基于通路的乳腺癌诊断表达谱。

Pathway-based expression profile for breast cancer diagnoses.

作者信息

Cava C, Bertoli G, Castiglioni I

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2014;2014:1151-4. doi: 10.1109/EMBC.2014.6943799.

DOI:10.1109/EMBC.2014.6943799

Abstract

Microarray experiments have made possible to identify breast cancer marker gene signatures. However, gene expression-based signatures present limitations because they do not consider metabolic role of the genes and are affected by genetic heterogeneity across patient cohorts. Considering the activity of entire pathways rather than the expression levels of individual genes can be a way to exceed these limits. We evaluated and compared five methods of pathway-level aggregation of gene expression data. Our results confirmed the important role of pathway expression profile in breast cancer diagnostic classification (accuracy >90%). However, although assessed on a limited number of samples and datasets, this study shows that using dissimilarity representation among patients does not improve the classification of pathway-based expression profiles.

摘要

微阵列实验使得识别乳腺癌标志物基因特征成为可能。然而，基于基因表达的特征存在局限性，因为它们没有考虑基因的代谢作用，并且受到不同患者队列间基因异质性的影响。考虑整个信号通路的活性而非单个基因的表达水平可能是一种突破这些限制的方法。我们评估并比较了五种基因表达数据通路水平汇总的方法。我们的结果证实了通路表达谱在乳腺癌诊断分类中的重要作用（准确率>90%）。然而，尽管本研究是在有限数量的样本和数据集上进行评估的，但结果表明，利用患者间的差异表示并不能改善基于通路的表达谱分类。