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MicroRNA profiling of clear cell renal cell cancer identifies a robust signature to define renal malignancy.

MPS-Authors

Mollenkopf,  Hans-Joachim
Max Planck Society;

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Grimm,  Christina
In vitro Ligand Screening (Zoltán Konthur), Dept. of Vertebrate Genomics (Head: Hans Lehrach), Max Planck Institute for Molecular Genetics, Max Planck Society;

Wagner,  Ina
Max Planck Society;

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Lehrach,  Hans
Dept. of Vertebrate Genomics (Head: Hans Lehrach), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Nietfeld,  Wilfried
Dept. of Vertebrate Genomics (Head: Hans Lehrach), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Citation

Jung, M., Mollenkopf, H.-J., Grimm, C., Wagner, I., Albrecht, M., Waller, T., et al. (2009). MicroRNA profiling of clear cell renal cell cancer identifies a robust signature to define renal malignancy. Journal of Cellular and Molecular Medicine, 13(9b), 3918-3928. doi:10.1111/j.1582-4934.2009.00705.x.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0010-7E10-5
Abstract
MicroRNAs are short single-stranded RNAs that are associated with gene regulation at the transcriptional and translational level. Changes in their expression were found in a variety of human cancers. Only few data are available on microRNAs in clear cell renal cell carcinoma (ccRCC). We performed genome-wide expression profiling of microRNAs using microarray analysis and quantification of specific microRNAs by TaqMan real-time RT-PCR. Matched malignant and non-malignant tissue samples from two independent sets of 12 and 72 ccRCC were profiled. The microarray-based experiments identified 13 over-expressed and 20 down-regulated microRNAs in malignant samples. Expression in ccRCC tissue samples compared with matched non-malignant samples measured by RT-PCR was increased on average by 2.7- to 23-fold for the hsa-miR-16, −452*, −224, −155 and −210, but decreased by 4.8- to 138-fold for hsa-miR-200b, −363, −429, −200c, −514 and −141. No significant associations between these differentially expressed microRNAs and the clinico-pathological factors tumour stage, tumour grade and survival rate were found. Nevertheless, malignant and non-malignant tissue could clearly be differentiated by their microRNA profile. A combination of miR-141 and miR-155 resulted in a 97% overall correct classification of samples. The presented differential microRNA pattern provides a solid basis for further validation, including functional studies.