Conventional renal cell carcinomas

ABSTRACT: Our goal was to identify gene expression features, using comprehensive gene expression profiling, that correlate with survival in conventional renal cell carcinomas (cRCCs). We profiled 177 cRCCs using high-density cDNA microarrays. Unsupervised hierarchical clustering analysis segregated cRCC into five gene expression subgroups. Expression subgroup was correlated with survival in long-term follow-up and was independent of grade, stage, and performance status. The tumors were then divided evenly into training and test sets that were balanced for grade, stage, performance status, and length of follow-up. A semisupervised learning algorithm (supervised principal components analysis) was applied to identify transcripts whose expression was associated with survival in the training set, and th

ORGANISM(S): Homo sapiens

SUBMITTER: Hongjuan Zhao 

PROVIDER: E-GEOD-3538 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress