@article{ArltBiehlTayloretal.2011,
  author    = {Arlt, Wiebke and Biehl, Michael and Taylor, Angela E. and Hahner, Stefanie and Lib{\´e}, Rossella and Hughes, Beverly A. and Schneider, Petra and Smith, David J. and Stiekema, Han and Krone, Nils and Porfiri, Emilio and Opocher, Giuseppe and Bertherat, Jer{\^o}me and Mantero, Franco and Allolio, Bruno and Terzolo, Massimo and Nightingale, Peter and Shackleton, Cedric H. L. and Bertagna, Xavier and Fassnacht, Martin and Stewart, Paul M.},
  title     = {Urine Steroid Metabolomics as a Biomarker Tool for Detecting Malignancy in Adrenal Tumors},
  series = {The Journal of Clinical Endocrinology \& Metabolism},
  volume    = {96},
  journal   = {The Journal of Clinical Endocrinology \& Metabolism},
  number    = {12},
  doi       = {10.1210/jc.2011-1565},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-154682},
  pages     = {3775 -- 3784},
  year      = {2011},
  abstract  = {Context: Adrenal tumors have a prevalence of around 2\% in the general population. Adrenocortical carcinoma (ACC) is rare but accounts for 2-11\% of incidentally discovered adrenal masses. Differentiating ACC from adrenocortical adenoma (ACA) represents a diagnostic challenge in patients with adrenal incidentalomas, with tumor size, imaging, and even histology all providing unsatisfactory predictive values. Objective: Here we developed a novel steroid metabolomic approach, mass spectrometry-based steroid profiling followed by machine learning analysis, and examined its diagnostic value for the detection of adrenal malignancy. Design: Quantification of 32 distinct adrenal derived steroids was carried out by gas chromatography/mass spectrometry in 24-h urine samples from 102 ACA patients (age range 19-84 yr) and 45 ACC patients (20-80 yr). Underlying diagnosis was ascertained by histology and metastasis in ACC and by clinical follow-up [median duration 52 (range 26-201) months] without evidence of metastasis in ACA. Steroid excretion data were subjected to generalized matrix learning vector quantization (GMLVQ) to identify the most discriminative steroids. Results: Steroid profiling revealed a pattern of predominantly immature, early-stage steroidogenesis in ACC. GMLVQ analysis identified a subset of nine steroids that performed best in differentiating ACA from ACC. Receiver-operating characteristics analysis of GMLVQ results demonstrated sensitivity = specificity = 90\% (area under the curve = 0.97) employing all 32 steroids and sensitivity = specificity = 88\% (area under the curve = 0.96) when using only the nine most differentiating markers. Conclusions: Urine steroid metabolomics is a novel, highly sensitive, and specific biomarker tool for discriminating benign from malignant adrenal tumors, with obvious promise for the diagnostic work-up of patients with adrenal incidentalomas.},
  language  = {en}
}
@article{WeigandRonchiRizkRabinetal.2017,
  author    = {Weigand, Isabel and Ronchi, Cristina L. and Rizk-Rabin, Marthe and Dalmazi, Guido Di and Wild, Vanessa and Bathon, Kerstin and Rubin, Beatrice and Calebiro, Davide and Beuschlein, Felix and Bertherat, J{\´e}r{\^o}me and Fassnacht, Martin and Sbiera, Silviu},
  title     = {Differential expression of the protein kinase A subunits in normal adrenal glands and adrenocortical adenomas},
  series = {Scientific Reports},
  volume    = {7},
  journal   = {Scientific Reports},
  number    = {49},
  doi       = {10.1038/s41598-017-00125-8},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-157952},
  year      = {2017},
  abstract  = {Somatic mutations in protein kinase A catalytic α subunit (PRKACA) were found to be causative for 30-40\% of cortisol-producing adenomas (CPA) of the adrenal gland, rendering PKA signalling constitutively active. In its resting state, PKA is a stable and inactive heterotetramer, consisting of two catalytic and two regulatory subunits with the latter inhibiting PKA activity. The human genome encodes three different PKA catalytic subunits and four different regulatory subunits that are preferentially expressed in different organs. In normal adrenal glands all regulatory subunits are expressed, while CPA exhibit reduced protein levels of the regulatory subunit IIβ. In this study, we linked for the first time the loss of RIIβ protein levels to the PRKACA mutation status and found the down-regulation of RIIβ to arise post-transcriptionally. We further found the PKA subunit expression pattern of different tumours is also present in the zones of the normal adrenal cortex and demonstrate that the different PKA subunits have a differential expression pattern in each zone of the normal adrenal gland, indicating potential specific roles of these subunits in the regulation of different hormones secretion.},
  language  = {en}
}
@article{SiebertCiatoMurakamietal.2019,
  author    = {Siebert, Claudia and Ciato, Denis and Murakami, Masanori and Frei-Stuber, Ludwig and Perez-Rivas, Luis Gustavo and Monteserin-Garcia, Jos{\´e} Luis and N{\"o}lting, Svenja and Maurer, Julian and Feuchtinger, Annette and Walch, Axel K. and Haak, Harm R. and Bertherat, J{\´e}r{\^o}me and Mannelli, Massimo and Fassnacht, Martin and Korpershoek, Esther and Reincke, Martin and Stalla, G{\"u}nter K. and Hantel, Constanze and Beuschlein, Felix},
  title     = {Heat Shock Protein 90 as a Prognostic Marker and Therapeutic Target for Adrenocortical Carcinoma},
  series = {Frontiers in Endocrinology},
  volume    = {10},
  journal   = {Frontiers in Endocrinology},
  doi       = {10.3389/fendo.2019.00487},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-238029},
  year      = {2019},
  abstract  = {Background: Adrenocortical carcinoma (ACC) is a rare tumor entity with restricted therapeutic opportunities. HSP90 (Heat Shock Protein 90) chaperone activity is fundamental for cell survival and contributes to different oncogenic signaling pathways. Indeed, agents targeting HSP90 function have shown therapeutic efficacy in several cancer types. We have examined the expression of HSP90 in different adrenal tumors and evaluated the use of HSP90 inhibitors in vitro as possible therapy for ACC. Methods: Immunohistochemical expression of HSP90 isoforms was investigated in different adrenocortical tumors and associated with clinical features. Additionally, a panel of N-terminal (17-allylamino-17-demethoxygeldanamycin (17-AAG), luminespib, and ganetespib) and C-terminal (novobiocin and silibinin) HSP90 inhibitors were tested on various ACC cell lines. Results: Within adrenocortical tumors, ACC samples exhibited the highest expression of HSP90β. Within a cohort of ACC patients, HSP90β expression levels were inversely correlated with recurrence-free and overall survival. In functional assays, among five different compounds tested luminespib and ganetespib induced a significant decrease in cell viability in single as well as in combined treatments with compounds of the clinically used EDP-M scheme (etoposide, doxorubicin, cisplatin, mitotane). Inhibition of cell viability correlated furthermore with a decrease in proliferation, in cell migration and an increase in apoptosis. Moreover, analysis of cancer pathways indicated a modulation of the ERK1/2—and AKT—pathways by luminespib and ganetespib treatment. Conclusions: Our findings emphasize HSP90 as a marker with prognostic impact and promising target with N-terminal HSP90 inhibitors as drugs with potential therapeutic efficacy toward ACC.},
  language  = {en}
}