Plasma Metabolome Profiling for the Diagnosis of Catecholamine Producing Tumors

Pheochromocytomas and paragangliomas (PPGL) cause catecholamine excess leading to a characteristic clinical phenotype. Intra-individual changes at metabolome level have been described after surgical PPGL removal. The value of metabolomics for the diagnosis of PPGL has not been studied yet. Evaluatio...

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Published in:Frontiers in endocrinology (Lausanne) Vol. 12; p. 722656
Main Authors: März, Juliane, Kurlbaum, Max, Roche-Lancaster, Oisin, Deutschbein, Timo, Peitzsch, Mirko, Prehn, Cornelia, Weismann, Dirk, Robledo, Mercedes, Adamski, Jerzy, Fassnacht, Martin, Kunz, Meik, Kroiss, Matthias
Format: Journal Article
Language:English
Published: Switzerland Frontiers Media S.A 07.09.2021
Subjects:
adrenal
Adrenal Gland Neoplasms - blood
Adrenal Gland Neoplasms - diagnosis
Adrenal Gland Neoplasms - metabolism
Adult
Blood Cells - metabolism
Blood Chemical Analysis - methods
Case-Control Studies
catecholamines
Catecholamines - metabolism
Chromatography, Liquid
Endocrinology
Female
Germany
Humans
Male
mass spectronomy
Metabolome
Metabolomics - methods
Middle Aged
paraganglioma
Paraganglioma - blood
Paraganglioma - diagnosis
Paraganglioma - metabolism
pheochromocytoma
Pheochromocytoma - blood
Pheochromocytoma - diagnosis
Pheochromocytoma - metabolism
Tandem Mass Spectrometry
targeted metabolomics
Germany
catecholamines
adrenal
pheochromocytoma
targeted metabolomics
mass spectronomy
machine learning
feature selection
paraganglioma
ISSN:1664-2392, 1664-2392
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Summary:Pheochromocytomas and paragangliomas (PPGL) cause catecholamine excess leading to a characteristic clinical phenotype. Intra-individual changes at metabolome level have been described after surgical PPGL removal. The value of metabolomics for the diagnosis of PPGL has not been studied yet. Evaluation of quantitative metabolomics as a diagnostic tool for PPGL. Targeted metabolomics by liquid chromatography-tandem mass spectrometry of plasma specimens and statistical modeling using ML-based feature selection approaches in a clinically well characterized cohort study. Prospectively enrolled patients (n=36, 17 female) from the Prospective Monoamine-producing Tumor Study (PMT) with hormonally active PPGL and 36 matched controls in whom PPGL was rigorously excluded. Among 188 measured metabolites, only without considering false discovery rate, 4 exhibited statistically significant differences between patients with PPGL and controls (histidine p=0.004, threonine p=0.008, lyso PC a C28:0 p=0.044, sum of hexoses p=0.018). Weak, but significant correlations for histidine, threonine and lyso PC a C28:0 with total urine catecholamine levels were identified. Only the sum of hexoses (reflecting glucose) showed significant correlations with plasma metanephrines.By using ML-based feature selection approaches, we identified diagnostic signatures which all exhibited low accuracy and sensitivity. The best predictive value (sensitivity 87.5%, accuracy 67.3%) was obtained by using Gradient Boosting Machine Modelling. The diabetogenic effect of catecholamine excess dominates the plasma metabolome in PPGL patients. While curative surgery for PPGL led to normalization of catecholamine-induced alterations of metabolomics in individual patients, plasma metabolomics are not useful for diagnostic purposes, most likely due to inter-individual variability.
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This article was submitted to Cancer Endocrinology, a section of the journal Frontiers in Endocrinology
These authors have contributed equally to this work
Edited by: Antongiulio Faggiano, Sapienza University of Rome, Italy
Reviewed by: Valentina Vaira, University of Milan, Italy; Paraskevi Xekouki, University of Crete, Greece
ISSN:1664-2392
1664-2392
DOI:10.3389/fendo.2021.722656