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前列腺癌中小非编码 RNA 转录组的诊断和预后特征。

Diagnostic and prognostic signatures from the small non-coding RNA transcriptome in prostate cancer.

机构信息

Department of Urology, Josephine Nefkens Institute, Erasmus MC, Rotterdam, The Netherlands.

出版信息

Oncogene. 2012 Feb 23;31(8):978-91. doi: 10.1038/onc.2011.304. Epub 2011 Jul 18.

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.

摘要

前列腺癌(PCa)是男性最常见的恶性肿瘤,也是西方国家癌症相关死亡的第二大主要原因。目前的临床和病理方法在预测术后结果方面存在局限性。越来越明显的是,小非编码 RNA(ncRNA)物种与这种恶性肿瘤的发生和发展有关。为了评估 PCa 中小 ncRNA 的多样性和丰度,我们通过 Illumina/Solexa 深度测序分析了整个小转录组的组成。我们进一步通过 miRNA 微阵列分析了 102 个新鲜冷冻患者样本中 miRNA 的表达特征。两个平台都通过定量逆转录-PCR 进行了交叉验证。除了几个 miRNA 的表达改变外,我们的深度测序分析还揭示了小核仁 RNA(snoRNA)和转移 RNA(tRNA)的强烈差异表达。通过微阵列分析,我们得出了一个 miRNA 诊断分类器,可以准确地区分正常和癌症样本。此外,我们还能够构建一个能够独立预测术后结果的 PCa 预后预测器。重要的是,预测器中包含的大多数 miRNA 也表现出高序列计数和在 Illumina PCa 样本中的一致差异表达,这得到了定量逆转录-PCR 的支持。我们的研究结果提供了 miRNA 表达特征,可作为 PCa 诊断和预后的准确工具。

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