Serum Molecular Signatures of Weight Change during Early Breast Cancer Chemotherapy

Keun, Hector C.; Sidhu, Jasmin; Pchejetski, Dimitri; Lewis, Jacqueline S.; Marconell, Helena; Patterson, Michael; Bloom, S R; Amber, Vian; Coombes, R. Charles; Stebbing, Justin

doi:10.1158/1078-0432.ccr-09-1452

Cited by 57 publications

(45 citation statements)

References 43 publications

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“…Adam et al showed that the power of a single variable in discriminating prostate cancer from normal patients could be determined by AUC, which ranges from 0.5 (no discriminating power) to 1.0 (complete separation) (34). Another study demonstrated that metabolite significance in differentiating weight gain group during early breast cancer chemotherapy could also be revealed by AUC (35).…”

Section: Fig 2 Pca Score Plots Based On the Data From (A) Rp Separamentioning

confidence: 99%

Bladder Cancer Determination Via Two Urinary Metabolites: A Biomarker Pattern Approach

Huang

Lin

Gao

et al. 2011

Molecular & Cellular Proteomics

124

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The purpose of this study was to use metabonomic profiling to identify a potential specific biomarker pattern in urine as a noninvasive bladder cancer (BC) detection strategy. A liquid chromatography-mass spectrometry based method, which utilized both reversed phase liquid chromatography and hydrophilic interaction chromatography separations, was performed, followed by multivariate data analysis to discriminate the global urine profiles of 27 BC patients and 32 healthy controls. Data from both columns were combined, and this combination proved to be effective and reliable for partial least squares-discriminant analysis. Following a critical selection criterion, several metabolites showing significant differences in expression levels were detected. Receiver operating characteristic analysis was used for the evaluation of potential biomarkers. Carnitine C9:1 and component I, were combined as a biomarker pattern, with a sensitivity and specificity up to 92.6% and 96.9%, respectively, for all patients and 90.5% and 96.9%, respectively for lowgrade BC patients. Metabolic pathways of component I and carnitine C9:1 are discussed. These results indicate that metabonomics is a practicable tool for BC diagnosis given its high efficacy and economization. The combined biomarker pattern showed better performance than single metabolite in discriminating bladder cancer

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Section: Fig 2 Pca Score Plots Based On the Data From (A) Rp Separamentioning

confidence: 99%

Bladder Cancer Determination Via Two Urinary Metabolites: A Biomarker Pattern Approach

Huang

Lin

Gao

et al. 2011

Molecular & Cellular Proteomics

124

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“…In the first validated study with human patients, as opposed to volunteers, Keun et al [79] used 600 MHz 1 H NMR to show that pre-treatment serum levels of alanine and lactate together with % body fat were predictive of weight gain in women undergoing chemotherapy treatment for breast cancer. This is important as weight gain is associated with a risk of cancer recurrence.…”

Section: Prediction Of Drug Safety Studiesmentioning

confidence: 99%

NMR-based pharmacometabonomics: A new paradigm for personalised or precision medicine

Everett

2017

Progress in Nuclear Magnetic Resonance Spectroscopy

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Metabolic profiling by NMR spectroscopy or hyphenated mass spectrometry, known as metabonomics or metabolomics, is an important tool for systemsbased approaches in biology and medicine. The experiments are typically done in a diagnostic fashion where changes in metabolite profiles are interpreted as a consequence of an intervention or event; be that a change in diet, the administration of a drug, physical exertion or the onset of a disease. By contrast, pharmacometabonomics takes a prognostic approach to metabolic profiling, in order to predict the effects of drug dosing before it occurs. Differences in predose metabolite profiles between groups of subjects are used to predict postdose differences in response to drug administration. Thus the paradigm is inverted and pharmacometabonomics is the metabolic equivalent of pharmacogenomics. Although the field is still in its infancy, it is expected that pharmacometabonomics, alongside pharmacogenomics, will assist with the delivery of personalised or precision medicine to patients, which is a critical goal of 21 st century healthcare. Highlights metabonomics or metabolomics involves metabolic profiling by NMR or MS methods  metabonomics is used in a diagnostic mode to study the effects of an intervention  pharmacometabonomics is a prognostic method to predict the effects of drugs  pharmacometabonomics is a special case of predictive metabonomics  pharmacometabonomics will help to deliver personalised medicine in the future Graphical AbstractNMR-Based Pharmacometabonomics PNMRS 2017

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“…Keun and coworkers demonstrated in 2009 that serum biomarkers could be used to predict weight gain in women undergoing chemotherapy for breast cancer. 69 This represents the first validated pharmacometabonomic study with patients as opposed to volunteers. PLS-DA analysis of 600 MHz 1 H NMR spectra of serum established that pretreatment concentrations of lactate, alanine and percentage of body fat were significantly predictive of weight gain in individuals.…”

Section: Progress In Clinical Pharmacometabonomicsmentioning

confidence: 99%

Pharmacometabonomics and personalized medicine

2013

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Background: Pharmacometabonomics is a new branch of science, first described in 2006 and defined as 'the prediction of the effects of a drug on the basis of a mathematical model of pre-dose metabolite profiles'. Pharmacometabonomics has been used to predict drug metabolism, pharmacokinetics (PK), drug safety and drug efficacy in both animals and humans and is complementary to both pharmacogenomics (PGx) and pharmacoproteomics. Methods: A literature review using the search terms pharmacometabonomics, pharmacometabolomics, pharmacometabonomics, pharmaco-metabolomics and the singular form of all those terms was conducted in October 2012 using PubMed and Web of Science. The review was updated until mid April 2013. Results: Since the original description of pharmacometabonomics in 2006, 21 original publications and eight reviews have emerged, covering a broad range of applications from the prediction of PK to the prediction of drug metabolism, efficacy and safety in humans and animals. Conclusions: Pharmacometabonomics promises to be an important new approach to the delivery of personalized medicine to improve both drug efficacy and safety for patients in the future. Pharmacometabonomics is particularly powerful as it is sensitive to both genetic and environmental factors such as diet, drug intake and most importantly, a person's microbiome. PGx is now over 50 years old and although it has not achieved as much as some hoped, it is starting to have important applications in personalized medicine. We predict that pharmacometabonomics will be equally important in the next few decades and will be both valuable in its own right and complementary to pharmacoproteomics and PGx.

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Serum Molecular Signatures of Weight Change during Early Breast Cancer Chemotherapy

Cited by 57 publications

References 43 publications

Bladder Cancer Determination Via Two Urinary Metabolites: A Biomarker Pattern Approach

Bladder Cancer Determination Via Two Urinary Metabolites: A Biomarker Pattern Approach

NMR-based pharmacometabonomics: A new paradigm for personalised or precision medicine

Pharmacometabonomics and personalized medicine

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