A roadmap for interpreting 13 C metabolite labeling patterns from cells

Buescher, Joerg M.; Antoniewicz, Maciek R.; Boros, László G.; Burgess, Shawn C.; Brunengraber, Henri; Clish, Clary B.; DeBerardinis, Ralph J.; Feron, Olivier; Frezza, Christian; Ghesquière, Bart; Gottlieb, Eyal; Hiller, Karsten; Jones, Russell G.; Kamphorst, Jurre J.; Kibbey, Richard G.; Kimmelman, Alec C.; Locasale, Jason W.; Lunt, Sophia Y.; Maddocks, Oliver D.K.; Malloy, Craig R.; Metallo, Christian M.; Meuillet, Emmanuelle J.; Munger, Joshua; Nöh, Katharina; Rabinowitz, Joshua D.; Ralser, Markus; Sauer, Uwe; Stephanopoulos, Gregory; St-Pierre, Julie; Tennant, Daniel A.; Wittmann, Christoph; Heiden, Matthew G. Vander; Vázquez, Alexei; Vousden, Karen H.; Young, Jamey D.; Zamboni, Nicola; Fendt, Sarah-Maria

doi:10.1016/j.copbio.2015.02.003

Cited by 555 publications

(579 citation statements)

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“…To test this hypothesis, we first confirmed the PPP activity increase in PTL-treated AML cells by a second set of labeling experiments using the duallabeled [ 13 C 1,2 ]glucose. In this particular experiment, because one carbon atom is lost in the form of CO 2 during glucose oxidation steps through the PPP (38), the Mϩ1 isotopologue of [ 13 C]glyceraldehyde 3-phosphate is exclusively generated by glucose flux through the PPP, not glycolysis. Thus, the level of the Mϩ1 isotopologue represents the PPP activity.…”

Section: Identification Of the Proteomic Interactome Of Ptl In Primarymentioning

confidence: 99%

“…Calibration was performed before each analysis against positive or negative ion mode calibration mixes (Thermo Fisher Scientific) to ensure sub-ppm error on the intact mass. Upon conversion of .raw files into .mzXML format using MassMatrix, metabolite, and isotopologue assignments were performed using the software Maven following the rationale described by Buescher et al (38). Assignments were further confirmed by chemical formula determination from isotopic patterns and accurate intact mass and retention times against over 650 standards, including commercially available glycolytic and Krebs cycle intermediates, amino acids, glutathione intermediates, and nucleoside phosphates (Sigma, IROATech).…”

Section: Lc-ms/ms-based Identification Of the Proteomicmentioning

confidence: 99%

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Rational Design of a Parthenolide-based Drug Regimen That Selectively Eradicates Acute Myelogenous Leukemia Stem Cells

Pei¹,

Minhajuddin²,

D’Alessandro

et al. 2016

Journal of Biological Chemistry

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Although multidrug approaches to cancer therapy are common, few strategies are based on rigorous scientific principles. Rather, drug combinations are largely dictated by empirical or clinical parameters. In the present study we developed a strategy for rational design of a regimen that selectively targets human acute myelogenous leukemia (AML) stem cells. As a starting point, we used parthenolide, an agent shown to target critical mechanisms of redox balance in primary AML cells. Next, using proteomic, genomic, and metabolomic methods, we determined that treatment with parthenolide leads to induction of compensatory mechanisms that include up-regulated NADPH production via the pentose phosphate pathway as well as activation of the Nrf2-mediated oxidative stress response pathway. Using this knowledge we identified 2-deoxyglucose and temsirolimus as agents that can be added to a parthenolide regimen as a means to inhibit such compensatory events and thereby further enhance eradication of AML cells. We demonstrate that the parthenolide, 2-deoxyglucose, temsirolimus (termed PDT) regimen is a potent means of targeting AML stem cells but has little to no effect on normal stem cells. Taken together our findings illustrate a comprehensive approach to designing combination anticancer drug regimens.Numerous studies have documented the biological complexity of human tumor cell populations in which genetic, epigenetic, biochemical, and metabolic properties can often be quite heterogeneous (1, 2). As a result, complicated multidrug regimens are often employed to target various components of tumor biology and/or acquired drug resistance (3, 4). However, the rationale behind the design of multidrug regimens is usually inconsistent and often driven by pragmatism more than scientific rigor. Thus, establishing more effective means by which to identify optimal drug regimens is an important priority, particularly with the recent emergence of a broad range of targeted agents.

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Section: Identification Of the Proteomic Interactome Of Ptl In Primarymentioning

confidence: 99%

Section: Lc-ms/ms-based Identification Of the Proteomicmentioning

confidence: 99%

Rational Design of a Parthenolide-based Drug Regimen That Selectively Eradicates Acute Myelogenous Leukemia Stem Cells

Pei¹,

Minhajuddin²,

D’Alessandro

et al. 2016

Journal of Biological Chemistry

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“…Changes in the metabolic fate of glucose can be described by the fractional contribution (FC) of 13 C from 13 C 6 -glucose to citrate [FC(citrate)] or to lactate [FC(lactate)] (Buescher et al, 2015). FC(citrate) and FC(lactate) were calculated based on a mass distribution vector (MDV) describing the enrichment of each isotopomer (Fig.…”

mentioning

confidence: 99%

Rewiring of embryonic glucose metabolism via suppression of PFK-1 and aldolase during mouse chorioallantoic branching

Miyazawa¹,

Yamaguchi²,

Honda³

et al. 2017

Journal of Cell Science

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Adapting the energy metabolism state to changing bioenergetic demands is essential for mammalian development accompanying massive cell proliferation and cell differentiation. However, it remains unclear how developing embryos meet the changing bioenergetic demands during the chorioallantoic branching (CB) stage, when the maternal-fetal exchange of gases and nutrients is promoted. In this study, using metabolome analysis with mass-labeled glucose, we found that developing embryos redirected glucose carbon flow into the pentose phosphate pathway via suppression of the key glycolytic enzymes PFK-1 and aldolase during CB. Concomitantly, embryos exhibited an increase in lactate pool size and in the fractional contribution of glycolysis to lactate biosynthesis. Imaging mass spectrometry visualized lactate-rich tissues, such as the dorsal or posterior neural tube, somites and head mesenchyme. Furthermore, we found that the heterochronic gene Lin28a could act as a regulator of the metabolic changes observed during CB. Perturbation of glucose metabolism rewiring by suppressing Lin28a downregulation resulted in perinatal lethality. Thus, our work demonstrates that developing embryos rewire glucose metabolism following CB for normal development.

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“…Multiplex assays of 4 serum-based metabolite classifiers consisting of xylose, glutamate, aspartate and one unknown [Bin_225393] yielded accuracies of 66.9% and 72.7% in the discovery and test sets, respectively [4]. While these results are very encouraging, their performance may not be purely a reflection of cancer, given that metabolites such glutamate are also elevated in other pathologies and co-morbidities, such as diabetes [18,19]. Thus, in the case of glutamate, its value as a lung cancer-specific serum biomarker may hold very limited value when screening the general population.…”

Section: Commentarymentioning

confidence: 99%

N1,N12-Diacetylspermine as a Blood Based Lung Cancer Biomarker

Fahrmann¹,

Hanash²

2016

Biochem Anal Biochem

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It is becoming well recognized that metabolic perturbations are inherent hallmarks of tumorigenesis [1,2]. Metabolites represent the functional products of cellular processes, which are highly responsive to both pathological and environmental stimuli. As such, metabolites are the closest representation of an individual's current physiological state. Therefore, exploration of metabolic alterations in the context of disease pathophysiology, most notably cancer, holds great promise and considerable clinical value. This field of research has benefited from technological advances in mass spectrometry and ultraviolet-visible spectroscopic analyses that have enabled comprehensive metabolomic analyses of diverse arrays of metabolites, polyphenols and lipids in a variety of biological matrices with substantial robustness and sensitivity [3][4][5][6][7][8][9]. As a result, interest in the application of metabolomics to identify key metabolic differences related to pathological conditions has expanded. Indeed, metabolomics has been explored to gain insights into the pathophysiology of cancer, develop methods predictive of disease onset, and reveal new biomarkers relevant to disease diagnosis and prognosis [4-6] [10-12].The application of metabolomics to the discovery of blood-based biomarker in cancer has substantial potential clinical relevance. Recently, we have identified the polyamine end-product N1, N12-diacetylspermine (DAS) as a novel pre-diagnostic serum biomarker for non-small cell lung cancer (NSCLC) [6]. In this study, DAS alone yielded an AUC of 0.610 and AUC 0.710 for sera collected 6 to 12 months and 0 to 6 months before onset of symptoms and diagnosis, respectively, in the discovery set. These findings were subsequently confirmed in an independent and blinded validation set [6]. Single markers are unlikely to exhibit sufficient performance to be fully informative of disease status. Therefore in our study we examined the performance of DAS in combination with another marker Pro-SFTPB, which we previously validated as a blood based marker for NSCLC [13]. The combination of DAS and Pro-SFTPB resulted in improved performance compared to either alone (Overall AUCs of 0.732, 0.650 and 0.699 in the validation set for Pro-SFTPB + DAS, DAS only and Pro-SFTPB only, respectively) [6]. This study highlights the potential contributions of metabolomics to the discovery of biomarkers that inform about disease risk before the onset of symptoms and, importantly, illustrates the value of DAS as a complementary non-invasive biomarker. While the latter findings implicate that DAS is not specific to lung cancer, it does highlight conserved metabolic dysregulation of polyamine biosynthesis, which is strongly associated with tumorigenesis [15,16]. However, one caveat that must always be considered is whether serum or urinary DAS differs between malignant and benign tumors. This is particularly relevant in lung cancer as screening methodologies have been largely hindered by high false positive rates, a consequence of the low preval...

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A roadmap for interpreting 13 C metabolite labeling patterns from cells

Cited by 555 publications

References 100 publications

Rational Design of a Parthenolide-based Drug Regimen That Selectively Eradicates Acute Myelogenous Leukemia Stem Cells

Rational Design of a Parthenolide-based Drug Regimen That Selectively Eradicates Acute Myelogenous Leukemia Stem Cells

Rewiring of embryonic glucose metabolism via suppression of PFK-1 and aldolase during mouse chorioallantoic branching

N1,N12-Diacetylspermine as a Blood Based Lung Cancer Biomarker

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