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

Abstract

Aims: This study aimed to identify potential, non-invasive biomarkers for diagnosis and monitoring of the progress in multiple myeloma (MM) patients.Methods: MM patients and age-matched healthy controls (HC) were recruited in Discovery phase and Validation phase, respectively. MM patients were segregated into active group (AG) and responding group (RG). Serum samples were collected were conducted to non-targeted metabolomics analyses. Metabolites which were significantly changed (SCMs) among groups were identified in Discovery phase and was validated in Validation phase. The signaling pathways of these SCMs were enriched. The ability of SCMs to discriminate among groups in Validation phase was analyzed through receiver operating characteristic curve. The correlations between SCMs and clinical features, between SCMs and survival period of MM patients were analyzed.Results: Total of 23 SCMs were identified in AG compared with HC both in Discovery phase and Validation phase. Those SCMs were significantly enriched in arginine and proline metabolism and glycerophospholipid metabolism. 4 SCMs had the discriminatory ability between MM patients and healthy controls in Validation phase. Moreover, 12 SCMs had the ability to discriminate between the AG patients and RG patients in Validation phase. 10 out of 12 SCMs correlated with advanced features of MM. Moreover, 8 out of 12 SCMs had the negative impact on the survival of MM. 5′-Methylthioadenosine may be the only independent prognostic factor in survival period of MM.Conclusion: 10 SCMs identified in our study, which correlated with advanced features of MM, could be potential, novel, non-invasive biomarkers for active disease in MM.

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

“…Some recent works have pointed metabolic pathways and possible new therapeutic targets in MM 14 , 15 , 21 , 22 . Also, Ludwig et al 23 identified that the majority of the most represented metabolites in MGUS and MM are lipids.…”

“…LPC is described as an important low-density protein (LDL)/bioactive lipid and is responsible for the inflammatory effects of oxidized LDL on endothelial cells and stimulates basic fibroblast growth factor (bFGF) and the granulocyte–macrophage–cytokine colony-stimulating factor (GM-CSF) 40 . LPC have previously been reported as a biomolecule involved in inflammatory stimuli, promoting the release of IL-6 and other inflammatory factors, and resulting in the progression of MM 21 . Our LPC analysis showed lower plasma levels in controls versus MM and the decrease is more evident in advanced stages ISS 3.…”

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

“…The functional cluster analysis showed that 6 out of 8 SCMs, including LysoPC (17:0) (Figure 6A), LysoPC (20:4(8Z,11Z,14Z,17Z)) (Figure 6B), LysoPC (22:0) (Figure 6C), LysoPC (24:0) (Figure 6D), PE (P-16:0/22:4(7Z,10Z,13Z,16Z)) (Figure 6E), and SM (d18:1/22:1(13Z)) (Figure 6F), whose molecular formulas are C25H52NO7P, C28H50NO7P, C30H62NO7P, C32H66NO7P, C43H78NO7P, and C45H89N2O6P, were correlated with lipid metabolism. Among them, LysoPC (22:0) belongs to members of the lysophosphatidylcholines (LPCs), which are formed by hydrolysis of phosphatidylcholines (PCs) by the enzyme phospholipase A2 (16). The other SCMs were PE (P-16:0/22:4(7Z, 10Z, 13Z, 16Z)) and SM (d18:1/22:1(13Z)), which are essential components of membrane structure, signal transduction and lipoprotein metabolism.…”

Increased glutathione utilization augments tumor cell proliferation in Waldenstrom Macroglobulinemia

“…Non-targeted metabolomics analysis of the serum samples in multiple myeloma (MM) has identified significantly altered metabolites that differentiate patients with advanced disease from normal samples [ 5 ]. In another study, metabolomics analysis has shown the altered levels of some metabolites, including glutamine, lysine and cholesterol, at the time of diagnosis that are returned back to normal levels upon achieving complete remission, suggesting these metabolites as the potential biomarkers of response to the therapy [ 6 ].…”