| 1. |
- Beger, Richard D., et al.
(författare)
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Metabolomics enables precision medicine : "A White Paper, Community Perspective"
- 2016
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Ingår i: Metabolomics. - : Springer. - 1573-3882 .- 1573-3890. ; 12:10
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Tidskriftsartikel (refereegranskat)abstract
- INTRODUCTION BACKGROUND TO METABOLOMICS: Metabolomics is the comprehensive study of the metabolome, the repertoire of biochemicals (or small molecules) present in cells, tissues, and body fluids. The study of metabolism at the global or "-omics" level is a rapidly growing field that has the potential to have a profound impact upon medical practice. At the center of metabolomics, is the concept that a person's metabolic state provides a close representation of that individual's overall health status. This metabolic state reflects what has been encoded by the genome, and modified by diet, environmental factors, and the gut microbiome. The metabolic profile provides a quantifiable readout of biochemical state from normal physiology to diverse pathophysiologies in a manner that is often not obvious from gene expression analyses. Today, clinicians capture only a very small part of the information contained in the metabolome, as they routinely measure only a narrow set of blood chemistry analytes to assess health and disease states. Examples include measuring glucose to monitor diabetes, measuring cholesterol and high density lipoprotein/low density lipoprotein ratio to assess cardiovascular health, BUN and creatinine for renal disorders, and measuring a panel of metabolites to diagnose potential inborn errors of metabolism in neonates.OBJECTIVES OF WHITE PAPER—EXPECTED TREATMENT OUTCOMES AND METABOLOMICS ENABLING TOOL FOR PRECISION MEDICINE: We anticipate that the narrow range of chemical analyses in current use by the medical community today will be replaced in the future by analyses that reveal a far more comprehensive metabolic signature. This signature is expected to describe global biochemical aberrations that reflect patterns of variance in states of wellness, more accurately describe specific diseases and their progression, and greatly aid in differential diagnosis. Such future metabolic signatures will: (1) provide predictive, prognostic, diagnostic, and surrogate markers of diverse disease states; (2) inform on underlying molecular mechanisms of diseases; (3) allow for sub-classification of diseases, and stratification of patients based on metabolic pathways impacted; (4) reveal biomarkers for drug response phenotypes, providing an effective means to predict variation in a subject's response to treatment (pharmacometabolomics); (5) define a metabotype for each specific genotype, offering a functional read-out for genetic variants: (6) provide a means to monitor response and recurrence of diseases, such as cancers: (7) describe the molecular landscape in human performance applications and extreme environments. Importantly, sophisticated metabolomic analytical platforms and informatics tools have recently been developed that make it possible to measure thousands of metabolites in blood, other body fluids, and tissues. Such tools also enable more robust analysis of response to treatment. New insights have been gained about mechanisms of diseases, including neuropsychiatric disorders, cardiovascular disease, cancers, diabetes and a range of pathologies. A series of ground breaking studies supported by National Institute of Health (NIH) through the Pharmacometabolomics Research Network and its partnership with the Pharmacogenomics Research Network illustrate how a patient's metabotype at baseline, prior to treatment, during treatment, and post-treatment, can inform about treatment outcomes and variations in responsiveness to drugs (e.g., statins, antidepressants, antihypertensives and antiplatelet therapies). These studies along with several others also exemplify how metabolomics data can complement and inform genetic data in defining ethnic, sex, and gender basis for variation in responses to treatment, which illustrates how pharmacometabolomics and pharmacogenomics are complementary and powerful tools for precision medicine.CONCLUSIONS KEY SCIENTIFIC CONCEPTS AND RECOMMENDATIONS FOR PRECISION MEDICINE: Our metabolomics community believes that inclusion of metabolomics data in precision medicine initiatives is timely and will provide an extremely valuable layer of data that compliments and informs other data obtained by these important initiatives. Our Metabolomics Society, through its "Precision Medicine and Pharmacometabolomics Task Group", with input from our metabolomics community at large, has developed this White Paper where we discuss the value and approaches for including metabolomics data in large precision medicine initiatives. This White Paper offers recommendations for the selection of state of-the-art metabolomics platforms and approaches that offer the widest biochemical coverage, considers critical sample collection and preservation, as well as standardization of measurements, among other important topics. We anticipate that our metabolomics community will have representation in large precision medicine initiatives to provide input with regard to sample acquisition/preservation, selection of optimal omics technologies, and key issues regarding data collection, interpretation, and dissemination. We strongly recommend the collection and biobanking of samples for precision medicine initiatives that will take into consideration needs for large-scale metabolic phenotyping studies.
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| 2. |
- Bowden, John A., et al.
(författare)
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Harmonizing lipidomics : NIST interlaboratory comparison exercise for lipidomics using SRM 1950-Metabolites in Frozen Human Plasma
- 2017
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Ingår i: Journal of Lipid Research. - 0022-2275 .- 1539-7262. ; 58:12, s. 2275-2288
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Tidskriftsartikel (refereegranskat)abstract
- As the lipidomics field continues to advance, self-evaluation within the community is critical. Here, we performed an interlaboratory comparison exercise for lipidomics using Standard Reference Material (SRM) 1950-Metabolites in Frozen Human Plasma, a commercially available reference material. The interlaboratory study comprised 31 diverse laboratories, with each laboratory using a different lipidomics workflow. A total of 1,527 unique lipids were measured across all laboratories and consensus location estimates and associated uncertainties were determined for 339 of these lipids measured at the sum composition level by five or more participating laboratories. These evaluated lipids detected in SRM 1950 serve as community-wide benchmarks for intra-and interlaboratory quality control and method validation. These analyses were performed using nonstandardized laboratory-independent workflows. The consensus locations were also compared with a previous examination of SRM 1950 by the LIPID MAPS consortium.jlr While the central theme of the interlaboratory study was to provide values to help harmonize lipids, lipid mediators, and precursor measurements across the community, it was also initiated to stimulate a discussion regarding areas in need of improvement.
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| 3. |
- Brockmöller, Scarlet F., et al.
(författare)
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Integration of metabolomics and expression of glycerol-3-phosphate acyltransferase (GPAM) in breast cancer-link to patient survival, hormone receptor status, and metabolic profiling
- 2012
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Ingår i: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 11:2, s. 850-60
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Tidskriftsartikel (refereegranskat)abstract
- Changes in lipid metabolism are an important but not well-characterized hallmark of cancer. On the basis of our recent findings of lipidomic changes in breast cancer, we investigated glycerol-3-phosphate acyltransferase (GPAM), a key enzyme in the lipid biosynthesis of triacylglycerols and phospholipids. GPAM protein expression was evaluated and linked to metabolomic and lipidomic profiles in a cohort of human breast carcinomas. In addition, GPAM mRNA expression was analyzed using the GeneSapiens in silico transcriptiomics database. High cytoplasmic GPAM expression was associated with hormone receptor negative status (p = 0.013). On the protein (p = 0.048) and mRNA (p = 0.001) levels, increased GPAM expression was associated with a better overall survival. Metabolomic analysis by GC-MS showed that sn-glycerol-3-phosphate, the substrate of GPAM, was elevated in breast cancer compared to normal breast tissue. LC-MS based lipidomic analysis identified significantly higher levels of phospholipids, especially phosphatidylcholines in GPAM protein positive tumors. In conclusion, our results suggest that GPAM is expressed in human breast cancer with associated changes in the cellular metabolism, in particular an increased synthesis of phospholipids, the major structural component of cellular membranes.
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| 4. |
- Budczies, Jan, et al.
(författare)
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Comparative metabolomics of estrogen receptor positive and estrogen receptor negative breast cancer : alterations in glutamine and beta-alanine metabolism
- 2013
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Ingår i: Journal of Proteomics. - : Lippincott Williams & Wilkins. - 1874-3919 .- 1876-7737. ; 94, s. 279-288
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Tidskriftsartikel (refereegranskat)abstract
- UNLABELLED: Molecular subtyping of breast cancer is necessary for therapy selection and mandatory for all breast cancer patients. Metabolic alterations are considered a hallmark of cancer and several metabolic drugs are currently being investigated in clinical trials. However, the dependence of metabolic alterations on breast cancer subtypes has not been investigated on -omics scale. Thus, 204 estrogen receptor positive (ER+) and 67 estrogen receptor negative (ER-) breast cancer tissues were investigated using GC-TOFMS based metabolomics. 19 metabolites were detected as altered in a predefined training set (2/3 of tumors) and could be validated in a predefined validation set (1/3 of tumors). The metabolite changes included increases in beta-alanine, 2-hydroyglutarate, glutamate, xanthine and decreases in glutamine in the ER- subtype. Beta-alanine demonstrated the strongest change between ER- and ER+ breast cancer (fold change=2.4, p=1.5E-20). In a correlation analysis with genome-wide expression data in a subcohort of 154 tumors, we found a strong negative correlation (Spearman R=-0.62) between beta-alanine and 4-aminobutyrate aminotransferase (ABAT). Immunohistological analysis confirmed down-regulation of the ABAT protein in ER- breast cancer. In a Kaplan-Meier analysis of a large external expression data set, the ABAT transcript was demonstrated to be a positive prognostic marker for breast cancer (HR=0.6, p=3.2E-15).BIOLOGICAL SIGNIFICANCE: It is well-known for more than a decade that breast cancer exhibits distinct gene expression patterns depending on the molecular subtype defined by estrogen receptor (ER) and HER2 status. Here, we show that breast cancer exhibits distinct metabolomics patterns depending on ER status. Our observation supports the current view of ER+ breast cancer and ER- breast as different diseases requiring different treatment strategies. Metabolic drugs for cancer including glutaminase inhibitors are currently under development and tested in clinical trials. We found glutamate enriched and glutamine reduced in ER- breast cancer compared to ER+ breast cancer and compared to normal breast tissues. Thus, metabolomics analysis highlights the ER- subtype as a preferential target for glutaminase inhibitors. For the first time, we report on a regulation of beta-alanine catabolism in cancer. In breast cancer, ABAT transcript expression was variable and correlated with ER status. Low ABAT transcript expression was associated with low ABAT protein expression and high beta-alanine concentration. In a large external microarray cohort, low ABAT expression shortened recurrence-free survival in breast cancer, ER+ breast cancer and ER- breast cancer.
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| 5. |
- Budczies, Jan, et al.
(författare)
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Remodeling of central metabolism in invasive breast cancer compared to normal breast tissue - a GC-TOFMS based metabolomics study
- 2012
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Ingår i: BMC Genomics. - : Springer Science and Business Media LLC. - 1471-2164. ; 13:1
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Changes in energy metabolism of the cells are common to many kinds of tumors and are considered a hallmark of cancer. Gas chromatography followed by time-of-flight mass spectrometry (GC-TOFMS) is a well-suited technique to investigate the small molecules in the central metabolic pathways. However, the metabolic changes between invasive carcinoma and normal breast tissues were not investigated in a large cohort of breast cancer samples so far.RESULTS: A cohort of 271 breast cancer and 98 normal tissue samples was investigated using GC-TOFMS-based metabolomics. A total number of 468 metabolite peaks could be detected; out of these 368 (79%) were significantly changed between cancer and normal tissues (p<0.05 in training and validation set). Furthermore, 13 tumor and 7 normal tissue markers were identified that separated cancer from normal tissues with a sensitivity and a specificity of >80%. Two-metabolite classifiers, constructed as ratios of the tumor and normal tissues markers, separated cancer from normal tissues with high sensitivity and specificity. Specifically, the cytidine-5-monophosphate / pentadecanoic acid metabolic ratio was the most significant discriminator between cancer and normal tissues and allowed detection of cancer with a sensitivity of 94.8% and a specificity of 93.9%.CONCLUSIONS: For the first time, a comprehensive metabolic map of breast cancer was constructed by GC-TOF analysis of a large cohort of breast cancer and normal tissues. Furthermore, our results demonstrate that spectrometry-based approaches have the potential to contribute to the analysis of biopsies or clinical tissue samples complementary to histopathology.
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| 6. |
- Denkert, Carsten, et al.
(författare)
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Metabolomics of human breast cancer : new approaches for tumor typing and biomarker discovery
- 2012
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Ingår i: Genome Medicine. - London, United Kingdom : BioMed Central (BMC). - 1756-994X. ; 4:4
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Forskningsöversikt (refereegranskat)abstract
- Breast cancer is the most common cancer in women worldwide, and the development of new technologies for better understanding of the molecular changes involved in breast cancer progression is essential. Metabolic changes precede overt phenotypic changes, because cellular regulation ultimately affects the use of small-molecule substrates for cell division, growth or environmental changes such as hypoxia. Differences in metabolism between normal cells and cancer cells have been identified. Because small alterations in enzyme concentrations or activities can cause large changes in overall metabolite levels, the metabolome can be regarded as the amplified output of a biological system. The metabolome coverage in human breast cancer tissues can be maximized by combining different technologies for metabolic profiling. Researchers are investigating alterations in the steady state concentrations of metabolites that reflect amplified changes in genetic control of metabolism. Metabolomic results can be used to classify breast cancer on the basis of tumor biology, to identify new prognostic and predictive markers and to discover new targets for future therapeutic interventions. Here, we examine recent results, including those from the European FP7 project METAcancer consortium, that show that integrated metabolomic analyses can provide information on the stage, subtype and grade of breast tumors and give mechanistic insights. We predict an intensified use of metabolomic screens in clinical and preclinical studies focusing on the onset and progression of tumor development.
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| 7. |
- Hilvo, Mika, et al.
(författare)
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Novel theranostic opportunities offered by characterization of altered membrane lipid metabolism in breast cancer progression
- 2011
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Ingår i: Cancer Research. - Philadelphia, PA, USA : American Association for Cancer Research. - 0008-5472 .- 1538-7445. ; 71:9, s. 3236-45
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Tidskriftsartikel (refereegranskat)abstract
- Activation of lipid metabolism is an early event in carcinogenesis and a central hallmark of many cancers. However, the precise molecular composition of lipids in tumors remains generally poorly characterized. The aim of the present study was to analyze the global lipid profiles of breast cancer, integrate the results to protein expression, and validate the findings by functional experiments. Comprehensive lipidomics was conducted in 267 human breast tissues using ultraperformance liquid chromatography/ mass spectrometry. The products of de novo fatty acid synthesis incorporated into membrane phospholipids, such as palmitate-containing phosphatidylcholines, were increased in tumors as compared with normal breast tissues. These lipids were associated with cancer progression and patient survival, as their concentration was highest in estrogen receptor-negative and grade 3 tumors. In silico transcriptomics database was utilized in investigating the expression of lipid metabolism related genes in breast cancer, and on the basis of these results, the expression of specific proteins was studied by immunohistochemistry. Immunohistochemical analyses showed that several genes regulating lipid metabolism were highly expressed in clinical breast cancer samples and supported also the lipidomics results. Gene silencing experiments with seven genes [ACACA (acetyl-CoA carboxylase α), ELOVL1 (elongation of very long chain fatty acid-like 1), FASN (fatty acid synthase), INSIG1 (insulin-induced gene 1), SCAP (sterol regulatory element-binding protein cleavage-activating protein), SCD (stearoyl-CoA desaturase), and THRSP (thyroid hormone-responsive protein)] indicated that silencing of multiple lipid metabolism-regulating genes reduced the lipidomic profiles and viability of the breast cancer cells. Taken together, our results imply that phospholipids may have diagnostic potential as well as that modulation of their metabolism may provide therapeutic opportunities in breast cancer treatment.
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| 8. |
- Li, Qian, et al.
(författare)
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Longitudinal Metabolome-Wide Signals Prior to the Appearance of a First Islet Autoantibody in Children Participating in the TEDDY Study
- 2020
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Ingår i: Diabetes. - : American Diabetes Association. - 1939-327X .- 0012-1797. ; 69:3, s. 465-476
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Tidskriftsartikel (refereegranskat)abstract
- Children at increased genetic risk for type 1 diabetes (T1D) after environmental exposures may develop pancreatic islet autoantibodies (IA) at a very young age. Metabolic profile changes over time may imply responses to exposures and signal development of the first IA. Our present research in The Environmental Determinants of Diabetes in the Young (TEDDY) study aimed to identify metabolome-wide signals preceding the first IA against GAD (GADA-first) or against insulin (IAA-first). We profiled metabolomes by mass spectrometry from children's plasma at 3-month intervals after birth until appearance of the first IA. A trajectory analysis discovered each first IA preceded by reduced amino acid proline and branched-chain amino acids (BCAAs), respectively. With independent time point analysis following birth, we discovered dehydroascorbic acid (DHAA) contributing to the risk of each first IA, and γ-aminobutyric acid (GABAs) associated with the first autoantibody against insulin (IAA-first). Methionine and alanine, compounds produced in BCAA metabolism and fatty acids, also preceded IA at different time points. Unsaturated triglycerides and phosphatidylethanolamines decreased in abundance before appearance of either autoantibody. Our findings suggest that IAA-first and GADA-first are heralded by different patterns of DHAA, GABA, multiple amino acids, and fatty acids, which may be important to primary prevention of T1D.
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| 9. |
- Meyer, Rhonda C, et al.
(författare)
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Heterosis manifestation during early Arabidopsis seedling development is characterized by intermediate gene expression and enhanced metabolic activity in the hybrids
- 2012
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Ingår i: The Plant Journal. - Hoboken, USA : Wiley-Blackwell. - 0960-7412 .- 1365-313X. ; 71:4, s. 669-83
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Tidskriftsartikel (refereegranskat)abstract
- Heterosis-associated cellular and molecular processes were analyzed in seeds and seedlings of Arabidopsis thaliana accessions Col-0 and C24 and their heterotic hybrids. Microscopic examination revealed no advantages in terms of hybrid mature embryo organ sizes or cell numbers. Increased cotyledon sizes were detectable 4 days after sowing. Growth heterosis results from elevated cell sizes and numbers, and is well established at 10 days after sowing. The relative growth rates of hybrid seedlings were most enhanced between 3 and 4 days after sowing. Global metabolite profiling and targeted fatty acid analysis revealed maternal inheritance patterns for a large proportion of metabolites in the very early stages. During developmental progression, the distribution shifts to dominant, intermediate and heterotic patterns, with most changes occurring between 4 and 6 days after sowing. The highest incidence of heterotic patterns coincides with establishment of size differences at 4 days after sowing. In contrast, overall transcript patterns at 4, 6 and 10 days after sowing are characterized by intermediate to dominant patterns, with parental transcript levels showing the largest differences. Overall, the results suggest that, during early developmental stages, intermediate gene expression and higher metabolic activity in the hybrids compared to the parents lead to better resource efficiency, and therefore enhanced performance in the hybrids.
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| 10. |
- Rohin Rajan, Meenu, et al.
(författare)
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Comparative analysis of obesity-related cardiometabolic and renal biomarkers in human plasma and serum.
- 2019
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Ingår i: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 9:1
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Tidskriftsartikel (refereegranskat)abstract
- The search for biomarkers associated with obesity-related diseases is ongoing, but it is not clear whether plasma and serum can be used interchangeably in this process. Here we used high-throughput screening to analyze 358 proteins and 76 lipids, selected because of their relevance to obesity-associated diseases, in plasma and serum from age- and sex-matched lean and obese humans. Most of the proteins/lipids had similar concentrations in plasma and serum, but a subset showed significant differences. Notably, a key marker of cardiovascular disease PAI-1 showed a difference in concentration between the obese and lean groups only in plasma. Furthermore, some biomarkers showed poor correlations between plasma and serum, including PCSK9, an important regulator of cholesterol homeostasis. Collectively, our results show that the choice of biofluid may impact study outcome when screening for obesity-related biomarkers and we identify several markers where this will be the case.
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