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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| 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. |
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| AbstractList | 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. 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. 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 |
| Author_xml | – sequence: 1 givenname: Alessia surname: Lodi fullname: Lodi, Alessia – sequence: 2 givenname: Stefano surname: Tiziani fullname: Tiziani, Stefano – sequence: 3 givenname: Farhat L. surname: Khanim fullname: Khanim, Farhat L. – sequence: 4 givenname: Ulrich L. surname: Günther fullname: Günther, Ulrich L. – sequence: 5 givenname: Mark R. surname: Viant fullname: Viant, Mark R. – 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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| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 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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| 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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