@article{RonchiLeichSbieraetal.2012, author = {Ronchi, Cristina L. and Leich, Ellen and Sbiera, Silviu and Weismann, Dirk and Rosenwald, Andreas and Allolio, Bruno and Fassnacht, Martin}, title = {Single Nucleotide Polymorphism Microarray Analysis in Cortisol-Secreting Adrenocortical Adenomas Identifies New Candidate Genes and Pathways}, series = {Neoplasia}, volume = {14}, journal = {Neoplasia}, number = {3}, doi = {10.1593/neo.111758}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-134953}, pages = {206}, year = {2012}, abstract = {The genetic mechanisms underlying adrenocortical tumor development are still largely unknown. We used high-resolution single nucleotide polymorphism microarrays (Affymetrix SNP 6.0) to detect copy number alterations (CNAs) and copy-neutral losses of heterozygosity (cnLOH) in 15 cortisol-secreting adrenocortical adenomas with matched blood samples. We focused on microalterations aiming to discover new candidate genes involved in early tumorigenesis and/or autonomous cortisol secretion. We identified 962 CNAs with a median of 18 CNAs per sample. Half of them involved noncoding regions, 89\% were less than 100 kb, and 28\% were found in at least two samples. The most frequently gained regions were 5p15.33, 6q16.1, 7p22.3-22.2, 8q24.3, 9q34.2-34.3, 11p15.5, 11q11, 12q12, 16q24.3, 20p11.1-20q21.11, and Xq28 (>= 20\% of cases), most of them being identified in the same three adenomas. These regions contained among others genes like NOTCH1, CYP11B2, HRAS, and IGF2. Recurrent losses were less common and smaller than gains, being mostly localized at 1p, 6q, and 11q. Pathway analysis revealed that Notch signaling was the most frequently altered. We identified 46 recurrent CNAs that each affected a single gene (31 gains and 15 losses), including genes involved in steroidogenesis (CYP11B1) or tumorigenesis (CTNNB1, EPHA7, SGK1, STIL, FHIT). Finally, 20 small cnLOH in four cases affecting 15 known genes were found. Our findings provide the first high-resolution genome-wide view of chromosomal changes in cortisol-secreting adenomas and identify novel candidate genes, such as HRAS, EPHA7, and SGK1. Furthermore, they implicate that the Notch1 signaling pathway might be involved in the molecular pathogenesis of adrenocortical tumors.}, language = {en} } @article{MaerzKurlbaumRocheLancasteretal.2021, author = {M{\"a}rz, Juliane and Kurlbaum, Max and Roche-Lancaster, Oisin and Deutschbein, Timo and Peitzsch, Mirko and Prehn, Cornelia and Weismann, Dirk and Robledo, Mercedes and Adamski, Jerzy and Fassnacht, Martin and Kunz, Meik and Kroiss, Matthias}, title = {Plasma Metabolome Profiling for the Diagnosis of Catecholamine Producing Tumors}, series = {Frontiers in Endocrinology}, volume = {12}, journal = {Frontiers in Endocrinology}, issn = {1664-2392}, doi = {10.3389/fendo.2021.722656}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-245710}, year = {2021}, abstract = {Context 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. Objective Evaluation of quantitative metabolomics as a diagnostic tool for PPGL. Design 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. Patients 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. Results 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. Conclusions 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.}, language = {en} }