Analysis of the Metabolic Characteristics of Serum Samples in Patients With Multiple Myeloma

Metabolomics for hematologic malignancies: Advances and perspective

With the use of advanced technology, metabolomics allows for a thorough examination of metabolites and other small molecules found in biological specimens, blood, and tissues. In recent years, metabolomics has been recognized that is closely related to the development of malignancies in the hematological system. Alterations in metabolomic pathways and networks are important in the pathogenesis of hematologic malignancies and can also provide a theoretical basis for early diagnosis, efficacy evaluation, accurate staging, and individualized targeted therapy. In this review, we summarize the progress of metabolomics, including glucose metabolism, amino acid metabolism, and lipid metabolism in lymphoma, myeloma, and leukemia through specific mechanisms and pathways. The research of metabolomics gives a new insight and provides therapeutic targets for the treatment of patients with hematologic malignancies.

Metabolomic biomarkers of multiple myeloma: A systematic review

Multiple myeloma (MM) is an incurable malignancy of clonal plasma cells. Various diagnostic methods are used in parallel to accurately determine stage and severity of the disease. Identifying a biomarker or a panel of biomarkers could enhance the quality of medical care that patients receive by adopting a more personalized approach. Metabolomics utilizes high-throughput analytical platforms to examine the levels and quantities of biochemical compounds in biosamples. The aim of this review was to conduct a systematic literature search for potential metabolic biomarkers that may aid in the diagnosis and prognosis of MM. The review was conducted in accordance with PRISMA recommendations and was registered in PROSPERO. The systematic search was performed in PubMed, CINAHL, SciFinder, Scopus, The Cochrane Library and Google Scholar. Studies were limited to those involving people with clinically diagnosed MM and healthy controls as comparators. Articles had to be published in English and had no restrictions on publication date or sample type. The quality of articles was assessed according to QUADOMICS criteria. A total of 709 articles were collected during the literature search. Of these, 436 were excluded based on their abstract, with 26 more removed after a thorough review of the full text. Finally, 16 articles were deemed relevant and were subjected to further analysis of their data. A number of promising candidate biomarkers was discovered. Follow-up studies with large sample sizes are needed to determine their suitability for clinical applications.

Phenylalanine deprivation inhibits multiple myeloma progression by perturbing endoplasmic reticulum homeostasis

Amino acid metabolic remodeling is a hallmark of cancer, driving an increased nutritional demand for amino acids. Amino acids are pivotal for energetic regulation, biosynthetic support, and homeostatic maintenance to stimulate cancer progression. However, the role of phenylalanine in multiple myeloma (MM) remains unknown. Here, we demonstrate that phenylalanine levels in MM patients are decreased in plasma but elevated in bone marrow (BM) cells. After the treatment, phenylalanine levels increase in plasma and decrease in BM. This suggests that changes in phenylalanine have diagnostic value and that phenylalanine in the BM microenvironment is an essential source of nutrients for MM progression. The requirement for phenylalanine by MM cells exhibits a similar pattern. Inhibiting phenylalanine utilization suppresses MM cell growth and provides a synergistic effect with Bortezomib (BTZ) treatment in vitro and murine models. Mechanistically, phenylalanine deprivation induces excessive endoplasmic reticulum stress and leads to MM cell apoptosis through the ATF3-CHOP-DR5 pathway. Interference with ATF3 significantly affects phenylalanine deprivation therapy. In conclusion, we have identified phenylalanine metabolism as a characteristic feature of MM metabolic remodeling. Phenylalanine is necessary for MM proliferation, and its aberrant demand highlights the importance of low-phenylalanine diets as an adjuvant treatment for MM.

Enzyme-mediated depletion of methylthioadenosine restores T cell function in MTAP-deficient tumors and reverses immunotherapy resistance

Chromosomal region 9p21 containing tumor suppressors CDKN2A/B and methylthioadenosine phosphorylase (MTAP) is one of the most frequent genetic deletions in cancer. 9p21 loss is correlated with reduced tumor-infiltrating lymphocytes (TILs) and resistance to immune checkpoint inhibitor (ICI) therapy. Previously thought to be caused by CDKN2A/B loss, we now show that it is loss of MTAP that leads to poor outcomes on ICI therapy and reduced TIL density. MTAP loss causes accumulation of methylthioadenosine (MTA) both intracellularly and extracellularly and profoundly impairs T cell function via the inhibition of protein arginine methyltransferase 5 (PRMT5) and by adenosine receptor agonism. Administration of MTA-depleting enzymes reverses this immunosuppressive effect, increasing TILs and drastically impairing tumor growth and importantly, synergizes well with ICI therapy. As several studies have shown ICI resistance in 9p21/MTAP null/low patients, we propose that MTA degrading therapeutics may have substantial therapeutic benefit in these patients by enhancing ICI effectiveness.

Serum NMR-Based Metabolomics Profiling Identifies Lipoprotein Subfraction Variables and Amino Acid Reshuffling in Myeloma Development and Progression

Multiple myeloma (MM) is an incurable hematological cancer. It is preceded by monoclonal gammopathy of uncertain significance (MGUS)-an asymptomatic phase. It has been demonstrated that early detection increases the 5-year survival rate. However, blood-based biomarkers that enable early disease detection are lacking. Metabolomic and lipoprotein subfraction variable profiling is gaining traction to expand our understanding of disease states and, more specifically, for identifying diagnostic markers in patients with hematological cancers. This study aims to enhance our understanding of multiple myeloma (MM) and identify candidate metabolites, allowing for a more effective preventative treatment. Serum was collected from 25 healthy controls, 20 patients with MGUS, and 30 patients with MM. 1H-NMR (Nuclear Magnetic Resonance) spectroscopy was utilized to evaluate serum samples. The metabolite concentrations were examined using multivariate, univariate, and pathway analysis. Metabolic profiles of the MGUS patients revealed lower levels of alanine, lysine, leucine but higher levels of formic acid when compared to controls. However, metabolic profiling of MM patients, compared to controls, exhibited decreased levels of total Apolipoprotein-A1, HDL-4 Apolipoprotein-A1, HDL-4 Apolipoprotein-A2, HDL Free Cholesterol, HDL-3 Cholesterol and HDL-4 Cholesterol. Lastly, metabolic comparison between MGUS to MM patients primarily indicated alterations in lipoproteins levels: Total Cholesterol, HDL Cholesterol, HDL Free Cholesterol, Total Apolipoprotein-A1, HDL Apolipoprotein-A1, HDL-4 Apolipoprotein-A1 and HDL-4 Phospholipids. This study provides novel insights into the serum metabolic and lipoprotein subfraction changes in patients as they progress from a healthy state to MGUS to MM, which may allow for earlier clinical detection and treatment.

Simultaneous quantitation of multiple myeloma related dietary metabolites in serum using HILIC-LC-MS/MS

Background

Recent studies from targeted and untargeted metabolomics have consistently revealed that diet-related metabolites, including carnitine (C0), several species of acylcarnitines (AcyCNs), amino acids, ceramides, and lysophosphatidylcholines (LPCs) may serve as potential multiple myeloma (MM) biomarkers. However, most of these approaches had some intrinsic limitations, namely low reproducibility and compromising the accuracy of the results.

Objective

This study developed and validated a precise, efficient, and reliable liquid chromatography tandem mass spectrometric (LC-MS/MS) method for measuring these 28 metabolic risk factors in human serum.

Design

This method employed isopropanol to extract the metabolites from serum, gradient elution on a hydrophilic interaction liquid chromatographic column (HILIC) for chromatographic separation, and multiple reaction monitor (MRM) mode with positive electrospray ionization (ESI) for mass spectrometric detection.

Results

The correlation coefficients of linear response for this method were more than 0.9984. Analytical recoveries ranged from 91.3 to 106.3%, averaging 99.5%. The intra-run and total coefficients of variation were 1.1-5.9% and 2.0-9.6%, respectively. We have simultaneously determined the serological levels of C0, several subclasses of AcyCNs, amino acids, ceramides, and LPCs within 15 min for the first time.

Conclusion

The established LC-MS/MS method was accurate, sensitive, efficient, and could be valuable in providing insights into the association between diet patterns and MM disease and added value in further clinical research.

High expression of VARS promotes the growth of multiple myeloma cells by causing imbalance in valine metabolism

OBJECTIVES

Multiple myeloma (MM) is a plasma cell malignancy occurring in middle and old age. MM is still an incurable disease due to its frequent recurrence and drug resistance. However, its pathogenesis is still unclear. Abnormal amino acid metabolism is one of the important characteristics of MM, and the important metabolic pathway of amino acids participates in protein synthesis as basic raw materials. Aminoacyl transfer ribonucleic acid synthetase (ARS) gene is a key regulatory gene in protein synthesis. This study aims to explore the molecular mechanism for ARS, a key factor of amino acid metabolism, in regulating amino acid metabolism in MM and affecting MM growth.

METHODS

The corresponding gene number was combined with the gene expression profile GSE5900 dataset and GSE2658 dataset in Gene Expression Omnibus (GEO) database to standardize the gene expression data of ARS. GSEA_4.2.0 software was used to analyze the difference of gene enrichment between healthy donors (HD) and MM patients in GEO database. GraphPad Prism 7 was used to draw heat maps and perform data analysis. Kaplan-Meier and Cox regression model were used to analyze the expression of ARS gene and the prognosis of MM patients, respectively. Bone marrow samples from 7 newly diagnosed MM patients were collected, CD138+ and CD138- cells were obtained by using CD138 antibody magnetic beads, and the expression of ARS in MM clinical samples was analyzed by real-time RT-PCR. Human B lymphocyte GM12878 cells and human MM cell lines ARP1, NCI-H929, OCI-MY5, U266, RPMI 8266, OPM-2, JJN-3, KMS11, MM1.s cells were selected as the study objects. The expression of ARS in MM cell lines was analyzed by real-time RT-PCR and Western blotting. Short hairpin RNA (shRNA) lentiviruses were used to construct gene knock-out plasmids (VARS-sh group). No-load plasmids (scramble group) and gene knock-out plasmids (VARS-sh group) were transfected into HEK 293T cells with for virus packaging, respectively. Stable expression cell lines were established by infecting ARP1 and OCI-MY5 cells, and the effects of knockout valyl-tRNA synthetase (VARS) gene on proliferation and apoptosis of MM cells were detected by cell counting and flow cytometry, respectively. GEO data were divided into a high expression group and a low expression group according to the expression of VARS. Bioinformatics analysis was performed to explore the downstream pathways affected by VARS. Gas chromatography time-of-flight mass spectrometry (GC-TOF/MS) and high performance liquid chromatography (HPLC) were used to detect the valine content in CD138+ cells and ARP1, OCI-MY5 cells and supernatant of knockdown VARS gene in bone marrow samples from patients, respectively.

RESULTS

Gene enrichment analysis showed that tRNA processing related genes were significantly enriched in MM compared with HD (P<0.0001). Further screening of tRNA processing-pathway related subsets revealed that cytoplasmic aminoacyl tRNA synthetase family genes were significantly enriched in MM (P<0.0001). The results of gene expression heat map showed that the ARS family genes except alanyl-tRNA synthetase (AARS), arginyl-tRNA synthetase (RARS), seryl-tRNA synthetase (SARS) in GEO data were highly expressed in MM (all P<0.01). With the development of monoclonal gammopathy of undetermined significance (MGUS) to MM, the gene expression level was increased gradually. Kaplan-Meier univariate analysis of survival results showed that there were significant differences in the prognosis of MM patients in methionyl-tRNA synthetase (MARS), asparaginyl-tRNA synthetase (NARS) and VARS between the high expression group and the low expression group (all P<0.05). Cox regression model multivariate analysis showed that the high expression of VARS was associated with abnormal overall survival time of MM (HR=1.83, 95% CI 1.10 to 3.06, P=0.021). The high expression of NARS (HR=0.90, 95% CI 0.34 to 2.38) and MARS (HR=1.59, 95% CI 0.73 to 3.50) had no effect on the overall survival time of MM patients (both P>0.05). Real-time RT-PCR and Western blotting showed that VARS, MARS and NARS were highly expressed in CD138+ MM cells and MM cell lines of clinical patients (all P<0.05). Cell counting and flow cytometry results showed that the proliferation of MM cells by knockout VARS was significantly inhibited (P<0.01), the proportion of apoptosis was significantly increased (P<0.05). Bioinformatics analysis showed that in addition to several pathways including the cell cycle regulated by VARS, the valine, leucine and isoleucine catabolic pathways were upregulated. Non-targeted metabolomics data showed reduced valine content in CD138+ tumor cells in MM patients compared to HD (P<0.05). HPLC results showed that compared with the scramble group, the intracellular and medium supernatant content of ARP1 cells and the medium supernatant of OCI-MY5 in the VARS-shRNA group was increased (all P<0.05).

CONCLUSIONS

MM patients with abnormal high expression of VARS have a poor prognosis. VARS promotes the malignant growth of MM cells by affecting the regulation of valine metabolism.

Prolyl-tRNA synthetase as a novel therapeutic target in multiple myeloma

Multiple myeloma (MM) is a plasma cell malignancy characterised by aberrant production of immunoglobulins requiring survival mechanisms to adapt to proteotoxic stress. We here show that glutamyl-prolyl-tRNA synthetase (GluProRS) inhibition constitutes a novel therapeutic target. Genomic data suggest that GluProRS promotes disease progression and is associated with poor prognosis, while downregulation in MM cells triggers apoptosis. We developed NCP26, a novel ATP-competitive ProRS inhibitor that demonstrates significant anti-tumour activity in multiple in vitro and in vivo systems and overcomes metabolic adaptation observed with other inhibitor chemotypes. We demonstrate a complex phenotypic response involving protein quality control mechanisms that centers around the ribosome as an integrating hub. Using systems approaches, we identified multiple downregulated proline-rich motif-containing proteins as downstream effectors. These include CD138, transcription factors such as MYC, and transcription factor 3 (TCF3), which we establish as a novel determinant in MM pathobiology through functional and genomic validation. Our preclinical data therefore provide evidence that blockade of prolyl-aminoacylation evokes a complex pro-apoptotic response beyond the canonical integrated stress response and establish a framework for its evaluation in a clinical setting.

Single-Cell Metabolomics in Hematopoiesis and Hematological Malignancies

Aberrant metabolism contributes to tumor initiation, progression, metastasis, and drug resistance. Metabolic dysregulation has emerged as a hallmark of several hematologic malignancies. Decoding the molecular mechanism underlying metabolic rewiring in hematological malignancies would provide promising avenues for novel therapeutic interventions. Single-cell metabolic analysis can directly offer a meaningful readout of the cellular phenotype, allowing us to comprehensively dissect cellular states and access biological information unobtainable from bulk analysis. In this review, we first highlight the unique metabolic properties of hematologic malignancies and underscore potential metabolic vulnerabilities. We then emphasize the emerging single-cell metabolomics techniques, aiming to provide a guide to interrogating metabolism at single-cell resolution. Furthermore, we summarize recent studies demonstrating the power of single-cell metabolomics to uncover the roles of metabolic rewiring in tumor biology, cellular heterogeneity, immunometabolism, and therapeutic resistance. Meanwhile, we describe a practical view of the potential applications of single-cell metabolomics in hematopoiesis and hematological malignancies. Finally, we present the challenges and perspectives of single-cell metabolomics development.

Role of Sphingolipids in Multiple Myeloma Progression, Drug Resistance, and Their Potential as Therapeutic Targets

Multiple myeloma (MM) is an incapacitating hematological malignancy characterized by accumulation of cancerous plasma cells in the bone marrow (BM) and production of an abnormal monoclonal protein (M-protein). The BM microenvironment has a key role in myeloma development by facilitating the growth of the aberrant plasma cells, which eventually interfere with the homeostasis of the bone cells, exacerbating osteolysis and inhibiting osteoblast differentiation. Recent recognition that metabolic reprograming has a major role in tumor growth and adaptation to specific changes in the microenvironmental niche have led to consideration of the role of sphingolipids and the enzymes that control their biosynthesis and degradation as critical mediators of cancer since these bioactive lipids have been directly linked to the control of cell growth, proliferation, and apoptosis, among other cellular functions. In this review, we present the recent progress of the research investigating the biological implications of sphingolipid metabolism alterations in the regulation of myeloma development and its progression from the pre-malignant stage and discuss the roles of sphingolipids in in MM migration and adhesion, survival and proliferation, as well as angiogenesis and invasion. We introduce the current knowledge regarding the role of sphingolipids as mediators of the immune response and drug-resistance in MM and tackle the new developments suggesting the manipulation of the sphingolipid network as a novel therapeutic direction for MM.

Serum Metabolomics Coupling With Clinical Laboratory Indicators Reveal Taxonomic Features of Leukemia

Metabolic abnormality has been considered to be the seventh characteristic in cancer cells. The potential prospect of using serum biomarkers metabolites to differentiate ALL from AML remains unclear. The purpose of our study is to probe whether the differences in metabolomics are related to clinical laboratory-related indicators. We used LC-MS-based metabolomics analysis to study 50 peripheral blood samples of leukemia patients from a single center. Then Chi-square test and T test were used to analyze the clinical characteristics, laboratory indicators and cytokines of 50 patients with leukemia. Correlation analysis was used to explore the relationship between them and the differential metabolites of different types of leukemia. Our study shows that it is feasible to better identify serum metabolic differences in different types and states of leukemia by metabolomic analysis on existing clinical diagnostic techniques. The metabolism of choline and betaine may also be significantly related to the patient’s blood lipid profile. The main enrichment pathways for distinguishing differential metabolites in different types of leukemia are amino acid metabolism and fatty acid metabolism. All these findings suggested that differential metabolites and lipid profiles might identify different types of leukemia based on existing clinical diagnostic techniques, and their rich metabolic pathways help us to better understand the physiological characteristics of leukemia.

Serum Abnormal Metabolites for Evaluating Therapeutic Response and Prognosis of Patients With Multiple Myeloma

Aims

To evaluate abnormal metabolites related to treatment response and prognosis of multiple myeloma (MM) patients through ultra performance liquid chromatography tandem mass spectrometry (UPLC-MS).

Methods

Forty-six symptomatic MM patients were included in this study who had a prior high level of positive monoclonal proteins before receiving targeted therapy with bortezomib-based regimens. UPLC-MS along with traditional immunofixation was performed on MM diagnostic samples and effective serum samples, and UPLC-MS was used to target valuable metabolic markers related to M protein.MM patients were segregated into pre-therapy (pre-T) and post-therapy (post-T) groups according to the response after chemotherapy. A monoclonal protein could be detected at baseline in 33 newly diagnosed MM (NDMM), 13 refractory and relapsed MM (RRMM) patients and 20 healthy controls (HC) by immunofixation.

Results

Between pre-T and post-T patients, the data showed that 32, 28 and 3 different metabolites were significantly correlated with M protein in IgG, IgA and light chain-type MM, respectively. These identified metabolites were significantly enriched in arginine and proline metabolism as well as glycerophospholipid metabolism pathways. Among them, PC (19:0/22:2) was displayed to increase significantly and consistently with M protein in each subtype of MM after treatment, which obviously indicated that it was related to the treatment response of MM. Further survival analysis of metabolic markers found that aspartic acid, LysoPE (16:0), SM (d18:1/17:0), PC (18:0/24:1), PC (16:0/16:0), TG (18:1/18:1/22:5) and LysoPE (18:2) reaching a certain cutoff value may be associated with shorter progression free survival (PFS). Finally, Cox multivariate regression analysis identified three factors were independent prognostic factors of MM. Moreover, there were significantly different in PC (19:0/22:2) and in aspartic acid between MM patients and healthy people.

Conclusion

This work identified significant metabolic disorders in 46 pairs off pre- and post-therapy MM patients, specifically in arginine, proline and glycerophospholipid pathways. The abnormal metabolites have the potential to serve as new biomarkers for evaluating treatment response and prognosis, as well as early monitoring of disease activity. Therefore, these systematic studies on abnormal metabolites as biomarkers for diagnosis and treatment will provide the evidence for future precise treatment of MM.

Nontargeted and targeted metabolomics approaches reveal the key amino acid alterations involved in multiple myeloma

PURPOSE

Multiple myeloma (MM), a kind of malignant neoplasm of clonal plasma cells in the bone marrow, is a refractory disease. Understanding the metabolism disorders and identification of metabolomics pathways as well as key metabolites will provide new insights for exploring diagnosis and therapeutic targets of MM.

METHODS

We conducted nontargeted metabolomics analysis of MM patients and normal controls (NC) using ultra-high-performance liquid chromatography (UHPLC) combined with quadrupole time-of-flight mass spectrometry (Q-TOF-MS) in 40 cases of cohort 1 subjects. The targeted metabolomics analysis of amino acids using multiple reaction monitoring-mass spectrometry (MRM-MS) was also performed in 30 cases of cohort 1 and 30 cases of cohort 2 participants, to comprehensively investigate the metabolomics disorders of MM.

RESULTS

The nontargeted metabolomics analysis in cohort 1 indicated that there was a significant metabolic signature change between MM patients and NC. The differential metabolites were mainly enriched in metabolic pathways related to amino acid metabolism, such as protein digestion and absorption, and biosynthesis of amino acids. Further, the targeted metabolomics analysis of amino acids in both cohort 1 and cohort 2 revealed differential metabolic profiling between MM patients and NC. We identified 12 and 14 amino acid metabolites with altered abundance in MM patients compared to NC subjects, in cohort 1 and cohort 2, respectively. Besides, key differential amino acid metabolites, such as choline, creatinine, leucine, tryptophan, and valine, may discriminate MM patients from NC. Moreover, the differential amino acid metabolites were associated with clinical indicators of MM patients.

CONCLUSIONS

Our findings indicate that amino acid metabolism disorders are involved in MM. The differential profiles reveal the potential utility of key amino acid metabolites as diagnostic biomarkers of MM. The alterations in metabolome, especially the amino acid metabolome, may provide more evidences for elucidating the pathogenesis and development of MM.

Multi-omics tumor profiling technologies to develop precision medicine in multiple myeloma

Multiple myeloma (MM), the second most common hematologic cancer, is caused by accumulation of aberrant plasma cells in the bone marrow. Its molecular causes are not fully understood and its great heterogeneity among patients complicates therapeutic decision-making. In the past decades, development of new therapies and drugs have significantly improved survival of MM patients. However, resistance to drugs and relapse remain the most common causes of mortality and are the major challenges to overcome. The advent of high throughput omics technologies capable of analyzing big amount of clinical and biological data has changed the way to diagnose and treat MM. Integration of omics data (gene mutations, gene expression, epigenetic information, and protein and metabolite levels) with clinical histories of thousands of patients allows to build scores to stratify the risk at diagnosis and predict the response to treatment, helping clinicians to make better educated decisions for each particular case. There is no doubt that the future of MM treatment relies on personalized therapies based on predictive models built from omics studies. This review summarizes the current treatments and the use of omics technologies in MM, and their importance in the implementation of personalized medicine.

Multi-omics tumor profiling technologies to develop precision medicine in multiple myeloma

Multiple myeloma (MM), the second most common hematologic cancer, is caused by accumulation of aberrant plasma cells in the bone marrow. Its molecular causes are not fully understood and its great heterogeneity among patients complicates therapeutic decision-making. In the past decades, development of new therapies and drugs have significantly improved survival of MM patients. However, resistance to drugs and relapse remain the most common causes of mortality and are the major challenges to overcome. The advent of high throughput omics technologies capable of analyzing big amount of clinical and biological data has changed the way to diagnose and treat MM. Integration of omics data (gene mutations, gene expression, epigenetic information, and protein and metabolite levels) with clinical histories of thousands of patients allows to build scores to stratify the risk at diagnosis and predict the response to treatment, helping clinicians to make better educated decisions for each particular case. There is no doubt that the future of MM treatment relies on personalized therapies based on predictive models built from omics studies. This review summarizes the current treatments and the use of omics technologies in MM, and their importance in the implementation of personalized medicine.

Polycythemia Vera and Essential Thrombocythemia Patients Exhibit Unique Serum Metabolic Profiles Compared to Healthy Individuals and Secondary Thrombocytosis Patients

Simple Summary

Current diagnosis of myeloproliferative neoplasms (MPNs), including polycythemia vera (PV) and essential thrombocythemia (ET), is controversial due to limitations associated with the lack of reproducibility, subjectivity and the presence of common somatic mutations in the driver genes. Metabolomics represents a powerful approach to identify altered metabolites that can differentiate between disease status at the time of diagnosis. The objective of this study was to characterize the serum metabolic profile of MPNs patients (PV and ET) and compare it with healthy controls (HC) and secondary thrombocytosis (ST) patients. The analysis revealed metabolites following similar trends between PV and ET patients, as well as unique significant differences in the serum metabolite levels of MNPs patients compared to HC and ST patients. These results could contribute to better differentiate patients with these diseases from HC and ST patients.

Abstract

Most common myeloproliferative neoplasms (MPNs) include polycythemia vera (PV) and essential thrombocythemia (ET). Accurate diagnosis of these disorders remains a clinical challenge due to the lack of specific clinical or molecular features in some patients enabling their discrimination. Metabolomics has been shown to be a powerful tool for the discrimination between different hematological diseases through the analysis of patients’ serum metabolic profiles. In this pilot study, the potential of NMR-based metabolomics to characterize the serum metabolic profile of MPNs patients (PV, ET), as well as its comparison with the metabolic profile of healthy controls (HC) and secondary thrombocytosis (ST) patients, was assessed. The metabolic profile of PV and ET patients, compared with HC, exhibited higher levels of lysine and decreased levels of acetoacetic acid, glutamate, polyunsaturated fatty acids (PUFAs), scyllo-inositol and 3-hydroxyisobutyrate. Furthermore, ET patients, compared with HC and ST patients, were characterized by decreased levels of formate, N-acetyl signals from glycoproteins (NAC) and phenylalanine, while the serum profile of PV patients, compared with HC, showed increased concentrations of lactate, isoleucine, creatine and glucose, as well as lower levels of choline-containing metabolites. The overall analysis revealed significant metabolic alterations mainly associated with energy metabolism, the TCA cycle, along with amino acid and lipid metabolism. These results underscore the potential of metabolomics for identifying metabolic alterations in the serum of MPNs patients that could contribute to improving the clinical management of these diseases.

Biochemical phenotyping of multiple myeloma patients at diagnosis reveals a disorder of mitochondrial complexes I and II and a Hartnup-like disturbance as underlying conditions, also influencing different stages of the disease

The aim of this study was to identify novel plasma metabolic signatures with possible relevance during multiple myeloma (MM) development and progression. A biochemical quantitative phenotyping platform based on targeted electrospray ionization tandem mass spectrometry technology was used to aid in the identification of any eventual perturbed biochemical pathway in peripheral blood plasma from 36 MM patients and 73 healthy controls. Our results showed that MM cases present an increase in short and medium/long-chain species of acylcarnitines resembling Multiple AcylCoA Dehydrogenase Deficiency (MADD), particularly, associated with MM advanced International Staging System (ISS). Lipids profile showed lower concentrations of phosphatidylcholine (PC), lysophosphatidylcholine (LPC) and sphingomyelins (SM) in the MM patients and its respective ISS groups. MM cases were accompanied by a drop in the concentration of essential amino acids, especially tryptophan, with a significant inverse correlation between the progressive drop in tryptophan with the elevation of β2-microglobulin, with the increase in systemic methylation levels (Symmetric Arginine Dimethylation, SDMA) and with the accumulation of esterified carnitines in relation to free carnitine (AcylC/C0). Serotonin was significantly elevated in cases of MM, without a clear association with ISS. Kynurenine/tryptophan ratio demonstrates that the activity of dioxigenases is even higher in the cases classified as ISS 3. In conclusion, our study showed that MM patients at diagnosis showed metabolic disorders resembling both mitochondrial complexes I and II and Hartnup-like disturbances as underlying conditions, also influencing different stages of the disease.

Increased glutathione utilization augments tumor cell proliferation in Waldenstrom Macroglobulinemia

Metabolic reprogramming is a hallmark of cancer cells. In Waldenstrom Macroglobulinemia (WM), the infiltration of IgM-secreting lymphoplamacytic cells into the bone marrow (BM) could shift the homeostasis of proteins and metabolites towards a permissive niche for tumor growth. Here, we investigated whether alerted metabolic pathways contribute to the pathobiology of WM and whether the cytokine composition of the BM promotes such changes. Metabolomics analysis on WM patients and normal donors' serum samples revealed a total of 75 metabolites that were significantly altered between two groups. While these metabolites belonged to amino acids, glucose, glutathione and lipid metabolism pathways, the highest number of the differentially expressed metabolites belonged to glutathione metabolism. Proteomics analysis and immunohistochemical staining both confirmed the increased protein levels mediating glutathione metabolism, including GCLC, MT1X, QPCT and GPX3. Moreover, treatment with IL-6 and IL-21, cytokines that induce WM cell proliferation and IgM secretion, increased gene expression of the amino acid transporters mediating glutathione metabolism, including ASCT2, SLC7A11 and 4F2HC, indicating that cytokines in the WM BM could modulate glutathione metabolism. Glutathione synthesis inhibition using Buthionine sulphoximine (BSO) significantly reduced WM cells proliferation in vitro, accompanied with decreased NFκB-p65 and MAPK-p38 phosphorylation. Moreover, BSO treatment significantly reduced the tumor growth rate in a WM xenograft model, further highlighting the role of glutathione metabolism in promoting tumor growth and proliferation. In summary, our data highlight a central role for glutathione metabolism in WM pathobiology and indicate that intervening with the metabolic processes could be a potential therapy for WM patients.

Metabolomic and Lipidomic Profiling of Bone Marrow Plasma Differentiates Patients with Monoclonal Gammopathy of Undetermined Significance from Multiple Myeloma

Oncogenic drivers of progression of monoclonal gammopathy of undetermined significance (MGUS) to multiple myeloma (MM) such as c-MYC have downstream effects on intracellular metabolic pathways of clonal plasma cells (PCs). Thus, extracellular environments such as the bone marrow (BM) plasma likely have unique metabolite profiles that differ from patients with MGUS compared to MM. This study utilized an untargeted metabolite and targeted complex lipid profiling of BM plasma to identify significant differences in the relative metabolite levels between patients with MGUS and MM from an exploratory cohort. This was followed by verification of some of the metabolite differences of interest by targeted quantification of the metabolites using isotopic internal standards in the exploratory cohort as well as an independent validation cohort. Significant differences were noted in the amino acid profiles such as decreased branch chain amino acids (BCAAs) and increased catabolism of tryptophan to the active kynurenine metabolite 3-hydroxy-kynurenine between patients with MGUS and MM. A decrease in the total levels of complex lipids such as phosphatidylethanolamines (PE), lactosylceramides (LCER) and phosphatidylinositols (PI) were also detected in the BM plasma samples from MM compared to MGUS patients. Thus, metabolite and complex lipid profiling of the BM plasma identifies differences in levels of metabolites and lipids between patients with MGUS and MM. This may provide insight into the possible differences of the intracellular metabolic pathways of their clonal PCs.

Alterations of gut microbiome accelerate multiple myeloma progression by increasing the relative abundances of nitrogen-recycling bacteria

BACKGROUND

Gut microbiome alterations are closely related to human health and linked to a variety of diseases. Although great efforts have been made to understand the risk factors for multiple myeloma (MM), little is known about the role of the gut microbiome and alterations of its metabolic functions in the development of MM.

RESULTS

Here, in a cohort of newly diagnosed patients with MM and healthy controls (HCs), significant differences in metagenomic composition were discovered, for the first time, with higher bacterial diversity in MM. Specifically, nitrogen-recycling bacteria such as Klebsiella and Streptococcus were significantly enriched in MM. Also, the bacteria enriched in MM were significantly correlated with the host metabolome, suggesting strong metabolic interactions between microbes and the host. In addition, the MM-enriched bacteria likely result from the regulation of urea nitrogen accumulated during MM progression. Furthermore, by performing fecal microbiota transplantation (FMT) into 5TGM1 mice, we proposed a mechanistic explanation for the interaction between MM-enriched bacteria and MM progression via recycling urea nitrogen. Further experiments validated that Klebsiella pneumoniae promoted MM progression via de novo synthesis of glutamine in mice and that the mice fed with glutamine-deficient diet exhibited slower MM progression.

CONCLUSIONS

Overall, our findings unveil a novel function of the altered gut microbiome in accelerating the malignant progression of MM and open new avenues for novel treatment strategies via manipulation of the intestinal microbiota of MM patients. Video abstract.

The 60-kDa heat shock protein regulates energy rearrangement and protein synthesis to promote proliferation of multiple myeloma cells

To investigate the cellular mechanisms of multiple myeloma (MM), we used liquid chromatography-tandem mass spectrometry for proteomics analysis of CD138⁺ plasma cells from patients with MM and healthy controls. We found that the 60-kDa heat shock protein (HSP60, also known as HSPD1) was significantly upregulated in myeloma cells. HSP60 is an important chaperone protein that regulates the homeostasis of mitochondrial proteins and maintains mitochondrial function. Knockdown (KD) of HSP60 in myeloma cells resulted in inhibition of proliferation and reduced the quality of the mitochondria. Mitochondrial stress tests showed that HSP60 KD inhibited glycolysis and mitochondrial activity. Metabolomics showed a decrease in glycolysis and tricarboxylic acid cycle metabolites, and inhibited the formation of creatine and phosphocreatine by the reaction of S-adenosylmethionine (SAM) with amino acids mediated by demethyladenosine transferase 1, mitochondrial (TFB1M) and reduced energy storage substances. Moreover, HSP60 silencing influenced the synthesis of ribonucleotides and nicotinamide adenine dinucleotide phosphate (NADPH) by the pentose phosphate pathway to inhibit cell proliferation. HSP60 KD inhibited 5' adenosine monophosphate-activated protein kinase (AMPK), which inhibited the key enzyme 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 3 (PFKFB3), effecting the metabolism of fatty acids by inhibiting malonyl-coenzyme A. Our data suggest that reduced HSP60 expression alters metabolic reprogramming in MM, inhibits tumour progression and reduces mitochondrial-dependent biosynthesis, suggesting that HSP60 is a potential therapeutic target for MM treatment.

Metabolomics analysis identifies lysine and taurine as candidate prognostic biomarkers for AML-M2 patients

There is an ongoing search for potential biomarkers for acute myeloid leukemia (AML) patients using metabolic analysis. However, only few studies to date have focused on bone marrow samples or a specific subtype of AML. In the present study, we used gas chromatography time-of-flight mass spectrometry of plasma and bone marrow supernatants to compare the metabolic characteristics of patients with AML with maturation (AML-M2). This approach identified significantly altered metabolites. We next performed pathway analysis and determined relative mRNA expression by qRT-PCR. Our results show that lysine, methionine and serine were significantly decreased in AML-M2 patients compared with healthy control. Moreover, plasma abundance of lysine was negatively associated with patients' risk stratification. Taurine had higher plasma abundance in AML-M2 patients and plasma level of taurine was positively related with AML-M2 risk status, while the expression level of taurine transporter showed a negative correlation. Receiver operating characteristic curve analysis showed these four metabolites had high diagnostic value with lysine showing the highest sensitivity and specificity. These results suggest that plasma abundances of lysine and taurine may serve as potential metabolic biomarkers for the prognosis of patients with AML-M2.

Metabolomic Profiles for HBV Related Hepatocellular Carcinoma Including Alpha-Fetoproteins Positive and Negative Subtypes

Background: Hepatocellular carcinoma (HCC) is very common globally prevalent cancer. Due to its poor clinical prognosis, increasing the diagnostic rate of HCC is urgently needed. Herein, we validate discovered metabolomic biomarkers to distinguish Hepatitis B virus (HBV)-related HCC, including alpha-fetoprotein (AFP) negative (AFP–) and positive (AFP+) individuals.

Methods: We recruited 130 HCC subjects (independent case-control, randomized clinical cohorts) to our study. We separated the subjects randomly into two panels: (1) 58 individuals for the discovery panel; and (2) 72 individuals for the validation panel. For each panel, gender and age-matched hepatitis B group (HBG) and healthy group were included as controls. Plasma samples were collected for metabolic profiling by liquid chromatography—mass spectrometry—based metabolomics assays. We applied both non-targeted metabolomics analyses and targeted metabolomics analyses. Significantly changed metabolites (SCMs) were identified. The power of SCMs to discriminate HCC and HBG or healthy group was determined by receiver operating characteristic curve (ROC) analysis.

Results: Ten SCMs were selected form the discovery panel, and further verified in the validation panel. ROC analyses indicated that 1 SCMs (LysoPC (24:0)) could discriminate HCC from HBG (AUC = 0.765). Further, 8 SCMs including (LysoPC (17:0), LysoPC (20:4(8Z,11Z,14Z,17Z)), LysoPC (22:0), LysoPC (24:0), PE (P-16:0/22:4(7Z,10Z,13Z,16Z)), SM (d18:1/22:1(13Z)), Creatinine, and L-Isoleucine) displayed a heightened ability to discriminate between HCC and healthy controls (AUC were more than 0.800). Most of these SCMs were important in lipid metabolism.

Conclusions: LysoPC (24:0) could distinguished HCC from HBG, and 8 SCMs distinguished HCC from healthy controls. LysoPC and other metabolites have the potential to serve as non-invasive biomarkers for HBV related AFP– and AFP+ HCC.