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Multi-omics analysis defines core genomic alterations in pheochromocytomas and paragangliomas

ABSTRACT: Pheochromocytomas (PCC) and paragangliomas (PGL) are neural crest-derived tumors. We performed the integrated genomic analysis of a collection of PCC/PGL from the French COMETE network using SNP arrays, whole-exome sequencing, DNA methylation arrays, mRNA expression arrays and miRNA sequencing. We found that PCC/PGL are characterized by a low mutation rate, with few recurrent somatic mutations and focal copy number alterations (CNAs). In contrast, we detected recurrent broad CNAs strongly associated with known molecular groups, often leading to the biallelic inactivation of the known susceptibility genes of PCC/PGL. We also identified DNA methylation changes and miRNA expression clusters strongly associated with molecular groups. Of note, overexpression of the miRNA cluster 182/96/183 is specific of SDHB-mutated tumors and induces invasive traits, whereas silencing of the imprinted DLK1-MEG3 miRNA cluster due to a loss of heterozygosity of the 14q32.2 locus is a potential driver in a subset of sporadic tumors. This comprehensive analysis illustrates the functional interdependence between genomic and epigenomic dysregulations underlying PCC/PGL.

PROVIDER: EGAS00001000933 | EGA |

REPOSITORIES: EGA

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Multi-omics analysis defines core genomic alterations in pheochromocytomas and paragangliomas.

Castro-Vega Luis Jaime LJ Letouzé Eric E Burnichon Nelly N Buffet Alexandre A Disderot Pierre-Hélie PH Khalifa Emmanuel E Loriot Céline C Elarouci Nabila N Morin Aurélie A Menara Mélanie M Lepoutre-Lussey Charlotte C Badoual Cécile C Sibony Mathilde M Dousset Bertrand B Libé Rossella R Zinzindohoue Franck F Plouin Pierre François PF Bertherat Jérôme J Amar Laurence L de Reyniès Aurélien A Favier Judith J Gimenez-Roqueplo Anne-Paule AP

Nature communications 20150127

Pheochromocytomas and paragangliomas (PCCs/PGLs) are neural crest-derived tumours with a very strong genetic component. Here we report the first integrated genomic examination of a large collection of PCC/PGL. SNP array analysis reveals distinct copy-number patterns associated with genetic background. Whole-exome sequencing shows a low mutation rate of 0.3 mutations per megabase, with few recurrent somatic mutations in genes not previously associated with PCC/PGL. DNA methylation arrays and miRN ...[more]

PMID: 25625332

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Project description:Pheochromocytoma (PCC) and paraganglioma (PGL) are rare neuroendocrine neoplasias of neural crest origin. They can be part of several syndromes, and their mRNA profile is dependent on genetic background, but questions related to clinical behavior or even main location remain unanswered. MicroRNAs are key modulators of target genes through translational repression, mRNA degradation, or both, and therefore they could resolve some of these issues. To determine the role microRNAs play in tumorigenesis and progression of PCC/PGL, as well as to identify microRNA biomarkers specifically related to different PCC/PGL genetic classes known so far, we characterized microRNA profiles in a large series of frozen tumors with germline mutations in SDHD, SDHB, VHL, RET, NF1, and TMEM127 genes through microarray analysis. We identified microRNA signatures specific to, as well as common among, the genetic classes of PCC/PGLs, and the best candidate microRNAs (miR-122, miR-126*, miR-129*, miR-133b, miR-137, miR-183, miR-210, miR-382, miR-488, miR-885-5p, and miR-96) were validated in an independent series of formalin-fixed paraffin-embedded PCC/PGL samples by qRT-PCR. MicroRNA-137, -96/183, and -143/145 expression in PCC/PGLs correlated inversely with the differentiation status of tumor cells. MicroRNA-210, -382, and -380 could modulate pseudohypoxic cellular response in VHL-deficient PCC/PGL. MicroRNA-193b, -365, and -424 were commonly downregulated among all genetic classes, suggesting their involvement in cell cycle control and differentiation. Herein, we demonstrate that PCC/PGLs have different microRNA profiles according to the underlying primary mutation, suggesting they could be used as specific biomarkers and add information on the etiology of these tumors. For this study, we employed the Agilent-019118 Human miRNA Microarray 2.0 G4470B (with Labeling kit: Agilent miRNA labeling reagent and Hybridization Kit, Cat # 5190-0408) to perform microRNA expression profiling on a large series of 54 fresh-frozen tissue samples, including a total of 48 genetically characterized pheochromocytomas (n=37) and paragangliomas (n=11) (8 SDHB-related tumors, 4 SDHD-related tumors, 14 Ret-related tumors, 12 VHL-related tumors, 4 NF1-related tumors, 3 TMEM127-related tumors, and 3 familial pheochromocytoma (FPCC) samples), and 6 normal adrenal medulla. Normalization of array data was performed applying the robust multiarray average (RMA) method using the AgiMicroRna package in Bioconductor. RMA normalization, by default, merges replicates of each probe and produces an Eset with a single value for each microRNA.

Dataset Information

Multi-omics analysis defines core genomic alterations in pheochromocytomas and paragangliomas

Publications

Multi-omics analysis defines core genomic alterations in pheochromocytomas and paragangliomas.

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