To better understand the molecular mechanisms that underlie the tumorigenesis and progression of clear cell renal cell carcinoma (ccRCC), we studied the gene expression profiles of 29 ccRCC tumors obtained from patients with diverse clinical outcomes by using 21,632 cDNA microarrays. We identified gene expression alterations that were both common to most of the ccRCC studied and unique to clinical subsets. There was a significant distinction in gene expression profile between patients with a relatively nonaggressive form of the disease [100% survival after 5 years with the majority (15͞17 or 88%) having no clinical evidence of metastasis] versus patients with a relatively aggressive form of the disease (average survival time 25.4 months with a 0% 5-year survival rate). Approximately 40 genes most accurately make this distinction, some of which have previously been implicated in tumorigenesis and metastasis. To test the robustness and potential clinical usefulness of this molecular distinction, we simulated its use as a prognostic tool in the clinical setting. In 96% of the ccRCC cases tested, the prediction was compatible with the clinical outcome, exceeding the accuracy of prediction by staging. These results suggest that two molecularly distinct forms of ccRCC exist and that the integration of expression profile data with clinical parameters could serve to enhance the diagnosis and prognosis of ccRCC. Moreover, the identified genes provide insight into the molecular mechanisms of aggressive ccRCC and suggest intervention strategies.

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We analysed the expression profiles of 70 kidney tumors of different histological subtypes to determine if these subgroups can be distinguished by their gene expression profiles, and to gain insights into the molecular mechanisms underlying each subtype. In all, 39 clear cell renal cell carcinomas (RCC), seven primary and one metastatic papillary RCC, six granular RCC from old classification, five chromophobe RCC, five sarcomatoid RCC, two oncocytomas, three transitional cell carcinomas (TCC) of the renal pelvis and five Wilms' tumors were compared with noncancerous kidney tissues using microarrays containing 19 968 cDNAs. Based on global gene clustering of 3560 selected cDNAs, we found distinct molecular signatures in clear cell, papillary, chromophobe RCC/ oncocytoma, TCC and Wilms' subtypes. The close clustering in each of these subtypes points to different tumorigenic pathways as reflected by their histological characteristics. In the clear cell RCC clustering, two subgroups emerged that correlated with clinical outcomes, confirming the potential use of gene expression signatures as a predictor of survival. In the so-called granular cell RCC (terminology for a subtype that is no longer preferred), none of the six cases clusters together, supporting the current view that they do not represent a single entity. Blinded histological re-evaluation of four cases of 'granular RCC' led to their reassignment to other existing histological subtypes, each compatible with our molecular classification. Finally, we found gene sets specific to each subtype. In order to establish the use of some of these genes as novel subtype markers, we selected four genes and performed immunohistochemical analysis on 40 cases of primary kidney tumors. The results were consistent with the gene expression microarray data: glutathione S-transferase a was highly expressed in clear cell RCC, a methylacyl racemase in papillary RCC, carbonic anhydrase II in chromophobe RCC and K19 in TCC. In conclusion, we demonstrated that molecular profiles of kidney cancers closely correlated with their histological subtypes. We have also identified in these subtypes differentially expressed genes that could have important diagnostic and therapeutic implications.