Genomic expression and single-nucleotide polymorphism profiling discriminates chromophobe renal cell carcinoma and oncocytoma
- Min-Han Tan1, 2, 3, 4Email author,
- Chin Fong Wong5,
- Hwei Ling Tan2,
- Ximing J Yang6,
- Jonathon Ditlev1,
- Daisuke Matsuda1,
- Sok Kean Khoo1,
- Jun Sugimura1,
- Tomoaki Fujioka7,
- Kyle A Furge8,
- Eric Kort1, 9,
- Sophie Giraud10,
- Sophie Ferlicot11,
- Philippe Vielh12,
- Delphine Amsellem-Ouazana13,
- Bernard Debré19,
- Thierry Flam13,
- Nicolas Thiounn14,
- Marc Zerbib13,
- Gérard Benoît15,
- Stéphane Droupy15,
- Vincent Molinié16,
- Annick Vieillefond17,
- Puay Hoon Tan5,
- Stéphane Richard18, 19 and
- Bin Tean Teh1, 2Email author
© Tan et al; licensee BioMed Central Ltd. 2010
Received: 18 August 2009
Accepted: 12 May 2010
Published: 12 May 2010
Chromophobe renal cell carcinoma (chRCC) and renal oncocytoma are two distinct but closely related entities with strong morphologic and genetic similarities. While chRCC is a malignant tumor, oncocytoma is usually regarded as a benign entity. The overlapping characteristics are best explained by a common cellular origin, and the biologic differences between chRCC and oncocytoma are therefore of considerable interest in terms of carcinogenesis, diagnosis and clinical management. Previous studies have been relatively limited in terms of examining the differences between oncocytoma and chromophobe RCC.
Gene expression profiling using the Affymetrix HGU133Plus2 platform was applied on chRCC (n = 15) and oncocytoma specimens (n = 15). Supervised analysis was applied to identify a discriminatory gene signature, as well as differentially expressed genes. High throughput single-nucleotide polymorphism (SNP) genotyping was performed on independent samples (n = 14) using Affymetrix GeneChip Mapping 100 K arrays to assess correlation between expression and gene copy number. Immunohistochemical validation was performed in an independent set of tumors.
A novel 14 probe-set signature was developed to classify the tumors internally with 93% accuracy, and this was successfully validated on an external data-set with 94% accuracy. Pathway analysis highlighted clinically relevant dysregulated pathways of c-erbB2 and mammalian target of rapamycin (mTOR) signaling in chRCC, but no significant differences in p-AKT or extracellular HER2 expression was identified on immunohistochemistry. Loss of chromosome 1p, reflected in both cytogenetic and expression analysis, is common to both entities, implying this may be an early event in histogenesis. Multiple regional areas of cytogenetic alterations and corresponding expression biases differentiating the two entities were identified. Parafibromin, aquaporin 6, and synaptogyrin 3 were novel immunohistochemical markers effectively discriminating the two pathologic entities.
Gene expression profiles, high-throughput SNP genotyping, and pathway analysis effectively distinguish chRCC from oncocytoma. We have generated a novel transcript predictor that is able to discriminate between the two entities accurately, and which has been validated both in an internal and an independent data-set, implying generalizability. A cytogenetic alteration, loss of chromosome 1p, common to renal oncocytoma and chRCC has been identified, providing the opportunities for identifying novel tumor suppressor genes and we have identified a series of immunohistochemical markers that are clinically useful in discriminating chRCC and oncocytoma.
Epithelial renal cell carcinoma (RCC) is the most common malignancy of the adult kidney. RCC is a clinicopathologically heterogeneous disease that is traditionally classified by morphology into clear cell, papillary, chromophobe, and collecting duct carcinoma. Chromophobe renal cell carcinoma (chRCC) and renal oncocytoma are two distinct but related entities, with strong morphologic and genetic similarities . Distinguishing between the two tumors may present a significant diagnostic challenge on routine hematoxylin-eosin stained sections, especially in cases with features resembling both chRCC and oncocytoma, oncocytoma with associated invasion and even metastasis , and the eosinophilic variant of chRCC.
ChRCCs account for about 4-8% of all renal tumors, with a more favorable prognosis relative to clear cell renal cell carcinoma, which comprises the majority of all RCCs . On the other hand, oncocytoma is the most common benign renal tumor, comprising 5-8% of resected renal masses. The overlapping characteristics of these entities may be explained by a possible common origin from the intercalated cells of the distal tubule . Patients with Birt-Hogg-Dubé syndrome, a familial multi-tumor syndrome linked to mutation of the BHD gene, exhibit bilateral oncocytomas, chRCC and hybrid tumors [5, 6].
In our previous gene expression profiling studies of a limited number of chRCC and oncocytoma , we demonstrated that both tumors showed strong similarities in expression patterns suggesting a common underlying biology  and this was supported by subsequent expression profiling studies by other groups . We hypothesized that more effective discrimination might be achieved with a larger sample number with additional analyses, and that the differences might shed light on the underlying genetic drivers of tumorigenesis, diagnosis and clinical management. We set out to perform a comprehensive characterization of both entities by integrating gene expression and high resolution single-nucleotide polymorphism (SNP) profiling, proceeding to identify a useful and valid molecular predictor, as well as identifying novel immunohistochemical markers for each entity.
Gene expression profiles
A total of 30 frozen primary kidney tumors (15 chRCC and 15 oncocytomas) were obtained from the French Kidney Tumors Consortium, University of Chicago, Northwestern University, and Spectrum Health Hospital (Grand Rapids, MI). Each sample was confirmed by pathologic analysis and anonymized prior to the study. A portion of the tumor sample was frozen in liquid nitrogen immediately after surgery and stored at -80°C. Total RNA was isolated from the frozen tissues using Trizol reagent (Invitrogen, Carlsbad, CA) and purified using the RNEasy kit (Qiagen). Gene expression profiling was performed as previously described using the HGU133 Plus 2.0 Affymetrix GeneChip platform, with 54,675 distinct transcripts assayed . An external GEO data-set of gene expression profiles of oncocytomas and chRCC from Cornell University was obtained for validation (GSE12090) . Data for this study has been uploaded publicly in the Gene Expression Omnibus, with the accession number GSE19982.
DNA single-nucleotide polymorphism (SNP) arrays
DNA from an independent set of 6 chRCC and 8 oncocytomas obtained from the Cooperative Human Tissue Network were isolated using a Jetquick DNA extraction kit (Genomed, Lohne, Germany) according to the manufacturer's protocol. The SNP assay was performed according to the manufacturer's instructions using the Affymetrix GeneChip Mapping 100 K array (Affymetrix, Santa Clara, CA). The raw SNP array data was processed by Affymetrix GeneChip Genotyping analysis (GTYPE v.3) and human genome reference of NCBI build 36 was used for analysis.
Statistical analyses for expression data
Statistical analyses were performed in the statistical environment R 2.6.0, utilizing packages from the Bioconductor project . The robust multichip average (RMA) algorithm was used to perform pre-processing of the CEL files, including background adjustment, quartile normalization and summarization. For purposes of hierarchical analysis using complete linkage analysis, probe set filtering for coefficient of variation (≥0.05, with at least 2 samples showing log2 value expression of 8) was performed. Significance analysis of microarrays (SAM) on unfiltered data based on two-class unpaired analysis, assumption of unequal group variances and 10,000 permutations was used to derive a list of probe sets differentially expressed between tumor subclasses, and ordered by relative fold-change . A maximum false discovery rate threshold was defined as 0.05.
For derivation of a small gene classifier, we used prediction analysis of microarrays (PAM), an R implementation of nearest shrunken centroids methodology with 10-fold cross validation over 100 gene thresholds and an offset percentage of 30% on unfiltered data . A maximum acceptable cross-validated misclassification error was defined as ≤ 10%. The smallest predictor corresponding to this cross-validated error was selected for external validation. We inferred cytogenetic profiles for the tumors through the use of a refinement of the comparative genomic microarray analysis (CGMA) algorithm , which predicts chromosomal alterations based on regional changes in expression. Briefly, relative expression profiles R were generated from the single channel tumor expression profiles (T) and the mean expression values of 12 single channel cortical kidney expression profiles (N) such that R = log2(T) - log2(N).
KEGG pathway and gene ontology (GO) analysis of enriched gene sets was performed using hypergeometric tests available in the GOstats package in Bioconductor after having identified unique genes with corresponding annotations. For KEGG pathway analysis, the p-value threshold was 0.01. For GO analysis, conditional testing was performed, and the threshold for p was 0.001. Molecular function, biologic process, and cellular component analyses were performed.
DNA copy number analysis
DNA copy number (CN) was calculated based on the allele intensity of each SNP probe on the array using dChip http://biosun1.harvard.edu/complab/dchip/. Information about the cytobands and the physical position of all SNPs was obtained from Affymetrix and UCSC genome bioinformatics database (NCBI Build 36.1) http://genome.ucsc.edu. The working criteria for loss or gain are defined as the chromosomal region with at least four consecutive SNPs with CN < 1.6, or at least four consecutive SNPs with CN > 3.5, respectively. Copy number alteration (CNA) regions were identified when more than 30% of the samples showed copy number loss or gain.
Predictor derived via nearest shrunken centroid method for sample classification of chromophobe RCC and oncocytoma.
Affymetrix Probe ID
transmembrane channel-like 5
single immunoglobulin and toll-interleukin receptor (TIR) domain
cell division cycle 27 homolog (S. cerevisiae)
DEAH (Asp-Glu-Ala-His) box polypeptide 40
single immunoglobulin and toll-interleukin receptor (TIR) domain
transmembrane protein 17
leucine rich repeat and fibronectin type III domain containing 5
enoyl Coenzyme A hydratase domain containing 1
NADH dehydrogenase (ubiquinone) Fe-S protein 1
acyl-Coenzyme A dehydrogenase
Gene expression profiling
Predictor performance in sample classification of internal and external data-sets.
Gene predictor (14 probe sets)
DNA copy number profiling and comparative genomic microarray analysis
Molecular pathways discriminating chRCC and oncocytoma.
Pathways relatively upregulated in oncocytoma
Valine, leucine and isoleucine degradation
Citrate cycle (TCA cycle)
Arginine and proline metabolism
Ubiquitin mediated proteolysis
Pathways relatively upregulated in chRCC
T cell receptor signaling pathway
B cell receptor signaling pathway
Cell adhesion molecules (CAMs)
Leukocyte transendothelial migration
Chronic myeloid leukemia
Pathogenic Escherichia coli infection - EHEC
Pathogenic Escherichia coli infection - EPEC
Fc epsilon RI signaling pathway
Toll-like receptor signaling pathway
ErbB signaling pathway
mTOR signaling pathway
Epithelial cell signaling in Helicobacter pylori infection
Phosphatidylinositol signaling system
GnRH signaling pathway
Acute myeloid leukemia
Results of immunohistochemical staining showing sample discrimination.
ChRCC and oncocytoma are morphologic and genetically related entities, and distinction between these two tumors is important because of their different biological behaviors. However, these entities can be difficult to distinguish morphologically. We report the derivation of a novel and useful gene predictor validated both on an internal and an independent external data-set, implying its generalizability. Our results suggest that it is possible to classify accurately histopathologically challenging tumors. The degree of accuracy achieved at 93% is reasonable for a genetic classifier. However, integration into clinical practice requires a comprehensive evaluation of these classifiers within a clinical setting, comparing clinical outcomes in routine pathologic evaluation relative to that derived from novel classifiers. This may be most practically if not most ideally done in a retrospective fashion on paraffin-embedded tissue in a large multi-institutional collaboration, which we are currently pursuing. This issue may become progressively more important with the increase in incidentally detected small tumors on radiologic surveillance, where the dilemma between observation or intervention is commonly posed.
Integrating RNA and DNA genomic data allows us to verify genomic alterations in tumor samples and distinguish the genomic signatures of different tumor subtypes. Frequent losses of chromosome 1, 2, 6, 10, 13, 17, and 21 and gains in chromosome 4, 7, 11, 12, 14q and 18q were observed in chRCC, consistent with previously reported data [18, 19]. For renal oncocytoma, we show a high prevalence of chromosome 1p loss. Both chromophobe RCC and oncocytoma share this chromosomal alteration, consistent with a speculation that this may represent an early event in neoplastic transformation of a common progenitor cell.
Chromosome 1p loss represents a common cytogenetic alteration in both chRCC and renal oncocytoma identified by high-throughput SNP studies. This may suggest that this is an early event in the histogenesis of both tumors, before additional cellular events lead to malignancy in lesions that progress to chRCC, similar to chromosome 3p loss in clear cell renal cell carcinoma, which is thought to be an early event in carcinogenesis. Loss of chromosome 1p has been identified recently in renal oncocytoma , but this has not been previously shown to be a common cytogenetic alteration common to both entities, which is the key insight. Our delineation of the nature of chromosome 1p loss in renal oncocytoma provides the opportunity to identify novel tumor suppressor genes in future studies, and in establishing a possible carcinogenesis progression sequence.
There has been a recent advent of targeted therapies for a wide variety of cancers. Given the relative rarity of chRCC, there is no current standard of care and it is unlikely that any specific clinical trial is feasible or will be initiated. Here, we report two clinically relevant pathways--the c-erbB2/HER2 pathway and the mTOR signaling pathway--are dysregulated in chRCC on exploratory pathway analysis of mRNA expression, but our evaluation of extracellular HER2 and phospho-AKT immunohistochemical expression has not provided direct support for this mRNA finding. On a clinical trial level, in a subgroup analysis of a Phase III trial of temsirolimus, an mTOR inhibitor, in poor-prognosis RCC of all subtypes, patients of non-clear cell histology benefited as much as patients with clear cell histology, if not more . Our findings do not permit a single definitive conclusion about the nature of pathway activation in these two entities. Currently, mTOR inhibitors remain a clinical standard of care for poor-risk metastatic non-clear cell renal cell carcinoma. HER2 expression has been evaluated in chromophobe RCC and oncocytoma, with distinct patterns of peptide expression varying according to epitope . Interestingly, this study showed that strong intracellular HER2 expression (as defined by a 3+ expression) was strongly expressed in chromophobe RCC (9/19) but not in oncocytoma (1/11), whereas neither chromophobe RCC nor oncocytoma showed strong extracellular HER2 expression. Further evaluation of this is warranted, in conjunction with relevant fluorescent in-situ hybridization studies.
It has been previously reported that oxidative phosphorylation and energy pathway genes are overexpressed in chRCC and renal oncocytoma relative to the other subtypes of RCC . We are able to clarify this issue, demonstrating that even between these two entities, there are major differences in quantitative expression of the same pathways discriminating the two entities. Consistent with these results, it has been recently reported that oncocytomas exhibit mitochondrial DNA mutations with clonal expansion and complex I deficiencies . Oncocytoma contains a large number of mitochondria, and the overexpression of these genes involved in cellular metabolism may reflect the relative quantitative excess of the mitochondria. A similar profound modification in energy metabolism genes has been observed in thyroid oncocytomas, with high activity of the aerobic respiratory pathway . It may be speculated that potential inhibition of autophagy in the chromophobe RCC may correspond to this difference as well. Rohan et al have previously reported in a smaller data-set that gene expression profiling is able to discriminate oncocytomas and chRCC , and has reported that vesicular transport and cell junction proteins are relatively upregulated in chRCC.
In the process of validating our high-throughput expression studies, we report three novel markers discriminating between chRCC and oncocytoma: parafibromin, aquaporin 6, and synaptogyrin 3. Parafibromin, the protein product of the HRPT2 tumor suppressor gene, has been reported to be downregulated in a variety of tumors [17, 25], and a role has been assigned to it in the Wnt signaling pathway . While the mechanism of parafibromin downregulation in parathyroid carcinoma appears to be mediated through gene mutation, this does not seem to be the mechanism in chRCC, as we have not identified any HRPT2 mutations after analyzing DNA samples from 5 chRCC tumors (data not shown). Similarly, other investigators have reported allelic imbalances in the HRPT2 gene in oncocytoma and chromophobe RCC, but no mutations . Aquaporin 6 is an intracellular vesicle water channel protein reported to be expressed in the intercalated cells of the collecting duct , which is hypothesized to be the originating cell for oncocytoma and chRCC . Little is known about synaptogyrin-3, a tyrosine-phosphorylated protein that is expressed in synaptic vesicles . The reasons underlying the reduced expression of aquaporin 6 and increased expression of synaptogyrin-3 in chRCC, relative to oncocytoma are uncertain.
In summary, we have comprehensively characterized the molecular profiles of chRCC and oncocytoma using high throughput expression and SNP profiling. We have consequently derived discriminating expression signatures, pathways, cytogenetic profiles and protein markers that are of biologic, clinical and therapeutic interest.
Chromophobe renal cell carcinoma
renal cell carcinoma
robust multichip average
significance analysis of microarrays
prediction analysis of microarrays
comparative genomic microarray analysis
copy number alteration
mammalian target of rapamycin
epidermal growth factor.
We wish to thank the Fischer Family Foundation, the Singapore Cancer Society, the French National Cancer Institute (Kidney PNES, INCa), and the French League against Cancer (Comités du Cher et de l'Indre) for supporting this study. We would also like to thank the Hauenstein Foundation and the Van Andel Foundation for their continued support. We thank the Cooperative Human Tissue Network (CHTN) of the National Cancer Institute for providing samples for analysis. Min-Han Tan is supported by the Singapore Millenium Foundation and the National Kidney Foundation. We would also like to thank Sabrina Noyes for manuscript preparation and submission. We would like to acknowledge the reviewers for their comments which have improved the article.
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