Abstract 1964: MicroRNA expression profiles classify renal cell carcinoma subtypes.
Authors: Wach Sven , Nolte Elke , Theil Anne , Stoehr Christine , Rau Tilman , Hartmann Arndt , Ekici Arif B. , Keck Bastian , Taubert Helge , Wullich Bernd 
Published: August 2014

Abstract
Introduction. Renal cell carcinoma (RCC) accounts for nearly 4% of all malignancies worldwide. According to the WHO classification of tumors of the urinary system, RCC is a collection of different subtypes rather than one entity. Besides the conventional clear cell RCC (ccRCC), the papillary RCC (pRCC), with an incidence of 10%-15%, is the second most common entity among renal malignancies. By histological characteristics, pRCCs can further be sub-divided into two distinct subtypes. Hereby, pRCCs type 2 are correlated with a worse clinical outcome. To date, little is known about the molecular characteristics within the pRCC subtypes.
Material and Methods. We used commercial miRNA microarrays (GeneChip miRNA arrays, Affymetrix) to perform whole miRNome profiling in a set of seven cases of ccRCC and pRCC subtypes 1 and 2 each. The expression of a selected subset of miRNAs was validated by quantitative PCR. The best discriminating miRNAs of this initial set were used to establish a classification model for tissue samples. This core set of miRNAs was analyzed in a second, independent patient cohort of 69 tissue samples. Using the pre-defined classification rules, the samples of the independent patient cohort were classified in a double-blind fashion solely by their miRNA expression.
Results. Microarray results showed, that every RCC entity and subtype displayed a characteristic pattern of miRNA expression. Ten miRNAs were selected based on their ability to discriminate between tumor and normal tissue or between different subtypes of RCC. Binary logistic regression identified a core set of only five miRNAs that was able to fully classify any given sample with an overall accuracy of 88%. This classification scheme was applied to an independent patient cohort. Here, the five discriminating miRNAs (miRNAs miR-145, -200c, -210, -502-3p, and let-7c) were able to classify the samples with an overall accuracy of 64%. A pathway analysis indicated that target genes of deregulated miRNAs are members of the family of multidrug-resistance proteins (MRPs) or components of the Jak-STAT signaling pathway.
Conclusions. Every entity or subtype of RCC displays a characteristic and unique pattern of miRNA expression. Characteristic miRNAs can be used to distinguish not only between tumor and normal tissue samples but also between different tumor entities with high accuracy. Target genes of these characteristic miRNAs might contribute to the tumor biologic and clinical behavior of RCC entities and subtypes.
Citation Format: Sven Wach, Elke Nolte, Anne Theil, Christine Stoehr, Tilman Rau, Arndt Hartmann, Arif B. Ekici, Bastian Keck, Helge Taubert, Bernd Wullich. MicroRNA expression profiles classify renal cell carcinoma subtypes. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 1964. doi:10.1158/1538-7445.AM2013-1964