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Fidéline Bonnet-Serrano and Jérôme Bertherat

This review describes the molecular alterations observed in the various types of tumors of the adrenal cortex, excluding Conn adenomas, especially the alterations identified by genomic approaches these last five years. Two main forms of bilateral adrenocortical tumors can be distinguished according to size and aspect of the nodules: primary pigmented nodular adrenal disease (PPNAD), which can be sporadic or part of Carney complex and primary bilateral macro nodular adrenal hyperplasia (PBMAH). The bilateral nature of the tumors suggests the existence of an underlying genetic predisposition. PPNAD and Carney complex are mainly due to germline-inactivating mutations of PRKAR1A, coding for a regulatory subunit of PKA, whereas PBMAH genetic seems more complex. However, genome-wide approaches allowed the identification of a new tumor suppressor gene, ARMC5, whose germline alteration could be responsible for at least 25% of PBMAH cases. Unilateral adrenocortical tumors are more frequent, mostly adenomas. The Wnt/beta-catenin pathway can be activated in both benign and malignant tumors by CTNNB1 mutations and by ZNRF3 inactivation in adrenal cancer (ACC). Some other signaling pathways are more specific of the tumor dignity. Thus, somatic mutations of cAMP/PKA pathway genes, mainly PRKACA, coding for the catalytic alpha-subunit of PKA, are found in cortisol-secreting adenomas, whereas IGF-II overexpression and alterations of p53 signaling pathway are observed in ACC. Genome-wide approaches including transcriptome, SNP, methylome and miRome analysis have identified new genetic and epigenetic alterations and the further clustering of ACC in subgroups associated with different prognosis, allowing the development of new prognosis markers.

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Fady Hannah-Shmouni, Annabel Berthon, Fabio R Faucz, Juan Medina Briceno, Andrea Gutierrez Maria, Andrew Demidowich, Mirko Peitzsch, Jimmy Masjkur, Fidéline Bonnet-Serrano, Anna Vaczlavik, Jérôme Bertherat, Martin Reincke, Graeme Eisenhofer, and Constantine A Stratakis

Biochemical characterization of primary bilateral macronodular adrenocortical hyperplasia (PBMAH) by distinct plasma steroid profiles and its putative correlation to disease has not been previously studied. LC-MS/MS–based steroid profiling of 16 plasma steroids was applied to 36 subjects (22 females, 14 males) with PBMAH, 19 subjects (16 females, 3 males) with other forms of adrenal Cushing's syndrome (ACS), and an age and sex-matched control group. Germline ARMC5 sequencing was performed in all PBMAH cases. Compared to controls, PBMAH showed increased plasma 11-deoxycortisol, corticosterone, 11-deoxycorticosterone, 18-hydroxycortisol, and aldosterone, but lower progesterone, DHEA, and DHEA-S with distinct differences in subjects with and without pathogenic variants in ARMC5. Steroids that showed isolated differences included cortisol and 18-oxocortisol with higher (P < 0.05) concentrations in ACS than in controls and aldosterone with higher concentrations in PBMAH when compared to controls. Larger differences in PBMAH than with ACS were most clear for corticosterone, but there were also trends in this direction for 18-hydroxycortisol and aldosterone. Logistic regression analysis indicated four steroids – DHEA, 11-deoxycortisol, 18-oxocortisol, and corticosterone – with the most power for distinguishing the groups. Discriminant analyses with step-wise variable selection indicated correct classification of 95.2% of all subjects of the four groups using a panel of nine steroids; correct classification of subjects with and without germline variants in ARMC5 was achieved in 91.7% of subjects with PBMAH. Subjects with PBMAH show distinctive plasma steroid profiles that may offer a supplementary single-test alternative for screening purposes.

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Simon Faillot, Thomas Foulonneau, Mario Néou, Stéphanie Espiard, Simon Garinet, Anna Vaczlavik, Anne Jouinot, Windy Rondof, Amandine Septier, Ludivine Drougat, Karine Hécale-Perlemoine, Bruno Ragazzon, Marthe Rizk-Rabin, Mathilde Sibony, Fidéline Bonnet-Serrano, Jean Guibourdenche, Rosella Libé, Lionel Groussin, Bertrand Dousset, Aurélien de Reyniès, Jérôme Bertherat, and Guillaume Assié

Benign adrenal tumors cover a spectrum of lesions with distinct morphology and steroid secretion. Current classification is empirical. Beyond a few driver mutations, pathophysiology is not well understood. Here, a pangenomic characterization of benign adrenocortical tumors is proposed, aiming at unbiased classification and new pathophysiological insights. Benign adrenocortical tumors (n = 146) were analyzed by transcriptome, methylome, miRNome, chromosomal alterations and mutational status, using expression arrays, methylation arrays, miRNA sequencing, SNP arrays, and exome or targeted next-generation sequencing respectively. Pathological and hormonal data were collected for all tumors. Pangenomic analysis identifies four distinct molecular categories: (1) tumors responsible for overt Cushing, gathering distinct tumor types, sharing a common cAMP/PKA pathway activation by distinct mechanisms; (2) adenomas with mild autonomous cortisol excess and non-functioning adenomas, associated with beta-catenin mutations; (3) primary macronodular hyperplasia with ARMC5 mutations, showing an ovarian expression signature; (4) aldosterone-producing adrenocortical adenomas, apart from other benign tumors. Epigenetic alterations and steroidogenesis seem associated, including CpG island hypomethylation in tumors with no or mild cortisol secretion, miRNA patterns defining specific molecular groups, and direct regulation of steroidogenic enzyme expression by methylation. Chromosomal alterations and somatic mutations are subclonal, found in less than 2/3 of cells. New pathophysiological insights, including distinct molecular signatures supporting the difference between mild autonomous cortisol excess and overt Cushing, ARMC5 implication into the adreno-gonadal differentiation faith, and the subclonal nature of driver alterations in benign tumors, will orient future research. This first genomic classification provides a large amount of data as a starting point.