Published in

BioScientifica, Endocrine-Related Cancer, 6(19), p. 805-816, 2012

DOI: 10.1530/erc-12-0251

Links

Tools

Export citation

Search in Google Scholar

Quantitative, genome-wide analysis of the DNA methylome in sporadic pituitary adenomas

This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

Full text: Unavailable

Green circle
Preprint: archiving allowed
Green circle
Postprint: archiving allowed
Red circle
Published version: archiving forbidden
Data provided by SHERPA/RoMEO

Abstract

DNA methylation is one of the several epigenetic modifications that together with genetic aberrations are hallmarks of tumorigenesis including those emanating from the pituitary gland. In this study, we examined DNA methylation across 27 578 CpG sites spanning more than 14 000 genes in the major pituitary adenoma subtypes. Genome-wide changes were first determined in a discovery cohort comprising non-functioning (NF), growth hormone (GH), prolactin (PRL)-secreting and corticotroph (CT) adenoma relative to post-mortem pituitaries. Using stringent cut-off criteria, we validated increased methylation by pyrosequencing in 12 of 16 (75%) genes. Overall, these criteria identified 40 genes in NF, 21 in GH, six in PRL and two in CT that were differentially methylated relative to controls. In a larger independent cohort of adenomas, for genes in which hypermethylation had been validated, different frequencies of hypermethylation were apparent, where the KIAA1822 (HHIPL1) and TFAP2E genes were hypermethylated in 12 of 13 NF adenomas whereas the COL1A2 gene showed an increase in two of 13 adenomas. For genes showing differential methylation across and between adenoma subtypes, pyrosequencing confirmed these findings. In three of 12 genes investigated, an inverse relationship between methylation and transcript expression was observed where increased methylation of EML2, RHOD and HOXB1 is associated with significantly reduced transcript expression. This study provides the first genome-wide survey of adenoma, subtype-specific epigenomic changes and will prove useful for identification of biomarkers that perhaps predict or characterise growth patterns. The functional characterisation of identified genes will also provide insight of tumour aetiology and identification of new therapeutic targets.