Suppr超能文献

一种用于优化福尔马林固定石蜡包埋肿瘤样本基因表达谱分析的工作流程。

An optimized workflow for improved gene expression profiling for formalin-fixed, paraffin-embedded tumor samples.

作者信息

Thomas Marlene, Poignée-Heger Manuela, Weisser Martin, Wessner Stephanie, Belousov Anton

机构信息

Pharma Research and Early Development (pRED), Roche Diagnostics GmbH, TR-H, Bldg 231/206a, Nonnenwald 2, 82377 Penzberg, Germany.

出版信息

J Clin Bioinforma. 2013 May 3;3(1):10. doi: 10.1186/2043-9113-3-10.

Abstract

BACKGROUND

Whole genome microarray gene expression profiling is the 'gold standard' for the discovery of prognostic and predictive genetic markers for human cancers. However, suitable research material is lacking as most diagnostic samples are preserved as formalin-fixed, paraffin-embedded tissue (FFPET). We tested a new workflow and data analysis method optimized for use with FFPET samples.

METHODS

Sixteen breast tumor samples were split into matched pairs and preserved as FFPET or fresh-frozen (FF). Total RNA was extracted and tested for yield and purity. RNA from FFPET samples was amplified using three different commercially available kits in parallel, and hybridized to Affymetrix GeneChip® Human Genome U133 Plus 2.0 Arrays. The array probe set was optimized in silico to exclude misdesigned and misannotated probes.

RESULTS

FFPET samples processed using the WT-Ovation™ FFPE System V2 (NuGEN) provided 80% specificity and 97% sensitivity compared with FF samples (assuming values of 100%). In addition, in silico probe set redesign improved sequence detection sensitivity and, thus, may rescue potentially significant small-magnitude gene expression changes that could otherwise be diluted by the overall probe set background.

CONCLUSION

In conclusion, our FFPET-optimized workflow enables the detection of more genes than previous, nonoptimized approaches, opening new possibilities for the discovery, validation, and clinical application of mRNA biomarkers in human diseases.

摘要

背景

全基因组微阵列基因表达谱分析是发现人类癌症预后和预测性遗传标志物的“金标准”。然而,由于大多数诊断样本都保存为福尔马林固定石蜡包埋组织(FFPET),缺乏合适的研究材料。我们测试了一种针对FFPET样本优化的新工作流程和数据分析方法。

方法

将16个乳腺肿瘤样本分成匹配对,分别保存为FFPET或新鲜冷冻(FF)样本。提取总RNA并检测其产量和纯度。来自FFPET样本的RNA使用三种不同的市售试剂盒进行平行扩增,并与Affymetrix GeneChip®人类基因组U133 Plus 2.0阵列杂交。在计算机上对阵列探针集进行优化,以排除设计错误和注释错误的探针。

结果

与FF样本(假设值为100%)相比,使用WT-Ovation™ FFPE System V2(NuGEN)处理的FFPET样本具有80%的特异性和97%的灵敏度。此外,计算机辅助探针集重新设计提高了序列检测灵敏度,因此可能挽救潜在的显著小幅度基因表达变化,否则这些变化可能会被整个探针集背景所稀释。

结论

总之,我们针对FFPET优化的工作流程能够比以前的非优化方法检测到更多基因,为人类疾病中mRNA生物标志物的发现、验证和临床应用开辟了新的可能性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/64d5/3660273/aef4350f62e3/2043-9113-3-10-1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验