Signaling pathway-based stratification of clear cell renal cell carcinoma.
434 Background: There are marked differences in responses to therapy among patients with clear cell renal cell carcinoma (ccRCC), which makes the outcome difficult to predict. This study is aimed to define a new classification system that would elucidate distinctions between carcinomas in order to facilitate selection of the appropriate treatment. We mapped cell signaling pathways in individual renal cell carcinomas and identified different classes based on commonly shared phosphorylation-driven signaling networks. Methods: Laser capture microdissection and reverse-phase protein arrays were used to profile 75 key nodes in 16 primary clear cell renal cancers. These nodes represent many signaling pathways known to be important in tumorigenesis and progression. Results: Statistical analysis revealed significant differences (p <0.05) in signaling levels between two groups of samples, group A (4 samples) and group B (12 samples), for 27 of the 75 endpoints tested. In group A, high activation levels of EGFR, RET, and RASGFR1 converged to activate AKT/mTOR. Group B, showed high phosphorylation levels of ERK1/2 and STAT transcription factors and samples significantly partitioned in two clusters of 7 and 5 cases designated C and D. Group C showed elevated expression of a regulator of autophagy, LC3B; group D showed activation of Src and STAT transcription factors, suggesting the presence of cytokine-mediated cell survival pathways. A DNA copy number analysis was performed on the same samples and the results showed that group B represents some paradigmatic cases of ccRCC, with VHL loss-of-function mutations. Conclusions: The proteins identified appeared to be linked to pathways that are targeted by drugs typically used to treat clear cell renal cell carcinoma. Thus, this type of analysis could be useful for stratifying patients and selecting the best therapeutic approaches.