Altered bone marrow (BM) plasma amino acid (AA) composition reflects microenvironmental remodeling in patients with multiple myeloma (MM) compared to monoclonal gammopathy of unknown significance (MGUS)

Abstract Altered Bone Marrow (BM) Plasma Amino Acid (AA) Composition Reflects Microenvironmental Remodeling in Patients with Multiple Myeloma (MM) compared to Monoclonal Gammopathy of Unknown Significance (MGUS) Michael Egan, Yogesh Chawla, Puja Dey, Dragan Jevremovic, Taro Hitosugi, Shaji Kumar and Wilson Gonsalves BACKGROUND: MYC overexpression, a hallmark of progression from MGUS to MM, drives metabolic reprogramming, including enhanced AA uptake and utilization. However, the contribution of AAs to disease progression from MGUS to MM remains poorly defined. In this study, we comprehensively profiled AA levels in the BM plasma of MGUS and MM patients to determine whether shifts in the availability of specific AAs reflect microenvironmental remodeling and evolving metabolic demands of malignant plasma cells (PCs). METHODS: AA profiles of BM plasma samples—reflective of the BM microenvironment—from two different cohorts of patients with either MGUS or MM (Cohort #1: 49 MGUS and 50 newly diagnosed MM (NDMM) and Cohort #2: 50 MGUS and 64 NDMM) were acquired using liquid chromatography (LC) coupled with tandem mass spectrometry (MS). Individual AA were quantified by MS using single-point quantification with isotopically labeled internal standards of AAs. Individual relative and quantitative AA data were analyzed for differences between the groups using the parametric t-test, and significance was defined as p < 0.05. We utilized a Pearson correlation coefficient method to determine the association of the percentage of clonal PCs in the BM to the levels of the AAs. The areas under the curve (AUC) of receiver operating characteristic (ROC) analyses were created on the web-based tool MetaboAnalyst 6.0 to determine the ability of quantitative AA levels to be utilized as a model to distinguish MGUS vs. MM. RESULTS: In BM plasma samples from cohort #1, using a global untargeted metabolite profiling, we identified 28 AAs and their metabolites out of the 1,089 known metabolites detected. A targeted quantification of these AAs was performed in the same samples to validate any observed differences between the groups. Both aspartate and glycine were found to be more abundant in NDMM compared to MGUS in both untargeted and targeted assays. In contrast,12 AAs (branched chain AAs: valine, leucine and isoleucine, aromatic AAs: tryptophan, kynurenine, tyrosine and phenylalanine; essential AAs: threonine and lysine; non-essential AAs: ornithine, citrulline and asparagine) were found to be less abundant in NDMM compared to MGUS. We then validated the presence of these differences using targeted quantification of AAs in the BM plasma samples from cohort #2. Aspartate was the only AA consistently found to be present at higher levels in NDMM vs. MGUS. Whereas, 8 AAs—threonine, valine, citrulline, tyrosine, tryptophan, isoleucine, phenylalanine, and kynurenine—were consistently lower in NDMM vs. MGUS. We observed a statistically significant positive correlation between the concentration of aspartate and the percentage of clonal PCs present in the BM (r = 0.56). In contrast, there were statistically significant negative correlations between the concentrations of all 8 AAs consistently lower in NDMM vs. MGUS and the percentage of clonal PCs in the BM: threonine (r = -0.41), valine (r = -0.35), citrulline (r = -0.37), tyrosine (r = -0.28), tryptophan (r = -0.31), isoleucine (r = -0.21), phenylalanine (r = -0.19), and kynurenine (r = -0.19). Using only the quantitative concentrations of the 9 AAs that were significantly different between NDMM and MGUS across both patient cohorts, we performed ROC analyses to develop predictive models distinguishing NDMM from MGUS. In cohort #1, the models yielded AUC values ranging from 0.738 to 0.785, while in cohort #2, AUC values ranged from 0.798 to 0.835, depending on the number of AAs included in the model. CONCLUSIONS: Several AAs are present at significantly different levels in the BM plasma of patients with NDMM compared to MGUS. These findings support the emerging role of AA availability, across a diverse set of AAs, in the pathogenesis and progression of MGUS to MM. Future studies are warranted to validate these observations and to determine whether alterations in the BM AA landscape can be leveraged for diagnostic or therapeutic strategies.

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Publication Details

Journal
Blood
Published
2025-11-03
DOI
https://doi.org/10.1182/blood-2025-2149
Primary Topic
Multiple Myeloma Research and Treatments
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article
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article

Altered bone marrow (BM) plasma amino acid (AA) composition reflects microenvironmental remodeling in patients with multiple myeloma (MM) compared to monoclonal gammopathy of unknown significance (MGUS)

Blood
Multiple Myeloma Research and Treatments
article

Altered bone marrow (BM) plasma amino acid (AA) composition reflects microenvironmental remodeling in patients with multiple myeloma (MM) compared to monoclonal gammopathy of unknown significance (MGUS)

article en

Abstract

Abstract Altered Bone Marrow (BM) Plasma Amino Acid (AA) Composition Reflects Microenvironmental Remodeling in Patients with Multiple Myeloma (MM) compared to Monoclonal Gammopathy of Unknown Significance (MGUS) Michael Egan, Yogesh Chawla, Puja Dey, Dragan Jevremovic, Taro Hitosugi, Shaji Kumar and Wilson Gonsalves BACKGROUND: MYC overexpression, a hallmark of progression from MGUS to MM, drives metabolic reprogramming, including enhanced AA uptake and utilization. However, the contribution of AAs to disease progression from MGUS to MM remains poorly defined. In this study, we comprehensively profiled AA levels in the BM plasma of MGUS and MM patients to determine whether shifts in the availability of specific AAs reflect microenvironmental remodeling and evolving metabolic demands of malignant plasma cells (PCs). METHODS: AA profiles of BM plasma samples—reflective of the BM microenvironment—from two different cohorts of patients with either MGUS or MM (Cohort #1: 49 MGUS and 50 newly diagnosed MM (NDMM) and Cohort #2: 50 MGUS and 64 NDMM) were acquired using liquid chromatography (LC) coupled with tandem mass spectrometry (MS). Individual AA were quantified by MS using single-point quantification with isotopically labeled internal standards of AAs. Individual relative and quantitative AA data were analyzed for differences between the groups using the parametric t-test, and significance was defined as p < 0.05. We utilized a Pearson correlation coefficient method to determine the association of the percentage of clonal PCs in the BM to the levels of the AAs. The areas under the curve (AUC) of receiver operating characteristic (ROC) analyses were created on the web-based tool MetaboAnalyst 6.0 to determine the ability of quantitative AA levels to be utilized as a model to distinguish MGUS vs. MM. RESULTS: In BM plasma samples from cohort #1, using a global untargeted metabolite profiling, we identified 28 AAs and their metabolites out of the 1,089 known metabolites detected. A targeted quantification of these AAs was performed in the same samples to validate any observed differences between the groups. Both aspartate and glycine were found to be more abundant in NDMM compared to MGUS in both untargeted and targeted assays. In contrast,12 AAs (branched chain AAs: valine, leucine and isoleucine, aromatic AAs: tryptophan, kynurenine, tyrosine and phenylalanine; essential AAs: threonine and lysine; non-essential AAs: ornithine, citrulline and asparagine) were found to be less abundant in NDMM compared to MGUS. We then validated the presence of these differences using targeted quantification of AAs in the BM plasma samples from cohort #2. Aspartate was the only AA consistently found to be present at higher levels in NDMM vs. MGUS. Whereas, 8 AAs—threonine, valine, citrulline, tyrosine, tryptophan, isoleucine, phenylalanine, and kynurenine—were consistently lower in NDMM vs. MGUS. We observed a statistically significant positive correlation between the concentration of aspartate and the percentage of clonal PCs present in the BM (r = 0.56). In contrast, there were statistically significant negative correlations between the concentrations of all 8 AAs consistently lower in NDMM vs. MGUS and the percentage of clonal PCs in the BM: threonine (r = -0.41), valine (r = -0.35), citrulline (r = -0.37), tyrosine (r = -0.28), tryptophan (r = -0.31), isoleucine (r = -0.21), phenylalanine (r = -0.19), and kynurenine (r = -0.19). Using only the quantitative concentrations of the 9 AAs that were significantly different between NDMM and MGUS across both patient cohorts, we performed ROC analyses to develop predictive models distinguishing NDMM from MGUS. In cohort #1, the models yielded AUC values ranging from 0.738 to 0.785, while in cohort #2, AUC values ranged from 0.798 to 0.835, depending on the number of AAs included in the model. CONCLUSIONS: Several AAs are present at significantly different levels in the BM plasma of patients with NDMM compared to MGUS. These findings support the emerging role of AA availability, across a diverse set of AAs, in the pathogenesis and progression of MGUS to MM. Future studies are warranted to validate these observations and to determine whether alterations in the BM AA landscape can be leveraged for diagnostic or therapeutic strategies.

BloodVol. 146(Supplement 1)
Mayo Clinic (US), Berkeley College (US), Molecular Sciences Institute (US)
Openalex Percentile: Top 28%
Multiple Myeloma Research and Treatments
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