microRNA Profiling in Kidney Cancer: Accurate Molecular Classification of Subtypes and Correlation with Cytogenetic and mRNA Data.
Youssef M Youssef, Nicole MA White, Jorg Grigull, Adriana Krizova, Christina Samy, Salvador Mejia-Guerrera, Andrew Evans, George M Yousef. University of Toronto, ON, Canada; Li Ka Shing Knowledge Institute, Toronto, ON, Canada; York University, Toronto, ON, Canada; Toronto General Hospital, ON, Canada
Background: Renal cell carcinoma (RCC) encompasses different histological subtypes. Distinguishing between the subtypes is usually made on morphological basis but this is not always feasible or accurate. The aim of this study was to identify microRNA (miRNA) signatures that can distinguish between the different RCC tumor types and to explore their unique and shared biological pathways.
Design: miRNA microarray analysis was performed on fresh frozen tissues of three common RCC subtypes [clear cell RCC (ccRCC), chromophobe RCC (chRCC) and papillary (pRCC)], and the benign oncocytoma tumor. Results were validated on an independent set of tumors using quantitative real time PCR analysis with miRNA-specific primers. Extensive target prediction analysis was performed for differentially expressed miRNAs. We also did a comprehensive bioinformatics analysis to examine the correlation of gene expression and cytogenetic profiling data with the predicted miRNA targets.
Results: Unique miRNA signatures can distinguish between the different RCC subtypes and oncocytoma. We developed a hierarchical multi-step decision tree that can accurately identify each tumor type with very high sensitivity and specificity using specific miRNA pairs. Also a miRNA signature can also be used to distinguish between pairs of subtypes with almost 100% sensitivity (e.g. ccRCC vs. chRCC and chRCC vs. oncocytoma). Bioinformatics analysis showed that the pathogenesis of ccRCC is more closely related to pRCC, whereas chRCC showed a comparable expression profile to oncocytoma.
Conclusions: miRNA expression patterns can distinguish between RCC tumor types. Our hierarchical decision tree can accurately distinguish between RCC tumor types when diagnosis based on morphology alone is difficult. miRNA expression profiles point out to the presence of shared and unique dysregulated pathways among different RCC subtypes and oncocytoma.
Category: Genitourinary (including renal tumors)
Wednesday, March 2, 2011 9:30 AM
Poster Session V # 106, Wednesday Morning