Distinct transcriptional profiles of adrenocortical tumors uncovered by DNA microarray analysis

Abstract

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.

Figure 1.

Probe sets (n = 2913) with mean expression greater than 200 and SD divided by the mean >0.5 for the entire data set were selected. A: First two principal components for these probe sets. Probe sets were standardized by subtracting the mean and dividing by the SD. B: Dendrogram from average clustering using these probe sets. C and D: Similar principal components and dendrograms using only 91 probe sets with a fold change greater than three between the carcinoma and normal/adenoma cohorts with a P < 0.01 in both cases.

Figure 2.

Histology of typical ACC and the three outlying tumors identified by PCA. ACC13 is a well-differentiated or low-grade ACC. ACC14 is a myxoid variant of ACC. ACC19 is a poorly differentiated ACC. ACC17 is a typical high-grade ACC. H&E; original magnification, ×200.

Figure 3.

Ninety-one probe sets that gave P < 0.01 for F-tests of both carcinoma versus normal and carcinoma versus adenoma that also had both fold changes larger than three, or smaller than 0.333 (see text). A central value for each probe set was determined by averaging log-transformed data, and taking the anti-logarithm. Colors represent the fold change for each sample from this value. The heat map was made using Treeview. The probe set designation, the gene symbol, and the unigene title, as well as the fold change in transcript level, are shown. Samples are labeled as follows: N = NC, A = ACA, H = MNH, and C = ACC.

Figure 4.

Up-regulation of IGF2 in ACC. A: Expression of IGF2, represented by three probe sets (light gray = 36782_s_at, medium gray = 1591_s_at, and dark gray = 2079_s_at), in the adrenocortical samples. B: Q-RT-PCR for IGF2 and GAPDH in the adrenocortical samples. Samples are labeled as follows: N = NC, A = ACA, H = MNH, and C = ACC.

Figure 5.

Array transcript data and protein validation studies of select proliferation markers. A: Up-regulation of TOP2A in ACC. Transcript data for three probe sets (light gray = 40145_at, medium gray = 904_s_at, and dark gray = 1592_at) the adrenocortical cohort and two representative tissue cores that show high- and low-level immunoreactivity for TOP2A. B: Up-regulation of Ki-67 in ACC. Transcript data (419_at) for the adrenocortical cohort and two representative tissue cores that show high and moderate levels of mib-1 immunoreactivity.