• Made available online as an Accepted Preprint 5 January 2011
  • Accepted Preprint first posted online on 5 January 2011

Transcriptome analysis of adrenocortical cancers: from molecular classification to the identification of new treatments

  1. Jérôme Bertherat1,2,3
  1. 1Institut Cochin, Université Paris Descartes, CNRS (UMR 8104), 75014 Paris, France
    2Inserm, U1016, 75014 Paris, France
    3Department of Endocrinology, Reference Center for Rare Adrenal Diseases, Assistance Publique Hôpitaux de Paris, Hôpital Cochin, 75014 Paris, France
  1. (Correspondence should be addressed to J Bertherat who is now at Service des Maladies Endocriniennes et Métaboliques, Hôpital Cochin, 27, rue du Faubourg Saint-Jacques, 75014 Paris, France; Email: jerome.bertherat{at}cch.ap-hop-paris.fr)

Abstract

Transcriptome analysis has been successfully used to study the gene profile expression of adrenocortical tumors (ACT) for 7 years. The various studies reported to date have produced an abundance of new information on adrenocortical cancer (ACC), underlying the validity of this approach to study the molecular genetics and pathogenesis of these tumors. The gene expression profile of ACC clearly differs from that of benign adrenocortical adenomas (ACA). Interestingly, transcriptome analysis has the ability to establish a subclassification of ACC based on the gene expression profile. In particular, it is able to identify two groups of tumors with different outcomes (i.e. good prognosis and poor prognosis). This approach has been used to develop molecular markers for ACC diagnosis and prognostication. An IGF2 cluster of genes up-regulated in ACC has been identified. Transcriptome analysis has shown that, in comparison with ACA, IGF2 is indeed the gene most overexpressed in ACC. By contrast, genes associated with steroidogenesis are down-regulated in ACC. Genes controlling the cell cycle are dysregulated in ACC, and several are dramatically overexpressed. Analysis regarding the level of expression of Wnt/β-catenin and p53 signaling has shown alterations, in keeping with the known molecular somatic genetic defects of these pathways that are observed in ACC. This review summarizes the main findings of studies reporting ACC transcriptome analysis, demonstrating its power for ACT classification, and examines the resulting progress in understanding the pathogenesis of ACC. The potential for both ACC diagnosis and the identification of new therapeutic targets will be discussed.

  • Revision received 16 December 2010
  • Accepted 4 January 2011
| Table of Contents