The Metabolomic Profile of Lymphoma Subtypes: A Pilot Study

Abstract

Lymphoma defines a group of different diseases. This study examined pre-treatment plasma samples from 66 adult patients (aged 20–74) newly diagnosed with any lymphoma subtype, and 96 frequency matched population controls. We used gas chromatography-mass spectrometry (GC-MS) to compare the metabolic profile by case/control status and across the major lymphoma subtypes. We conducted univariate and multivariate analyses, and partial least square discriminant analysis (PLS-DA). When compared to the controls, statistically validated models were obtained for diffuse large B-cell lymphoma (DLBCL), chronic lymphocytic leukemia (CLL), multiple myeloma (MM), and Hodgkin lymphoma (HL), but not follicular lymphoma (FL). The metabolomic analysis highlighted interesting differences between lymphoma patients and population controls, allowing the discrimination between pathologic and healthy subjects: Important metabolites, such as hypoxanthine and elaidic acid, were more abundant in all lymphoma subtypes. The small sample size of the individual lymphoma subtypes prevented obtaining PLS-DA validated models, although specific peculiar features of each subtype were observed; for instance, fatty acids were most represented in MM and HL patients, while 2-aminoadipic acid, 2-aminoheptanedioic acid, erythritol, and threitol characterized DLBCL and CLL. Metabolomic analysis was able to highlight interesting differences between lymphoma patients and population controls, allowing the discrimination between pathologic and healthy subjects. Further studies are warranted to understand whether the peculiar metabolic patterns observed might serve as early biomarkers of lymphoma.

Multiomics Integration Elucidates Metabolic Modulators of Drug Resistance in Lymphoma

“…This is in line with the identification of unique metabolic profiles of lymphoma patient plasma samples from each cancer subtype. [33] Compared to other lymphomas, DLBCL patients were found to have increased circulating levels of glutamic acid and glycine, coupled with decreased levels of aspartic acid, tryptophan, and uric. These reports are not fully mirrored in our data, suggesting a unique metabolic profile of the resistant cells.…”

Metabolomic profile of patients with left ventricular assist devices: a pilot study

“…The analytical method has been described elsewhere (14). Briefly, 400 μL of PFP were treated with 1,200 μL of cold methanol in 2 mL Eppendorf tubes, vortex mixed, and centrifuged for ten minutes (min) at 14,000 rpm (16,900 G); 400 μL of the upper phase were transferred in glass vials (1.5 mL) and evaporated to dryness overnight; 50 μL of a 0.24 M (20 mg/mL) solution of methoxylamine hydrochloride in pyridine was added to each vial, samples were vortex mixed, and left to react for seventeen hours at room temperature in the dark.…”

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

“…This approach has been shown to be a powerful tool for the detection of metabolic deregulations associated with diverse cancers, leading to the identification of specific sets of metabolites that discriminate between different disease status [ 11 , 12 , 13 ]. Particularly, metabolomics has recently enabled the discrimination between different hematological diseases through the analysis of patient serum metabolic profiles [ 11 , 14 , 15 , 16 , 17 , 18 , 19 ]. In this context, the characterization of the serum metabolic profile of MPNs patients could contribute to a better understanding of the molecular mechanisms underlying these diseases and could help to improve patient management.…”