Gas chromatography-mass spectrometry untargeted profiling of non-Hodgkin’s lymphoma urinary metabolite markers

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dc.contributor.authorBueno Duarte G.H.
dc.contributor.authorde Piloto Fernandes A.M.A.
dc.contributor.authorSilva A.A.R.
dc.contributor.authorZamora-Obando H.R.
dc.contributor.authorAmaral A.G.
dc.contributor.authorde Sousa Mesquita A.
dc.contributor.authorSchmidt-Filho J.
dc.contributor.authorCordeiro de Lima V.C.
dc.contributor.authorD'Almeida Costa F.
dc.contributor.authorAndrade V.P.
dc.contributor.authorPorcari A.M.
dc.contributor.authorEberlin M.N.
dc.contributor.authorSimionato A.V.C.
dc.date.accessioned2024-03-12T23:46:12Z
dc.date.available2024-03-12T23:46:12Z
dc.date.issued2020
dc.description.abstract© 2020, Springer-Verlag GmbH Germany, part of Springer Nature.Non-Hodgkin’s lymphoma (NHL) is a cancer of the lymphatic system where the lymphoid and hematopoietic tissues are infiltrated by malignant neoplasms of B, T, and natural killer lymphocytes. Effective and less invasive methods for NHL screening are urgently needed. Herein, we report an untargeted gas chromatography-mass spectrometry (GC-MS) method to investigate metabolic changes in non-volatile derivatized compounds from urine samples of NHL patients (N = 15) and compare them to healthy controls (N = 34). Uni- and multivariate data analysis showed 18 endogenous metabolites, including amino acids and their metabolites, sugars, small organic acids, and vitamins, as statistically significant for group differentiation. A receiver operating characteristic curve (ROC) generated from a support vector machine (SVM) algorithm-based model achieved 0.998 of predictive accuracy, displaying the potential and relevance of GC-MS-detected urinary non-volatile compounds for predictive purposes. Furthermore, a specific panel of key metabolites was also evaluated, showing similar results. All in all, our results indicate that this robust GC-MS method is an effective screening tool for NHL diagnosis and it is able to highlight different pathways of the disease. [Figure not available: see fulltext.]
dc.description.firstpage7469
dc.description.issuenumber27
dc.description.lastpage7480
dc.description.volume412
dc.identifier.doi10.1007/s00216-020-02881-5
dc.identifier.issn1618-2650
dc.identifier.urihttps://dspace.mackenzie.br/handle/10899/34880
dc.relation.ispartofAnalytical and Bioanalytical Chemistry
dc.rightsAcesso Restrito
dc.subject.otherlanguageBiomarkers
dc.subject.otherlanguageGas chromatography-mass spectrometry
dc.subject.otherlanguageMetabolomics
dc.subject.otherlanguageNon-Hodgkin’s lymphoma
dc.titleGas chromatography-mass spectrometry untargeted profiling of non-Hodgkin’s lymphoma urinary metabolite markers
dc.typeArtigo
local.scopus.citations8
local.scopus.eid2-s2.0-85090473818
local.scopus.subjectEndogenous metabolites
local.scopus.subjectGas chromatography-mass spectrometry
local.scopus.subjectGas chromatography-mass spectrometry methods
local.scopus.subjectMultivariate data analysis
local.scopus.subjectNon-volatile compounds
local.scopus.subjectPredictive accuracy
local.scopus.subjectReceiver operating characteristic curves
local.scopus.subjectSupport vector machine algorithm
local.scopus.subjectAdult
local.scopus.subjectAged
local.scopus.subjectBiomarkers, Tumor
local.scopus.subjectFemale
local.scopus.subjectGas Chromatography-Mass Spectrometry
local.scopus.subjectHumans
local.scopus.subjectLymphoma, Non-Hodgkin
local.scopus.subjectMale
local.scopus.subjectMetabolome
local.scopus.subjectMetabolomics
local.scopus.subjectMiddle Aged
local.scopus.updated2024-05-01
local.scopus.urlhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85090473818&origin=inward
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