MicroRNA profiles classify papillary renal cell carcinoma subtypes

• Published in: British journal of cancer 2013-08, Vol.109 (3), p.714-722
• Main Authors: Wach, S, Nolte, E, Theil, A, Stöhr, C, T Rau, T, Hartmann, A, Ekici, A, Keck, B, Taubert, H, Wullich, B
• Format: Article
• Language: English
• Subjects: 631/337/384/331; 631/67/589/1588/1351; 692/53/2421; Accuracy; Biological and medical sciences; Biomedical and Life Sciences; Biomedicine; Cancer Research; Carcinoma, Renal Cell - classification; Carcinoma, Renal Cell - genetics; Carcinoma, Renal Cell - pathology; Classification; Cohort Studies; Drug Resistance; Epidemiology; Gene Expression Profiling; Genes; Humans; Kidney cancer; Kidney Neoplasms - classification; Kidney Neoplasms - genetics; Kidney Neoplasms - pathology; Kidneys; Medical research; Medical sciences; MicroRNAs; MicroRNAs - biosynthesis; MicroRNAs - genetics; Molecular Diagnostics; Molecular Medicine; Multiple tumors. Solid tumors. Tumors in childhood (general aspects); Mutation; Nephrology. Urinary tract diseases; Oncology; Pathology; Patients; Principal Component Analysis; Prostate cancer; Tumors; Tumors of the urinary system
• ISSN: 0007-0920; 1532-1827
• DOI: 10.1038/bjc.2013.313

Background: Besides the conventional clear-cell renal cell carcinoma (ccRCC), papillary RCC (pRCC) is the second most common renal malignancy. Papillary RCCs can further be subdivided into two distinct subtypes. Although a clinical relevance of pRCC subtyping has been shown, little is known about the molecular characteristics of both pRCC subtypes. Methods: We performed microarray-based microRNA (miRNA) expression profiling of primary ccRCC and pRCC cases. A subset of miRNAs was identified and used to establish a classification model for ccRCC, pRCC types 1 and 2 and normal tissue. Furthermore, we performed gene set enrichment analysis with the predicted miRNA target genes. Results: Only five miRNAs ( miR-145 , -200c , -210 , -502-3p and let-7c ) were sufficient to identify the samples with high accuracy. In a collection of 111 tissue samples, 73.9% were classified correctly. An enrichment of miRNA target genes in the family of multidrug-resistance proteins was noted in all tumours. Several components of the Jak-STAT signalling pathway might be targets for miRNAs that define pRCC tumour subtypes. Conclusion: MicroRNAs are able to accurately classify RCC samples. Deregulated miRNAs might contribute to the high chemotherapy resistance of RCC. Furthermore, our results indicate that pRCC type 2 tumours could be dependent on oncogenic MYC signalling.