Plasma Metabolomic Profiles in Breast Cancer Patients and Healthy Controls: By Race and Tumor Receptor Subtypes

Shen, Jie; Yan, Li; Liu, Song; Ambrosone, Christine B.; Zhao, Hua

doi:10.1593/tlo.13619

Cited by 65 publications

(68 citation statements)

References 39 publications

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“…Surprisingly, we didn't observe lower levels of amino acids especially in the triple negative cell line MDA-MB-231 as observed in human blood plasma samples by Shen et al[40]. Ingeneral, decreased amino acid levels might be a consequence of elevated energy demand in cancer cells which might result in channeling of amino acids into the tricarboxylic acid (TCA) cycle.…”

contrasting

confidence: 56%

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Metabolic profiling of breast cancer: Differences in central metabolism between subtypes of breast cancer cell lines

Willmann

Schlimpert

Halbach

et al. 2015

Journal of Chromatography B

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contrasting

confidence: 56%

“…Significantly lower levels of amino acids have been observed in blood plasma of breast cancer patients compared to healthy volunteers, especially in triple negative patients [40]. to all other investigated cell lines (Figure 8).…”

Section: Endometabolite Analysismentioning

confidence: 86%

Metabolic profiling of breast cancer: Differences in central metabolism between subtypes of breast cancer cell lines

Willmann

Schlimpert

Halbach

et al. 2015

Journal of Chromatography B

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“…It has great promise for the discovery of novel clinical biomarkers and the elucidation of diseasespecific pathways to improve prognosis, diagnosis and therapy (Brindle et al 2002;Fiehn 2002;Madsen et al 2011;Zhang et al 2013;Shen et al 2013). Metabolomics research is mainly based on mass spectrometry (MS) and/or nuclear magnetic resonance (NMR) spectroscopy combined with multivariate statistics in order to understand and interpret the resulting data ( Van der Greef et al 1983;Nicholson et al 1999;Lindon and Nicholson 2008).…”

Section: Msmentioning

confidence: 99%

Influence of preanalytical sampling conditions on the 1H NMR metabolic profile of human blood plasma and introduction of the Standard PREanalytical Code used in biobanking

et al. 2015

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Variations in sample collection, processing and storage within the field of clinical metabolomics might hamper its effective implementation. In this study, the impact of relevant preanalytical conditions on the plasma 1 H NMR metabolic profile was examined. The biobanking community recently developed a method for coding preanalytical conditions called the Standard PREanalytical Code (SPREC). It is envisaged that SPREC will ultimately identify which samples are fit for a particular analysis, based on prior validation by a panel of experts in the respective field. In an effort to validate SPREC for 1 H NMR plasma metabolomics, we have coded the conditions used here, when possible, according to SPREC and evaluated its power to identify preanalytical conditions that affect the plasma 1 H NMR metabolic profile. From all preanalytical conditions studied, only prolonged processing delays (3 and 8 h) have a significant impact on the plasma 1 H NMR metabolic profile as compared to the reference condition (30 min). Principal component analysis shows a clear systematic shift as a function of increasing processing delay. Nevertheless, the inter-individual variation is clearly much larger than this preanalytical variation, indicating that the impact on multivariate group classification will be minimal. Nonetheless, we recommend to keep the time gap between blood collection and centrifugation similar for all samples within a study. The implementation of SPREC within clinical metabolomics allows for an appropriate sample encoding and exclusion of samples that were subjected to unwanted, interfering preanalytical conditions. Without doubt, it will contribute to the validation of 1 H NMR metabolomics in clinical, biobank and multicenter research settings.

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“…A decrease of most amino acid levels has been reported in the blood plasma of breast cancer patients [28] and different breast cancer cell lines [29]. Assuming elevated energy consumption and consequent channeling of amino acids into the TCA cycle, Val, Tyr, Phe, Trp, Met, and Leu were decreased in breast cancer in both of the two studies.…”

Section: Resultsmentioning

confidence: 85%

“…The alteration of metabolites could be a result of genetic, pathological, or environmental changes. As reported, many metabolite levels were altered in the blood plasma and urine of cancer patients or cancer cell lines [24,25,26,27,28,29,30,31]. Metabolic profiling can reveal the alteration of metabolite levels in cancer patients, and, consequently, novel biomarkers could be discovered [32].…”

Section: Introductionmentioning

confidence: 99%

Metabolic Response to XD14 Treatment in Human Breast Cancer Cell Line MCF-7

Pan

Kather

Willmann

et al. 2016

IJMS

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XD14 is a 4-acyl pyrrole derivative, which was discovered by a high-throughput virtual screening experiment. XD14 inhibits bromodomain and extra-terminal domain (BET) proteins (BRD2, BRD3, BRD4 and BRDT) and consequently suppresses cell proliferation. In this study, metabolic profiling reveals the molecular effects in the human breast cancer cell line MCF-7 (Michigan Cancer Foundation-7) treated by XD14. A three-day time series experiment with two concentrations of XD14 was performed. Gas chromatography-mass spectrometry (GC-MS) was applied for untargeted profiling of treated and non-treated MCF-7 cells. The gained data sets were evaluated by several statistical methods: analysis of variance (ANOVA), clustering analysis, principle component analysis (PCA), and partial least squares discriminant analysis (PLS-DA). Cell proliferation was strongly inhibited by treatment with 50 µM XD14. Samples could be discriminated by time and XD14 concentration using PLS-DA. From the 117 identified metabolites, 67 were significantly altered after XD14 treatment. These metabolites include amino acids, fatty acids, Krebs cycle and glycolysis intermediates, as well as compounds of purine and pyrimidine metabolism. This massive intervention in energy metabolism and the lack of available nucleotides could explain the decreased proliferation rate of the cancer cells.

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Plasma Metabolomic Profiles in Breast Cancer Patients and Healthy Controls: By Race and Tumor Receptor Subtypes

Abstract: Because of small sample size, the clinical usage of the metabolites from this study is unclear. Further validation of those significant metabolites is warranted, especially with the consideration of racial difference.

Cited by 65 publications

References 39 publications

Metabolic profiling of breast cancer: Differences in central metabolism between subtypes of breast cancer cell lines

Metabolic profiling of breast cancer: Differences in central metabolism between subtypes of breast cancer cell lines

Influence of preanalytical sampling conditions on the 1H NMR metabolic profile of human blood plasma and introduction of the Standard PREanalytical Code used in biobanking

Metabolic Response to XD14 Treatment in Human Breast Cancer Cell Line MCF-7

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