Centre for Cancer Research, Monash Institute of Medical Research, Monash University, Clayton, Victoria 3168, Australia.
RNA. 2013 Jul;19(7):876-88. doi: 10.1261/rna.035055.112. Epub 2013 May 24.
Recent studies have established that mutations or deletions in microRNA (miRNA) processing enzymes resulting in a global decrease of miRNA expression are frequent across cancers and can be associated with a poorer prognosis. While very popular in miRNA profiling studies, it remains unclear whether miRNA microarrays are suited or not to accurately detecting global miRNA decreases seen in cancers. In this work, we analyzed the miRNA profiles of samples with global miRNA decreases using Affymetrix miRNA microarrays following the inducible genetic deletion of Dicer1. Surprisingly, up to a third of deregulated miRNAs identified upon Dicer1 depletion were found to be up-regulated following standard robust multichip average (RMA) background correction and quantile normalization, indicative of normalization bias. Our comparisons of five preprocess steps performed at the probe level demonstrated that the use of cyclic loess relying on non-miRNA small RNAs present on the Affymetrix platform significantly improved specificity and sensitivity of detection of decreased miRNAs. These findings were validated in samples from patients with prostate cancer, where conjugation of robust normal-exponential background correction with cyclic loess normalization and array weights correctly identified the greatest number of decreased miRNAs, and the lowest amount of false-positive up-regulated miRNAs. These findings highlight the importance of miRNA microarray normalization for the detection of miRNAs that are truly differentially expressed and suggest that the use of cyclic loess based on non-miRNA small RNAs can help to improve the sensitivity and specificity of miRNA profiling in cancer samples with global miRNA decrease.
最近的研究已经证实,miRNA(微小 RNA)加工酶的突变或缺失导致 miRNA 表达的全面下降在癌症中很常见,并且可能与预后不良有关。虽然在 miRNA 分析研究中非常流行,但 miRNA 微阵列是否适合准确检测癌症中所见的全局 miRNA 降低仍不清楚。在这项工作中,我们使用 Affymetrix miRNA 微阵列分析了使用诱导性遗传缺失 Dicer1 导致全局 miRNA 降低的样本的 miRNA 图谱。令人惊讶的是,在 Dicer1 耗尽后鉴定出的多达三分之一的失调 miRNA 在经过标准稳健多重芯片平均(RMA)背景校正和分位数归一化后被发现上调,这表明存在归一化偏差。我们在探针水平上比较了五种预处理步骤,发现使用基于 Affymetrix 平台上存在的非 miRNA 小 RNA 的循环局部最小二乘法可以显著提高检测降低的 miRNA 的特异性和灵敏度。这些发现在来自前列腺癌患者的样本中得到了验证,其中稳健正态指数背景校正与循环局部最小二乘法归一化和阵列权重的结合正确地鉴定出了最多数量的降低的 miRNA,以及最少数量的假阳性上调的 miRNA。这些发现强调了 miRNA 微阵列归一化对于检测真正差异表达的 miRNA 的重要性,并表明使用基于非 miRNA 小 RNA 的循环局部最小二乘法可以帮助提高具有全局 miRNA 降低的癌症样本中 miRNA 分析的灵敏度和特异性。