Poster Presentation 25th Lorne Cancer Conference 2013

Molecular profiling of Pheochromocytoma  (#176)

Aidan Flynn 1 , Diana Benn 2 , Roderick Clifton-Bligh 2 , Alison Trainer 1 , Paul James 1 , Annette Hogg 1 , Bruce Robinson 2 , Richard Tothill 1 , Rodney J Hicks 1
  1. Peter MacCallum Cancer Centre, East Melbourne, VIC, Australia
  2. Kolling Institute, Royal North Shore Hospital, Sydney, NSW, Australia

Pheochromocytoma (PC) are neuroendocrine tumours that arise from adrenal medullary and extra-adrenal chromaffin cells. Paraganglioma (PGL) are a closely related tumour arising either from chromaffin cells in sympathetic paraganglia or non-chromaffin cells in parasympathetic glomera. These tumours are relatively rare with an estimated incidence of around 1 per 100,000 people2 and can be classified as either functional or non-functional depending on their ability to secrete catecholamines. There are currently 13 genes linked to an increased risk of developing pheochromocytoma alone or as part of a multi-site cancer syndrome. Mutations in these genes account for more than 90% of ostensibly heritable PC but only around 15% of sporadic PC3 , as such, the genetic events contributing to sporadic PC remain largely unknown.  Microarray analysis and unsupervised clustering performed on a large cohort revealed that PC gene expression patterns cluster into two major groups; a pseudo-hypoxia group which consists of tumours with a mutation in VHL or any of the SDHx genes, and a Receptor Tyrosine Kinase (RTK) signaling group harboring mutations in RET, NF1, or TMEM1271.  Recent developments in biotechnology have accelerated biological discovery and given rise to integrated genomics, a process whereby data from two or more genomic technologies are integrated to better understand the genomic landscape. This project aims to combine RNA-Seq, exome sequencing, and copy number variation (CNV) analysis to better understand the underlying genetic changes driving PC. Through development of a cross platform classifier, we aim to leverage existing microarray data to classify our RNA-Seq data into psuedo-Hypoxia or RTK sub groups. The sub-classification will be used to guide selection of candidate genes found to be mutated by exome sequencing and/or found to be in a region of chromosome instability by CNV analysis.

  1. Dahia, P. L., K. N. Ross, et al. (2005). "A HIF1alpha regulatory loop links hypoxia and mitochondrial signals in pheochromocytomas." PLoS Genet 1(1): 72-80.
  2. Beard, C. M., S. G. Sheps, et al. (1983). "Occurrence of pheochromocytoma in Rochester, Minnesota, 1950 through 1979." Mayo Clin Proc 58(12): 802-804.
  3. Mannelli, M., M. Castellano, et al. (2009). "Clinically guided genetic screening in a large cohort of italian patients with pheochromocytomas and/or functional or nonfunctional paragangliomas." J Clin Endocrinol Metab 94(5): 1541-1547