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NDT Advance Access originally published online on March 6, 2006
Nephrology Dialysis Transplantation 2006 21(7):1816-1824; doi:10.1093/ndt/gfl071
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© The Author [2006]. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Original Articles: Clinical Nephrology

Gene profiling of polycystic kidneys

Gisela Schieren2, Brigitta Rumberger1, Marinella Klein1, Clemens Kreutz3, Jochen Wilpert1, Marcel Geyer1, Daniel Faller3, Jens Timmer3, Ivo Quack2, Lars Christian Rump2, Gerd Walz1 and Johannes Donauer1

1 Renal Division, Department of Internal Medicine, University Hospital, Freiburg, 2 Renal Division, Department of Internal Medicine, Ruhr-University Hospital Bochum at Marienhospital Herne and 3 Freiburg Center for Data Analysis and Modeling, Department of Physics, University of Freiburg, Freiburg, Germany

Correspondence and offprint requests to: Johannes Donauer, Medizinische Klinik IV, Hugstetter Strasse 55, 79106 Freiburg, Germany. Email: donauer{at}med1.ukl.uni-freiburg.de



   Abstract
Top
 Abstract
Introduction
 Subjects and methods
 Results
 Discussion
 References
 
Background. While the genetic basis of autosomal dominant polycystic kidney disease (ADPKD) has been clearly established, the pathogenesis of renal failure in ADPKD remains elusive. Cyst formation originates from proliferating renal tubular epithelial cells that de-differentiate. Fluid secretion with cyst expansion and reactive changes in the extracellular matrix composition combined with increased apoptosis and proliferation rates have been implicated in cystogenesis.

Methods. To identify genes that characterize pathogenical changes in ADPKD, we compared the expression profiles of 12 ADPKD kidneys, 13 kidneys with chronic transplant nephropathy and 16 normal kidneys using a 7 k cDNA microarray. RT–PCR and immunohistochemical techniques were used to confirm the microarray data.

Results. Hierarchical clustering revealed that the gene expression profiles of normal, ADPKD and rejected kidneys were clearly distinct. A total of 87 genes were specifically regulated in ADPKD; 26 of these 87 genes were typical for smooth muscle, suggesting epithelial-to-myofibroblast transition (EMT) as a pathogenetic factor in ADPKD. Immunohistology revealed that smooth muscle actin, a typical marker for myofibroblast transition, and caldesmon were mainly expressed in the interstitium of ADPKD kidneys. In contrast, up-regulated keratin 19 and fibulin-1 were confined to cystic epithelia.

Conclusion. Our results show that the end stage of ADPKD is associated with increased markers of EMT, suggesting that EMT contributes to the progressive loss of renal function in ADPKD.

Keywords: ADPKD; end-stage renal disease; epithelial-to-myofibroblast transition; gene expression; microarray



   Introduction
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 Abstract
 Introduction
Subjects and methods
 Results
 Discussion
 References
 
Autosomal dominant polycystic kidney disease (ADPKD) is a common hereditary disease, caused by mutations of either PKD1 or PKD2. The onset of the disease is poorly defined, but the findings of microcysts in embryonal kidneys suggest that cyst formation starts during renal development (see [1] for a recent review) and progresses continuously in adulthood. Most individuals with PKD1 mutations experience renal failure in their fifth decade of life, while the onset of end-stage renal disease (ESRD) is delayed by about two decades in patients with PKD2 mutations.

Polycystin-1, the protein encoded by PKD1, is a large integral membrane protein with a domain architecture suggesting a function in cell–cell or cell–matrix interaction [2].

Polycystin-2 is a member of the calcium-permeable subfamily of transient receptor potential channels, and forms a complex with polycystin-1 [3,4]. Both polycystin-1 and polycystin-2 are present in the primary cilium of tubular epithelial cells, and the rise in intracellular calcium mediated by cilial bending requires the presence of both proteins [5].

Despite these recent advances in understanding the function of polycystin-1 and polycystin-2, the pathogenesis of cyst formation and particularly, the development of ESRD in ADPKD have remained elusive. Less-than-terminal differentiation of epithelial cells that line the cysts, persistent proliferation due to mislocalization of epidermal growth factor receptors, stimulation of proto-oncogenes, and cyst expansion as a result of inappropriate fluid secretion, have been implicated to explain, why a few hundred cysts cause complete destruction of the renal parenchyma [6]. However, increased apoptosis rates detected in the normal tissue surrounding renal cysts suggest that additional factors account for the progressive loss of renal function [7].

We chose cDNA microarrays to screen for mechanisms possibly involved in cyst formation and/or progression of the disease. Expression profiling revealed smooth muscle actin (SMA), caldesmon, sarcospan-2, fibulin-1, 22 kDa smooth muscle protein and other genes involved in epithelial-to-myofibroblast transition (EMT) to be specifically up-regulated in ADPKD. RT–PCR and immunohistochemistry confirmed our results on RNA and protein level and suggest that the absence of functional polycystins results in increased expression of EMT genes.



   Subjects and methods
Top
 Abstract
 Introduction
 Subjects and methods
Results
 Discussion
 References
 
Microarrays
cDNA microarrays were produced and processed essentially according to the Stanford protocol described by Eisen and Brown [8]. Approximately 7000 annotated genes from the RZPD (Resource Center and Primary Database, Berlin, Germany) were obtained as bacterial stocks. Plasmids were purified using the Qiagen 96-well Turbo Kit (Qiagen, Hilden, Germany), and inserts were purified by PCR using vector primers flanking the individual inserts (5'-CTG CAA GGC GAT TAA GTT GGG TAA C -3' and 5'-GTG AGC GGA TAA CAA TTT CAC ACA GGA AAC AGC-3'). PCR products were purified by ethanol precipitation and resuspended in H2O. Aliquots were transferred into 384-well plates, dried and resuspended in 3 x SSC or DMSO 10% to a final concentration of ~40 ng/µl. Printing was performed on aminosilane-coated slides (CMT-GAP II Slides, Corning, NY, USA), using an arrayer that was assembled according to specifications by the Stanford group using software kindly provided by J. de Risi (http://cmgm.stanford.edu/pbrown).

Tissue samples
Informed consent was obtained from all patients, according to the study protocol approved by the ethics committee of Freiburg University. Elective transplant removal was performed on all renal graft recipients at the Freiburg transplant centre after transplant failure and reinitiation of renal replacement therapy. Normal renal tissue was obtained from tumour nephrectomies; tumour infiltration was excluded by histology. Nephrectomies of cystic kidneys were done in most cases pre-transplant or in context with complications caused by the organ such as bleeding or pain. Tissue samples (approximately 1 x 1 x 2 cm in size or 3 x 3 cm in cystic kidneys) were removed and either snap-frozen in liquid nitrogen for RNA isolation or fixed in 4% paraformaldehyde for immunohistochemistry immediately after organ removal. After the exclusion of insufficient or tumour-contaminated samples, 12 kidneys with end-stage PKD, 13 chronically rejected renal allografts, and 16 normal renal tissues were analysed by microarrays.

RNA preparation
Frozen tissue was homogenized in 4 M guanidinium isothiocyanate with 0.72% ß-mercaptoethanol using a polytron (PT-MR2100, Kinematica AG, Lucerne, Switzerland). Total RNA was subsequently purified on a cesium chloride gradient. After ethanol precipitation, RNA was resuspended at a concentration of 0.4–4 µg/µl and stored at –80°C.

Hybridization
All hybridizations were performed in the presence of an equal amount of reference RNA (Stratagene, La Jolla, CA, USA) as published by Boldrick et al. [9]. Two micrograms of either tissue or reference-RNA were transcribed into cDNA in the presence of Cy3- and Cy5-labelled dUTP, using Superscript II reverse transcriptase (Invitrogen, Carlsbad, CA, USA). All other steps, including hybridization, were performed following the protocol published by Brown et al. (see http://cmgm.stanford.edu/pbrown for details); a PCR-purification kit (Qiagen, Hilden, Germany) was used for cDNA purification after dye-labelling.

Data analysis
Signal intensities were measured by an Axon 4000A scanner using GenePix 3.0 software (Axon Instruments Inc., Union City, CA, USA). The experimental design included a colour-reversal experiment for every tissue sample to correct for dye-specific effects. Initially, the log-ratio of measured Cy3/Cy5 values obtained from the image analysis software was computed. Global normalization of expression values was performed by adjusting the data to zero median and unit variance in order to obtain an identical distribution of the overall gene expression. Taking the mean of the expression values of the dye-swap experiments allows correction for dye-specific effects. Following an approach proposed by Dudoit et al. [10], the computed expression ratios should not depend on the intensity of the spots. Hence, a smooth non-linear least-squares fit was computed to correct for an intensity-dependent bias. A two sample t-test was used for a statistical analysis of differentially expressed genes. In order to adjust the obtained P-values, the method by Benjamini and Hochberg [11] was applied to control for multiple testing. Hierarchical clustering was performed using the R-statistical software package (www.r-project.org).

Semiquantitative RT–PCR
Total RNA (1 µg) from all normal and polycystic kidneys was purified with the RNase free DNase set (Qiagen, Hilden, Germany), and reversely transcribed into cDNAs using oligo (dT) 12–18 primer and Superscript II reverse transcriptase (Invitrogen, Carlsbad, CA, USA). Each PCR was carried out with GAPDH as an internal control in each reaction vial. The following primers were used (5–3'): glyceraldehyde-phosphate dehydrogenase—GTCTTCTGGGTGGCAGTTAG and TGGAAATCCCATCACCATCT; Keratin 19—GTGCCACCATTGAGAACTCC and AGCTCTTCCTTCAGGCCTTC; Fibulin-1—AGTAACCCGTCTTGCATTCG and GGGCATACATGCATCAACAC; Calponin—TCACCCCATACTTGGTGATG and GGAGCTGAGAGAGTGGATCG; Caldesmon—TTGTTGGGTCGAACTCCTTC and GAATCCTTGGGACAGGTGAC. The amplification cycle consisted of a hot start at 94°C for 5 min, followed by multiple cycles of denaturation at 94°C at 1 min, annealing at 58°C for 1 min and elongation at 72°C for 2 min. Cycle number was adjusted to mRNA expression level of the different genes. The PCR products were run on a 3% agarose gel and evaluated in relation to the corresponding GAPDH band using Scion Image Software (Scion, Frederick, ML, USA).

Immunochemistry
Genes of different fold expression changes were randomly selected for validation by immunochemistry. Tissue samples were fixed in 4% paraformaldehyde, dehydrated and paraffin-embedded. After rehydration procedure 10 µm tissue sections were incubated with 5% horse serum in phosphate-buffered saline (PBS), pH 7.4, for 1 h at room temperature and then incubated with the respective primary antibody, diluted in PBS–BSA 1%, for 16 h at 4°C. Sections were rinsed three times with PBS–BSA 1%, followed by incubation with the respective rhodamine-red conjugated secondary antibody for 30 min at room temperature. After extensive washing with PBS–BSA 1% stained sections were examined with a Zeiss microscope.

The following antibodies were used: affinity-purified murine monoclonal antibody against pancytokeratin, affinity-purified murine monoclonal antibody against CD3 (used as negative control for murine monoclonal antibodies) (Sigma-Aldrich, Taufkirchen, Germany); horse serum and affinity-purified murine monoclonal antibodies against SMA, affinity-purified murine monoclonal antibody against keratin 19 (DakoCytomation, Hamburg, Germany); affinity-purified polyclonal antibody from goat against fibulin-1 (Santa Cruz, Heidelberg, Germany) and affinity-purified murine monoclonal antibody against caldesmon (Biomol, Hamburg, Germany), Rhodamine Red-X AP-conjugated donkey anti-goat IgG, Rhodamine Red-X AP-conjugated goat anti-mouse (Dianova, Hamburg, Germany).



   Results
Top
 Abstract
 Introduction
 Subjects and methods
 Results
Discussion
 References
 
Hierarchical clustering differentiates polycystic kidneys, normal kidney and chronically rejected transplant kidneys
To characterize end-stage ADPKD, we used samples of PKD kidneys that were removed during organ transplantation, and yielded a minimal amount of 50 µg of total RNA. Twelve samples fulfilled this criterion, and were included in our analysis. To identify genes that are specifically regulated in ADPKD, we used non-affected renal tissue removed during 16 tumour nephrectomies, and 13 samples from patients with end-stage renal allograft failure. To compare individual kidneys, each microarray analysis was performed against a standard reference RNA. In addition, each hybridization was repeated with inversed dyes to correct for the effects of different dye-incorporation, and to reduce the statistical error. Stringent data analysis of 16 control kidneys, 12 polycystic kidneys and 13 renal transplants with chronic transplant failure, entailing more than 550 000 single measurements, permitted the identification of a distinct gene expression pattern for polycystic kidneys in comparison with normal kidneys and end-stage renal transplants. Approximately 16% of the genes were differentially regulated in ADPKD compared with normal kidney tissue (P<0.0005), and approximately 14.5% of those were altered more than 3-fold. To select genes specifically regulated in ADPKD, we limited our analysis to genes that were at least 1.5-fold up- or down-regulated compared with normal kidney tissue (P<0.05). Furthermore, we eliminated genes generally altered in ESRD by applying the same criteria (P<0.05 and minimal 1.5-fold regulation) between ADPKD and chronically rejected kidneys. A total of 87 genes met these criteria (Table 1). Two-dimensional cluster analysis of these 87 genes separated ADPKD kidneys from normal and transplanted kidneys (Figure 1). One branch of the dendrogram contained all ADPKD kidneys, while the other branch contained three subgroups: 12 of 14 normal kidneys, seven transplants (Tx1, Tx5, Tx7, Tx10, Tx11, Tx13, Tx14), and two normal kidneys clustered with the remaining five transplant kidneys (Tx2, Tx3, Tx4, Tx6, Tx8, Tx9). Thus, the dendrogram confirmed that the expression profile in end-stage ADPKD differs from normal kidneys, and is more closely related to other kidneys with ESRD.


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  		Table 1. Eighty-seven regulated genes differentiate polycystic kidneys in renal failure from normal kidneys and chronically rejected transplants (P<0.05). Only genes that are at least 1.5-fold up- or down-regulated are shown

 

Figure 1
Figure 1
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  		Fig. 1. Hierarchical cluster analysis of 16 normal kidneys, 13 transplant kidneys and 12 kidneys with polycystic kidney disease. Hierarchical clustering was based on genes differentiating the three tissues at a significance level of P<0.05, and a more than 1.5-fold up- or down-regulation (ADPKD vs normal kidneys, and ADPKD vs chronically rejected transplant kidneys). The cluster dendrogram [Figure 1A, normal kidneys (closed square)/ADPKD (closed triangle)/chronic allograft rejection (closed circle)] and the heat map (Figure 1B, red = up-regulation/green = down-regulation) reveal that the gene expression profiles of normal, ADPKD and rejected transplant kidneys are clearly distinct.

 
Genes specific for polycystic kidney disease
Examining the functional categories of genes which distinguish ADPKD, we found a number of regulated genes coding for proteins involved in metabolism and homeostasis (n = 24), signalling (n = 18), adhesion/extracellular matrix (n = 12), cytoskeletal proteins (n=14), immune response (n = 8), transcription (n = 6), differentiation (n = 1) and ion transport (n = 1). The function of three genes is currently unknown (Table 1).

Verification of differentially expressed candidate genes by RT–PCR
To confirm the differential regulation of genes found in the microarrays with a different technique, we performed semiquantitative RT–PCR on all RNA-samples of the normal and the ADPKD tissue for calponin, caldesmon, fibulin-1 and keratin 19. Although this method might underestimate the difference in gene expression, mRNA expression in cystic kidneys was clearly up- or down-regulated in ADPKD compared with normal kidneys, thus mirroring very closely the microarray data (Figures 2 and 3). GAPDH mRNA expression was used as internal control.


Figure 2
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  		Fig. 2. Confirmation of gene expression data obtained by microarray analysis using RT–PCR. Semiquantitative RT–PCR was performed for four candidate genes. The mean of the ratios of gene expression was calculated with the Scion Image Software (Scion, Frederick, MD).

 

Figure 3
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  		Fig. 3. According to the depiction of Figure 2, the four diagrams show the results of the microarray experiments for each of the ADPKD and normal kidney samples. Gene expression in comparison with GAPDH is given on a logarithmic scale. Microarrays and RT–PCR show comparable levels of gene regulation.

 
Verification of differentially expressed candidate genes by immunochemistry
To further validate the expression profiles, we performed immunohistochemistry of selected gene products. Paraformaldehyde-fixed sections of paraffin-embedded tissue of four normal kidneys and four cystic kidneys were stained for SMA, caldesmon, fibulin-1 and keratin 19. Representative results for one patient are shown in Figure 4. All four proteins were present in both cystic kidneys as well as in normal renal tissues. Keratin 19 and fibulin-1 were confined to the epithelial cells lining the cysts. In the normal kidney, both proteins were observed only in a few tubules. Consistent with its strong up-regulation on microarrays, elevated SMA and caldesmon mRNA expression was accompanied by a dramatic increase in the protein level, mainly located in the enlarged interstitium of cystic kidneys, while SMA was restricted to vascular epithelium in the normal kidney. In addition to the interstitial localization, caldesmon protein was also observed in cyst-lining epithelia in ADPKD kidneys as well as in a few discrete tubules in the normal kidney specimen.


Figure 4
Figure 4
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  		Fig. 4. Immunofluorescence of selected genes in normal and ADPKD kidneys. The staining pattern (Rhodamine Red) of representative areas in normal (A) and polycystic (B) kidneys are shown. In normal kidney tissue, fibulin-1, keratin 19 and pancytokeratin were detected only in some tubular epithelia, while these proteins were preferentially expressed in cystic epithelia of ADPKD kidneys. SMA and caldesmon were preferentially detected in the interstitium of ADPKD kidneys.

 


   Discussion
Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
References
 
Although the genetic defects leading to ADPKD have been elucidated, the process that underlies progressive cyst formation and renal failure are poorly understood (see [12] for recent review). To elucidate mechanisms associated with ESRD in ADPKD, we analysed ADPKD kidneys that were removed during renal transplantation. To eliminate differential gene expression triggered by uraemia, we compared ADPKD kidneys with non-functional renal transplants. This approach eliminated genes with identical regulation in ADPKD and chronic transplant failure. Using a threshold of >1.5-fold change in gene expression at a level of P<0.05, cDNA-microarray analysis revealed significant changes for 87 ADPKD-specific genes. Although the absolute changes in expression level may not reflect their biological significance, we focused on a subset of genes with either dramatic up- or down-regulation. Cluster analysis confirmed that these genes depict a disease-specific gene expression pattern.

A recent study by Husson et al. [13] compared the gene expression profiles of immortalized cell lines derived from either normal or cystic kidney epithelial cells using serial analysis of gene expression (SAGE). The 205 candidate genes identified with SAGE were subsequently used for a cDNA-microarray analysis comparing ADPKD and normal kidney tissue. The results show no overlap to our data. This is not surprising, since Husson et al. [13] used cultured cell lines while we used tissue samples. In addition, the differences of the techniques used and the limited number of genes assessed by both methods may contribute to this discrepancy.

About 25% of the differentially regulated genes are encoded by cytoskeletal or matrix proteins as well as proteins involved in differentiation. Interestingly, a subset of genes belonged to smooth muscle-related genes suggesting that EMT contributes to the progression of renal failure in ADPKD. One EMT marker, SM22, a protein expressed at early stages of EMT, revealed a 4.33-fold increase. Using immunohistochemistry, we confirmed the RNA-based expression data at the protein level.

EMT transdifferentiation has been implicated in the process of tubulointerstitial fibrosis, and appears to represent a final common pathway of progressive kidney failure. While myofibroblasts, typically expressing SMA, are rarely found in the interstitium of normal kidneys, their number increases with disease progression, and correlates with the deterioration of renal function [14]. Growing evidence now suggests that interstitial myofibroblasts originate from tubular epithelial cells by EMT. EMT of human tubular epithelial cells can be induced by transforming growth factor-ß [15], and co-stimulation with EGF and TGF-ß induces expression of the myofibroblast-specific marker proteins, such as vimentin and FSP-1 [16]. Since cyst fluid of human ADPKD kidneys contains several growth factors, including EGF, HGF, FGF-2 and TGF-ß [17], the growth factor activities contained in cyst fluid could therefore directly trigger the EMT and the changes in gene expression reported in this study.

Caldesmon, a cytoskeleton-associated protein typically present in smooth muscle thin filaments of differentiating smooth muscle cells, was up-regulated in the interstitium and the cyst-lining epithelia of ADPKD kidneys. In IgA nephropathy, caldesmon expression correlates with advanced fibrosis [18], suggesting that up-regulation of caldesmon in ADPKD coincides with the loss of normal renal tissue.

Fibulin-1 is a calcium-binding glycoprotein, produced by mesenchymal and endothelial cells. Fibulin-1 deficiency in knock-out mice is lethal, and homozygote animals die within 24–48 h after birth, due to massive haemorrhage and endothelial dysfunction. During organogenesis, fibulin-1 is detected in mesenchymal cells involved in mesenchymal-to-epithelial transition [19]. In ADPKD kidneys, fibulin-1 was localized to cyst-lining epithelia. Since fibulin-1 interacts with the C-type lectin domains of versican and aggrican [20], fibulin-1 could directly interact with the C-type lectin present in the amino-terminal domain of polycystin-1. Thus, up-regulation of fibulin-1 could be explained by either induction of EMT, or by a missing negative regulatory feedback signal, normally triggered by an interaction between fibulin-1 and polycystin-1. A second member of the fibulin family, fibulin 4 was up-regulated in ADPKD. Fibulin-4 is found in the medial layers of large veins and arteries and in some small capillaries. Although the up-regulation of smooth muscle and cytoskeletal proteins in ADPKD kidneys likely play no role in cyst development, the accelerated EMT in ADPKD appears to contribute to the progression of renal failure and development of ESRD in ADPKD. Growth activities contained in cyst fluid may directly contribute to EMT and the progressive renal failure of ADPKD. Thus, therapeutic strategies directed to suppress EMT may ameliorate the clinical course of polycystic kidney disease. In addition, up-regulation of other hormone and growth factor receptors such as prostaglandin E, endothelin and serotonin receptor may point to additional therapeutic targets to prevent cyst progression.

The authors wish it to be known that, in their opinion, the first two authors contributed equally to this work.

Conflict of interest statement. None declared.



   References
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 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 

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Received for publication: 24.10.05
Accepted in revised form: 7. 2.06


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