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剪接体分析工具(SplicerAV):一种挖掘微阵列表达数据中 RNA 处理变化的工具。

SplicerAV: a tool for mining microarray expression data for changes in RNA processing.

机构信息

Molecular Cancer Biology Program, Duke University Medical Center, Durham, USA.

出版信息

BMC Bioinformatics. 2010 Feb 25;11:108. doi: 10.1186/1471-2105-11-108.

Abstract

BACKGROUND

Over the past two decades more than fifty thousand unique clinical and biological samples have been assayed using the Affymetrix HG-U133 and HG-U95 GeneChip microarray platforms. This substantial repository has been used extensively to characterize changes in gene expression between biological samples, but has not been previously mined en masse for changes in mRNA processing. We explored the possibility of using HG-U133 microarray data to identify changes in alternative mRNA processing in several available archival datasets.

RESULTS

Data from these and other gene expression microarrays can now be mined for changes in transcript isoform abundance using a program described here, SplicerAV. Using in vivo and in vitro breast cancer microarray datasets, SplicerAV was able to perform both gene and isoform specific expression profiling within the same microarray dataset. Our reanalysis of Affymetrix U133 plus 2.0 data generated by in vitro over-expression of HRAS, E2F3, beta-catenin (CTNNB1), SRC, and MYC identified several hundred oncogene-induced mRNA isoform changes, one of which recognized a previously unknown mechanism of EGFR family activation. Using clinical data, SplicerAV predicted 241 isoform changes between low and high grade breast tumors; with changes enriched among genes coding for guanyl-nucleotide exchange factors, metalloprotease inhibitors, and mRNA processing factors. Isoform changes in 15 genes were associated with aggressive cancer across the three breast cancer datasets.

CONCLUSIONS

Using SplicerAV, we identified several hundred previously uncharacterized isoform changes induced by in vitro oncogene over-expression and revealed a previously unknown mechanism of EGFR activation in human mammary epithelial cells. We analyzed Affymetrix GeneChip data from over 400 human breast tumors in three independent studies, making this the largest clinical dataset analyzed for en masse changes in alternative mRNA processing. The capacity to detect RNA isoform changes in archival microarray data using SplicerAV allowed us to carry out the first analysis of isoform specific mRNA changes directly associated with cancer survival.

摘要

背景

在过去的二十年中,已经使用 Affymetrix HG-U133 和 HG-U95 GeneChip 微阵列平台对超过 50000 个独特的临床和生物学样本进行了分析。这个庞大的存储库被广泛用于描述生物样本之间基因表达的变化,但以前没有大规模地挖掘 mRNA 加工变化。我们探索了使用 HG-U133 微阵列数据识别几种可用存档数据集中的替代 mRNA 加工变化的可能性。

结果

现在可以使用这里描述的程序 SplicerAV 从这些和其他基因表达微阵列数据中挖掘转录本异构体丰度变化。使用体内和体外乳腺癌微阵列数据集,SplicerAV 能够在同一微阵列数据集中执行基因和异构体特异性表达分析。我们对 Affymetrix U133 plus 2.0 数据的重新分析,这些数据是通过体外过表达 HRAS、E2F3、β-连环蛋白(CTNNB1)、SRC 和 MYC 生成的,确定了数百个癌基因诱导的 mRNA 异构体变化,其中之一识别了一种以前未知的 EGFR 家族激活机制。使用临床数据,SplicerAV 在低级别和高级别乳腺癌之间预测了 241 个异构体变化;这些变化在编码鸟苷酸交换因子、金属蛋白酶抑制剂和 mRNA 加工因子的基因中富集。在三个乳腺癌数据集中,15 个基因的异构体变化与侵袭性癌症相关。

结论

使用 SplicerAV,我们确定了数百种以前未被描述的由体外癌基因过表达诱导的异构体变化,并揭示了人类乳腺上皮细胞中 EGFR 激活的一种以前未知的机制。我们分析了三个独立研究中超过 400 个人类乳腺癌肿瘤的 Affymetrix GeneChip 数据,这是对大规模替代 mRNA 加工变化进行的最大规模的临床数据集分析。使用 SplicerAV 在存档微阵列数据中检测 RNA 异构体变化的能力使我们能够直接分析与癌症生存相关的异构体特异性 mRNA 变化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/78a9/2838864/8eecb3e46f14/1471-2105-11-108-1.jpg

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