Untargeted metabolomics for profiling oncogene-specific metabolic signatures of prostate cancer.
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ABSTRACT:
SUBMITTER: Priolo C
PROVIDER: S-EPMC4905328 | biostudies-other | 2015 Oct-Dec
REPOSITORIES: biostudies-other
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Project description:BackgroundThe complex yet interrelated connections between cancer metabolism and oncogenic driver genes are relatively unexplored but have the potential to identify novel biomarkers and drug targets with prognostic and therapeutic value. The goal of this study was to identify global metabolic profiles of breast tumors isolated from multiple transgenic mouse models and to identify unique metabolic signatures driven by these oncogenes.MethodsUsing mass spectrometry (GC-MS, LC-MS/MS, and capillary zone electrophoresis (CZE)-MS platforms), we quantified and compared the levels of 374 metabolites in breast tissue from normal and transgenic mouse breast cancer models overexpressing a panel of oncogenes (PyMT, PyMT-DB, Wnt1, Neu, and C3-TAg). We also compared the mouse metabolomics data to published human metabolomics data already linked to clinical data.ResultsThrough analysis of our metabolomics data, we identified metabolic differences between normal and tumor breast tissues as well as metabolic differences unique to each initiating oncogene. We also quantified the metabolic profiles of the mammary fat pad versus mammary epithelium by CZE-MS/MS. However, the differences between the tissues did not account for the majority of the metabolic differences between the normal mammary gland and breast tumor tissues. Therefore, the differences between the cohorts were unlikely due to cellular heterogeneity. Of the mouse models used in this study, C3-TAg was the only cohort with a tumor metabolic signature composed of ten metabolites that had significant prognostic value in breast cancer patients. Gene expression analysis identified candidate genes that may contribute to the metabolic reprogramming.ConclusionsThis study identifies oncogene-induced metabolic reprogramming within mouse breast tumors and compares the results to that of human breast tumors, providing a unique look at the relationship between and clinical value of oncogene initiation and metabolism during breast cancer.
| S-EPMC5881178 | biostudies-literature
Project description:PurposeGastric cancer is a common tumor of the digestive system. Identification of potential molecules associated with gastric cancer progression and validation of potential biomarkers for gastric cancer diagnosis are very important. Thus, the aim of our study was to determine the serum metabolic characteristics of the serum of patients with chronic gastritis (CG) or gastric cancer (GC) and validate candidate biomarkers for disease diagnosis.Experimental designA total of 123 human serum samples from patients with CG or GC were collected for untargeted metabolomic analysis via UHPLC-Q-TOF/MS to determine characteristics of the serum. Principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and heat map were used for multivariate analysis. In addition, commercial databases were used to identify the pathways of metabolites. Differential metabolites were identified based on a heat map with a t-test threshold (p < 0.05), fold-change threshold (FC > 1.5 or FC < 2/3) and variable importance in the projection (VIP >1). Then, differential metabolites were analyzed by receiver operating characteristic (ROC) curve to determine candidate biomarkers. All samples were analyzed for fasting lipid profiles.ResultsAnalysis of serum metabolomic profiles indicated that most of the altered metabolic pathways in the three groups were associated with lipid metabolism (p < 0.05) and lipids and lipid-like molecules were the predominating metabolites within the top 100 differential metabolites (p < 0.05, FC > 1.5 or FC < 2/3, and VIP >1). Moreover, differential metabolites, including hexadecasphinganine, linoleamide, and N-Hydroxy arachidonoyl amine had high diagnostic performance according to PLS-DA. In addition, fasting lipid profile analysis showed the serum levels of total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C) and apolipoprotein A1 (Apo-A1) were decreased concomitant to the progression of the progression of the disease compared with those in the control group (p < 0.05).ConclusionsThus, this study demonstrated that lipid metabolism may influence the development of CG to GC. Hexadecasphinganine, linoleamide, and N-Hydroxy arachidonoyl amine were selected as candidate diagnostic markers for CG and GC.
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Project description:Fatty acid synthase (FAS) is a key enzyme involved in de novo lipogenesis that produces lipids that are necessary for cell growth and signal transduction, and it is known to be overexpressed, especially in cancer cells. Although lipid metabolism alteration is an important metabolic phenotype in cancer cells, the development of drugs targeting FAS to block lipid synthesis is hampered by the characteristics of cancer cells with metabolic flexibility leading to rapid adaptation and resistance. Therefore, to confirm the metabolic alterations at the cellular level during FAS inhibition, we treated LNCaP-LN3 prostate cancer cells with FAS inhibitors (Fasnall, GSK2194069, and TVB-3166). With untargeted metabolomics, we observed significant changes in a total of 56 metabolites in the drug-treated groups. Among the altered metabolites, 28 metabolites were significantly changed in all of the drug-treated groups. To our surprise, despite the inhibition of FAS, which is involved in palmitate production, the cells increase their fatty acids and glycerophospholipids contents endogenously. Also, some of the notable changes in the metabolic pathways include polyamine metabolism and energy metabolism. This is the first study to compare and elucidate the effect of FAS inhibition on cellular metabolic flexibility using three different FAS inhibitors through metabolomics. We believe that our results may provide key data for the development of future FAS-targeting drugs.
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Project description:The rapidly increasing number of engineered nanoparticles (NPs), and products containing NPs, raises concerns for human exposure and safety. With this increasing, and ever changing, catalogue of NPs it is becoming more difficult to adequately assess the toxic potential of new materials in a timely fashion. It is therefore important to develop methods which can provide high-throughput screening of biological responses. The use of omics technologies, including metabolomics, can play a vital role in this process by providing relatively fast, comprehensive, and cost-effective assessment of cellular responses. These techniques thus provide the opportunity to identify specific toxicity pathways and to generate hypotheses on how to reduce or abolish toxicity.We have used untargeted metabolome analysis to determine differentially expressed metabolites in human lung epithelial cells (A549) exposed to copper oxide nanoparticles (CuO NPs). Toxicity hypotheses were then generated based on the affected pathways, and critically tested using more conventional biochemical and cellular assays. CuO NPs induced regulation of metabolites involved in oxidative stress, hypertonic stress, and apoptosis. The involvement of oxidative stress was clarified more easily than apoptosis, which involved control experiments to confirm specific metabolites that could be used as standard markers for apoptosis; based on this we tentatively propose methylnicotinamide as a generic metabolic marker for apoptosis.Our findings are well aligned with the current literature on CuO NP toxicity. We thus believe that untargeted metabolomics profiling is a suitable tool for NP toxicity screening and hypothesis generation.
| S-EPMC5017021 | biostudies-other
Project description:Prostate cancer (PC) is one of the most common male cancers worldwide. Until now, there is no consensus about using urinary metabolomic profiling as novel biomarkers to identify PC. In this study, urine samples from 50 PC patients and 50 non-cancerous individuals (control group) were collected. Based on 1H nuclear magnetic resonance (1H-NMR) analysis, 20 metabolites were identified. Subsequently, principal component analysis (PCA), partial least squares-differential analysis (PLS-DA) and ortho-PLS-DA (OPLS-DA) were applied to find metabolites to distinguish PC from the control group. Furthermore, Wilcoxon test was used to find significant differences between the two groups in metabolite urine levels. Guanidinoacetate, phenylacetylglycine, and glycine were significantly increased in PC, while L-lactate and L-alanine were significantly decreased. The receiver operating characteristics (ROC) analysis revealed that the combination of guanidinoacetate, phenylacetylglycine, and glycine was able to accurately differentiate 77% of the PC patients with sensitivity = 80% and a specificity = 64%. In addition, those three metabolites showed significant differences in patients stratified for Gleason score 6 and Gleason score ≥7, indicating potential use to detect significant prostate cancer. Pathway enrichment analysis using the KEGG (Kyoto Encyclopedia of Genes and Genomes) and the SMPDB (The Small Molecule Pathway Database) revealed potential involvement of KEGG "Glycine, Serine, and Threonine metabolism" in PC. The present study highlights that guanidinoacetate, phenylacetylglycine, and glycine are potential candidate biomarkers of PC. To the best knowledge of the authors, this is the first study identifying guanidinoacetate, and phenylacetylglycine as potential novel biomarkers in PC.
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Project description:BackgroundFood allergy (FA) affects an increasing proportion of children for reasons that remain obscure. Novel disease biomarkers and curative treatment options are strongly needed.ObjectiveWe sought to apply untargeted metabolomic profiling to identify pathogenic mechanisms and candidate disease biomarkers in patients with FA.MethodsMass spectrometry-based untargeted metabolomic profiling was performed on serum samples of children with either FA alone, asthma alone, or both FA and asthma, as well as healthy pediatric control subjects.ResultsIn this pilot study patients with FA exhibited a disease-specific metabolomic signature compared with both control subjects and asthmatic patients. In particular, FA was uniquely associated with a marked decrease in sphingolipid levels, as well as levels of a number of other lipid metabolites, in the face of normal frequencies of circulating natural killer T cells. Specific comparison of patients with FA and asthmatic patients revealed differences in the microbiota-sensitive aromatic amino acid and secondary bile acid metabolism. Children with both FA and asthma exhibited a metabolomic profile that aligned with that of FA alone but not asthma. Among children with FA, the history of severe systemic reactions and the presence of multiple FAs were associated with changes in levels of tryptophan metabolites, eicosanoids, plasmalogens, and fatty acids.ConclusionsChildren with FA have a disease-specific metabolomic profile that is informative of disease mechanisms and severity and that dominates in the presence of asthma. Lower levels of sphingolipids and ceramides and other metabolomic alterations observed in children with FA might reflect the interplay between an altered microbiota and immune cell subsets in the gut.
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Project description:Herein, murine prostate cancer cell lines, generated via selective transduction with a single oncogene (c-Myc, Ha-Ras, and v-Src), showed oncogene-specific prostate cancer molecular signatures that were recapitulated in human prostate cancer and developed lung metastasis in immune-competent mice. Interrogation of two independent retrospective cohorts of patient samples using the oncogene signature showed an ability to distinguish tumor from normal prostate with a predictive value for prostate cancer of 98% to 99%. In a blinded study, the signature algorithm showed independent substratification of reduced recurrence-free survival by Kaplan-Meier analysis. The generation of new oncogene-specific prostate cancer cell lines that recapitulate human prostate cancer gene expression, which metastasize in immune-competent mice, are a valuable new resource for testing targeted therapy, whereas the molecular signatures identified herein provides further value over current gene signature markers of prediction and outcome.
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Project description:ObjectiveProstate cancer (PCa) is the second most common male malignancy globally. Prostate-specific antigen (PSA) is an important biomarker for PCa diagnosis. However, it is not accurate in the diagnostic gray zone of 4-10 ng/ml of PSA. In the current study, the performance of serum metabolomics profiling in discriminating PCa patients from benign prostatic hyperplasia (BPH) individuals with a PSA concentration in the range of 4-10 ng/ml was explored.MethodsA total of 220 individuals, including patients diagnosed with PCa and BPH within PSA levels in the range of 4-10 ng/ml and healthy controls, were enrolled in the study. Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS)-based non-targeted metabolomics method was utilized to characterize serum metabolic profiles of participants. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) methods were used for multivariate analysis. Receiver operating characteristic (ROC) curve analysis was performed to explore the diagnostic value of candidate metabolites in differentiating PCa from BPH. Correlation analysis was conducted to explore the relationship between serum metabolites and common clinically used fasting lipid profiles.ResultsSeveral differential metabolites were identified. The top enriched pathways in PCa subjects such as glycerophospholipid and glycerolipid metabolisms were associated with lipid metabolism. Lipids and lipid-like compounds were the predominant metabolites within the top 50 differential metabolites selected using fold-change threshold >1.5 or <2/3, variable importance in projection (VIP) > 1, and Student's t-test threshold p < 0.05. Eighteen lipid or lipid-related metabolites were selected including 4-oxoretinol, anandamide, palmitic acid, glycerol 1-hexadecanoate, dl-dihydrosphingosine, 2-methoxy-6Z-hexadecenoic acid, 3-oxo-nonadecanoic acid, 2-hydroxy-nonadecanoic acid, N-palmitoyl glycine, 2-palmitoylglycerol, hexadecenal, d-erythro-sphingosine C-15, N-methyl arachidonoyl amine, 9-octadecenal, hexadecyl acetyl glycerol, 1-(9Z-pentadecenoyl)-2-eicosanoyl-glycero-3-phosphate, 3Z,6Z,9Z-octadecatriene, and glycidyl stearate. Selected metabolites effectively discriminated PCa from BPH when PSA levels were in the range of 4-10 ng/ml (area under the curve (AUC) > 0.80). Notably, the 18 identified metabolites were negatively corrected with total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and Apo-B levels in PCa patients; and some were negatively correlated with high-density lipoprotein cholesterol (HDL-C) and Apo-A levels. However, the metabolites were not correlated with triglycerides (TG).ConclusionThe findings of the present study indicate that metabolic reprogramming, mainly lipid metabolism, is a key signature of PCa. The 18 lipid or lipid-associated metabolites identified in this study are potential diagnostic markers for differential diagnosis of PCa patients and BPH individuals within a PSA level in the gray zone of 4-10 ng/ml.
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Project description:We apply stable isotope tracing, mass-spectrometry-based untargeted metabolomics, to reveal the biochemical space labeled by 13C-substrates in bone-marrow-derived macrophages. At the pathway level, classically (lipopolysaccharide [LPS]-polarized, M1) and alternatively (interleukin [IL]-4-polarized, M2) polarized macrophages were 13C-labeled with surprising concordance. Total pools of uridine diphosphate N-acetylglucosamine (UDP-GlcNAc), an intermediate in the hexosamine biosynthetic pathway, were equally abundant in LPS- and IL-4-polarized macrophages. Informatic scrutiny of 13C-isotopologues revealed that LPS-polarized macrophages leverage the pentose phosphate pathway to generate UDP-GlcNAc, whereas IL-4-polarized macrophages rely on intact glucose and mitochondrial metabolism of glucose carbon. Labeling from [13C]glucose is competed by unlabeled fatty acids and acetoacetate, underscoring the broad roles for substrate metabolism beyond energy conversion. Finally, the LPS-polarized macrophage metabolite itaconate is imported into IL-4-polarized macrophages, in which it reprograms [13C]glucose metabolism. Thus, use of fully unsupervised isotope tracing metabolomics in macrophages reveals polarization-state-specific metabolic pathway connectivity, substrate competition, and metabolite allocation among cellular compartments.
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Project description:Tumour angiogenesis is an important hallmark of cancer and the study of its metabolic adaptations, downstream to any cellular change, can reveal attractive targets for inhibiting cancer growth. In the tumour microenvironment, endothelial cells (ECs) interact with heterogeneous tumour cell types that drive angiogenesis and metastasis. In this study we aim to characterize the metabolic alterations in ECs influenced by the presence of tumour cells with extreme metastatic abilities. Human umbilical vein endothelial cells (HUVECs) were subjected to different microenvironmental conditions, such as the presence of highly metastatic PC-3M and highly invasive PC-3S prostate cancer cell lines, in addition to the angiogenic activator vascular endothelial growth factor (VEGF), under normoxia. Untargeted high resolution liquid chromatography-mass spectrometry (LC-MS) based metabolomics revealed significant metabolite differences among the various conditions and a total of 25 significantly altered metabolites were identified including acetyl L-carnitine, NAD+, hypoxanthine, guanine and oleamide, with profile changes unique to each of the experimental conditions. Biochemical pathway analysis revealed the importance of fatty acid oxidation and nucleotide salvage pathways. These results provide a global metabolic preview that could help in selectively targeting the ECs aiding in either cancer cell invasion or metastasis in the heterogeneous tumour microenvironment.
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