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The Metabolomic Profile of Lymphoma Subtypes: A Pilot Study

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...

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Autores principales: Barberini, Luigi, Noto, Antonio, Fattuoni, Claudia, Satta, Giannina, Zucca, Mariagrazia, Cabras, Maria Giuseppina, Mura, Ester, Cocco, Pierluigi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6650891/
https://www.ncbi.nlm.nih.gov/pubmed/31248049
http://dx.doi.org/10.3390/molecules24132367
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author Barberini, Luigi
Noto, Antonio
Fattuoni, Claudia
Satta, Giannina
Zucca, Mariagrazia
Cabras, Maria Giuseppina
Mura, Ester
Cocco, Pierluigi
author_facet Barberini, Luigi
Noto, Antonio
Fattuoni, Claudia
Satta, Giannina
Zucca, Mariagrazia
Cabras, Maria Giuseppina
Mura, Ester
Cocco, Pierluigi
author_sort Barberini, Luigi
collection PubMed
description 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.
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spelling pubmed-66508912019-08-07 The Metabolomic Profile of Lymphoma Subtypes: A Pilot Study Barberini, Luigi Noto, Antonio Fattuoni, Claudia Satta, Giannina Zucca, Mariagrazia Cabras, Maria Giuseppina Mura, Ester Cocco, Pierluigi Molecules Article 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. MDPI 2019-06-26 /pmc/articles/PMC6650891/ /pubmed/31248049 http://dx.doi.org/10.3390/molecules24132367 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Barberini, Luigi
Noto, Antonio
Fattuoni, Claudia
Satta, Giannina
Zucca, Mariagrazia
Cabras, Maria Giuseppina
Mura, Ester
Cocco, Pierluigi
The Metabolomic Profile of Lymphoma Subtypes: A Pilot Study
title The Metabolomic Profile of Lymphoma Subtypes: A Pilot Study
title_full The Metabolomic Profile of Lymphoma Subtypes: A Pilot Study
title_fullStr The Metabolomic Profile of Lymphoma Subtypes: A Pilot Study
title_full_unstemmed The Metabolomic Profile of Lymphoma Subtypes: A Pilot Study
title_short The Metabolomic Profile of Lymphoma Subtypes: A Pilot Study
title_sort metabolomic profile of lymphoma subtypes: a pilot study
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6650891/
https://www.ncbi.nlm.nih.gov/pubmed/31248049
http://dx.doi.org/10.3390/molecules24132367
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