Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Virtual-Karyotyping with SNP microarrays in morphologically challenging renal cell neoplasms

ABSTRACT: 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.

ORGANISM(S): Homo sapiens

PROVIDER: GSE14670 | GEO | 2009/03/13

SECONDARY ACCESSION(S): PRJNA112365

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Similar Datasets

Virtual-Karyotyping with SNP microarrays in morphologically challenging renal cell neoplasms

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).

2009-03-13 | E-GEOD-14670 | biostudies-arrayexpress

Diagnosis of Morphologically Challenging Cases of Renal Epithelial Neoplasms by Virtual Karyotypes with SNP Arrays

2008-11-01 | GSE11447 | GEO

Genotyping of human morphologically challenging cases of renal epithelial neoplasms by virtual karyotypes

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. Experiment Overall Design: We analyzed 50 paraffin-embedded tissues representing tumors with classic morphology from clear cell renal cell carcinoma (RCC), papillary RCC, chromophobe RCC, and oncocytoma with Affymetrix GeneChip 10K 2.0 Mapping arrays. We then analyzed 25 tumors that could not be classified by morphology and classified them based on the presence of defining chromosomal anomalies identified in the "classic" cohort.

2008-11-13 | E-GEOD-11447 | biostudies-arrayexpress

Detection of chromosomal aberrations in renal tumors by virtual karyotyping with SNP microarrays

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.

2009-02-19 | E-GEOD-12808 | biostudies-arrayexpress

Detection of chromosomal aberrations in renal tumors by virtual karyotyping with SNP microarrays

2009-02-19 | GSE12808 | GEO

Virtual Karyotyping of Androgen Insensitive Prostate Cancer

Project description:We investigated chromosomal imbalances in samples from patients with androgen insensitive prostate cancer. 4 archival FFPE tumor samples were analyzed with Affymetrix 250K Nsp SNP microarrays and virtual-karyotype results for PTEN region were compared to PTEN deletion analysis by FISH.

2010-04-03 | E-GEOD-13439 | biostudies-arrayexpress