in NMR analysis for assessing global lipid content and isotopic enrichment of mixtures of complex lipids for two cell lines (PC3 and UMUC3) using both 13C6 glucose and 13C5 glutamine tracers.

An Ion Chromatography-Ultrahigh-Resolution-MS1/Data-Independent High-Resolution MS2 Method for Stable Isotope-Resolved Metabolomics Reconstruction of Central Metabolic Networks

The metabolome comprises a complex network of interconnecting enzyme-catalyzed reactions that involve transfers of numerous molecular subunits. Thus, the reconstruction of metabolic networks requires metabolite substructures to be tracked. Subunit tracking can be achieved by tracing stable isotopes through metabolic transformations using NMR and ultrahigh -resolution (UHR)-mass spectrometry (MS). UHR-MS¹ readily resolves and counts isotopic labels in metabolites but requires tandem MS to help identify isotopic enrichment in substructures. However, it is challenging to perform chromatography-based UHR-MS¹ with its long acquisition time, while acquiring MS² data on many coeluting labeled isotopologues for each metabolite. We have developed an ion chromatography (IC)-UHR-MS¹/data-independent(DI)-HR-MS² method to trace the fate of ¹³C atoms from [¹³C₆]-glucose ([¹³C₆]-Glc) in 3D A549 spheroids in response to anticancer selenite and simultaneously ¹³C/¹⁵N atoms from [¹³C₅,¹⁵N₂]-glutamine ([¹³C₅,¹⁵N₂]-Gln) in 2D BEAS-2B cells in response to arsenite transformation. This method retains the complete isotopologue distributions of metabolites via UHR-MS¹ while simultaneously acquiring substructure label information via DI-MS². These details in metabolite labeling patterns greatly facilitate rigorous reconstruction of multiple, intersecting metabolic pathways of central metabolism, which are illustrated here for the purine/pyrimidine nucleotide biosynthesis. The pathways reconstructed based on subunit-level isotopologue analysis further reveal specific enzyme-catalyzed reactions that are impacted by selenite or arsenite treatments.

Comparing Stable Isotope Enrichment by Gas Chromatography with Time-of-Flight, Quadrupole Time-of-Flight, and Quadrupole Mass Spectrometry

Stable isotope tracers are applied for in vivo and in vitro studies to reveal the activity of enzymes and intracellular metabolic pathways. Most often, such tracers are used with gas chromatography coupled to mass spectrometry (GC-MS) owing to its ease of operation and reproducible mass spectral databases. Differences in isotope tracer performance of the classic GC-quadrupole MS instrument and newer time-of-flight instruments are not well studied. Here, we used three commercially available instruments for the analysis of identical samples from a stable isotope labeling study that used [U-13C6] d-glucose to investigate the metabolism of the bacterium Rothia mucilaginosa with respect to 29 amino acids and hydroxyl acids involved in primary metabolism. The prokaryote R. mucilaginosa belongs to the family of Micrococcaceae and is present and metabolically active in the airways and sputum of cystic fibrosis patients. Overall, all three GC-MS instruments (low-resolution GC-SQ MS, low-resolution GC-TOF MS, and high-resolution GC-QTOF MS) can be used to perform stable isotope tracing studies for glycolytic intermediates, tricarboxylic acid (TCA) metabolites, and amino acids, yielding similar biological results, with high-resolution GC-QTOF MS offering additional capabilities to identify the chemical structures of unknown compounds that might show significant isotope enrichments in biological studies.

NMR-Based Metabolomics

Nuclear magnetic resonance (NMR) spectroscopy is a major analytical method used in the growing field of metabolomics. Although NMR is relatively less sensitive than mass spectrometry, this analytical platform has numerous characteristics including its high reproducibility and quantitative abilities, its nonselective and noninvasive nature, and the ability to identify unknown metabolites in complex mixtures and trace the downstream products of isotope labeled substrates ex vivo, in vivo, or in vitro. Metabolomic analysis of highly complex biological mixtures has benefitted from the advances in both NMR data acquisition and analysis methods. Although metabolomics applications span a wide range of disciplines, a majority has focused on understanding, preventing, diagnosing, and managing human diseases. This chapter describes NMR-based methods relevant to the rapidly expanding metabolomics field.

Serine synthesis influences tamoxifen response in ER+ human breast carcinoma

Estrogen receptor-positive breast cancer (ER+ BC) is the most common form of breast carcinoma accounting for approximately 70% of all diagnoses. Although ER-targeted therapies have improved survival outcomes for this BC subtype, a significant proportion of patients will ultimately develop resistance to these clinical interventions, resulting in disease recurrence. Phosphoserine aminotransferase 1 (PSAT1), an enzyme within the serine synthetic pathway (SSP), has been previously implicated in endocrine resistance. Therefore, we determined whether expression of SSP enzymes, PSAT1 or phosphoglycerate dehydrogenase (PHGDH), affects the response of ER+ BC to 4-hydroxytamoxifen (4-OHT) treatment. To investigate a clinical correlation between PSAT1, PHGDH, and endocrine resistance, we examined microarray data from ER+ patients who received tamoxifen as the sole endocrine therapy. We confirmed that higher PSAT1 and PHGDH expression correlates negatively with poorer outcomes in tamoxifen-treated ER+ BC patients. Next, we found that SSP enzyme expression and serine synthesis were elevated in tamoxifen-resistant compared to tamoxifen-sensitive ER+ BC cells in vitro. To determine relevance to endocrine sensitivity, we modified the expression of either PSAT1 or PHGDH in each cell type. Overexpression of PSAT1 in tamoxifen-sensitive MCF-7 cells diminished 4-OHT inhibition on cell proliferation. Conversely, silencing of either PSAT1 or PHGDH resulted in greater sensitivity to 4-OHT treatment in LCC9 tamoxifen-resistant cells. Likewise, the combination of a PHGDH inhibitor with 4-OHT decreased LCC9 cell proliferation. Collectively, these results suggest that overexpression of serine synthetic pathway enzymes contribute to tamoxifen resistance in ER+ BC, which can be targeted as a novel combinatorial treatment option.

Cancer Cell Metabolites: Updates on Current Tracing Methods

Cancer is the second leading cause of death-1 in 6 deaths globally is due to cancer. Cancer metabolism is a complex and one of the most actively researched area in cancer biology. Metabolic reprogramming in cancer cells entails activities that involve several enzymes and metabolites to convert nutrient into building blocks that alter energy metabolism to fuel rapid cell division. Metabolic dependencies in cancer generate signature metabolites that have key regulatory roles in tumorigenesis. In this minireview, we highlight recent advances in the popular methods ingrained in biochemistry research such as stable and flux isotope analysis, as well as radioisotope labeling, which are valuable in elucidating cancer metabolites. These methods together with analytical tools such as chromatography, nuclear magnetic resonance spectroscopy and mass spectrometry have helped to bring about exploratory work in understanding the role of important as well as obscure metabolites in cancer cells. Information obtained from these analyses significantly contribute in the diagnosis and prognosis of tumors leading to potential therapeutic targets for cancer therapy.

Long non‑coding RNA MEG3 suppresses epithelial‑to‑mesenchymal transition by inhibiting the PSAT1‑dependent GSK‑3β/Snail signaling pathway in esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is the main subtype of esophageal cancer in China, and the prognosis of patients remains poor mainly due to the occurrence of lymph node and distant metastasis. The long non‑coding RNA (lncRNA) maternally expressed gene 3 (MEG3) has been shown to have tumor‑suppressive properties and to play an important role in epithelial‑to‑mesenchymal transition (EMT) in some solid tumors. However, whether MEG3 is involved in EMT in ESCC remains unclear. In the present study, the MEG3 expression level and its association with tumorigenesis were determined in 43 tumor tissues of patients with ESCC and in ESCC cells using reverse transcription‑quantitative PCR analysis. Gene microarray analysis was performed to detect differentially expressed genes (DEGs). Based on the functional annotation results, the effects of ectopic expression of MEG3 on cell growth, migration, invasion and EMT were assessed. MEG3 expression level was found to be markedly lower in tumor tissues and cells. Statistical analysis revealed that MEG3 expression was significantly negatively associated with lymph node metastasis and TNM stage in ESCC. Fluorescence in situ hybridization assay demonstrated that MEG3 was expressed mainly in the nucleus. Ectopic expression of MEG3 inhibited cell proliferation, migration, invasion and cell cycle progression in EC109 cells. Gene microarray results demonstrated that 177 genes were differentially expressed ≥2.0 fold in MEG3‑overexpressing cells, including 23 upregulated and 154 downregulated genes. Functional annotation revealed that the DEGs were mainly involved in amino acid biosynthetic process, mitogen‑activated protein kinase signaling, and serine and glycine metabolism. Further experiments indicated that the ectopic expression of MEG3 significantly suppressed cell proliferation, migration, invasion and EMT by downregulating phosphoserine aminotransferase 1 (PSAT1). In pathological tissues, PSAT1 and MEG3 were significantly negatively correlated, and high expression of PSAT1 predicted poor survival. Taken together, these results suggest that MEG3 may be a useful prognostic biomarker and may suppress EMT by inhibiting the PSAT1‑dependent glycogen synthase kinase‑3β/Snail signaling pathway in ESCC.

Estrogen-Related Receptor α (ERRα) and G Protein-Coupled Estrogen Receptor (GPER) Synergistically Indicate Poor Prognosis in Patients with Triple-Negative Breast Cancer

Purpose

The present study aims to demonstrate the correlation between estrogen-related receptor α (ERRα) and G protein-coupled estrogen receptor (GPER) expression and its predictive role in the prognosis of patients with triple-negative breast cancer (TNBC).

Methods

A retrospective review of 199 cases of TNBC was conducted to assess the GPER and ERRα expression, and its clinicopathologic and prognostic implications. Subsequently, the effects of ERRα and GPER on cell viability, migration, and invasion induced by estrogen were also investigated in vitro.

Results

Compared to TNBCs with ERRα low expression, ERRα-high patients exhibited higher nuclear grade, more frequent lymph nodal metastasis, a higher rate of local recurrence, and distant metastasis. Survival analyses revealed that ERRα-high patients had decreased overall survival (OS), local recurrence-free survival (LRFS), and distant disease-free survival (DDFS) than ERRα-low patients. The GPER expression level positively correlated with ERRα (R=0.167, P=0.18), and TNBCs with ERRα-low/GPER-low demonstrated the best survival outcomes among groups. In vitro, E2 significantly enhanced cell viability, migration, and invasion in BT-549 and MDA-MB-231 cell lines, which was associated with the increased expression of ERRα. Moreover, the overexpression of ERRα induced by estrogen and G1 (GPER agonist) was reversed by knocking down of GPER and blocking the MAPK signaling with PD98059 in both cell lines.

Conclusion

Our findings suggest that ERRα and GPER synergistically predict unfavorable prognosis in TNBCs. Mechanically, GPER mediates the upregulation expression of ERRα induced by estrogen and promotes cell viability, migration, and invasion.

Resolving Metabolic Heterogeneity in Experimental Models of the Tumor Microenvironment from a Stable Isotope Resolved Metabolomics Perspective

The tumor microenvironment (TME) comprises complex interactions of multiple cell types that determines cell behavior and metabolism such as nutrient competition and immune suppression. We discuss the various types of heterogeneity that exist in solid tumors, and the complications this invokes for studies of TME. As human subjects and in vivo model systems are complex and difficult to manipulate, simpler 3D model systems that are compatible with flexible experimental control are necessary for studying metabolic regulation in TME. Stable Isotope Resolved Metabolomics (SIRM) is a valuable tool for tracing metabolic networks in complex systems, but at present does not directly address heterogeneous metabolism at the individual cell level. We compare the advantages and disadvantages of different model systems for SIRM experiments, with a focus on lung cancer cells, their interactions with macrophages and T cells, and their response to modulators in the immune microenvironment. We describe the experimental set up, illustrate results from 3D cultures and co-cultures of lung cancer cells with human macrophages, and outline strategies to address the heterogeneous TME.

Metabolic reprogramming in tumors: Contributions of the tumor microenvironment

The genetic alterations associated with cell transformation are in large measure expressed in the metabolic phenotype as cancer cells proliferate and change their local environment, and prepare for metastasis. Qualitatively, the fundamental biochemistry of cancer cells is generally the same as in the untransformed cells, but the cancer cells produce a local environment, the TME, that is hostile to the stromal cells, and compete for nutrients. In order to proliferate, cells need sufficient nutrients, either those that cannot be made by the cells themselves, or must be made from simpler precursors. However, in solid tumors, the nutrient supply is often limiting given the potential for rapid proliferation, and the poor quality of the vasculature. Thus, cancer cells may employ a variety of strategies to obtain nutrients for survival, growth and metastasis. Although much has been learned using established cell lines in standard culture conditions, it is becoming clear from in vivo metabolic studies that this can also be misleading, and which nutrients are used for energy production versus building blocks for synthesis of macromolecules can vary greatly from tumor to tumor, and even within the same tumor. Here we review the operation of metabolic networks, and how recent understanding of nutrient supply in the TME and utilization are being revealed using stable isotope tracers in vivo as well as in vitro.

Circadian and Sleep Metabolomics Across Species

Under normal circadian function, metabolic control is temporally coordinated across tissues and behaviors with a 24-h period. However, circadian disruption results in negative consequences for metabolic homeostasis including energy or redox imbalances. Yet, circadian disruption has become increasingly prevalent within today's society due to many factors including sleep loss. Metabolic consequences of both have been revealed by metabolomics analyses of circadian biology and sleep. Specifically, two primary analytical platforms, mass spectrometry and nuclear magnetic resonance spectroscopy, have been used to study molecular clock and sleep influences on overall metabolic rhythmicity. For example, human studies have demonstrated the prevalence of metabolic rhythms in human biology, as well as pan-metabolome consequences of sleep disruption. However, human studies are limited to peripheral metabolic readouts primarily through minimally invasive procedures. For further tissue- and organism-specific investigations, a number of model systems have been studied, based upon the conserved nature of both the molecular clock and sleep across species. Here we summarize human studies as well as key findings from metabolomics studies using mice, Drosophila, and zebrafish. While informative, a limitation in existing literature is a lack of interpretation regarding dynamic synthesis or catabolism within metabolite pools. To this extent, future work incorporating isotope tracers, specific metabolite reporters, and single-cell metabolomics may provide a means of exploring dynamic activity in pathways of interest.

Applications of Chromatography-Ultra High-Resolution MS for Stable Isotope-Resolved Metabolomics (SIRM) Reconstruction of Metabolic Networks

Metabolism is a complex network of compartmentalized and coupled chemical reactions, which often involve transfers of substructures of biomolecules, thus requiring metabolite substructures to be tracked. Stable isotope resolved metabolomics (SIRM) enables pathways reconstruction, even among chemically identical metabolites, by tracking the provenance of stable isotope-labeled substructures using NMR and ultrahigh resolution (UHR) MS. The latter can resolve and count isotopic labels in metabolites and can identify isotopic enrichment in substructures when operated in tandem MS mode. However, MS2 is difficult to implement with chromatography-based UHR-MS due to lengthy MS1 acquisition time that is required to obtain the molecular isotopologue count, which is further exacerbated by the numerous isotopologue source ions to fragment. We review here recent developments in tandem MS applications of SIRM to obtain more detailed information about isotopologue distributions in metabolites and their substructures.

Glucose Favors Lipid Anabolic Metabolism in the Invasive Breast Cancer Cell Line MDA-MB-231

Metabolic reprogramming in tumor cells is considered one of the hallmarks of cancer. Many studies have been carried out in order to elucidate the effects of tumor cell metabolism on invasion and tumor progression. However, little is known about the immediate substrate preference in tumor cells. In this work, we wanted to study this short-time preference using the highly invasive, hormone independent breast cancer cell line MDA-MB-231. By means of Seahorse and uptake experiments, our results point to a preference for glucose. However, although both glucose and glutamine are required for tumor cell proliferation, MDA-MB-231 cells can survive two days in the absence of glucose, but not in the absence of glutamine. On the other hand, the presence of glucose increased palmitate uptake in this cell line, which accumulates in the cytosol instead of going to the plasma membrane. In order to exert this effect, glucose needs to be converted to glycerol-3 phosphate, leading to palmitate metabolism through lipid synthesis, most likely to the synthesis of triacylglycerides. The effect of glucose on the palmitate uptake was also found in other triple-negative, invasive breast cancer cell lines, but not in the non-invasive ones. The results presented in this work suggest an important and specific role of glucose in lipid biosynthesis in triple-negative breast cancer.

Air pollution-derived particulate matter dysregulates hepatic Krebs cycle, glucose and lipid metabolism in mice

Exposure to ambient air particulate matter (PM_2.5) is well established as a risk factor for cardiovascular and pulmonary disease. Both epidemiologic and controlled exposure studies in humans and animals have demonstrated an association between air pollution exposure and metabolic disorders such as diabetes. Given the central role of the liver in peripheral glucose homeostasis, we exposed mice to filtered air or PM_2.5 for 16 weeks and examined its effect on hepatic metabolic pathways using stable isotope resolved metabolomics (SIRM) following a bolus of ¹³C₆-glucose. Livers were analyzed for the incorporation of ¹³C into different metabolic pools by IC-FTMS or GC-MS. The relative abundance of ¹³C-glycolytic intermediates was reduced, suggesting attenuated glycolysis, a feature found in diabetes. Decreased ¹³C-Krebs cycle intermediates suggested that PM_2.5 exposure led to a reduction in the Krebs cycle capacity. In contrast to decreased glycolysis, we observed an increase in the oxidative branch of the pentose phosphate pathway and ¹³C incorporations suggestive of enhanced capacity for the de novo synthesis of fatty acids. To our knowledge, this is one of the first studies to examine ¹³C₆-glucose utilization in the liver following PM_2.5 exposure, prior to the onset of insulin resistance (IR).

Metabolic crosstalk in the breast cancer microenvironment

During tumorigenesis, breast tumour cells undergo metabolic reprogramming, which generally includes enhanced glycolysis, tricarboxylic acid cycle activity, glutaminolysis and fatty acid biosynthesis. However, the extension and functional importance of these metabolic alterations may diverge not only according to breast cancer subtypes, but also depending on the interaction of cancer cells with the complex surrounding microenvironment. This microenvironment comprises a variety of non-cancerous cells, such as immune cells (e.g. macrophages, lymphocytes, natural killer cells), fibroblasts, adipocytes and endothelial cells, together with extracellular matrix components and soluble factors, which influence cancer progression and are predictive of clinical outcome. The continuous interaction between cancer and stromal cells results in metabolic competition and symbiosis, with oncogenic-driven metabolic reprogramming of cancer cells shaping the metabolism of neighbouring cells and vice versa. This review addresses current knowledge on this metabolic crosstalk within the breast tumour microenvironment (TME). Improved understanding of how metabolism in the TME modulates cancer development and evasion of tumour-suppressive mechanisms may provide clues for novel anticancer therapeutics directed to metabolic targets.

Diverse Roads Taken by 13C-Glucose-Derived Metabolites in Breast Cancer Cells Exposed to Limiting Glucose and Glutamine Conditions

In cancers, tumor cells are exposed to fluctuating nutrient microenvironments with limiting supplies of glucose and glutamine. While the metabolic program has been related to the expression of oncogenes, only fractional information is available on how variable precarious nutrient concentrations modulate the cellular levels of metabolites and their metabolic pathways. We thus sought to obtain an overview of the metabolic routes taken by ¹³C-glucose-derived metabolites in breast cancer MCF-7 cells growing in combinations of limiting glucose and glutamine concentrations. Isotopologue profiles of key metabolites were obtained by gas chromatography/mass spectrometry (GC/MS). They revealed that in limiting and standard saturating medium conditions, the same metabolic routes were engaged, including glycolysis, gluconeogenesis, as well as the TCA cycle with glutamine and pyruvate anaplerosis. However, the cellular levels of ¹³C-metabolites, for example, serine, alanine, glutamate, malate, and aspartate, were highly sensitive to the available concentrations and the ratios of glucose and glutamine. Notably, intracellular lactate concentrations did not reflect the Warburg effect. Also, isotopologue profiles of ¹³C-serine as well as ¹³C-alanine show that the same glucose-derived metabolites are involved in gluconeogenesis and pyruvate replenishment. Thus, anaplerosis and the bidirectional flow of central metabolic pathways ensure metabolic plasticity for adjusting to precarious nutrient conditions.

Benchmarking to the Gold Standard: Hyaluronan-Oxime Hydrogels Recapitulate Xenograft Models with In Vitro Breast Cancer Spheroid Culture

Many 3D in vitro models induce breast cancer spheroid formation; however, this alone does not recapitulate the complex in vivo phenotype. To effectively screen therapeutics, it is urgently needed to validate in vitro cancer spheroid models against the gold standard of xenografts. A new oxime-crosslinked hyaluronan (HA) hydrogel is designed, manipulating gelation rate and mechanical properties to grow breast cancer spheroids in 3D. This HA-oxime breast cancer model maintains the gene expression profile most similar to that of tumor xenografts based on a pan-cancer gene expression profile (comprising 730 genes) of three different human breast cancer subtypes compared to Matrigel or conventional 2D culture. Differences in gene expression between breast cancer cultures in HA-oxime versus Matrigel or 2D are confirmed for 12 canonical pathways by gene set variation analysis. Importantly, drug response is dependent on the culture method. Breast cancer cells respond better to the Rac inhibitor (EHT-1864) and the PI3K inhibitor (AZD6482) when cultured in HA-oxime versus Matrigel. This study demonstrates the superiority of an HA-based hydrogel as a platform for in vitro breast cancer culture of both primary, patient-derived cells and cell lines, and provides a hydrogel culture model that closely matches that in vivo.

Improved segmented-scan spectral stitching for stable isotope resolved metabolomics (SIRM) by ultra-high-resolution Fourier transform mass spectrometry

We have implemented a linear ion trap (LIT)-based SIM-stitching method for ultra-high-resolution Fourier transform mass spectrometry (FTMS) that increases the S/N over a wide m/z range compared to non-segmented wide full-scan (WFS) spectra. Here we described an improved segmented spectral scan stitching method that was based on quadrupole mass filter (QMF)-SIM, which overcame previous limitations of ion signal loss in LIT. This allowed for accurate representation of isotopologue distributions, both at natural abundance and in stable isotope-resolved metabolomics (SIRM)-based experiments. We also introduced a new spectral binning method that provided more precise and resolution-independent bins for irreversibly noise-suppressed FTMS spectra. We demonstrated a substantial improvement in S/N and sensitivity (typically > 10-fold) for ¹³C labeled lipid extracts of human macrophages grown as three-dimensional (3D) cell culture, with detection of an increased number of ¹³C isotopologue ions. The method also enabled analysis of extracts from very limited biological samples.

Can Metabolic Pathways Be Therapeutic Targets in Rheumatoid Arthritis?

The metabolic rewiring of tumor cells and immune cells has been viewed as a promising source of novel drug targets. Many of the molecular pathways implicated in rheumatoid arthritis (RA) directly modify synovium metabolism and transform the resident cells, such as the fibroblast-like synoviocytes (FLS), and the synovial tissue macrophages (STM), toward an overproduction of enzymes, which degrade cartilage and bone, and cytokines, which promote immune cell infiltration. Recent studies have shown metabolic changes in stromal and immune cells from RA patients. Metabolic disruption in the synovium provide the opportunity to use in vivo metabolism-based imaging techniques for patient stratification and to monitor treatment response. In addition, these metabolic changes may be therapeutically targetable. Thus, resetting metabolism of the synovial membrane offers additional opportunities for disease modulation and restoration of homeostasis in RA. In fact, rheumatologists already use the antimetabolite methotrexate, a chemotherapy agent, for the treatment of patients with inflammatory arthritis. Metabolic targets that do not compromise systemic homeostasis or corresponding metabolic functions in normal cells could increase the drug armamentarium in rheumatic diseases for combination therapy independent of systemic immunosuppression. This article summarizes what is known about metabolism in synovial tissue cells and highlights chemotherapies that target metabolism as potential future therapeutic strategies for RA.

Multiplexed Single-Cell Measurements of FDG Uptake and Lactate Release Using Droplet Microfluidics

INTRODUCTION

Glucose utilization and lactate release are 2 important indicators of cancer metabolism. Most tumors consume glucose and release lactate at a higher rate than normal tissues due to enhanced aerobic glycolysis. However, these 2 indicators of metabolism have not previously been studied on a single-cell level, in the same cell.

OBJECTIVE

To develop and characterize a novel droplet microfluidic device for multiplexed measurements of glucose uptake (via its analog ¹⁸F-fluorodeoxyglucose) and lactate release, in single live cells encapsulated in an array of water-in-oil droplets.

RESULTS

Surprisingly, ¹⁸F-fluorodeoxyglucose uptake and lactate release were only marginally correlated at the single-cell level, even when assayed in a standard cell line (MDA-MB-231). While ¹⁸F-fluorodeoxyglucose-avid cells released substantial amounts of lactate, the reverse was not true, and many cells released high amounts of lactate without taking up ¹⁸F-fluorodeoxyglucose.

DISCUSSION

These results confirm that cancer cells rely on multiple metabolic pathways in addition to aerobic glycolysis and that the use of these pathways is highly heterogeneous, even under controlled culture conditions. Clinically, the large cell-to-cell variability suggests that positron emission tomography measurements of ¹⁸F-fluorodeoxyglucose uptake represent metabolic flux only in an aggregate sense, not for individual cancer cells within the tumor.

Metabolic Labeling of Cultured Mammalian Cells for Stable Isotope-Resolved Metabolomics: Practical Aspects of Tissue Culture and Sample Extraction

Stable isotope-resolved metabolomics (SIRM) methods are used increasingly by cancer researchers to probe metabolic pathways and identify vulnerabilities in cancer cells. Analytical and computational advances are being made constantly, but tissue culture and sample extraction procedures are often variable and not elaborated in the literature. This chapter discusses basic aspects of tissue culture practices as they relate to the use of stable isotope tracers and provides a detailed metabolic labeling and metabolite extraction procedure designed to maximize the amount of information that can be obtained from a single tracer experiment.

Stable Isotope Tracers for Metabolic Pathway Analysis

Stable isotope tracing allows a metabolic substrate to be followed through downstream biochemical reactions, thereby providing unparalleled insights into the metabolic wiring of cells. This approach stops short of modeling absolute fluxes but is relatively straightforward and has become increasingly accessible due to the widespread adoption of high-resolution mass spectrometers. Analysis of both dynamic and steady-state labeling patterns in downstream metabolites provides valuable qualitative information as to their origin and relative rates of production. Stable isotope tracing is, therefore, a powerful way to understand the impact of genetic alterations and defined perturbations on metabolism. In this chapter, we describe a liquid chromatography-mass spectrometry (LC-MS) protocol for stable isotope tracing using ¹³C-L-arginine in a macrophage cell line. A similar approach can be used to follow other stable isotope tracers, and notes are provided with advice on how this protocol can be generalized for use in other settings.

Dynamic Metabolic Response to Adriamycin-Induced Senescence in Breast Cancer Cells

Cellular senescence displays a heterogeneous set of phenotypes linked to tumor suppression; however, after drug treatment, senescence may also be involved in stable or recurrent cancer. Metabolic changes during senescence can provide detailed information on cellular status and may also have implications for the development of effective treatment strategies. The metabolic response to Adriamycin (ADR) treatment, which causes senescence as well as cell death, was obtained with the aid of metabolic profiling and isotope tracing in two human breast cancer cell lines, MCF7 and MDA-MB-231. After 5 days of ADR treatment, more than 60% of remaining, intact cells entered into a senescent state, characterized by enlarged and flattened morphology and positive blue staining using SA-β-gal. Metabolic trajectory analysis showed that the two cell lines' responses were significantly different and were divided into two distinct stages. The metabolic shift from the first stage to the second was reflected by a partial recovery of the TCA cycle, as well as amino acid and lipid metabolisms. Isotope tracing analysis indicated that the higher level of glutamine metabolism helped maintain senescence. The results suggest that the dynamic changes during senescence indicate a multi-step process involving important metabolic pathways which might allow breast cancer cells to adapt to persistent ADR treatment, while the higher level of anapleurosis may be important for maintaining the senescent state. Ultimately, a better understanding of metabolic changes during senescence might provide targets for cancer therapy and tumor eradication.

Interplay between hypoxia and androgen controls a metabolic switch conferring resistance to androgen/AR-targeted therapy

Despite recent advances, the efficacy of androgen/androgen receptor (AR)-targeted therapy remains  limited for many patients with metastatic prostate cancer. This is in part because prostate cancers adaptively switch to the androgen/AR-independent pathway for survival and growth, thereby conferring therapy resistance. Tumor hypoxia is considered as a major cause of treatment resistance. However, the exact mechanism is largely unclear. Here we report that chronic-androgen deprivation therapy (ADT) in the condition of hypoxia induces adaptive androgen/AR-independence, and therefore confers resistance to androgen/AR-targeted therapy, e.g., enzalutamide. Mechanistically, this is mediated by glucose-6-phosphate isomerase (GPI), which is transcriptionally repressed by AR in hypoxia, but restored and increased by AR inhibition. In turn, GPI maintains glucose metabolism and energy homeostasis in hypoxia by redirecting the glucose flux from androgen/AR-dependent pentose phosphate pathway (PPP) to hypoxia-induced glycolysis pathway, thereby reducing the growth inhibitory effect of enzalutamide. Inhibiting GPI overcomes the therapy resistance in hypoxia in vitro and increases enzalutamide efficacy in vivo.

NMR and MS-based Stable Isotope-Resolved Metabolomics and Applications in Cancer Metabolism

There is considerable interest in defining metabolic reprogramming in human diseases, which is recognized as a hallmark of human cancer. Although radiotracers have a long history in specific metabolic studies, stable isotope-enriched precursors coupled with modern high resolution mass spectrometry and NMR spectroscopy have enabled systematic mapping of metabolic networks and fluxes in cells, tissues and living organisms including humans. These analytical platforms are high in information content, are complementary and cross-validating in terms of compound identification, quantification, and isotope labeling pattern analysis of a large number of metabolites simultaneously. Furthermore, new developments in chemoselective derivatization and in vivo spectroscopy enable tracking of labile/low abundance metabolites and metabolic kinetics in real-time. Here we review developments in Stable Isotope Resolved Metabolomics (SIRM) and recent applications in cancer metabolism using a wide variety of stable isotope tracers that probe both broad and specific aspects of cancer metabolism required for proliferation and survival.

Stable Isotope-Resolved Metabolomics Shows Metabolic Resistance to Anti-Cancer Selenite in 3D Spheroids versus 2D Cell Cultures

Conventional two-dimensional (2D) cell cultures are grown on rigid plastic substrates with unrealistic concentration gradients of O₂, nutrients, and treatment agents. More importantly, 2D cultures lack cell–cell and cell–extracellular matrix (ECM) interactions, which are critical for regulating cell behavior and functions. There are several three-dimensional (3D) cell culture systems such as Matrigel, hydrogels, micropatterned plates, and hanging drop that overcome these drawbacks but they suffer from technical challenges including long spheroid formation times, difficult handling for high throughput assays, and/or matrix contamination for metabolic studies. Magnetic 3D bioprinting (M3DB) can circumvent these issues by utilizing nanoparticles that enable spheroid formation and growth via magnetizing cells. M3DB spheroids have been shown to emulate tissue and tumor microenvironments while exhibiting higher resistance to toxic agents than their 2D counterparts. It is, however, unclear if and how such 3D systems impact cellular metabolic networks, which may determine altered toxic responses in cells. We employed a Stable Isotope-Resolved Metabolomics (SIRM) approach with ¹³C₆-glucose as tracer to map central metabolic networks both in 2D cells and M3DB spheroids formed from lung (A549) and pancreatic (PANC1) adenocarcinoma cells without or with an anti-cancer agent (sodium selenite). We found that the extent of ¹³C-label incorporation into metabolites of glycolysis, the Krebs cycle, the pentose phosphate pathway, and purine/pyrimidine nucleotide synthesis was largely comparable between 2D and M3DB culture systems for both cell lines. The exceptions were the reduced capacity for de novo synthesis of pyrimidine and sugar nucleotides in M3DB than 2D cultures of A549 and PANC1 cells as well as the presence of gluconeogenic activity in M3DB spheroids of PANC1 cells but not in the 2D counterpart. More strikingly, selenite induced much less perturbation of these pathways in the spheroids relative to the 2D counterparts in both cell lines, which is consistent with the corresponding lesser effects on morphology and growth. Thus, the increased resistance of cancer cell spheroids to selenite may be linked to the reduced capacity of selenite to perturb these metabolic pathways necessary for growth and survival.

Untargeted and stable isotope-assisted metabolomic analysis of MDA-MB-231 cells under hypoxia

INTRODUCTION

Hypoxia commonly occurs in cancers and is highly related with the occurrence, development and metastasis of cancer. Treatment of triple negative breast cancer remains challenge. Knowledge about the metabolic status of triple negative breast cancer cell lines in hypoxia is valuable for the understanding of molecular mechanisms of this tumor subtype to develop effective therapeutics.

OBJECTIVES

Comprehensively characterize the metabolic profiles of triple negative breast cancer cell line MDA-MB-231 in normoxia and hypoxia and the pathways involved in metabolic changes in hypoxia.

METHODS

Differences in metabolic profiles affected pathways of MDA-MB-231 cells in normoxia and hypoxia were characterized using GC-MS based untargeted and stable isotope assisted metabolomic techniques.

RESULTS

Thirty-three metabolites were significantly changed in hypoxia and nine pathways were involved. Hypoxia increased glycolysis, inhibited TCA cycle, pentose phosphate pathway and pyruvate carboxylation, while increased glutaminolysis in MDA-MB-231 cells.

CONCLUSION

The current results provide metabolic differences of MDA-MB-231 cells in normoxia and hypoxia conditions as well as the involved metabolic pathways, demonstrating the power of combined use of untargeted and stable isotope-assisted metabolomic methods in comprehensive metabolomic analysis.

Influence of media selection on NMR based metabolic profiling of human cell lines

INTRODUCTION

Comparative metabolic profiling of different human cancer cell lines can reveal metabolic pathways up-regulated or down-regulated in each cell line, potentially providing insight into distinct metabolism taking place in different types of cancer cells. It is noteworthy, however, that human cell lines available from public repositories are deposited with recommended media for optimal growth, and if cell lines to be compared are cultured on different growth media, this introduces a potentially serious confounding variable in metabolic profiling studies designed to identify intrinsic metabolic pathways active in each cell line.

OBJECTIVES

The goal of this study was to determine if the culture media used to grow human cell lines had a significant impact on the measured metabolic profiles.

METHODS

NMR-based metabolic profiles of hydrophilic extracts of three human pancreatic cancer cell lines, AsPC-1, MiaPaCa-2 and Panc-1, were compared after culture on Dulbecco's Modified Eagle Medium (DMEM) or Roswell Park Memorial Institute (RPMI-1640) medium.

RESULTS

Comparisons of the same cell lines cultured on different media revealed that the concentrations of many metabolites depended strongly on the choice of culture media. Analyses of different cell lines grown on the same media revealed insight into their metabolic differences.

CONCLUSION

The choice of culture media can significantly impact metabolic profiles of human cell lines and should be considered an important variable when designing metabolic profiling studies. Also, the metabolic differences of cells cultured on media recommended for optimal growth in comparison to a second growth medium can reveal critical insight into metabolic pathways active in each cell line.

Quantitative profiling of carbonyl metabolites directly in crude biological extracts using chemoselective tagging and nanoESI-FTMS

The extensive range of chemical structures, wide range of abundances, and chemical instability of metabolites present in the metabolome pose major analytical challenges that are difficult to address with existing technologies. To address these issues, one approach is to target a subset of metabolites that share a functional group, such as ketones and aldehydes, using chemoselective tagging. Here we report a greatly improved chemoselective method for the quantitative analysis of hydrophilic and hydrophobic carbonyl-containing metabolites directly in biological samples. This method is based on direct tissue or cells extraction with simultaneous derivatization of stable and labile carbonylated metabolites using N-[2-(aminooxy)ethyl]-N,N-dimethyl-1-dodecylammonium (QDA) and 13CD3 labeled QDA. We combined innovations of direct quenching of biological sample with frozen derivatization conditions under the catalyst N,N-dimethyl-p-phenylenediamine, which facilitated the formation of oxime stable-isotope ion pairs differing by m/z 4.02188 while minimizing metabolite degradation. The resulting oximes were extracted by HyperSep C8 tips to remove interfering compounds, and the products were detected using nano-electrospray ionization interfaced with a Thermo Fusion mass spectrometer. The quaternary ammonium tagging greatly increased electrospray MS detection sensitivity and the signature ions pairs enabled simple identification of carbonyl compounds. The improved method showed the lower limits of quantification for carbonyl standards to be in the range of 0.20-2 nM, with linearity of R2 > 0.99 over 4 orders of magnitude. We have applied the method to assign 66 carbonyls in mouse tumor tissues, many of which could not be assigned solely by accurate mass and tandem MS. Fourteen of the metabolites were quantified using authentic standards. We also demonstrated the suitability of this method for determining 13C labeled isotopologues of carbonyl metabolites in 13C6-glucose-based stable isotope-resolved metabolomic (SIRM) studies.