Eur J Endocrinol
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DOI: 10.1530/eje.1.02116
European Journal of Endocrinology, Vol 154, Issue 4, 587-598
Copyright © 2006 by European Society of Endocrinology
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EXPERIMENTAL STUDY

Analysis by cDNA microarrays of gene expression patterns of human adrenocortical tumors

E P Slater, S M Diehl, P Langer, B Samans1, A Ramaswamy2, A Zielke and D K Bartsch

Department of Surgery, 1 Institute of Medical Biometry and Epidemiology and 2 Department of Pathology, Philipps-University Marburg, Baldingerstrasse, 35033 Marburg, Germany

(Correspondence should be addressed to E P Slater; Email: slater{at}med.uni-marburg.de)


   Abstract
Top
 Abstract
Introduction
 Materials and methods
 Results
 Discussion
 References
 
Objectives: Adrenocortical carcinoma (ACC) is a rare malignant neoplasm with extremely poor prognosis. The molecular mechanisms of adrenocortical tumorigenesis are still not well understood. The comparative analysis by cDNA microarrays of gene-expression patterns of benign and malignant adrenocortical tumors allows us to identify new tumor-suppressor genes and proto-oncogenes underlying adrenocortical tumorigenesis.

Design and methods: Total RNA from fresh-frozen tissue of 10 ACC and 10 benign adrenocortical adenomas was isolated after histologic confirmation of neoplastic cellularity of at least 85%. The reference consisted of pooled RNA of 10 normal adrenal cortex samples. Amplified RNA of tumor and reference was used to synthesize Cy3- and Cy5-fluorescently labeled cDNA in a flip-color technique. D-chips containing 11 540 DNA spots were hybridized and scanned and the images were analyzed by ImaGene 3.0 software.

Results: The comparative analysis of gene expression revealed many genes with more than fourfold expression difference between ACC and normal tissue (42 genes), cortical adenoma and normal tissue (11 genes), and ACC and cortical adenoma (21 genes) respectively. As confirmed by real-time PCR, the IGF2 gene was significantly upregulated in ACCs versus cortical adenomas and normal cortical tissue. Genes that were downregulated in adrenocortical tumors included chromogranin B and early growth response factor 1.

Conclusions: Comprehensive expression profiling of adrenocortical tumors by the cDNA microarray technique is a very powerful tool to elucidate the molecular steps associated with the tumorigenesis of these ill-defined neoplasms. To evaluate the role of identified genes, further detailed analyses, including correlation with clinical data, are required.


   Introduction
Top
 Abstract
 Introduction
Materials and methods
 Results
 Discussion
 References
 
Adrenal masses are a common disorder, affecting 3–7% of the population. Most turn out to be benign adrenocortical adenomas, which may be functional or nonfunctional. Much more rarely, these masses represent primary adrenal carcinoma (1). Adrenocortical carcinoma (ACC) is a highly malignant tumor with an incidence of ~1 per 1.7 million inhabitants per year in the West. Although ACC is rare, its highly aggressive behavior and 5-year survival rate of only 10–20% urgently require the decoding of its molecular basis to develop new strategies for diagnosis and treatment (2–6). The genetic background of adrenocortical tumorigenesis is poorly characterized. In other endocrine tissues, such as thyroid, there is conclusive evidence that hyperplasia and adenomas can precede cancer. In the adrenal, there are clinical cases of either hyperplasia or adenoma associated with later development of cancer. However, only a few studies have attempted to characterize this process on a molecular basis (7). Although it is unclear whether there is an adenoma-carcinoma sequence, common patterns seen in adenomas and carcinomas, and the accumulation of chromosomal imbalances with tumor progression support the existence of an adenoma-carcinoma sequence (8). X-chromosome inactivation analysis has shown that ACCs are of monoclonal origin, whereas benign adenomas may be monoclonal or polyclonal (9–11). The evidence gathered so far shows that the transition from adrenal adenoma to carcinoma involves a monoclonal proliferation of cells that, among other yet to be characterized defects, have undergone chromosomal duplication at the 11p15.5 locus, leading to overexpression of the insulin-like growth factor (IGF)2 gene and abrogation of expression of the CDKN1C and H19 genes (12, 13). TP53 has been shown to be involved in progression to carcinoma in a subset of patients, and it has been suggested that the frequency of adrenocorticotropic hormone (ACTH) receptor deletion might also be involved (1). Other key oncogenes and tumor suppressor genes remain to be identified. However, a recent study has reported that chromosomal loci 1p, 2p16, 11q13 and 17p may harbor potential tumor-suppressor genes, and chromosomes 4, 5 and 12 potential oncogenes associated with adrenal tumorigenesis (1). Therefore, detailed analysis of the genes involved is highly desirable. The development of the cDNA micro-array technique offers the opportunity to analyze a large number of genes, and allows comparative analysis of gene-expression profiling in benign and malignant adrenocortical tumors and the identification of tumor-suppressor genes and proto-oncogenes associated with the initiation and progression of adrenocortical tumors. Findings from these analyses might clarify adrenocortical tumorigenesis and lead to the establishment of new diagnostic and prognostic markers as well as the characterization of novel strategies for treatment. Therefore, we have performed a comprehensive and representative analysis of neoplastic and nonneoplastic adrenocortical tissue samples. We were particularly interested in evaluating the differential profile of 11 500 genes with established importance for development and progression of malignant diseases (1), to assess whether combinations of genes can predict malignant tumors (2) and to validate the results by real time RT–PCR of selected candidate genes (3).


   Materials and methods
Top
 Abstract
 Introduction
 Materials and methods
Results
 Discussion
 References
 
Normal and tumor samples

The adrenocortical tissues analyzed in this study were obtained from the collection of fresh frozen adrenal tissue of the Department of Surgery, Philipps-University Marburg, Germany, collected between 1996 and 2003. For the purpose of this study, 10 ACCs and 10 adrenocortical adenomas (four from Conn’s syndrome, four from Cushing’s disease and two nonfunctional adenomas), as well as 10 nonneoplastic adrenal cortical tissue samples, were evaluated. The classification was determined by both conventional histologic methods (14) and Weiss score (15) where adenomas met fewer than four and carcinomas at least four of the criteria. The ethics committee of the university approved this study, and all patients participating in the study consented to sampling. Frozen tumor samples were formalin-fixed and embedded in paraffin, and sections were evaluated by hematoxylin and eosin (HE) staining regarding diagnosis and neoplastic cellularity. Only tumor samples with neoplasticity of greater than 85% were included in the analysis. Control samples consisted of 10 histologically confirmed normal adrenal cortices.

RNA isolation was performed as follows. Frozen control and tumor tissue samples were dissected by the pathologist (A M) and homogenized in the presence of TRIzol Reagent (Invitrogen, Karlsruhe, Germany) by the manufacturer’s protocol. Total RNA was then further purified by digestion with DNase I and recovery of RNA with the RNeasy kit (Qiagen, Hilden, Germany) by the supplier’s protocol. To determine the integrity of RNA, standard RT–PCR for the amplification of 17{alpha}-hydroxylase and ß-actin was performed on 25 ng RNA with Qiagen’s OneStep RT–PCR kit by the manufacturer’s protocol. The primer sequences were as follows:

The reaction mixture was incubated at 50 ° C for 30 min and 95 ° C for 15 min, followed by 30 cycles of standard PCR (1-min denaturation at 95 ° C, 1-min annealing at 58 ° C and 1-min extension at 72 ° C). PCR products were visualized by ethidium bromide staining of PAGE. Only samples showing expression of Cyp17 as well as ß-actin were included in analysis. RNA (2 µ g) from 10 ACC and 10 adenomas (eight functional and two nonfunctional adenomas) was amplified with the Messa-geAmp aRNA Kit (Ambion, Huntingdon, UK). For the reference, the 10 control samples were amplified and then pooled. Amino allyl-cDNA was synthesized with 2 µ g aRNA and then labeled and purified with the CyScribe Post-Labeling Kit (Amersham Biosciences, Freiburg, Germany). Samples were fluorescently labeled with Cy3 and Cy5 by the flip-color technique.

For gene-expression profiling, the reference and tumor samples were mixed, denatured and then hybridized to microarrays for 16 h at 56 ° C and washed at a stringency of 0.1% SSC and 0.1% SDS. The microarray contains 11 540 DNA spots; detailed protocols and data description of the chip are available from the website: www.im-t.uni-marburg.de. Each experiment was performed as a sandwich hybridization with two arrays. Spot intensities were extracted from a scanned image with ImaGene 3.0 Software (BioDiscovery, Los Angeles, CA, USA). For each spot, median signal and background intensities for both channels were obtained. To account for spot differences, the background-corrected ratios of the two channels were calculated and log2-transformed. To balance the fluorescence intensities for the two dyes as well as to allow comparison of expression levels across experiments, the raw data were standardized. We used a spatial and intensity-dependent standardization (like Yang et al. (16)) to correct for inherent bias on each chip (the lowest scatter-plot). As each gene was measured twice in the sandwich hybridization, mean log-ratios M were calculated from replicates. If gene replicates differed more than the maximum of threefold and 75% of the calculated average log-ratio, or the background intensity was higher than signal intensity, the spot was excluded on that array. Differentially expressed genes were selected by a fold-change difference of at least 2 and an absolute value of the t-statistic of 1.96. Prior to the cluster analysis, the expression profile of each gene was centered by subtracting the mean observed value. Average linkage hierarchic clustering was then performed for genes as well as for chips with the Euclidean distance metric as implemented in the program Genesis (17).

The microarray results were validated for three candidate genes known to be expressed in adrenocortical tissue, including chromogranin B (CgB), early growth response gene 1 (Egr-1), and IGF2 by real-time RT–PCR analysis. For validation, 10 µ g total RNA were reverse transcribed with Superscript II reverse transcriptase (Invitrogen) and an oligo dT15 primer, according to the manufacturer’s instructions and previously published methods (18). Real-time PCR with the LightCycler System (Roche, Mannheim, Germany) was performed in a reaction mixture of 20 µ l using the QuantiTect SYBR Green PCR Kit according to the manufacturer (Qiagen). Primers designed for analysis were as follows:

The cycle threshold values for each gene were analyzed relative to those for GAPDH.


   Results
Top
 Abstract
 Introduction
 Materials and methods
 Results
Discussion
 References
 
For this study, 10 adrenocortical cancers, as established by histology, and 10 adenomas, of which eight were functional, including four aldosterone-producing adenomas, four cortisol-producing adenomas, and two nonfunctional adenomas (incidentalomas), were selected from the tissue bank of the Department of Surgery, Philipps-University Marburg. The clinicopathologic data of the adrenocortical tumors analyzed are summarized in Table 1Go. Normal adrenal cortex, adrenocortical adenoma and ACC were analyzed histologically to confirm tissue origin, lack of necrosis and, for tumors, neoplasticity of greater than 85%, before proceeding with nucleic acid purification. The normal tissue displayed regularly shaped nuclei and fat content. Fig. 1Go shows representative examples of HE staining of tissue samples used for the RNA purification. The adrenal origin of the samples was additionally ensured by the RNA expression of 17{alpha}-hydroxylase (Cyp17), in addition to ß-actin, by RT–PCR. All samples chosen for further analysis were positive for both Cyp17 and ß-actin (data not shown). Microarray analysis demonstrated that ACCs were more dissimilar to normal adrenal than adenomas. The adenomas were more closely related to each other and to normal adrenal; this is not an entirely unexpected result given the histologic similarity of the tissues. In particular, 40 differentially expressed genes were found in adenomas in comparison to normal adrenal (Table 2Go), and 144 differentially expressed genes were detected in ACCs (Table 3Go). As shown in Fig. 2Go and Table 4Go, more than 60 genes were found with at least a threefold change in mRNA levels. Both up- and downregulated genes were identified (Table 4Go). These genes, with at least threefold differences in mRNA expression, were then subjected to cluster analysis. Transcriptional profiles, which distinguish between benign and malignant adrenocortical tumors, identified several differentially expressed transcripts as demonstrated by cluster analysis (Fig. 2Go). The sample dendrogram revealed the similarities among the adenomas (T) and the carcinomas (A) respectively, and clearly distinguished the two groups. Two major clusters of genes were differentially expressed in the carcinomas compared with the adenomas: genes that were expressed at a higher level in the carcinomas and those that were expressed at a lower level in the carcinomas. The former include the gene for IGF-2 and potential oncogenes. The latter represent potential tumor-suppressor genes.


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  		Table 1 Pathologic and clinical aspects of adrenocortical cases used for profiling studies.
 

Figure 1
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  		Figure 1 HE staining of normal adrenal cortex (A), adenoma (B) and adrenocortical carcinoma (C). x 100.

 

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  		Table 2 List of genes found to be differentially regulated in adenomas relative to normal adrenal cortical tissue in microarray analysis.
 

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  		Table 3 List of genes found to be differentially regulated in ACC relative to normal adrenal cortical tissue in the microarray analysis.
 

Figure 2
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  		Figure 2 Hierarchic cluster analysis of differentially expressed genes in adrenal cortical adenomas and carcinomas. Both genes and individual tumors are clustered in this diagram. Green indicates downregulation of a gene in a given tumor; red indicates upregulation relative to the mean. Gray spots indicate missing data. Table 4Go provides the fold regulation for each gene. The numbers at the top identify the individual tumors. Brackets above the tumors and on the right side of gene list indicate the clustering.

 

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  		Table 4 List of Genes found to be differentially regulated in ACC relative to adenomas in the microarray analysisa.
 
Some of the differentially expressed genes were chosen for further analysis to ensure the validity of the microarray results. As expected from the literature (1, 12, 19), the IGF-2 gene expression was 3–7-fold greater in ACCs than in adenomas. Real-time RT–PCR confirmed this result where the cycle threshold crossing point (CT) for the ACC samples was 3–5 values less, representing a maximal increase in expression of 8–32-fold in comparison to the control or adenoma samples (Fig. 3Go).


Figure 3
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  		Figure 3 Real-time RT–PCR. Shown is a comparison of the results of the microarray analysis and quantitative PCR experiments documenting the expression of the indicated genes. The plot shows the change in the level of expression found in the microarray analysis ({square}) and the change in the cycle-threshold value from control found in real-time RT–PCR ({blacksquare}) for each gene relative to GAPDH. ACC: adrenocortical carcinoma.

 
As one of our main interests is the identification of potential tumor-suppressor genes whose investigation may contribute to the understanding of the pathomechanism of ACC, we decided to concentrate in our initial analysis on clearly downregulated genes. The tissue-specifically expressed gene, chromogranin B (CgB), was found to be downregulated in both adenomas (28-fold) (Table 2Go) and ACCs (13-fold) (Table 3Go). The loss of a tissue-specifically expressed gene could reflect dedifferentiation of tumor tissue. This decrease in expression was confirmed by real-time RT–PCR, which demonstrated an increase in the CT value from 4 to 5, representing at most a 16–32-fold decrease in expression, for the adenomas analyzed, and from 3 to 4, or at most a 8–16-fold decrease for the ACCs.

The Egr-1 gene was downregulated in ACC in comparison to normal adrenal by eightfold (Fig. 3Go). This finding was also confirmed by real-time RT–PCR, where the CT values for the ACCs were increased by 4, representing a maximal decrease in expression of up to 16-fold, Thus, for each of these candidate genes, the differential gene expression was confirmed by real-time RT–PCR, and the findings were comparable to those of the microarray analysis (Fig. 3Go).


   Discussion
Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
References
 
DNA microarray technology allows comprehensive examination of the transcriptional profile of tumors. It is rapidly being applied to various problems in pathology and oncology, such as tumor classification, and it is a useful gene discovery tool to complement other similar technologies. In this study, we used DNA microarrays to generate transcriptional profiles of benign and malignant adrenocortical tumors with various hormonal secretion profiles (Table 1Go). We demonstrated for the first time that these profiles can distinguish normal and benign tissues from malignant tumors and identify differentially expressed genes that may help to explain the pathogenesis of the disease and have diagnostic and therapeutic implications. Surprisingly, only 11 genes were found to be differentially expressed more than fourfold in comparing adenomas to normal tissue (Table 2Go). A comparison of the ACCs to normal tissue resulted in a list of 42 genes that were differentially expressed more than fourfold (Table 3Go), and the comparison ACCs to adenomas resulted in 21 genes that were more than fourfold differentially expressed.

The gene for chromogranin B (CgB) was found to be downregulated in both adenomas (28-fold) (Table 2Go) and ACCs (13-fold) (Table 3Go). This finding was confirmed by real-time PCR (Fig. 3Go). Chromogranins are representative proteins contained in endocrine cells of various organs, including some ductal cells of the breast. Homology between the BRCA1 protein (1214–1223) and the chromogranins has been detected, suggesting that chromogranin may play the role of a tumor suppressor, like BRCA1 (20). Our results suggest that loss of CgB may be an early event in adrenocortical tumorigenesis. In patients with lymph-node-negative primary invasive ductal breast carcinoma, CgB-negative tumors demonstrated a significantly poorer prognosis than in patients with CgB-positive tumors. In univariate analysis, a significantly increased risk of disease progression and death was present in patients with CgA-poor and CgB-poor tumors respectively (21). It was concluded that the CgB immunostaining pattern of the primary tumor can distinguish patients with increased risk of death in patients with sporadic medullary thyroid carcinoma. The problem of whether CgB represents a prognostic factor in ACCs requires a large-scale study.

Another interesting potential tumor suppressor is the Egr-1 gene. As validated by real-time PCR, it was down-regulated in ACC in comparison to normal adrenal cortex tissue and adrenal adenoma by eightfold and threefold respectively (Fig. 3Go). Egr-1 is a transcription factor that has previously been suggested to be a master switch regulating inflammatory parameters (22). Egr-1 is also known as nerve growth factor induced-A (NGFI-A), Krox-24, ZIF268, ETR103 and TIS8. It is a phosphorylated zinc-finger-containing transcription factor often associated with cell growth stimulation (23). The gene for Egr-1 is located on the q31.1 ‘cytokine cluster’ region of chromosome 5 in man, and is rapidly and transiently induced by a large number of stressful stimuli as well as growth factors and cytokines. In fact, Egr-1 has been proposed as a master switch of gene expression underlying coordinated responses to various types of injury (23).

Apoptosis-regulating genes, such as TP53 and {Delta} Np73{alpha} , are known to increase the expression of Egr-1 (24, 25). Egr-1 has previously been implicated in the development and maintenance of prostate cancer (26, 27). Thus, further detailed, large-scale studies are warranted to clarify the role of Egr-1 in ACC.

One of the most interesting overexpressed genes is IGF2 on chromosome 11p15. Like other groups, we found a 3–7-fold overexpression of IGF2 in ACCs compared with adenomas and normal adrenal cortex (1, 13, 19). IGF-I and IGF-II are polypeptides involved in metabolism, growth and cell differentiation. They are synthesized in various tissues and have endocrine and auto/paracrine mechanisms of action depending on the tissue origin (2, 3). Both peptides are normally produced in adrenocotical cells (4, 19, 28). Through its action on steroidogenesis enzymes, IGF-I maintains the differentiated functions of the cell (19, 29). The precise role of IGF-II in mature adrenocortical gland is less clear. The IGF2 gene induction has previously been described as one of the most significant differences between ACCs and adrenal adenomas (1). Genetic alterations involving the 11p15 locus are very common in malignant tumors, but are found only in rare adrenal adenomas (13). The fact that we found this as well is further verification of our results. However, in adreno-cortical tumors associated with Beckwith–Wiedemann syndrome, allelic losses at the 11p15 locus have been found in both adenomas and carcinomas as well as in familial carcinomas. Current data suggest that abnormalities in structure and/or expression of the IGF-II gene are a late event in the multistep tumorigenesis of sporadic adrenocortical neoplasms.

Several other genes were over- or underexpressed in ACCs compared with adrenocortical adenomas and normal adrenal cortex tissues, but we have not yet validated the expression pattern by real-time PCR. The presence of a gene on the list in Table 4Go does not indicate that the gene product is either necessary or sufficient for causing ACC, but only that it is expressed as part of the complex pattern of gene expression that occurs during the initiation of the disease.

During the course of our studies, three other groups performed similar analyses of adrenocortical tissue (19, 30, 31). In the search for reliable markers for the clinical management of adrenal tumors, de Fraipont et al. (31) designed an adrenal-specific microarray. They identified two clusters of genes, the IGF2 cluster and the steroidogenesis cluster, which, in combination, provide a good predictor of malignancy. As in our studies, they also confirmed the finding from the earlier analysis by Giordano et al. (19) demonstrating upregulation of IGF2 expression (30). Adrenal hyperplasia was analyzed in a similar fashion by Bourdeau et al. (30).

In summary, our findings indicate that microarray analysis can distinguish between ACC and adenomas by the differential expression of a set of the genes analyzed. Further analysis of the IGF2 gene validated the experimental design. Underexpression of the CgB gene was found in both types of neoplasms, and the Egr-1 gene was downregulated in the ACCs. Further detailed analyses are warranted to elucidate the role of these genes in adrenal tumorigenesis.


   Acknowledgements
 
We thank Michael Krause and Martin Eilers for assistance with the microarrays, Serdar Sel for help with the real-time PCR, and Brunhilde Chaloupka for excellent technical assistance.


   References
Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 

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Received 20 June 2005
Accepted 12 January 2006




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