Purpose: Our understanding of adrenocortical carcinoma (ACC) has improved considerably, yet many unanswered questions remain. For instance, can molecular subtypes of ACC be identified?If so, what is their underlying pathogenetic basis and do they possess clinical significance? Experimental Design: We did a whole genome gene expression study of a large cohort of adrenocortical tissues annotated with clinicopathologic data. Using Affymetrix Human Genome U133 Plus 2.0 oligonucleotide arrays, transcriptional profiles were generated for10 normal adrenal cortices (NC), 22 adrenocortical adenomas (ACA), and 33 ACCs. Results: The overall classification of adrenocortical tumors was recapitulated using principal component analysis of the entire data set. The NC and ACA cohorts showed little intragroup variation, whereas the ACC cohort revealed much greater variation in gene expression. A robust list of 2,875 differentially expressed genes in ACC compared with both NC and ACA was generated and used in functional enrichment analysis to find pathways and attributes of biological significance. Cluster analysis of the ACCs revealed two subtypes that reflected tumor proliferation, as measured by mitotic counts and cell cycle genes. Kaplan-Meier analysis of these ACC clusters showed a significant difference in survival (P < 0.020). Multivariate Cox modeling using stage, mitotic rate, and gene expression data as measured by the first principal component for ACC samples showed that gene expression data contains significant independent prognostic information (P < 0.017).Conclusions: This study lays the foundation for the molecular classification and prognostication of adrenocortical tumors and also provides a rich source of potential diagnostic and prognostic markers.

Adrenocortical carcinomas are rare, highly malignant tumors that account for only 0.2% of deaths due to cancer. Given the limited number of patients seen in most medical centers with this diagnosis, series usually reported are small and clinical trials not randomized or blinded. In an attempt to answer important questions concerning the management of patients with adrenal cancer, a consensus conference was organized and held at the University of Michigan in Ann Arbor, MI, 11–13 September 2003, with the participation of an international group of physicians who had reported on the largest series of patients with this disease and who had recognized basic and clinical research expertise in adrenal cortical cancer. Totally 43 questions were addressed by the presenters and recommendations discussed in plenary and breakout sessions. Evidence for the recommendations of this conference was at the 2–4+ level and based on available literature and participants’ experience. In addition to setting up guidelines in specific areas of the diagnosis and treatment of adrenal cancer, the conference recommended and initiated the planning of an international prospective trial for treatment of patients with adrenal cancer in stages III and IV. In terms of new therapies, first trials of dendritic cell therapy in human subjects with adrenal cancer have been started, but it is too early to comment on efficacy. Different strategies of immunotherapy, including DNA vaccination are currently being tried in animal models. There are no clinical gene therapy trials for human adrenal cortical cancer. The adrenals are a preferred target for adenovirus and the results of gene therapy in preclinical studies are promising. In addition, there is evidence that histone deacetylase inhibitors can further enhance the rate of adenoviral infectivity in human adrenal cancer cells. Testing of retroviral vectors, non-viral vectors, small interfering RNA technology, and combined approaches could be performed in various laboratories. Anti-angiogenic substances have only been applied in preclinical studies. The use of these and other agents in the treatment of adrenal cancer should be hypothesis-driven and based on a thorough analysis of tumor biology.

Comprehensive expression profiling of tumors using DNA microarrays has been used recently for molecular classification and biomarker discovery, as well as a tool to identify and investigate genes involved in tumorigenesis. Application of this approach to a cohort of benign and malignant adrenocortical tissues would be potentially informative in all of these aspects. In this study, we generated transcriptional profiles of 11 adrenocortical carcinomas (ACCs), 4 adrenocortical adenomas (ACAs), 3 normal adrenal cortices (NCs), and 1 macronodular hyperplasia (MNH) using Affymetrix HG_U95Av2 oligonucleotide arrays representing approximately 10,500 unique genes. The expression data set was used for unsupervised hierarchical cluster analysis as well as principal component analysis to visually represent the expression data. An analysis of variance on the three classes (NC, ACA plus MNH, and ACC) revealed 91 genes that displayed at least threefold differential expression between the ACC cohort and both the NC and ACA cohorts at a significance level of P < 0.01. Included in these 91 genes were those known to be up-regulated in adrenocortical tumors, such as insulin-like growth factor (IGF2), as well as novel differentially expressed genes such as osteopontin (SPP) and serine threonine kinase 15 (STK15). Increased expression of IGF2 was identified in 10 of 11 ACCs (90.9%) and was verified by quantitative reverse transcriptase-polymerase chain reaction. Select proliferation-related genes (TOP2A and Ki-67) were validated at the protein level using immunohistochemistry and adrenocortical tissue microarrays. Our results demonstrated significant and consistent gene expression changes in ACCs compared to benign adrenocortical lesions. Moreover, we identified several genes that represent potential diagnostic markers and may play a role in the pathogenesis of ACC.

Thyroid cancer poses a significant clinical challenge, and our understanding of its pathogenesis is incomplete. To gain insight into the pathogenesis of papillary thyroid carcinoma, transcriptional profiles of four normal thyroids and 51 papillary carcinomas (PCs) were generated using DNA microarrays. The tumors were genotyped for their common activating mutations: BRAF V600E point mutation, RET/PTC1 and 3 rearrangement and point mutations of KRAS, HRAS and NRAS. Principal component analysis based on the entire expression data set separated the PCs into three groups that were found to reflect tumor morphology and mutational status. By combining expression profiles with mutational status, we defined distinct expression profiles for the BRAF, RET/PTC and RAS mutation groups. Using small numbers of genes, a simple classifier was able to classify correctly the mutational status of all 40 tumors with known mutations. One tumor without a detectable mutation was predicted by the classifier to have a RET/PTC rearrangement and was shown to contain one by fluorescence in situ hybridization analysis. Among the mutation-specific expression signatures were genes whose differential expression was a direct consequence of the mutation, as well as genes involved in a variety of biological processes including immune response and signal transduction. Expression of one mutationspecific differentially expressed gene, TPO, was validated at the protein level using immunohistochemistry and tissue arrays containing an independent set of tumors. The results demonstrate that mutational status is the primary determinant of gene expression variation within these tumors, a finding that may have clinical and diagnostic significance and predicts success for therapies designed to prevent the consequences of these mutations.