MicroRNA profiles classify papillary renal cell carcinoma subtypes

Br J Cancer. 2013 Aug 6;109(3):714-22. doi: 10.1038/bjc.2013.313. Epub 2013 Jun 25.

Abstract

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Carcinoma, Renal Cell / classification
  • Carcinoma, Renal Cell / genetics*
  • Carcinoma, Renal Cell / pathology
  • Cohort Studies
  • Gene Expression Profiling
  • Humans
  • Kidney Neoplasms / classification
  • Kidney Neoplasms / genetics*
  • Kidney Neoplasms / pathology
  • MicroRNAs / biosynthesis
  • MicroRNAs / genetics*
  • Principal Component Analysis

Substances

  • MicroRNAs