Proton NMR-Based Metabolite Analyses of Archived Serial Paired Serum and Urine Samples from Myeloma Patients at Different Stages of Disease Activity Identifies Acetylcarnitine as a Novel Marker of Active Disease

Biomarker identification is becoming increasingly important for the development of personalized or stratified therapies. Metabolomics yields biomarkers indicative of phenotype that can be used to characterize transitions between health and disease, disease progression and therapeutic responses. The...

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Published in:PloS one Vol. 8; no. 2; p. e56422
Main Authors: Lodi, Alessia, Tiziani, Stefano, Khanim, Farhat L., Günther, Ulrich L., Viant, Mark R., Morgan, Gareth J., Bunce, Christopher M., Drayson, Mark T.
Format: Journal Article
Language:English
Published: United States Public Library of Science 19.02.2013
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ISSN:1932-6203, 1932-6203
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Abstract Biomarker identification is becoming increasingly important for the development of personalized or stratified therapies. Metabolomics yields biomarkers indicative of phenotype that can be used to characterize transitions between health and disease, disease progression and therapeutic responses. The desire to reproducibly detect ever greater numbers of metabolites at ever diminishing levels has naturally nurtured advances in best practice for sample procurement, storage and analysis. Reciprocally, since many of the available extensive clinical archives were established prior to the metabolomics era and were not processed in such an 'ideal' fashion, considerable scepticism has arisen as to their value for metabolomic analysis. Here we have challenged that paradigm. We performed proton nuclear magnetic resonance spectroscopy-based metabolomics on blood serum and urine samples from 32 patients representative of a total cohort of 1970 multiple myeloma patients entered into the United Kingdom Medical Research Council Myeloma IX trial. Using serial paired blood and urine samples we detected metabolite profiles that associated with diagnosis, post-treatment remission and disease progression. These studies identified carnitine and acetylcarnitine as novel potential biomarkers of active disease both at diagnosis and relapse and as a mediator of disease associated pathologies. These findings show that samples conventionally processed and archived can provide useful metabolomic information that has important implications for understanding the biology of myeloma, discovering new therapies and identifying biomarkers potentially useful in deciding the choice and application of therapy.
AbstractList Biomarker identification is becoming increasingly important for the development of personalized or stratified therapies. Metabolomics yields biomarkers indicative of phenotype that can be used to characterize transitions between health and disease, disease progression and therapeutic responses. The desire to reproducibly detect ever greater numbers of metabolites at ever diminishing levels has naturally nurtured advances in best practice for sample procurement, storage and analysis. Reciprocally, since many of the available extensive clinical archives were established prior to the metabolomics era and were not processed in such an 'ideal' fashion, considerable scepticism has arisen as to their value for metabolomic analysis. Here we have challenged that paradigm. We performed proton nuclear magnetic resonance spectroscopy-based metabolomics on blood serum and urine samples from 32 patients representative of a total cohort of 1970 multiple myeloma patients entered into the United Kingdom Medical Research Council Myeloma IX trial. Using serial paired blood and urine samples we detected metabolite profiles that associated with diagnosis, post-treatment remission and disease progression. These studies identified carnitine and acetylcarnitine as novel potential biomarkers of active disease both at diagnosis and relapse and as a mediator of disease associated pathologies. These findings show that samples conventionally processed and archived can provide useful metabolomic information that has important implications for understanding the biology of myeloma, discovering new therapies and identifying biomarkers potentially useful in deciding the choice and application of therapy.
Background Biomarker identification is becoming increasingly important for the development of personalized or stratified therapies. Metabolomics yields biomarkers indicative of phenotype that can be used to characterize transitions between health and disease, disease progression and therapeutic responses. The desire to reproducibly detect ever greater numbers of metabolites at ever diminishing levels has naturally nurtured advances in best practice for sample procurement, storage and analysis. Reciprocally, since many of the available extensive clinical archives were established prior to the metabolomics era and were not processed in such an ‘ideal’ fashion, considerable scepticism has arisen as to their value for metabolomic analysis. Here we have challenged that paradigm. Methods We performed proton nuclear magnetic resonance spectroscopy-based metabolomics on blood serum and urine samples from 32 patients representative of a total cohort of 1970 multiple myeloma patients entered into the United Kingdom Medical Research Council Myeloma IX trial. Findings Using serial paired blood and urine samples we detected metabolite profiles that associated with diagnosis, post-treatment remission and disease progression. These studies identified carnitine and acetylcarnitine as novel potential biomarkers of active disease both at diagnosis and relapse and as a mediator of disease associated pathologies. Conclusions These findings show that samples conventionally processed and archived can provide useful metabolomic information that has important implications for understanding the biology of myeloma, discovering new therapies and identifying biomarkers potentially useful in deciding the choice and application of therapy.
BACKGROUND: Biomarker identification is becoming increasingly important for the development of personalized or stratified therapies. Metabolomics yields biomarkers indicative of phenotype that can be used to characterize transitions between health and disease, disease progression and therapeutic responses. The desire to reproducibly detect ever greater numbers of metabolites at ever diminishing levels has naturally nurtured advances in best practice for sample procurement, storage and analysis. Reciprocally, since many of the available extensive clinical archives were established prior to the metabolomics era and were not processed in such an 'ideal' fashion, considerable scepticism has arisen as to their value for metabolomic analysis. Here we have challenged that paradigm. METHODS: We performed proton nuclear magnetic resonance spectroscopy-based metabolomics on blood serum and urine samples from 32 patients representative of a total cohort of 1970 multiple myeloma patients entered into the United Kingdom Medical Research Council Myeloma IX trial. FINDINGS: Using serial paired blood and urine samples we detected metabolite profiles that associated with diagnosis, post-treatment remission and disease progression. These studies identified carnitine and acetylcarnitine as novel potential biomarkers of active disease both at diagnosis and relapse and as a mediator of disease associated pathologies. CONCLUSIONS: These findings show that samples conventionally processed and archived can provide useful metabolomic information that has important implications for understanding the biology of myeloma, discovering new therapies and identifying biomarkers potentially useful in deciding the choice and application of therapy.
Biomarker identification is becoming increasingly important for the development of personalized or stratified therapies. Metabolomics yields biomarkers indicative of phenotype that can be used to characterize transitions between health and disease, disease progression and therapeutic responses. The desire to reproducibly detect ever greater numbers of metabolites at ever diminishing levels has naturally nurtured advances in best practice for sample procurement, storage and analysis. Reciprocally, since many of the available extensive clinical archives were established prior to the metabolomics era and were not processed in such an 'ideal' fashion, considerable scepticism has arisen as to their value for metabolomic analysis. Here we have challenged that paradigm.BACKGROUNDBiomarker identification is becoming increasingly important for the development of personalized or stratified therapies. Metabolomics yields biomarkers indicative of phenotype that can be used to characterize transitions between health and disease, disease progression and therapeutic responses. The desire to reproducibly detect ever greater numbers of metabolites at ever diminishing levels has naturally nurtured advances in best practice for sample procurement, storage and analysis. Reciprocally, since many of the available extensive clinical archives were established prior to the metabolomics era and were not processed in such an 'ideal' fashion, considerable scepticism has arisen as to their value for metabolomic analysis. Here we have challenged that paradigm.We performed proton nuclear magnetic resonance spectroscopy-based metabolomics on blood serum and urine samples from 32 patients representative of a total cohort of 1970 multiple myeloma patients entered into the United Kingdom Medical Research Council Myeloma IX trial.METHODSWe performed proton nuclear magnetic resonance spectroscopy-based metabolomics on blood serum and urine samples from 32 patients representative of a total cohort of 1970 multiple myeloma patients entered into the United Kingdom Medical Research Council Myeloma IX trial.Using serial paired blood and urine samples we detected metabolite profiles that associated with diagnosis, post-treatment remission and disease progression. These studies identified carnitine and acetylcarnitine as novel potential biomarkers of active disease both at diagnosis and relapse and as a mediator of disease associated pathologies.FINDINGSUsing serial paired blood and urine samples we detected metabolite profiles that associated with diagnosis, post-treatment remission and disease progression. These studies identified carnitine and acetylcarnitine as novel potential biomarkers of active disease both at diagnosis and relapse and as a mediator of disease associated pathologies.These findings show that samples conventionally processed and archived can provide useful metabolomic information that has important implications for understanding the biology of myeloma, discovering new therapies and identifying biomarkers potentially useful in deciding the choice and application of therapy.CONCLUSIONSThese findings show that samples conventionally processed and archived can provide useful metabolomic information that has important implications for understanding the biology of myeloma, discovering new therapies and identifying biomarkers potentially useful in deciding the choice and application of therapy.
Biomarker identification is becoming increasingly important for the development of personalized or stratified therapies. Metabolomics yields biomarkers indicative of phenotype that can be used to characterize transitions between health and disease, disease progression and therapeutic responses. The desire to reproducibly detect ever greater numbers of metabolites at ever diminishing levels has naturally nurtured advances in best practice for sample procurement, storage and analysis. Reciprocally, since many of the available extensive clinical archives were established prior to the metabolomics era and were not processed in such an 'ideal' fashion, considerable scepticism has arisen as to their value for metabolomic analysis. Here we have challenged that paradigm. We performed proton nuclear magnetic resonance spectroscopy-based metabolomics on blood serum and urine samples from 32 patients representative of a total cohort of 1970 multiple myeloma patients entered into the United Kingdom Medical Research Council Myeloma IX trial. Using serial paired blood and urine samples we detected metabolite profiles that associated with diagnosis, post-treatment remission and disease progression. These studies identified carnitine and acetylcarnitine as novel potential biomarkers of active disease both at diagnosis and relapse and as a mediator of disease associated pathologies. These findings show that samples conventionally processed and archived can provide useful metabolomic information that has important implications for understanding the biology of myeloma, discovering new therapies and identifying biomarkers potentially useful in deciding the choice and application of therapy.
Audience Academic
Author Morgan, Gareth J.
Lodi, Alessia
Günther, Ulrich L.
Viant, Mark R.
Bunce, Christopher M.
Tiziani, Stefano
Khanim, Farhat L.
Drayson, Mark T.
AuthorAffiliation 3 Dell Pediatric Research Institute, The University of Texas at Austin, Austin, Texas, United States of America
1 School of Cancer Sciences, The University of Birmingham, Birmingham, United Kingdom
George Washington University, United States of America
4 School of Biosciences, The University of Birmingham, Birmingham, United Kingdom
5 Institute of Cancer Research, Royal Marsden NHS Foundation Trust, London, United Kingdom
2 Department of Nutritional Sciences, The University of Texas at Austin, Austin, Texas, United States of America
6 School of Immunity and Infection, The University of Birmingham, Birmingham, United Kingdom
AuthorAffiliation_xml – name: 2 Department of Nutritional Sciences, The University of Texas at Austin, Austin, Texas, United States of America
– name: 1 School of Cancer Sciences, The University of Birmingham, Birmingham, United Kingdom
– name: 5 Institute of Cancer Research, Royal Marsden NHS Foundation Trust, London, United Kingdom
– name: 6 School of Immunity and Infection, The University of Birmingham, Birmingham, United Kingdom
– name: 4 School of Biosciences, The University of Birmingham, Birmingham, United Kingdom
– name: George Washington University, United States of America
– name: 3 Dell Pediatric Research Institute, The University of Texas at Austin, Austin, Texas, United States of America
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  givenname: Alessia
  surname: Lodi
  fullname: Lodi, Alessia
– sequence: 2
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  surname: Tiziani
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  givenname: Farhat L.
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  surname: Günther
  fullname: Günther, Ulrich L.
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– sequence: 6
  givenname: Gareth J.
  surname: Morgan
  fullname: Morgan, Gareth J.
– sequence: 7
  givenname: Christopher M.
  surname: Bunce
  fullname: Bunce, Christopher M.
– sequence: 8
  givenname: Mark T.
  surname: Drayson
  fullname: Drayson, Mark T.
BackLink https://www.ncbi.nlm.nih.gov/pubmed/23431376$$D View this record in MEDLINE/PubMed
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ContentType Journal Article
Copyright COPYRIGHT 2013 Public Library of Science
2013 Lodi et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
2013 Lodi et al 2013 Lodi et al
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– notice: 2013 Lodi et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
– notice: 2013 Lodi et al 2013 Lodi et al
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Competing Interests: The authors have declared that no competing interests exist.
Clinical lead on Myeloma IX: GJM. Clinical investigator on Myeloma IX: MTD. Conceived and designed the experiments: AL ST FLK ULG MRV GJM CMB MTD. Performed the experiments: AL ST. Analyzed the data: AL ST FLK ULG MRV GJM CMB MTD. Contributed reagents/materials/analysis tools: ULG MRV GJM CMB MTD. Wrote the paper: AL ST FLK ULG MRV GJM CMB MTD.
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Snippet Biomarker identification is becoming increasingly important for the development of personalized or stratified therapies. Metabolomics yields biomarkers...
Background Biomarker identification is becoming increasingly important for the development of personalized or stratified therapies. Metabolomics yields...
BACKGROUND: Biomarker identification is becoming increasingly important for the development of personalized or stratified therapies. Metabolomics yields...
Background Biomarker identification is becoming increasingly important for the development of personalized or stratified therapies. Metabolomics yields...
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SubjectTerms Acetylcarnitine - blood
Acetylcarnitine - urine
Aged
Aged, 80 and over
Apoptosis
Archives
Archives & records
B cells
Best practice
Biological products
Biology
Biomarkers
Biomarkers, Tumor - blood
Biomarkers, Tumor - urine
Blood
Cancer therapies
Carnitine
Carnitine - blood
Carnitine - urine
Chemistry
Chemotherapy
Clinical Trials, Phase III as Topic
Development and progression
Diagnosis
Diagnostic imaging
Drug dosages
Fatty acids
Female
Health aspects
Humans
Magnetic resonance
Magnetic Resonance Spectroscopy
Male
Medical prognosis
Medical research
Medical treatment
Medicine
Metabolism
Metabolites
Metabolome
Metabolomics
Middle Aged
Multicenter Studies as Topic
Multiple myeloma
Multiple Myeloma - blood
Multiple Myeloma - pathology
Multiple Myeloma - therapy
Multiple Myeloma - urine
Multivariate Analysis
Neoplasm Staging
NMR
Nuclear magnetic resonance
Nuclear magnetic resonance spectroscopy
Patients
Pediatrics
Procurement
Remission
Remission Induction
Spectroscopy
Treatment Outcome
Urine
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Title Proton NMR-Based Metabolite Analyses of Archived Serial Paired Serum and Urine Samples from Myeloma Patients at Different Stages of Disease Activity Identifies Acetylcarnitine as a Novel Marker of Active Disease
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