改进福尔马林固定石蜡包埋肿瘤样品基因表达谱的优化工作流程。

Marlene Thomas, Manuela Poignée-Heger, Martin Weisser, Stephanie Wessner, Anton Belousov
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引用次数: 18

摘要

背景:全基因组微阵列基因表达谱是发现人类癌症预后和预测性遗传标记的“金标准”。然而,由于大多数诊断样本都是用福尔马林固定石蜡包埋组织(FFPET)保存的,因此缺乏合适的研究材料。我们测试了一种新的工作流程和数据分析方法,该方法针对FFPET样品进行了优化。方法:将16例乳腺肿瘤标本分成配对对,分别采用FFPET或新鲜冷冻(FF)保存。提取总RNA并检测产量和纯度。使用三种不同的市售试剂盒对FFPET样品中的RNA进行平行扩增,并与Affymetrix GeneChip®Human Genome U133 Plus 2.0 Arrays杂交。对阵列探针集进行了优化,以排除设计不当和标注错误的探针。结果:与FF样品(假设值为100%)相比,使用WT-Ovation™FFPE System V2 (NuGEN)处理的FFPET样品具有80%的特异性和97%的灵敏度。此外,在硅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,否则可能被整个探针集背景稀释。结论:总的来说,我们的ffpet优化工作流程比以前的非优化方法能够检测到更多的基因,为mRNA生物标志物在人类疾病中的发现、验证和临床应用开辟了新的可能性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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

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

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

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

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.

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