Abstract
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 miRNA sequencing identify DNA methylation changes and miRNA expression clusters strongly associated with messenger RNA expression profiling. Overexpression of the miRNA cluster 182/96/183 is specific in SDHB-mutated tumours and induces malignant traits, whereas silencing of the imprinted DLK1-MEG3 miRNA cluster appears as a potential driver in a subgroup of sporadic tumours. Altogether, the complete genomic landscape of PCC/PGL is mainly driven by distinct germline and/or somatic mutations in susceptibility genes and reveals different molecular entities, characterized by a set of unique genomic alterations.
Highlights
Pheochromocytomas and paragangliomas (PCCs/PGLs) are neural crest-derived tumours with a very strong genetic component
We demonstrated that ectopic expression of miR-183/96 but not miR-182 in immortalized mouse chromaffin cells induces an epithelial-to-mesenchymal transition (EMT) phenotype (Fig. 3d and Supplementary Fig. 5)
The integrative genomic analysis of the well-annotated and genotyped Cortico et Medullosurrenale: les Tumeurs Endocrines’ (COMETE) cohort demonstrated that mutation status in PCC/PGL susceptibility genes is strongly correlated with multiomics data
Summary
Pheochromocytomas and paragangliomas (PCCs/PGLs) are neural crest-derived tumours with a very strong genetic component. 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. The complete genomic landscape of PCC/PGL is mainly driven by distinct germline and/or somatic mutations in susceptibility genes and reveals different molecular entities, characterized by a set of unique genomic alterations. At least 12 susceptibility genes have been identified comprising two oncogenes (RET and HIF2A) and ten tumour suppressors (NF1, VHL, SDHA, SDHB, SDHC, SDHD, SDHAF2, FH, TMEM127 and MAX). We present an integrated genomic analysis including whole-exome sequencing, single-nucleotide polymorphism (SNP) array, as well as mRNA, miRNA and DNA methylation profiling, aiming to characterize the major genomic alterations underlying PCCs/PGLs
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