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Whole Genome Expression Profiling of Glucose-Dependent Insulinotropic Peptide (GIP)- and Adrenocorticotropin-Dependent Adrenal Hyperplasias Reveals Novel Targets for the Study of GIP-Dependent Cushing’s Syndrome

Laboratories of Endocrine Pathophysiology, Cellular Biology of Hypertension, and Molecular Medicine, Department of Medicine, Centre Hospitalier de l’Université de Montréal, Montreal, Québec, Canada H2W1T8

Address all correspondence and requests for reprints to: Dr. André Lacroix, Department of Medicine, Hôtel-Dieu du Centre Hospitalier de l’Université de Montréal, Montréal, Québec, Canada H2W 1T8. E-mail: andre.lacroix{at}umontreal.ca.

	Abstract

Top Abstract Introduction Subjects and Methods Results Discussion References

 
Context: The mechanisms responsible for the ectopic adrenal expression of glucose-dependent insulinotropic peptide (GIP) receptor (GIPR) in GIP-dependent Cushing’s syndrome (CS) are unknown. Chronic adrenal stimulation by ACTH in Cushing’s disease or GIP in GIP-dependent ACTH-independent macronodular adrenal hyperplasia both lead to the induction of genes implicated in adrenal proliferation and steroidogenesis.

Objective: The objective of the study was to identify genes differentially expressed specifically in GIP-dependent CS that could be implicated in the ectopic expression of GIPR.

Methods: We used the Affymetrix U133 plus 2.0 microarray oligochips to compare the whole genome expression profile of adrenal tissues from five cases of GIP-dependent bilateral ACTH-independent macronodular adrenal hyperplasia with CS, one case of GIP-dependent unilateral adenoma with CS, five cases of ACTH-dependent hyperplasias, and a pool of adrenals from 62 normal individuals.

Results: After data normalization and statistical filtering, 723 genes with differential expression were identified, including 461 genes or sequences with a known functional implication, classified in eight dominant functional classes. Specific findings include repression of perilipin, the overexpression of 13 G protein-coupled receptors, and the potential involvement of Rho-GTPases. We also isolated 94 probe sets potentially linked to the formation of GIP-dependent nodules adjacent to the diffuse hyperplasia. These included probe sets related to the linker histone H1 and repression of RXRa and CCND2. The expression profiles for eight genes were confirmed by real-time RT-PCR.

Conclusion: This study identified an extensive series of potentially novel target candidate genes that could be implicated in the molecular mechanisms of ectopic expression of the GIPR as well as in the multistep progression of GIP-dependent CS.

	Introduction

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PRIMARY CUSHING’S SYNDROME (CS) is most frequently secondary to unilateral adrenocortical adenomas and less frequently to carcinomas. Approximately 10% of cases are secondary to bilateral ACTH-independent macronodular adrenal hyperplasias (AIMAH) and primary pigmented nodular adrenocortical disease (1). Unlike in primary pigmented nodular adrenocortical disease, with or without Carney complex, no gene mutation has yet been described as the predominant cause of AIMAH, except for rare cases of GNAS1 mutations without McCune Albright syndrome (2).

Clinical manifestations of CS usually do not occur before the fifth or sixth decade of life in patients with AIMAH (3). Most cases of AIMAH appear to be sporadic, but there are now several reports of familial cases of AIMAH with presentation, suggesting an autosomal dominant transmission (3). Analysis of AIMAH tissues showed different clonal patterns between glands and between nodules, which suggests that different stages of a common multistep tumoral process are present in different locations in AIMAH at the same time (4, 5, 6). Because both adrenals are affected in either familial or sporadic cases, AIMAH is likely to be secondary to a germinal mutation or a somatic mutation occurring at an early stage of embryogenesis in a cell, which will give rise to both adrenal glands. This initial genetic event would be responsible for the development of early diffuse hyperplasia. Several secondary clonal events would be responsible for the development of the heterogeneous nodules appearing progressively during the following decades of life (7).

The most frequently observed feature of AIMAH is the adrenal expression of one or several aberrant G protein-coupled receptors (GPCRs), regulating steroidogenesis (7, 8). The aberrant GPCRs have included those for glucose-dependent insulinotropic peptide (GIP), vasopressin, catecholamines, LH/human chorionic gonadotropin (hCG), serotonin, angiotensin II, and possibly leptin (3, 7, 8). The GIP receptor (GIPR) gene sequence analysis did not reveal mutations in adrenals of patients with GIP-dependent CS that could account for its ectopic expression (9). Although specificity protein-1 and -3 transcription factors (Sp1 and Sp3) are required determinants in GIPR’s gene expression, we did not observe any specific changes in the expression levels of these factors in GIP-dependent AIMAH (10). Whether the ectopic expression of the GIPR is a primary event in AIMAH development is still unknown; however, it was recently shown that bovine adrenal cells transfected with the GIPR and implanted under the renal capsule of mice develop adenomatous tissue and mild ACTH-independent CS (11).

The purpose of this study was to identify genes responsible for the ectopic adrenocortical expression of GIPR in GIP-dependent CS and delineate the molecular mechanisms and signaling pathways potentially implicated in the formation of AIMAH. We investigated the transcriptome profile of six patients with GIP-dependent CS, five from bilateral AIMAH, and one from unilateral adenoma and compared it with five patients with ACTH-dependent CS and a pool of normal adrenal glands. Using the U133 plus 2.0 oligochips (Affymetrix, Santa Clara, CA) spanning the entire human genome with more than 56,000 probe sets per slide, we identified 723 probe sets closely related to GIP-dependent AIMAH. Eight selected genes had their expression profile confirmed by real-time RT-PCR.

	Subjects and Methods

Top Abstract Introduction Subjects and Methods Results Discussion References

 
Subjects

Adrenal glands were surgically removed from patients and rapidly snap frozen. We studied adrenal tissues from five patients with Cushing’s disease (ACTH-dependent CS, H1-H5) and six patients with GIP-dependent CS. Of the latter, five presented sporadic nonfamilial AIMAH (G1-G5) and one a unilateral adenoma (A1). In one of the five AIMAH cases (G5), the disease had progressed asynchronously in both adrenals as the right adrenal included two GIP-dependent nodules that developed adjacent to the diffuse GIP-dependent hyperplasia [previously published (12)]; each nodule was studied in separate chips (N1 and N2) and compared with the diffuse hyperplasia portion (G5). Clinical details of the patients with GIP-dependent CS have been published previously [A1 (13), G1 (14), G2 and G4 (15, 16), and G5 (12)]. No other aberrant receptors were identified during this in vivo evaluation in addition to GIPR in these patients (17). A pool of commercially available RNA (CLONTECH, Palo Alto, CA), isolated from normal adrenal glands of 62 Caucasian subjects aged 15–61 yr, was also included as the normal control. This study was approved by the Institutional Ethical Committee of Centre Hospitalier de l’Université de Montréal, and all patients provided written informed consent.

RNA isolation and purification

Total RNA was isolated using TriZOL reagent (Invitrogen, Carlsbad, CA) following the manufacturer’s recommendations. RNAs with a 260:280 nm absorbance ratio between 1.8 and 2.2 were further purified on an RNeasy minikit (QIAGEN, Valencia, CA). Quality of total RNA was evaluated on an Agilent 2100 Bioanalyzer system (Agilent, Palo Alto, CA).

Sample labeling and hybridization

Microarray experiments were performed using the human expression HG-U133 plus 2.0 gene chip arrays (Affymetrix) following the manufacturer’s recommendations. Briefly, 5 µg total RNA were reverse transcribed with a T7-(dT) 24 oligonucleotide as primer, labeled with biotin, and fragmented using Affymetrix’s reagents. Ten micrograms of the resulting cRNA were loaded on each chip. After washing and staining with streptavidin-phycoerythrin (Invitrogen), the chips were scanned with a Genechip Scanner 3000 workstation (Affymetrix).

Statistical analysis

Probe set intensity levels were extracted from scanned oligochips by the gene chip operating system (version 1.2; Affymetrix) and normalized using all probe sets and a target value of 500. Two normalization steps were then applied to render the data sets comparable. First, each oligochip’s data set was centered on its median intensity. Second, each probe set was normalized to the control RNA. Probe sets statistically related to GIP-dependent cases were identified using a Student’s two-tailed heteroscedastic t test with an alpha of 0.05 (18). This cluster of probe sets was then filtered based on their flags (present, marginal, or absent, determined by gene chip operating system) and levels of expression. We retained only probe sets flagged as present in at least two of the five GIP-dependent AIMAH and represented by a minimum of a 2-fold increase in intensity. For probe sets with a mean ratio below –2, a present flag was to be scored in the control tissue. More information on detection calls can be gathered on Affymetrix’s web site (www.affymetrix.com). The resulting data set was inserted in the significance analysis of microarrays module (19) of The Institute Genomic Research’s multiple experiment viewer (TMEV) (20) to determine the false discovery rate of significant genes. Gene function analysis was performed based on information provided by Affymetrix’s NetAffx Analysis center (21) and the National Center for Biotechnology Information’s various databases. We used the Gfinder tool (22) to identify predominant gene ontology terms in the data set. Hierarchical clustering was performed on TMEV using average linkage and Pearson correlation as the distance metric (23). We also used the class predictor function of Genespring 7.2 (Agilent Technologies, Inc., Wilmington, DE) that identifies a list of genes whose expression profiles can discriminate tissues along a predetermined classification.

The data are presented as base 2 logarithm value of the ratio of expression in each tissue vs. control. Signal log ratios (SLR) better represent down-regulation data (24).

Real-time PCR quantification

The expression levels of eight genes of interest were further confirmed using real-time RT-PCR analysis. cDNA was created using Moloney murine leukemia virus reverse transcriptase (Invitrogen) and random primers (Invitrogen). We used the Quantitect SYBR green RT-PCR kit (QIAGEN) and a Rotor Gene 3000 cycler (Corbett Research, Sydney, Australia) to perform the reaction following the manufacturer’s protocols. Primers were designed to have a melting temperature of 60 C and amplify fragments between 90 and 110 bp long. Sequences for all the primers used are found in supplemental Table 1, published as supplemental data on The Endocrine Society’s Journals Online web site at http://jcem.endojournals.org. After a 15-min denaturation at 95 C, data were acquired for 50 cycles of 15 sec at 95 C, 30 sec at 59 C, and 30 sec at 72 C, followed by 7 min at 72 C. Melting curve analysis was routinely performed by incrementing the temperature from 60 to 95 C. Reaction efficiencies were estimated in a series of dilution curves. We used QuantumRNA 18S internal standards (Ambion, Austin, TX) as internal controls.

The entire data set was submitted to the Gene Omnibus database at the National Center for Biotechnology Information’s web site (no. GSE4060).

	Results

Top Abstract Introduction Subjects and Methods Results Discussion References

 
Expression profiles of GIP-dependent AIMAH

To identify molecular determinants of the ectopic expression of GIPR in cases of GIP-dependent CS, we compared the gene expression profile of the entire genome of five patients with GIP-dependent AIMAH with those observed in ACTH-dependent CS. It was hypothesized that genes implicated in cell proliferation could be similarly expressed in Cushing’s disease and GIP-dependent CS adrenals, compared with the normal control. However, genes related to the ectopic expression of GIPR should be found only in GIP-dependent AIMAH. Using a filtering protocol, 723 probe sets were identified and further analyzed (supplemental Table 2, published on The Endocrine Society’s Journals Online web site at http://jcem.endojournals.org). Using a hierarchical clustering of this data set, three major clusters of expression profile were identified and discriminated GIP-dependent AIMAH from Cushing’s disease (Fig. 1A).

View larger version (50K): [in this window] [in a new window]   FIG. 1. Hierarchical clustering using Pearson correlation as metrics. The data for 723 probe sets selected by an extraction procedure described in Subjects and Methods was submitted to hierarchical clustering of the probe sets’ intensity levels (A) and samples (B). Included in the experiment were five GIP-dependent hyperplasias (G1-G5), five ACTH-dependent hyperplasias (H1-H5), two GIP-dependent nodules (N1 and N2), and a GIP-dependent adenoma (A1).

Validation of microarray data

The expression profiles for eight different genes were confirmed by real-time RT-PCR (Fig. 2). A strong correlation was found between the expression profiles of the targeted genes in microarray and RT-PCR techniques; a Pearson correlation factor of 0.8 or more was observed for every target when comparing expression profiles obtained by microarray and RT-PCR in each tissue, except for Pyruvate carboxykinase 1 and GRM3 whose differential expression levels were higher in RT-PCR.

View larger version (18K): [in this window] [in a new window]   FIG. 2. Real-time RT-PCR confirmation of the data. Each gene was assayed in triplicate using sets of primer reported in supplemental Table 1. They were normalized using 18S as a housekeeping gene. Presented also are the SD and results of a Student’s t test between GIP-dependent (G1-G5) and ACTH-dependent (H1-H5) tissues. *, P < 0.05; **, P < 0.01; ***, P < 0.001. Except for GRM3 and PCK1, microarray and RT-PCR data were similar enough in each tissue to observe a Pearson correlation factor of 0.8, indicative of a satisfying reproducibility between both techniques.

Functional classification of the data

Our analysis revealed 10 predominant functional classes in which we could classify the 461 probe sets with a known function (Table 1). Some pathways and biological processes are found predominantly such as global metabolism, intracellular transport, cell signaling, and immunological processes. An 11th class was assigned to probe sets related to genes for which the only information available is that their expression is under the specific control of a known biological pathway (i.e. TNF induced protein); these probe sets are actual markers of the activation of a given pathway.

Sixty-nine probe sets were related to signaling processing, at both the membrane (Table 2) and intracellular levels. In these 69 probe sets, 17 were related to receptors, 13 of which are coupled to G protein, part of the family of seven-transmembrane domain receptors. Aside from two probe sets related to melanocortin receptor (MC2R), all of them including the GPR54, serotonin receptor 2B (HTR2B), GPCR 4 (GPR4), and endothelial differentiation sphingolipid GPCR 8 (EDG8) were overrepresented in GIP-dependent AIMAH. MC2R-related probe sets were all underrepresented in GIP-dependent tissues (SLR = –2.35, P = 0.009) and normal in ACTH-dependent cases (SLR = –0.2).

Metabolic, anabolic, and protein modification processes

Accounting for more than 20% of the gene list, the group of metabolic modification is the group with the largest number of probe sets, including many related to lipid metabolism (Table 3). We found repression of key genes such as lipoprotein lipase (SLR = –1.73; P = 0.02), lipidosin (SLR = –2.96; P = 0.02), and perilipin (SLR = –5.26; P = 0.03). This last gene was confirmed by RT-PCR (Fig. 2). Perilipin knockout studies have identified metabolic adaptations such as the repression of gluconeogenesis (26). PCK1 is the main control point of this step, and we found a strong repression of this gene by real-time RT-PCR (SLR = –5.01, P = 0.05). This repression goes along with a disruption in perilipin’s function.

In the different lists of probe sets related to signal transduction (supplemental Table 3), it is possible to identify key genes that could better define the molecular signaling mechanisms implicated in GIP-dependent AIMAH. One of the main observations is the presence of many members of the Rho/Rac/Cdc42 family of small GTPases. The overexpression of Rac2 (SLR = 3.19; P = 0.0008) was confirmed by RT-PCR (Fig. 2).

Immunological processes

We observed the presence of a few probe sets related to immunological processes that were highly overexpressed. This functional class was the only one overrepresented in one of the three clusters identified in the hierarchical clustering (Fig. 1A, red cluster) with 92% of the related probe sets up-regulated (Table 1). Overexpression of the Janus kinase 3 (SLR = 3.48, P = 8.4 x 10^–5), a key molecule in the Janus kinase/signal transducer and activator of transcription signaling pathway, was confirmed by RT-PCR.

Biological markers

We termed biological markers the probe sets related to sequences whose expression levels are known to be under the influence of specific stimuli. This list includes the specifically androgen-regulated gene (SLR = 4.36, P = 0.01), confirmed by RT-PCR. This gene is known to respond to stimulation by androgens but not glucocorticoids (27). Along with the apparent overexpression of the androgen receptor gene (SLR = 1.13, P = 0.003) and the repression of an estrogen-regulated gene in breast cancer (GREB1, SLR = –3.12, P = 0.02), the data suggest a potential activation of the androgen receptor-mediated transcription process.

Gene expression profiling in GIP-dependent adenoma and GIP-dependent nodules adjacent to GIP-dependent AIMAH

We studied the expression profiles of two GIP-dependent nodules that had developed adjacent to the G5 hyperplasia (samples N1 and N2) and a case of GIP-dependent adenoma (sample A1). We first performed a hierarchical clustering of different types of tissues using the entire set of genes. AIMAHs and ACTH-dependent tissues were closely clustered, followed by both nodules (Fig. 3), whereas the GIP-dependent adenoma was segregated (Fig. 3). To better understand the mechanisms behind the formation of the different nodules, we used the class prediction tool in Genespring 7.2 to isolate a list of genes whose expression profile is sufficient alone to discriminate tissues following predetermined criteria as training sets (here, tumor type, i.e. GIP-dependent nodules vs. hyperplasia). We isolated 200 tumor-type-specific genes; 94 had a ratio vs. control of at least 2 in either N1 or N2 (supplemental Table 4, published on The Endocrine Society’s Journals Online web site at http://jcem.endojournals.org), 55 overrepresented. Interestingly, 11 of these 55 genes were related to subunits of the linker histone H1. In the rest of the probe sets, we noted the presence of retinoid X receptor- (RXR) and cyclin D2 (CCND2), both repressed in the two nodules and not changed in the normal control tissue.

View larger version (9K): [in this window] [in a new window]   FIG. 3. Hierarchical clustering of tumor types. Each sample was pooled according to its tumor type and submitted to hierarchical clustering with Pearson correlation as distance metrics.

	Discussion

Top Abstract Introduction Subjects and Methods Results Discussion References

The abnormal expression of several other GPCRs could be secondary to a dysfunction in a common factor regulating the expression for these receptors. One of the only repressed GPCRs is the MC2R (SLR = –3.79; P = 0.01), already identified by RT-PCR in previous studies (15). Although ACTH’s implication in GIPR ectopic expression was suggested in one study (28), this finding, along with the barely detectable levels of ACTH observed in patients with GIP-dependent CS, suggest that a role for ACTH in GIPR overexpression is most unlikely. The aberrant expression of several receptors was not suspected based on the in vivo investigation protocol that certainly underestimates a very wide range of other GPCRs. Previous studies described the combined expression of leptin receptor (29) or LH/hCG receptor (30) along with GIPR. No statistical differences were observed between both groups for these two receptors (SLR = 0.75 and 0.26 with P = 0.85 and 0.64 for the leptin and LH/hCG receptors, respectively).

We also identified the potential implication of key proteins in lipid metabolism and signaling. GIPR is increasingly recognized for its implication in lipid metabolism (31), in particular at the level of lipid storage in adipocytes in response to insulin. Perilipin is a key protein in the availability of triglycerides and cholesterol in adipocytes (32) and steroidogenic tissues such as Leydig and adrenal cells (33). Coating lipid particles, this protein protects their content from hormone-sensitive lipase (34). A repression of this gene could be caused by stimulation of the cell by TNF (35, 36), leading to depletion of intracellular lipid pools and the necessity to incorporate triglycerides. Because GIPR regulates intracellular lipid storage (31), it will be interesting to examine whether perilipin can regulate GIPR expression. Lynn et al. (37) actually reported that a fatty acid load elevated GIPR’s gene expression. It is interesting to note that among the 11 GPCRs found to be overexpressed in this study, five have a function related to lipid metabolism and/or signaling: GIPR (31), elongation of very long fatty acids-like 4 (ELOVL4) (38), neuropeptide Y-6 receptor (NPY6R) (39), GPCR 4 (GPR4) (40), and endothelial differentiation, sphingolipid GPCR 8 (EDG8) (41).

Rac2 is one of the most highly overexpressed genes in the entire data set. Closely related to Rac1 (42), it functions as a hematopoietic-specific component of the nicotinamide adenine dinucleotide phosphate reduced (NADPH) oxidase complex, mediating cellular motility, intracellular signaling, focal adhesion, and cellular growth (43). It is interesting that this gene is strongly expressed in all hyperplasias and nodules but not in the GIP-dependent adenoma. It is also known that Rac2 is implicated in the stimulation of p38-MAPK (44), one of the end points of GIPR’s signaling pathway (45). Overexpression of subunits of the H1 histone, repression of RXR, and the repression of CCND2 in both nodules adjacent to an early GIP-dependent hyperplasia suggest that in addition to the ectopic expression of GIPR, secondary events are implicated in the development of more rapidly growing nodules in AIMAH.

There were many differences between a GIP-dependent adenoma and GIP-dependent AIMAH. Although the pathologies share the stimulation of cortisol production in adrenals by the GIP hormone, the adenoma was the only GIP-dependent tissue that did not share enough similarity with the GIP-dependent AIMAH to be included in the same hierarchical cluster (Fig. 1A). The same initiating events leading to aberrant receptor expression may be shared between both etiologies. Nevertheless, many secondary events are likely to occur in different cells of the initial diffuse hyperplasia during the long process of AIMAH evolution, leading to the secondary formation of multiple nodules (3, 7). We could argue that an adenoma is more likely to result from a single genetic alteration, whereas hyperplasias are most likely polyclonal and display more differences with ACTH-dependent tissues.

We also identified the modified expression of many other biological processes potentially involved in the formation of GIP-dependent AIMAH such as the overexpression of many genes of the immune system. Knowing that tumor cells can secrete cytokines or other complex of major histocompatibility molecules that can stimulate the immune system, the presence of so many probe sets significantly related to GIP-dependent AIMAH could be yet another explanation for this finding.

In conclusion, we used the most stringent statistical protocol with a biological significance (GIPR’s specific overexpression in GIP-dependent cases) to extract a list of 723 probe sets with intensity levels statistically related to GIP-dependent CS. Of these probe sets, we analyzed the 461 related to a gene with a known function in the literature. We were able to highlight key proteins and signaling pathways as potential players in the overexpression of the GIPR in GIP-dependent AIMAH such as perilipin’s repression, the overexpression of a series of GPCRs, the overexpression of immunity-related genes, and the potential involvement of Rho-GTPases. Those are new targets for the further elucidation of the molecular mechanism responsible for the ectopic expression of the GIPR and the multistep progression of GIP-dependent AIMAH.

	Acknowledgments

 
The authors acknowledge the technical help of Gilles Corbeil for the microarray hybridization technique and Gregory Voisin for the statistical analysis. We also thank Drs. Lynnette K. Nieman (Bethesda, MD); Wouter W. de Herder (Rotterdam, The Netherlands); Helga Gerl (Berlin, Germany); and Olivier Chabre (Grenoble, France) for providing us with the clinical data and adrenal tissues of some of the GIP-dependent Cushing’s syndrome patients.

	Footnotes

 
This work was supported by Grant MT-13-189 from the Canadian Institute of Health Research.

First Published Online June 13, 2006

Abbreviations: AIMAH, ACTH-independent macronodular adrenal hyperplasia; CS, Cushing’s syndrome; GIP, glucose-dependent insulinotropic polypeptide; GIPR, GIP receptor; GPCR, G protein-coupled receptor; hCG, human chorionic gonadotropin; MCR, melanocortin receptor; SLR, signal log ratio.

Received February 1, 2006.

Accepted June 6, 2006.

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