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Testicular Gene Expression in Cryptorchid Boys at Risk of Azoospermia

Despite timely and successful surgery, 32% of patients with bilateral and 10% with unilateral cryptorchidism will develop azoospermia. Cryptorchid boys at risk of azoospermia display a typical testicular histology of impaired mini-puberty at the time of the orchidopexy. During mini-puberty increased gonadotropin and testosterone secretion stimulate transformation of gonocytes into Ad spermatogonia. In the azoospermia risk group this transformation is to a great extent impaired. This study aimed to analyze data on whole genome expression signatures of undescended testes at risk of developing azoospermia. Twenty-three testicular biopsies from 22 boys were analyzed (19 testes from 18 boys with cryptorchidism and 4 contralateral descended testes from patients with testicular agenesis). Expression profiling identified 483 genes not or under-expressed in the azoospermia risk group compared with the control and low risk for azoospermia (LAZR) groups. Annotated loci were associated with spermatogenesis. Other significant genes were cellular defense response genes and hormone-controlled loci involved in spermatogenesis. Some genes transcribed in normal adult meiotic and post-meiotic germ cells are activated in healthy juvenile Ad spermatogonia. Thus, molecular events initiating the testicular expression program at the onset of puberty and maintaining it during adulthood occur very early in prepubertal testes. This molecular event is to a great extent impaired in the high risk for azoospermia (HAZR) group lacking Ad spermatogonia (stem cells for spermatozoa) indicating impaired mini-puberty.

cytoplasm and a bright spot within the nucleus that distinguishes them from fetal and A pale (Ap) spermatogonia [Seguchi and Hadziselimovic, 1974;Nistal and Paniagua, 1984;Paniagua and Nistal, 1984]. A surge in gonadotropin and testosterone levels during early postnatal development (mini-puberty) is required for the differentiation of gonocytes into Ad spermatogonia, a process that is proposed to be essential for normal adult fertility [Hadziselimovic et al., 1986[Hadziselimovic et al., , 2005Hadziselimovic and Zivkovic, 2007].
Endocrine or primary end organ failure are 2 different etiological factors thought to be responsible for the increased incidence of azoospermia and subfertility in unilateral as well as bilateral cryptorchidism [Hadziselimovic et al., 1979[Hadziselimovic et al., , 2004[Hadziselimovic et al., , 2005Job et al., 1987;Cortes et al., 1996;Gracia et al., 2000;Hamza et al., 2001;Toppari et al., 2007]. In this study, data from whole-genome expression signatures of undescended testes lacking Ad spermatogonia and at risk of developing azoospermia are provided and analyzed in the context of data obtained from descended and cryptorchid testes with Ad spermatogonia.

Testicular Biopsies and Pooling of Patients
At our institution, it is routine practice to perform testicular biopsy during surgery for undescended testis. We find that testicular biopsy provides useful information about future semen quality and helps identify patients with atypical spermatogonia or carcinoma in situ.
Cryptorchid testis is defined as a testis localized outside the scrotum and incapable of being brought into a stable scrotal position. Twenty-three rice-grain-large testicular biopsies from 22 boys were analyzed (19 testes from 18 boys with cryptorchidism and 4 contralateral descended testes from patients with testicular agenesis). Not all contralateral testes in patients with testicular agenesis are expected to have normal histology and may require subsequent hormonal treatment [Huff et al., 1991]. Therefore, we routinely biopsy these testes during the period of testicular fixation performed to prevent testicular torsion. All contralateral testes were selected for normal histology according to age. The mean age of the patients at surgery was 3.4 (95% CI 0.6-6.1) years and 3.9 (95% CI 2.3-5.4) years for the controls. All patients had an extensive clinical examination. We could not find any clinical signs of developmental malformations or syndromes, and none had hypospadias. In particular no clinical sign for Kallmann syndrome was observed. Furthermore, all patients had normal thyroid screening and no features of hypopituitarism were discernible. Biopsies were fixed in 3% glutaraldehyde and embedded in Epon. Semi-thin 1-m-thick sections were examined by Zeiss Axioscope phase-contrast and conventional light microscopy (Plan-Apochromat 63 ! /1.40 oil). An aliquot of each biopsy fraction, flash frozen into liquid nitrogen and stored at -80 ° C, was fixed in PBS containing 1% formaldehyde (Polio, France) and 1% fetal calf serum (Eurabbie, France) and analyzed by DNA flow cytometry to determine its relative DNA content. An aliquot was processed with Affymetrix target synthesis kits currently available for 3 IVT arrays. Amplifications were based upon T7 RNA polymerase using oligo-dT priming and the same arrays were used to minimize variability. Cell pellets and tissues were sheared in RLT buffer (Qiagen) supplemented with 1% ␤ -mercaptoethanol from which aqueous phases were taken out for RNA isolation. Total RNA isolation was performed using RNeasy Mini Kit according to standard protocols. RNA quality was monitored using RNA Nano 6000 Chips and the 2100 BioAnalyzer (Agilent). Targets were synthesized using the Affymetrix One-Cycle cDNA Synthesis Kit or Affymetrix 3 IVT Express Kit. Following quality-check on BioAnalyzer, targets were hybridized onto GeneChip Human Genome U133 Plus 2.0 Arrays at 45 ° C for 17 h. Arrays were washed on a Fluidics Station 450 (Affymetrix) using the Hybridization Wash and Stain Kit (Affymetrix) and the Washing Procedure FS450_0007. Arrays were scanned on a Scanner 3000 7G (Affymetrix) and CEL files generated by AGCC software (Affymetrix). Raw data files are available at the EBI ArrayExpress repository [Parkinson et al., 2007] via the accession numbers E-TABM-130 and E-TABM-174 and GEO (GSE25518).

Statistical Analysis and Interpretation of Microarray Data
The data analysis and gene filtering was performed using R/ Bioconductor [Gentleman et al., 2004]. Signal condensation was performed using only the RNA from the Bioconductor Affy package. Differentially expressed genes were identified using the Benjamin-Hochberg false discovery rate correction implemented in the LIMMA package and adjusted with the False Discovery Rate (FDR) method [Wettenhall and Smyth, 2004]. We selected these probe sets with a log2 average contrast signal of at least 5, an adjusted p value ! 0.05, and an absolute log2-fold change of 1 0.585 (1.5-fold in linear space). Hierarchical clustering and visualization was performed in R. The minimum number of genes in a cluster associated with a given annotation term was set at 6 3. BioGRID, MINT, and IntAct (PSI MI 2.5 format) interactome data sets were uploaded and combined into AMEN. To improve gene annotation and interactome information, mouse, rat, and human protein entries were combined and converted into Ho-moloGene identifiers [Wheeler et al., 2007]. A data set containing gene identifiers and corresponding expression values was uploaded into the application. Gene lists from the resulting contrasts were further classified into regulatory networks and pathways with Ingenuity Pathways Analysis (Ingenuity Systems, www.ingenuity.com). Each gene identifier was mapped to its corresponding gene object in the Ingenuity Pathways Knowledge Base.
These genes, called focus genes, were overlaid into a global molecular network developed from information contained in the Ingenuity Pathways Knowledge Base. Networks of these focus genes were then algorithmically generated based on their connectivity. Functional analyses associated with biological functions and/or diseases in the Ingenuity Pathways Knowledge Base were considered, and Fisher's exact test was used to calculate a p value, determining the probability that each biological function and/or disease assigned to that data set is due to chance and chance alone.
Quantitative Real-Time PCR Quantitative real-time PCR (qRT-PCR) was performed using a Corbett Research RG-6000 instrument. cDNAs were synthesized with the Reverse Transcriptase Core Kit (Eurogentec, cat# RT-RTCK-03) using random primers [Hadziselimovic et al., 2009]. Real-time PCR runs were performed using SYBR Fast Kit (Kapa Biosystems, cat# KK4602) with each gene-specific primer at 200 n M final concentration in a total volume of 17.5 l. Wave lengths for source and detection were set at 470 and 510 nm, respectively. Gain was set at 8.33. The PCR program was set as follows: 95 ° C for 60 s, then 45 cycles at 95 ° C for 3 s, 60 ° C for 10 s, and 72 ° C for 4 s followed by a melting curve analysis (65 ° C to 95 ° C, rising by 0.65 ° C during each step) to attest to amplification specificity. Threshold cycles (crossing point) were determined using Rotor-Gene software version 6.1. Good PCR efficiency was checked by performing a dilution series of the cDNA. Minus RT controls were performed for each sample studied. Threshold cycles (crossing point) were determined using Rotor-Gene software version 6.1. Expression levels were normalized to TFRC and GAPDH using the geometric mean of their level of expression. These genes were selected because they showed the smallest variation between individual samples (both on microarrays and by qPCR). Fold differences were calculated using the ⌬ Ct method (online supplement figure 1; for all online supplement material, see www. karger.com/doi/10.1159/000323955).

Antibody Validation
For immunohistochemical analysis, the Epon was removed from the tissue sections. The sections were treated with 2% bovine serum albumin to reduce non-specific binding and then incubated with the primary antibody overnight at 4 ° C. All samples were washed with PBS between incubations. We validated 8 antibodies: DDX25, EGR1, EGR4, CBL, ALDH1A2, KLF4, MAGEA4, and COL4A3 ( fig. 1 -3 , online suppl. table 1 ). Secondary antibodies, labeled with horseradish peroxidase-polymer (HRP; goat polyclonal anti-rabbit IgG, mouse IgG and IgM, prediluted ab2891, Abcam, Cambridge, UK) were used to detect the binding of the primary antibody. The chromogenic reaction was developed by adding a freshly prepared solution of 3,3-diaminobenzidine solution (DAB + chromogen; DAKO). The DAB reaction was terminated by washing in Tris-buffered saline (0.05 M TBS and 0.85 M NaCl, pH 7.6). To visualize the histology of testicular cells, the samples were counterstained with toluidine blue. Antibody binding was indicated by a brown precipitate. Different cell types were identified based on their nuclear morphology and position within the developing gonad. Immunohistochemistry experiments were performed at least twice on at least 4 patients from each group, and only those with identical results between experiments for each sample were considered acceptable. Controls for non-specific binding of the secondary antibody were performed in all experiments by omitting the primary antibody; these consistently yielded no signal within the seminiferous epithelium or the interstitial space. The interstitial staining observed in the presence of the primary antibody was considered to be nonspecific because it was not associated with, or localized within, a particular cell type. However, staining of interstitial cells was recorded.
Experimental design, biomaterials and treatments, reporters, staining, imaging data, and image characterization were performed in compliance with the minimum information specification for immunohistochemistry experiments [Deutsch et al., 2008].

Ethical Considerations and Approval
In accordance with the Declaration of Helsinki, the Institutional Review Board and the Independent Ethics Committee of the Children's Clinic Liestal approved all aspects of this study. Approval was provided for research involving the use of material (data records or biopsy specimens) that had been collected for non-research purposes. Immunohistochemical staining for MAGEA4 in the LAZR group. In all cases antibody binding was visualized using peroxidase as a substrate to generate brown color. Sections were counterstained with toluidine blue. sp: Immunopositive spermatogonia. Horizontal bar = 0.1 mm.

An Expression Signature Distinguishes High Azoospermia Risk from Control Patients
Total RNA and cRNA samples were of high quality and the signal intensity distributions were similar and within the normal range. Our statistical filtration strat-egy identified 483 transcripts differentially expressed between the azoospermia risk group and control patients, and 370 transcripts differentially expressed between the high risk for azoospermia (HAZR) and low risk for azoospermia (LAZR) groups ( fig. 4 ). Notably, 62 genes involved in germ cell development were equally expressed in the LAZR and control groups, whereas 46/62 genes  were not and 16/62 genes were expressed at lower levels in the HAZR group ( table 1 ). Furthermore, 18/27 genes proposed as being involved in A spermatogonia self-renewal [Wu et al., 2009] were not expressed in the HAZR group, but were expressed in the LAZR and control groups (online suppl. table 2). Nei-ther GDNF (glial cell-derived neurotrophic factor) nor its regulatory genes, BHLHB2 (basic helix-loop-helix domain containing, class B, 2), LHX1 (LIM homeobox 1), GFRA1 (GDNF family receptor alpha 1), and TEC (Tec protein tyrosine kinase), were found to be expressed in all groups studied. Compared with controls, we found that  Gene s interacting with hypothalamus-pituitary-testicular axis are indicated in bold. The limit of the essay detection is 5.

HIR-Signature Genes Encode Factors That Directly Interact with Each Other
To further explore and extend the RNA profiling data, we next investigated if genes differentially expressed in the azoospermia risk group and in control patients encode proteins that are physically associated with other factors. Information on direct protein-protein interactions was retrieved from the BioGRID, MINT, and IntAct databases and processed using AMEN [Stark et al., 2006;Chatraryamontri et al., 2007;Kerrien et al., 2007]. We found 2 interaction networks comprising 9 genes (AMPH, CACNA2D2, CSRP2, DPYSL4, KIF21B, LIN7B, RGS7, SH3GL2 , and SNAP91) and 4 genes (TLE1, DTL, FOXG1B and SIX1) , respectively. The proteins in this group were associated with diverse biological processes including microtubule-based movement and mitosis (KIF2C, KIF21B) and signal transduction (LIN7B, RGS7, SH3GL2). Proteins in the smaller complexes were annotated as DNA-dependent regulators of transcription (TLE1, SIX1, FOXG1B, SSX2) or proteins involved in DNA replication (DTL). We also identified a cancer/testis gene (MAGEC1) whose hallmark is to be actively transcribed in the germ line, repressed in normal somatic tissues, and de-repressed in various cancers [Simpson et al., 2005]. Finally, we found the BRAF gene which encodes a protein belonging to the raf/mil family of serine/threonine protein kinases to be under-expressed in the HAZR group. This protein plays a role in regulating the MAP kinase/ERKs signaling pathway, which affects cell division, differentiation, and has a key role in transcriptional activation of GnRH-responsive genes. The third interaction network includes the DAZ (deleted in azoospermia) gene family ( table 1 ). Proteins in this group are associated with spermatogenesis development and function. Furthermore, no testicular expression of CDC20, ESX1, RBMY1A1 and SYCP3 genes involved in azoospermia development were observed in the HAZR group ( table 1 ).

Immunohistochemical and qRT-PCR Validation
We wanted to determine whether greater transcript expression corresponded with greater protein expression. Immunoperoxidase histochemistry, although not a quantitative method, is currently the only practical way to detect proteins in small fixed tissue samples. Identical cytoplasmic localization was found for all proteins analyzed ( fig. 1-3 ). In addition to their expression in germ and Leydig cells, we found that the CBL gene was also expressed in Sertoli cells. Finally, we validated our microarray data by qRT-PCR for 4 genes that showed significant expression changes; all of these showed a high correlation with the obtained transcriptional profiles (online suppl. fig. 1 ).

Discussion
The estimated frequency of azoospermia in the normal population is 0.4% (3/711) [Itoh et al., 2001]. Despite successful surgery, azoospermia was found 25 times more often in unilateral and 80 times more often in bilateral cryptorchidism ( table 2 ). Thus cryptorchidism represents one of the most frequent causes of azoospermia in man. Furthermore, according to the testicular histology, 50% of cryptorchid patients in our cohort belonged to the high azoospermia risk group . Absence of Ad spermatogonia was a typical pathological finding for this group of patients. During testicular maturation, gonocytes from cryptorchid boys undergoing abnormal mini-puberty fail to differentiate into Ad spermatogonia [Hadziselimovic and Herzog, 2001;Hadziselimovic and Hoecht, 2008]. This developmental process requires increased gonadotropin and testosterone secretion [Hadziselimovic et al., 1986[Hadziselimovic et al., , 2005. Several different physiological functions have been attributed to mini-puberty [Hutanhemi, 2003]. Our findings, however, suggest that the male fertility potential is established during this period [Hadziselimovic et al., 2005]. Furthermore, analyzing the whole genome expression profiling of testicular tissue, we found that cryptorchid boys lacking Ad spermatogonia had decreased expression of most of the genes essential for hypothalamo-pituitary-testicular axis function ( table 1 ). In particular, EGR4 , which is involved in regulating the secretion of luteinizing hormone, was virtually silent in the HAZR group [Hadziselimovic et al., 2009].
In the present study, the whole genome expression profiling analysis of prepubertal Ad-positive spermatogonia (Ad+) and Ad-negative spermatogonia (Ad-) testes yielded the unexpected result that several genes important for the meiotic and post-meiotic stages of spermatogenesis can be detected in Ad+ prepubertal testes but not in Ad-samples. A critical question arises as to which cell types express the mRNAs identified as being present in Ad+ but not in Ad-testes.
We observed that many of the genes for which transcriptional activity was detected in Ad+ but not in Ad-testes are implicated in spermatogenesis and fertility. This group includes MORC1 , encoding an ATPase-like protein required for the transition through meiosis [Watson et al., 1998;Inoue et al., 1999], CLGN , a factor required for sperm function [Ikawa et al., 2001], and the transcriptional inhibitor ID4 , which was shown to be FSH-or cAMP-inducible in Sertoli cells [Norton et al., 1998;Chaudhary et al., 2001] as well as the tudor (TDRD) genes, which are also necessary for gametogenesis and rule the PIWI-interacting RNA pathway, helping to maintain the integrity of the genome and the development of the germ cells [Siomi et al., 2010] ( table 1 ). Noticeably, expression of Tdrd5 was absent in testes isolated from We/We mouse embryos, which completely lack germ cells [Smith et al., 2004]. Furthermore, a group of genes was identified that appear not to be expressed in juvenile Ad-gonads, although they display peak transcription in adult Sertoli cells. Since both Ad+ and Ad-gonads contain juvenile Sertoli cells, the differences might be caused by an absence of spermatogonia in SCO-type gonads or, more likely, impaired maturation of Sa-type Sertoli cells. It is noteworthy that this group includes DUSP5 , a member of the dual-specificity protein phosphatase subfamily involved in MAP kinase and IL-2 signaling, the cell cycle and cell adhesion as well as influencing GnRH effect [Kovanen et al., 2003;Jeong et al., 2007;Armstrong et al., 2009], and DMRTB1 from the DMRT family (doublesex and mab-3 related transcription factor) involved in the regulation of postnatal testis differentiation [Raymond et al., 2000]. The important testis developmental gene SRY (sex-determining region of Y chromosome), implicated in sexual development of the reproductive system and specification of Sertoli and Leydig cell lineages [Barsoum and Yao, 2006], was not expressed in the HAZR group ( table 1 ). Furthermore, genes known to be essential for mouse stem cell self-renewal such as Ret, Gfra1 and Bcl6b were more highly expressed in human prepubertal spermatogonia than in somatic cells [Wu et al., 2009]. A hypothesis was proposed that glial cell linederived neurotrophic factor (GDNF) is essential for human stem cell (A spermatogonia) renewal [Wu et al., 2009].
Neither GDNF nor its regulatory genes BHLHB2, LHX1, GFRA1 , and TEC were expressed in all groups studied. Additionally, 2 regulatory genes, BCL6B and RET , were equally expressed in all 3 groups. This contradictory observation may result from the different methods utilized: analysis of isolated germ cells versus in situ analysis. The strength of the current study is that spermatogonia were analyzed directly in their cognate microenvironment. Thus, our result seriously questions the hypothesis of GDNF-driven regulation of human Ad spermatogonia self-renewal.
Microdeletions of the long arm of the Y chromosome (Yq) involving 3 azoospermia factor (AZF) loci, AZFa, AZFb, and AZFc, represent one of the main molecular determinants of male infertility, and account for about 10% of cases of non-obstructive azoospermia or severe oligozoospermia [Stuppia et al., 1998]. The most frequent deletion of the Y chromosome is AZFc, b2/b4 [Kuroda-Kawaguchi et al., 2001]. However, among the 32 men with a history of cryptorchidism, only 1 had Y microdeletions [Fedder et al., 2004]. This result is consistent with additional studies in which it was not possible to detect Y microdeletions in any of 66 men treated for cryptorchidism in childhood [Fagerli et al., 1999;Vutyavanich et al., 2007]. Therefore, Y microdeletions as a cause of azoospermia in cryptorchidism are rather unlikely.
Among the deleted genes involved in azoospermia development, the main candidates for spermatogenesis failure are the DAZ gene, a testis-specific gene present in 4 copies within AZFc, encoding an RNA-binding protein, and the RBMY gene, which is declared to be the major AZFb gene [Yen, 2004;Vogt et al., 2005]. Furthermore, the cell division cycle molecule CDC20 was found to be down-regulated in azoospermic testes [Yang et al., 2009]. Azoospermia associated with a decrease in DAZ gene function in humans may, in part, be a consequence of failure at synapses caused by reduced levels of SYCP3 protein [Reynolds et al., 2007]. We found that specimens from the azoospermia risk group did not exhibit CDC20, DAZ1,2,3,4/DAZL , RBMY1A1 , and SYCP3 gene expression ( table 1 ). Recently, up-regulated expression of the EGR4 gene was described in azoospermic men with AZFc deletion and lack of DAZ gene expression [Gatta et al., 2010]. The observed lack of DAZ1 and EGR4 gene expression in the HAZR group implies that the EGR4 gene functions as an upstream regulator of the DAZ/DAZL gene pathway. It should be emphasized that prepubertal treatment of boys at risk for azoospermia and infertility (aged 6-36 months) with buserelin (luteinizing hormone releasing hormone analogue) restored full fertility in 86% of the cases (none had azoospermia), whereas all boys re-ceiving surgery who were not treated became oligospermic, and 20% developed azoospermia [Hadziselimovic, 2006]. These data are in keeping with hypogonadotropic hypogonadism being critically involved in cryptorchidism [Hadziselimovic et al., 1986[Hadziselimovic et al., , 2004[Hadziselimovic et al., , 2009Job et al., 1987;Hamza et al., 2001] and argue against primary testicular failure (testicular dysgenesis) [Cortes et al., 1996;Gracia et al., 2000;Toppari et al., 2007;Virtanen et al., 2007] as the major cause of azoospermia and infertility.
Taken together, our results support the notion that azoospermia and infertility induced by cryptorchidism are predominantly an endocrine disease of impaired mini-puberty rather than the mutation of the CDC20, DAZ / DAZL / SYCP3 or RBMY / RBMY1A1 genes. Finally, we present additional evidence that molecular events initiating the adult testicular expression program, occurring very early in prepubertal testes, were abnormal in cryptorchid boys at risk for azoospermia development. Thus, we found a transcript expression signature that distinguishes the high azoospermia and the low azoospermia risk groups.