SFEBES2009 Oral Communications Young Endocrinologists prize session (8 abstracts)
Development of urinary steroid profiling as a high-throughput screening tool for the detection of malignancy in patients with adrenal tumours
Angela Taylor 1 , Michael Biehl 2 , Beverly Hughes 1 , Han Stiekema 2 , Petra Schneider 2 , David Smith 1 , Peter Nightingale 3 , Cedric Shackleton 1 , Paul Stewart 1 & Wiebke Arlt 1
1School of Clinical and Experimental Medicine, Centre for Endocrinology, Diabetes and Metabolism, University of Birmingham, Birmingham, UK; 2Institute fior Mathematics and Computing Science, University of Groningen, Groningen, The Netherlands; 3Wellcome Trust Clinical Research Facility, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
Adrenal tumors have an incidence of 2–3% in the general population and the work-up of incidentally discovered adrenal masses represents a major burden to the health system. Differentiating adrenocortical adenoma (ACA) from adrenocortical carcinoma (ACC) represents a continuous challenge, with unfavorable sensitivities and specificities provided by tumor size, imaging and even histology. Here, we aimed to develop a reliable screening tool for the detection of adrenal malignancy. We performed urinary steroid profiling by gas chromatography/mass spectrometry (GC/MS) in scanning and selected-ion-recording mode, quantifying 32 distinct steroids. We analysed 24-h urine samples from 102 patients with ACA (39m, 64f, 19–83 years) and 45 patients with ACC (24 m, 21f, 20–80 years) recruited by the European Network for the Study of Adrenal Tumours (www.ensat.org). Diagnosis in ACC was confirmed by metastasis; patients with ACA had undergone a median follow-up of 45 months without evidence of metastasis. Total steroid excretion was independent of tumour size (ACA: 26 (9–78) mm; ACC: 90 (14–230) mm). Steroid output data from ACA, ACC and healthy controls (n=88) were subjected to matrix relevance learning vector quantization, carried out over 1000 random splits into training (90%) and test (10%) data sets. This identified a subset of nine steroids that performed best in differentiating ACA from ACC. Receiver-operated characteristics analysis revealed sensitivity=specificity=91% (AUC 0.97) employing all 32 steroids and sens=spec=89% (AUC 0.96) when using only the nine most differentiating markers. While GC/MS was invaluable in documenting the distinct ACC metabolome, it is unsuited to use in widespread screening. We are transferring the methodology to a Waters uPLC/tandem mass spectrometry platform. All nine targeted steroid markers can be separated and quantified within 5 min using positive ion mode. These results suggest that urinary steroid profiling is a highly sensitive and specific biomarker tool for differentiating benign from malignant adrenal tumours.
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Endocrine Abstracts
ISSN 1470-3947 (print) | ISSN 1479-6848 (online)
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