Computer Science Department, Technion - Israel Institute of Technology, Haifa, Israel.
Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway.
PLoS One. 2021 Jan 12;16(1):e0245215. doi: 10.1371/journal.pone.0245215. eCollection 2021.
The patient's immune system plays an important role in cancer pathogenesis, prognosis and susceptibility to treatment. Recent work introduced an immune related breast cancer. This subtyping is based on the expression profiles of the tumor samples. Specifically, one study showed that analyzing 658 genes can lead to a signature for subtyping tumors. Furthermore, this classification is independent of other known molecular and clinical breast cancer subtyping. Finally, that study shows that the suggested subtyping has significant prognostic implications.
In this work we develop an efficient signature associated with survival in breast cancer. We begin by developing a more efficient signature for the above-mentioned breast cancer immune-based subtyping. This signature represents better performance with a set of 579 genes that obtains an improved Area Under Curve (AUC). We then determine a set of 193 genes and an associated classification rule that yield subtypes with a much stronger statistically significant (log rank p-value < 2 × 10-4 in a test cohort) difference in survival. To obtain these improved results we develop a feature selection process that matches the high-dimensionality character of the data and the dual performance objectives, driven by survival and anchored by the literature subtyping.
患者的免疫系统在癌症的发病机制、预后和对治疗的敏感性方面起着重要作用。最近的研究引入了一种免疫相关的乳腺癌。这种分型是基于肿瘤样本的表达谱。具体来说，一项研究表明，分析 658 个基因可以为肿瘤分型生成一个特征。此外，这种分类独立于其他已知的分子和临床乳腺癌分型。最后，该研究表明，所建议的分型具有显著的预后意义。
在这项工作中，我们开发了一种与乳腺癌生存相关的有效特征。我们首先为上述基于乳腺癌免疫的分型开发了一种更有效的特征。这个特征代表了更好的性能，使用了一组 579 个基因，获得了改进的曲线下面积（AUC）。然后，我们确定了一组 193 个基因和一个相关的分类规则，这些规则产生的亚型在生存方面有更强的统计学显著差异（对数秩检验 p 值 < 2×10-4 在测试队列中）。为了获得这些改进的结果，我们开发了一个特征选择过程，该过程匹配数据的高维特征和由生存和文献分型驱动的双重性能目标。
