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乳腺癌预后基因表达特征缺乏合理的生物学意义。

Prognostic gene expression signatures of breast cancer are lacking a sensible biological meaning.

机构信息

Predictive Society and Data Analytics Lab, Tampere University, Tampere, Korkeakoulunkatu 10, 33720, Tampere, Finland.

Computational Systems Biology, Tampere University, Tampere, Korkeakoulunkatu 10, 33720, Tampere, Finland.

出版信息

Sci Rep. 2021 Jan 8;11(1):156. doi: 10.1038/s41598-020-79375-y.

Abstract

The identification of prognostic biomarkers for predicting cancer progression is an important problem for two reasons. First, such biomarkers find practical application in a clinical context for the treatment of patients. Second, interrogation of the biomarkers themselves is assumed to lead to novel insights of disease mechanisms and the underlying molecular processes that cause the pathological behavior. For breast cancer, many signatures based on gene expression values have been reported to be associated with overall survival. Consequently, such signatures have been used for suggesting biological explanations of breast cancer and drug mechanisms. In this paper, we demonstrate for a large number of breast cancer signatures that such an implication is not justified. Our approach eliminates systematically all traces of biological meaning of signature genes and shows that among the remaining genes, surrogate gene sets can be formed with indistinguishable prognostic prediction capabilities and opposite biological meaning. Hence, our results demonstrate that none of the studied signatures has a sensible biological interpretation or meaning with respect to disease etiology. Overall, this shows that prognostic signatures are black-box models with sensible predictions of breast cancer outcome but no value for revealing causal connections. Furthermore, we show that the number of such surrogate gene sets is not small but very large.

摘要

识别预测癌症进展的预后生物标志物是一个重要的问题,原因有二。首先,此类生物标志物在临床环境中对患者的治疗具有实际应用价值。其次,对生物标志物本身的研究被认为可以深入了解疾病的机制以及导致病理行为的潜在分子过程。对于乳腺癌,已有许多基于基因表达值的特征被报道与总生存期相关。因此,这些特征已被用于提出对乳腺癌和药物机制的生物学解释。在本文中,我们针对大量乳腺癌特征表明,这种推断是没有根据的。我们的方法系统地消除了特征基因所有生物学意义的痕迹,并表明在剩余的基因中,可以形成具有可区分的预后预测能力和相反生物学意义的替代基因集。因此,我们的结果表明,在所研究的特征中,没有一个具有关于疾病病因的合理生物学解释或意义。总体而言,这表明预后特征是具有合理乳腺癌预后预测能力的黑箱模型,但对于揭示因果关系没有价值。此外,我们还表明,这种替代基因集的数量不是很小,而是非常大。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9ef2/7794581/e204e94ff417/41598_2020_79375_Fig1_HTML.jpg

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