Whole genome SNP arrays as a potential diagnostic tool for the detection of characteristic chromosomal aberrations in renal epithelial tumors
Monzon FA, Hagenkord JM, Lyons-Weiler MA, Balani JP, Parwani AV, Sciulli CM, Li J, Chandran UR, Bastacky SI, Dhir R. Whole genome SNP arrays as a potential diagnostic tool for the detection of characteristic chromosomal aberrations in renal epithelial tumors. Modern Pathology : An Official Journal of The United States and Canadian Academy of Pathology, Inc. 2008 May;21(5):599-608. PMID: 18246049. DOI: 10.1038/modpathol.2008.20.
Renal tumors with complex or unusual morphology require extensive workup for accurate classification. Chromosomal aberrations that define subtypes of renal epithelial neoplasms have been reported. We explored if whole-genome chromosome copy number and loss-of-heterozygosity analysis with single nucleotide polymorphism (SNP) arrays can be used to identify these aberrations and classify renal epithelial tumors. We analyzed 20 paraffin-embedded tissues representing clear cell, papillary renal and chromophobe renal cell carcinoma, as well as oncocytoma with Affymetrix GeneChip 10K 2.0 Mapping arrays. SNP array results were in concordance with known genetic aberrations for each renal tumor subtype. Additional chromosomal aberrations were detected in all renal cell tumor types. The unique patterns allowed 19 out of 20 tumors to be readily categorized by their chromosomal copy number aberrations. One papillary renal cell carcinoma type 2 did not show the characteristic 7/17 trisomies. Clustering using the median copy number of each chromosomal arm correlated with histological class when using a restricted set of chromosomes. In addition, three morphologically challenging tumors were analyzed to explore the potential clinical utility of this method. In these cases, the SNP array-based copy number evaluation yielded information with potential clinical value. These results show that SNP arrays can detect characteristic chromosomal aberrations in paraffin-embedded renal tumors, and thus offer a high-resolution, genome-wide method that can be used as an ancillary study for classification and potentially for prognostic stratification of these tumors.