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. 2018 Aug 10;13(8):e0202045.
doi: 10.1371/journal.pone.0202045. eCollection 2018.

The Metabolomic Plasma Profile of Myeloma Patients Is Considerably Different From Healthy Subjects and Reveals Potential New Therapeutic Targets

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Free PMC article

The Metabolomic Plasma Profile of Myeloma Patients Is Considerably Different From Healthy Subjects and Reveals Potential New Therapeutic Targets

Normann Steiner et al. PLoS One. .
Free PMC article

Abstract

Introduction: Multiple myeloma (MM), a malignant plasma cell disorder, is still an incurable disease. Thus, the identification of novel therapeutic targets is of utmost importance. Here, we evaluated the peripheral blood-based metabolic profile of patients with MM.

Material & methods: Peripheral blood plasma levels of 188 endogenous metabolites, including amino acids, biogenic amines, acylcarnitines, glycerophospholipids, sphingomyelins, and hexoses were determined in patients with plasma cell dyscrasias: monoclonal gammopathy of undetermined significance, a precursor stage of MM (MGUS, n = 15), newly diagnosed MM, (NDMM, n = 32), relapsed/refractory MM (RRMM, n = 19) and in 25 healthy controls by mass spectrometry.

Results: Patients with NDMM, RRMM and MGUS have a substantially different metabolomic profile than healthy controls. The amount of eight plasma metabolites significantly differs between the NDMM and MGUS group: free carnitine, acetylcarnitine, glutamate, asymmetric dimethylarginine (ADMA) and four phosphatidylcholine (PC) species. In addition, the levels of octadecanoylcarnitine, ADMA and six PCs were significantly different between RRMM and MGUS patients. 13 different concentrations of metabolites were found between RRMM and NDMM patients (free carnitine, acetylcarnitine, creatinine, five LysoPCs and PCs). Pathway analyses revealed a distinct metabolic profile with significant alterations in amino acid, lipid, and energy metabolism in healthy volunteers compared to MGUS/MM patients.

Conclusion: We identified different metabolic profiles in MGUS und MM patients in comparison to healthy controls. Thus, different metabolic processes, potentially the immunoregulation by indoleamine 2,3 dioxygenase-1 (IDO), which is involved in cancer development and progression supporting inflammatory processes in the tumor microenvironment and glutaminolysis, can serve as novel promising therapeutic targets in MM.

Conflict of interest statement

We have the following interests. Müller Udo is employed by Biocrates Life Sciences AG. There are no patents, products in development or marketed products to declare. This does not alter the authors’ adherence to all the PLOS ONE policies on sharing data and materials, as detailed online in the guide for authors.

Figures

Fig 1
Fig 1. Multivariate PLS-DA of the metabolomic dataset. MM patients versus healthy controls.
PLS-DA was applied on the cleaned, imputed and log2 transformed data set. 95% confidence interval ellipses are shown for the different groups.
Fig 2
Fig 2. Multivariate PLS-DA of the metabolomic dataset. Separation between MGUS-, NDMM- and RRMM patients.
PLS-DA was applied on the cleaned, imputed and log2 transformed data set. 95% confidence interval ellipses are shown for the different groups.
Fig 3
Fig 3
A) Pathways representation of significantly altered metabolites between healthy controls and NDMM. B) Pathways representation of significantly altered metabolites between healthy controls and MGUS. C) Pathways representation of significantly altered metabolites between healthy controls and RRMM. D) Pathways representation of significantly altered metabolites between MGUS and NDMM. E) Pathways representation of significantly altered metabolites between MGUS and RRMM. F) Pathways representation of significantly altered metabolites between NDMM and RRMM. Measured metabolites of the different pathways including glycolysis, TCA-Cycle and Urea Cycle are shown in circles. Statistically significant single metabolites or metabolites within a specific biochemical class (LysoPCs, PCs, Sphingomyelins, Acylcarnitines) are highlighted in blue and red.

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Grant support

The authors received no specific funding for this work. Biocrates Life Sciences AG provided support in the form of salaries for author Müller Udo, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific role of this author is articulated in the ‘author contributions’ section.
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