Homo sapiens
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ABSTRACT:
PROVIDER: PRJNA106477 | ENA |
REPOSITORIES: ENA
Similar Datasets
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
Project description:Virtual-Karyotyping with SNP microarrays in morphologically challenging renal cell neoplasms
| PRJNA112365 | ENA
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.
2009-03-13 | GSE14670 | GEO
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
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.
2009-02-19 | GSE12808 | GEO
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
2008-11-01 | GSE11447 | GEO
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
2008-01-24 | GSE9469 | GEO
Project description:Background: Clear cell renal cell carcinoma (ccRCC) and chromophobe renal cell carcinoma (chRCC) can usually be distinguished by histologic characteristics. Occasionally, diagnosis proves challenging and diagnostic difficulty will likely increase as needle biopsies of renal lesions become more common. Method: To identify markers that aid in differentiating ccRCC from chRCC, we used gene expression profiles to identify candidate markers that correlate with histology. 39 antisera and antibodies, including 35 for transcripts identified from gene expression profiling, were evaluated. Promising markers were tested on a tissue microarray (TMA) containing 428 renal neoplasms. Strength of staining of each core on the TMA was formally scored and the distribution of staining across different types of renal neoplasms was analyzed. Results: Based on results from initial immunohistochemical staining of multitissue titer arrays, 23 of the antisera and antibodies were selected for staining of the TMA. For 7 of these markers, strength of staining of each core on the TMA was formally scored. Vimentin (positive in ccRCC) and CD9 (positive in chRCC) best distinguished ccRCC from chRCC. The combination of vimentin negativity and CD9 positivity was found to distinguish chRCC from ccRCC with a sensitivity of 100.0% and a specificity of 95.2%. Conclusions: Based on gene expression analysis, we identify CD9 and vimentin as candidate markers for distinguishing between ccRCC and chRCC. In difficult cases and particularly when the amount of diagnostic tissue is limited, vimentin and CD9 staining could serve as a useful adjunct in the differential diagnosis of ccRCC and chRCC. A disease state experiment design type is where the state of some disease such as infection, pathology, syndrome, etc is studied. Disease State: Stage of Clear Cell renal cell carcinoma (I - V)) disease_state_design
2010-08-20 | E-GEOD-17746 | biostudies-arrayexpress
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
Project description:Background: Clear cell renal cell carcinoma (ccRCC) and chromophobe renal cell carcinoma (chRCC) can usually be distinguished by histologic characteristics. Occasionally, diagnosis proves challenging and diagnostic difficulty will likely increase as needle biopsies of renal lesions become more common. Method: To identify markers that aid in differentiating ccRCC from chRCC, we used gene expression profiles to identify candidate markers that correlate with histology. 39 antisera and antibodies, including 35 for transcripts identified from gene expression profiling, were evaluated. Promising markers were tested on a tissue microarray (TMA) containing 428 renal neoplasms. Strength of staining of each core on the TMA was formally scored and the distribution of staining across different types of renal neoplasms was analyzed. Results: Based on results from initial immunohistochemical staining of multitissue titer arrays, 23 of the antisera and antibodies were selected for staining of the TMA. For 7 of these markers, strength of staining of each core on the TMA was formally scored. Vimentin (positive in ccRCC) and CD9 (positive in chRCC) best distinguished ccRCC from chRCC. The combination of vimentin negativity and CD9 positivity was found to distinguish chRCC from ccRCC with a sensitivity of 100.0% and a specificity of 95.2%. Conclusions: Based on gene expression analysis, we identify CD9 and vimentin as candidate markers for distinguishing between ccRCC and chRCC. In difficult cases and particularly when the amount of diagnostic tissue is limited, vimentin and CD9 staining could serve as a useful adjunct in the differential diagnosis of ccRCC and chRCC. A disease state experiment design type is where the state of some disease such as infection, pathology, syndrome, etc is studied. Disease State: Stage of Clear Cell renal cell carcinoma (I - V))
2010-08-20 | GSE17746 | GEO