Open Access Research

Virtual karyotyping with SNP microarrays reduces uncertainty in the diagnosis of renal epithelial tumors

Jill M Hagenkord1, Anil V Parwani1, Maureen A Lyons-Weiler2, Karla Alvarez3, Robert Amato3, Zoran Gatalica4, Jose M Gonzalez-Berjon5, Leif Peterson3, Rajiv Dhir1 and Federico A Monzon356*

Author Affiliations

1 Department of Pathology, University of Pittsburgh, Pittsburgh, PA, USA

2 Clinical Genomics Facility, University of Pittsburgh, Pittsburgh, PA, USA

3 Department of Pathology, The Methodist Hospital Research Institute, Houston, TX, USA

4 Department of Pathology, Creighton University Medical Center, Omaha, NE, USA

5 Department of Pathology, The Methodist Hospital, Houston, TX, USA

6 Pathology, Weill Medical College of Cornell University, New York, NY, USA

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Diagnostic Pathology 2008, 3:44  doi:10.1186/1746-1596-3-44

Published: 6 November 2008

Abstract

Background

Renal epithelial tumors are morphologically, biologically, and clinically heterogeneous. Different morphologic subtypes require specific management due to markedly different prognosis and response to therapy. Each common subtype has characteristic chromosomal gains and losses, including some with prognostic value. However, copy number information has not been readily accessible for clinical purposes and thus has not been routinely used in the diagnostic evaluation of these tumors. This information can be useful for classification of tumors with complex or challenging morphology. 'Virtual karyotypes' generated using SNP arrays can readily detect characteristic chromosomal lesions in paraffin embedded renal tumors and can be used to correctly categorize the common subtypes with performance characteristics that are amenable for routine clinical use.

Methods

To investigate the use of virtual karyotypes for diagnostically challenging renal epithelial tumors, we evaluated 25 archived renal neoplasms where sub-classification could not be definitively rendered based on morphology and other ancillary studies. We generated virtual karyotypes with the Affymetrix 10 K 2.0 mapping array platform and identified the presence of genomic lesions across all 22 autosomes.

Results

In 91% of challenging cases the virtual karyotype unambiguously detected the presence or absence of chromosomal aberrations characteristic of one of the common subtypes of renal epithelial tumors, while immunohistochemistry and fluorescent in situ hybridization had no or limited utility in the diagnosis of these tumors.

Conclusion

These results show that virtual karyotypes generated by SNP arrays can be used as a practical ancillary study for the classification of renal epithelial tumors with complex or ambiguous morphology.