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  • Metabolome-guided genomics to identify pathogenic variants in isocitrate dehydrogenase, fumarate hydratase, and succinate dehydrogenase genes in pheochromocytoma and paraganglioma.

Metabolome-guided genomics to identify pathogenic variants in isocitrate dehydrogenase, fumarate hydratase, and succinate dehydrogenase genes in pheochromocytoma and paraganglioma.

Genetics in medicine : official journal of the American College of Medical Genetics (2018-07-28)
Susan Richter, Laura Gieldon, Ying Pang, Mirko Peitzsch, Thanh Huynh, Rocio Leton, Bruna Viana, Tonino Ercolino, Anastasios Mangelis, Elena Rapizzi, Mario Menschikowski, Daniela Aust, Matthias Kroiss, Felix Beuschlein, Volker Gudziol, Henri Jlm Timmers, Jacques Lenders, Massimo Mannelli, Alberto Cascon, Karel Pacak, Mercedes Robledo, Graeme Eisenhofer, Barbara Klink
RESUMEN

Metabolic aberrations have been described in neoplasms with pathogenic variants (PV) in the Krebs cycle genes encoding succinate dehydrogenase (SDH), fumarate hydratase (FH) and isocitrate dehydrogenase (IDH). In turn, accumulation of oncometabolites succinate, fumarate, and 2-hydroxyglutarate can be employed to identify tumors with those PV . Additionally, such metabolic readouts may aid in genetic variant interpretation and improve diagnostics. Using liquid chromatography-mass spectrometry, 395 pheochromocytomas and paragangliomas (PPGLs) from 391 patients were screened for metabolites to indicate Krebs cycle aberrations. Multigene panel sequencing was applied to detect driver PV in cases with indicative metabolite profiles but undetermined genetic drivers. Aberrant Krebs cycle metabolomes identified rare cases of PPGLs with germline PV in FH and somatic PV in IDHx and SDHx, including the first case of a somatic IDH2 PV in PPGL. Metabolomics also reliably identified PPGLs with SDHx loss-of-function (LOF) PV. Therefore we utilized tumor metabolite profiles to further classify variants of unknown significance in SDHx, thereby enabling missense variants associated with SDHx LOF to be distinguished from benign variants. We propose incorporation of metabolome data into the diagnostics algorithm in PPGLs to guide genetic testing and variant interpretation and to help identify rare cases with PV in FH and IDHx.