Differential gene expression identifies subgroups of renal cell carcinoma

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Abstract

Clear cell carcinoma of the kidney, the most common subtype of renal cell cancer, displays different biological behavior in different patients. This heterogeneity cannot be recognized by light microscopy. In this study, gene expression in 16 clear cell renal cell carcinoma samples and 17 non-malignant tissue types comprising 539 samples was determined using oligonucleotide microarrays representing approximately 40,000 known genes and ESTs. Differences in gene expression were quantified as the fold change in gene expression between the various sets of samples. A set of genes was identified that was overexpressed in the renal cell carcinoma samples compared with the normal kidney samples. Principle component analysis of the set of renal cell carcinomas using this set of genes overexpressed in renal cell cancer revealed the existence of 2 major subgroups among the renal carcinomas. A series of principle component analyses of the set of renal cell carcinomas using different gene sets composed of genes involved in different metabolic pathways also revealed the same 2 major subgroups of the renal cell cancers. Eisen clustering using the same genes also revealed the same 2 major renal cell cancer subsets. Review of the pathology suggested that these 2 subgroups differed in pathologic grade. Genes differentially expressed between the 2 renal cell cancer subsets were identified. Examination of gene expression in each renal cell cancer subset and the pool of renal cell carcinoma samples compared with that in 17 different normal tissues revealed genes specifically overexpressed in renal cell cancer compared with these normal tissues. The authors conclude that gene expression patterns may be useful in helping to further classify subtypes of renal cell carcinoma that may have clinical significance. In addition, the genes identified as overexpressed in each set of clear cell renal cell carcinomas compared with normal tissues may represent useful targets for therapy.

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