Project description:Genetic lesions characteristic for RCC subtypes can be identified by virtual karyotyping with SNP microarrays. In this study, we examined whether virtual karyotypes could be used to better classify a cohort of morphologically challenging/unclassified RCC.
Project description:Genetic lesions characteristic for RCC subtypes can be identified by virtual karyotyping with SNP microarrays. In this study, we examined whether virtual karyotypes could be used to better classify a cohort of morphologically challenging/unclassified RCC. Tumor resection specimens from 17 patients were profiled by virtual karyotyping with Affymetrix 10K 2.0 or 250K Nsp SNP Mapping arrays and were also evaluated independently by a panel of seven genito-urinary pathologists. Tumors were classified by the established pattern of genomic imbalances based on a reference cohort of 98 cases with classic morphology and compared to the morphologic diagnosis of the pathologist panel. In 3 cases, samples from areas with different morphologic appearance were also tested (n=5).
Project description:Renal tumors with complex 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 in cases where morphology was unable to definitively classify these tumors. Keywords: Chromosome copy number and LOH analysis (virtual karyotyping) with SNP Genotyping Arrays Keywords: Genome variation profiling by SNP array
Project description:Renal epithelial neoplasms have characteristic chromosomal imbalances that can be used for classification. We have previously shown that virtual karyotypes (v-karyotype) derived from SNP microarrays can be performed on formalin-fixed paraffin embedded (FFPE) tissue samples but a direct comparison with karyotypes obtained by conventional cytogenetics has not been done. 20 archival FFPE tumor samples were analyzed with Affymetrix 10K 2.0 or 250K Nsp SNP microarrays. 19 archival FFPE tumor samples were analyzed with Affymetrix 10K 2.0 or 250K Nsp SNP microarrays and virtual-karyotype results compared to those obtained by Cytogenetics.
Project description:Renal epithelial neoplasms have characteristic chromosomal imbalances that can be used for classification. We have previously shown that virtual karyotypes (v-karyotype) derived from SNP microarrays can be performed on formalin-fixed paraffin embedded (FFPE) tissue samples but a direct comparison with karyotypes obtained by conventional cytogenetics has not been done. 20 archival FFPE tumor samples were analyzed with Affymetrix 10K 2.0 or 250K Nsp SNP microarrays.
Project description:Renal tumors with complex 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. Keywords: Chromosome copy number and LOH analysis with SNP Genotyping Arrays
Project description:Renal tumors with complex 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. Experiment Overall Design: We analyzed 20 paraffin-embedded tissues representing conventional renal cell carcinoma (RCC), papillary RCC, chromophobe RCC, and oncocytoma with Affymetrix GeneChip 10K 2.0 Mapping arrays.
