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Oncogene ; 31(8): 978-91, 2012 Feb 23.
Article in English | MEDLINE | ID: mdl-21765474

ABSTRACT

Prostate cancer (PCa) is the most frequent male malignancy and the second most common cause of cancer-related death in Western countries. Current clinical and pathological methods are limited in the prediction of postoperative outcome. It is becoming increasingly evident that small non-coding RNA (ncRNA) species are associated with the development and progression of this malignancy. To assess the diversity and abundance of small ncRNAs in PCa, we analyzed the composition of the entire small transcriptome by Illumina/Solexa deep sequencing. We further analyzed the microRNA (miRNA) expression signatures of 102 fresh-frozen patient samples during PCa progression by miRNA microarrays. Both platforms were cross-validated by quantitative reverse transcriptase-PCR. Besides the altered expression of several miRNAs, our deep sequencing analyses revealed strong differential expression of small nucleolar RNAs (snoRNAs) and transfer RNAs (tRNAs). From microarray analysis, we derived a miRNA diagnostic classifier that accurately distinguishes normal from cancer samples. Furthermore, we were able to construct a PCa prognostic predictor that independently forecasts postoperative outcome. Importantly, the majority of miRNAs included in the predictor also exhibit high sequence counts and concordant differential expression in Illumina PCa samples, supported by quantitative reverse transcriptase-PCR. Our findings provide miRNA expression signatures that may serve as an accurate tool for the diagnosis and prognosis of PCa.


Subject(s)
Biomarkers, Tumor/metabolism , MicroRNAs/metabolism , Prostatic Neoplasms/diagnosis , Prostatic Neoplasms/metabolism , Transcriptome , Adult , Aged , Aged, 80 and over , Cell Line, Tumor , Gene Expression , Gene Expression Profiling , High-Throughput Nucleotide Sequencing , Humans , Kaplan-Meier Estimate , Lymphatic Metastasis , Male , MicroRNAs/genetics , Middle Aged , Oligonucleotide Array Sequence Analysis , Primary Cell Culture , Prognosis , Prostate/metabolism , Prostatic Neoplasms/mortality , Prostatic Neoplasms/pathology , RNA, Small Nucleolar/genetics , RNA, Small Nucleolar/metabolism , RNA, Transfer/genetics , RNA, Transfer/metabolism , ROC Curve , Real-Time Polymerase Chain Reaction
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