Sophie Schweitzer, Meik Kunz, Max Kurlbaum, Johannes Vey, Sabine Kendl, Timo Deutschbein, Stefanie Hahner, Martin Fassnacht, Thomas Dandekar and Matthias Kroiss
Current workup for the pre-operative distinction between frequent adrenocortical adenomas (ACAs) and rare but aggressive adrenocortical carcinomas (ACCs) combines imaging and biochemical testing. We here investigated the potential of plasma steroid hormone profiling by liquid chromatography tandem mass spectrometry (LC-MS/MS) for the diagnosis of malignancy in adrenocortical tumors.
Retrospective cohort study of prospectively collected EDTA-plasma samples in a single tertiary reference center.
Steroid hormone profiling by liquid chromatography tandem mass spectrometry (LC-MS/MS) in random plasma samples and logistic regression modeling.
Fifteen steroid hormones were quantified in 66 ACAs (29 males; M) and 42 ACC (15 M) plasma samples. Significantly higher abundances in ACC vs ACA were observed for 11-deoxycorticosterone, progesterone, 17-hydroxyprogesterone, 11-deoxycortisol, DHEA, DHEAS and estradiol (all P < 0.05). Maximal areas under the curve (AUC) for discrimination between ACA and ACC for single analytes were only 0.76 (estradiol) and 0.77 (progesterone), respectively. Logistic regression modeling enabled the discovery of diagnostic signatures composed of six specific steroids for male and female patients with AUC of 0.95 and 0.94, respectively. Positive predictive values in males and females were 92 and 96%, negative predictive values 90 and 86%, respectively.
This study in a large adrenal tumor patient cohort demonstrates the value of plasma steroid hormone profiling for diagnosis of ACC. Application of LC-MS/MS analysis and of our model may facilitate diagnosis of malignancy in non-expert centers. We propose to continuously evaluate and improve diagnostic accuracy of LC-MS/MS profiling by applying machine-learning algorithms to prospectively obtained steroid hormone profiles.
Zoran Erlic, Max Kurlbaum, Timo Deutschbein, Svenja Nölting, Aleksander Prejbisz, Henri Timmers, Susan Richter, Cornelia Prehn, Dirk Weismann, Jerzy Adamski, Andrzej Januszewicz, Martin Reincke, Martin Fassnacht, Mercedes Robledo, Graeme Eisenhofer, Felix Beuschlein and Matthias Kroiss
Excess catecholamine release by pheochromocytomas and paragangliomas (PPGL) leads to characteristic clinical features and increased morbidity and mortality. The influence of PPGLs on metabolism is ill described but may impact diagnosis and management. The objective of this study was to systematically and quantitatively study PPGL-induced metabolic changes at a systems level.
Targeted metabolomics by liquid chromatography-tandem mass spectrometry of plasma specimens in a clinically well-characterized prospective cohort study.
Analyses of metabolic profiles of plasma specimens from 56 prospectively enrolled and clinically well-characterized patients (23 males, 33 females) with catecholamine-producing PPGL before and after surgery, as well as measurement of 24-h urinary catecholamine using LC-MS/MS.
From 127 analyzed metabolites, 15 were identified with significant changes before and after surgery: five amino acids/biogenic amines (creatinine, histidine, ornithine, sarcosine, tyrosine) and one glycerophospholipid (PCaeC34:2) with increased concentrations and six glycerophospholipids (PCaaC38:1, PCaaC42:0, PCaeC40:2, PCaeC42:5, PCaeC44:5, PCaeC44:6), two sphingomyelins (SMC24:1, SMC26:1) and hexose with decreased levels after surgery. Patients with a noradrenergic tumor phenotype had more pronounced alterations compared to those with an adrenergic tumor phenotype. Weak, but significant correlations for 8 of these 15 metabolites with total urine catecholamine levels were identified.
This first large prospective metabolomics analysis of PPGL patients demonstrates broad metabolic consequences of catecholamine excess. Robust impact on lipid and amino acid metabolism may contribute to increased morbidity of PPGL patients.