Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA141351 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Whole genome expression of 39 clear-cell renal cell carcinomas tumors 39 frozen tissue from recent nephrectomies for clear-cell renal cell carcinoma; association with clinical characteristics
2011-05-28 | E-GEOD-29609 | biostudies-arrayexpress
Project description:Whole genome expression of 39 clear-cell renal cell carcinomas tumors
2011-05-28 | GSE29609 | GEO
Project description:Materials and Methods Results Discussion References Renal cell carcinoma comprises several histological types with different clinical behavior. Accurate pathological characterization is important in the clinical management of these tumors. We describe gene expression profiles in 41 renal tumors determined by using DNA microarrays containing 22,648 unique cDNAs representing 17,083 different UniGene Clusters, including 7230 characterized human genes. Differences in the patterns of gene expression among the different tumor types were readily apparent; hierarchical cluster analysis of the tumor samples segregated histologically distinct tumor types solely based on their gene expression patterns. Conventional renal cell carcinomas with clear cells showed a highly distinctive pattern of gene expression. Papillary carcinomas formed a tightly clustered group, as did tumors arising from the distal nephron and the normal kidney samples. Surprisingly, conventional renal cell carcinomas with granular cytoplasm were heterogeneous, and did not resemble any of the conventional carcinomas with clear cytoplasm in their pattern of gene expression. Characterization of renal cell carcinomas based on gene expression patterns provides a revised classification of these tumors and has the potential to supply significant biological and clinical insights.
2005-10-05 | E-SMDB-1890 | biostudies-arrayexpress
Project description:Renal cell carcinoma comprises several histological types with different clinical behavior. Accurate pathological characterization is important in the clinical management of these tumors. We describe gene expression profiles in 41 renal tumors determined by using DNA microarrays containing 22,648 unique cDNAs representing 17,083 different UniGene Clusters, including 7230 characterized human genes. Differences in the patterns of gene expression among the different tumor types were readily apparent; hierarchical cluster analysis of the tumor samples segregated histologically distinct tumor types solely based on their gene expression patterns. Conventional renal cell carcinomas with clear cells showed a highly distinctive pattern of gene expression. Papillary carcinomas formed a tightly clustered group, as did tumors arising from the distal nephron and the normal kidney samples. Surprisingly, conventional renal cell carcinomas with granular cytoplasm were heterogeneous, and did not resemble any of the conventional carcinomas with clear cytoplasm in their pattern of gene expression. Characterization of renal cell carcinomas based on gene expression patterns provides a revised classification of these tumors and has the potential to supply significant biological and clinical insights. A disease state experiment design type is where the state of some disease such as infection, pathology, syndrome, etc is studied. Computed
2006-01-31 | E-GEOD-4125 | biostudies-arrayexpress
Project description:We performed a microRNA (miRNA) microarray on 10 metastatic RCC tumors and compared differential miRNA expresison to 19 primary clear cell renal cell carcinomas (ccRCC). We found there were 65 significantly dysregulated miRNAs; 9 miRNAs were significantly upregulated and 56 miRNAs were significantly downregulated in metastatic RCC when compared to primary clear cell renal cell carcinoma. miRNA microarray was performed on 10 metastatic RCC tumors
2012-08-13 | E-GEOD-39440 | biostudies-arrayexpress
Project description:Renal cell carcinoma comprises several histological types with different clinical behavior. Accurate pathological characterization is important in the clinical management of these tumors. We describe gene expression profiles in 41 renal tumors determined by using DNA microarrays containing 22,648 unique cDNAs representing 17,083 different UniGene Clusters, including 7230 characterized human genes. Differences in the patterns of gene expression among the different tumor types were readily apparent; hierarchical cluster analysis of the tumor samples segregated histologically distinct tumor types solely based on their gene expression patterns. Conventional renal cell carcinomas with clear cells showed a highly distinctive pattern of gene expression. Papillary carcinomas formed a tightly clustered group, as did tumors arising from the distal nephron and the normal kidney samples. Surprisingly, conventional renal cell carcinomas with granular cytoplasm were heterogeneous, and did not resemble any of the conventional carcinomas with clear cytoplasm in their pattern of gene expression. Characterization of renal cell carcinomas based on gene expression patterns provides a revised classification of these tumors and has the potential to supply significant biological and clinical insights. A disease state experiment design type is where the state of some disease such as infection, pathology, syndrome, etc is studied. Keywords: disease_state_design
2006-02-01 | GSE4125 | GEO
Project description:Identification of metastamirs as metastasis-associated microRNAs in clear cell renal cell carcinomas
| PRJNA166875 | ENA
Project description:We performed a microRNA (miRNA) microarray on 10 metastatic RCC tumors and compared differential miRNA expresison to 19 primary clear cell renal cell carcinomas (ccRCC). We found there were 65 significantly dysregulated miRNAs; 9 miRNAs were significantly upregulated and 56 miRNAs were significantly downregulated in metastatic RCC when compared to primary clear cell renal cell carcinoma.
2012-08-14 | GSE39440 | GEO
Project description:To understand the relationship of radiomic and transcriptomic features of metastatic clear cell renal cell carcinoma, we performed RNA-sequencing in clear cell renal cell carcinomas (ccRCCs).
2019-09-30 | GSE135091 | GEO