Division of Bioinformatics, Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC 3052, Australia.
School of Mathematics and Statistics, Faculty of Science, University of Melbourne, Parkville, VIC 3010, Australia.
Nucleic Acids Res. 2020 Nov 4;48(19):e113. doi: 10.1093/nar/gkaa802.
Gene expression signatures have been critical in defining the molecular phenotypes of cells, tissues, and patient samples. Their most notable and widespread clinical application is stratification of breast cancer patients into molecular (PAM50) subtypes. The cost and relatively large amounts of fresh starting material required for whole-transcriptome sequencing has limited clinical application of thousands of existing gene signatures captured in repositories such as the Molecular Signature Database. We identified genes with stable expression across a range of abundances, and with a preserved relative ordering across thousands of samples, allowing signature scoring and supporting general data normalisation for transcriptomic data. Our new method, stingscore, quantifies and summarises relative expression levels of signature genes from individual samples through the inclusion of these 'stably-expressed genes'. We show that our list of stable genes has better stability across cancer and normal tissue data than previously proposed gene sets. Additionally, we show that signature scores computed from targeted transcript measurements using stingscore can predict docetaxel response in breast cancer patients. This new approach to gene expression signature analysis will facilitate the development of panel-type tests for gene expression signatures, thus supporting clinical translation of the powerful insights gained from cancer transcriptomic studies.
基因表达谱在定义细胞、组织和患者样本的分子表型方面发挥了关键作用。它们最显著和广泛的临床应用是将乳腺癌患者分为分子（PAM50）亚型。全转录组测序所需的成本和相对大量的新鲜起始材料限制了数千个现有基因标记在储存库（如分子特征数据库）中的临床应用。我们鉴定了在一系列丰度范围内具有稳定表达的基因，并且在数千个样本中具有保留的相对排序，从而可以对标记进行评分，并支持转录组数据的一般数据归一化。我们的新方法 stingscore 通过包含这些“稳定表达的基因”来量化和总结来自单个样本的标记基因的相对表达水平。我们表明，与以前提出的基因集相比，我们的稳定基因列表在癌症和正常组织数据中的稳定性更好。此外，我们表明，使用 stingscore 从靶向转录测量计算得出的标记评分可以预测乳腺癌患者对多西紫杉醇的反应。这种新的基因表达谱分析方法将促进用于基因表达谱的面板型测试的开发，从而支持从癌症转录组研究中获得的强大见解的临床转化。
