• Jon Jones, Hasan Otu, Dimitrios Spentzos, Shakirahmed Kolia, Mehmet Inan, Wolf D Beecken, Christian Fellbaum, Xuesong Gu, Marie Joseph, Allan J Pantuck, Dietger Jonas, and Towia A Libermann.
• Beth Israel Deaconess Medical Center Genomics Center and Dana-Farber/Harvard Cancer Center Proteomics Core, Boston, Massachusetts 02115, USA.
• Clin Cancer Res. 2005 Aug 15; 11 (16): 5730-9.

PurposeTo address the progression, metastasis, and clinical heterogeneity of renal cell cancer (RCC).Experimental DesignTranscriptional profiling with oligonucleotide microarrays (22,283 genes) was done on 49 RCC tumors, 20 non-RCC renal tumors, and 23 normal kidney samples. Samples were clustered based on gene expression profiles and specific gene sets for each renal tumor type were identified. Gene expression was correlated to disease progression and a metastasis gene signature was derived.ResultsGene signatures were identified for each tumor type with 100% accuracy. Differentially expressed genes during early tumor formation and tumor progression to metastatic RCC were found. Subsets of these genes code for secreted proteins and membrane receptors and are both potential therapeutic or diagnostic targets. A gene pattern ("metastatic signature") derived from primary tumor was very accurate in classifying tumors with and without metastases at the time of surgery. A previously described "global" metastatic signature derived by another group from various non-RCC tumors was validated in RCC.ConclusionUnlike previous studies, we describe highly accurate and externally validated gene signatures for RCC subtypes and other renal tumors. Interestingly, the gene expression of primary tumors provides us information about the metastatic status in the respective patients and has the potential, if prospectively validated, to enrich the armamentarium of diagnostic tests in RCC. We validated in RCC, for the first time, a previously described metastatic signature and further showed the feasibility of applying a gene signature across different microarray platforms. Transcriptional profiling allows a better appreciation of the molecular and clinical heterogeneity in RCC.

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