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使用吸引子元基因和FGD3-SUSD3元基因的乳腺癌预后生物标志物。

Breast cancer prognostic biomarker using attractor metagenes and the FGD3-SUSD3 metagene.

作者信息

Ou Yang Tai-Hsien, Cheng Wei-Yi, Zheng Tian, Maurer Matthew A, Anastassiou Dimitris

机构信息

Department of Systems Biology, Columbia University, New York, New York. Department of Electrical Engineering, Columbia University, New York, New York.

Department of Statistics, Columbia University, New York, New York.

出版信息

Cancer Epidemiol Biomarkers Prev. 2014 Dec;23(12):2850-6. doi: 10.1158/1055-9965.EPI-14-0399. Epub 2014 Sep 23.

Abstract

BACKGROUND

The winning model of the Sage Bionetworks/DREAM Breast Cancer Prognosis Challenge made use of several molecular features, called attractor metagenes, as well as another metagene defined by the average expression level of the two genes FGD3 and SUSD3. This is a follow-up study toward developing a breast cancer prognostic test derived from and improving upon that model.

METHODS

We designed a feature selector facility calculating the prognostic scores of combinations of features, including those that we had used earlier, as well as those used in existing breast cancer biomarker assays, identifying the optimal selection of features for the test.

RESULTS

The resulting test, called BCAM (Breast Cancer Attractor Metagenes), is universally applicable to all clinical subtypes and stages of breast cancer and does not make any use of breast cancer molecular subtype or hormonal status information, none of which provided additional prognostic value. BCAM is composed of several molecular features: the breast cancer-specific FGD3-SUSD3 metagene, four attractor metagenes present in multiple cancer types (CIN, MES, LYM, and END), three additional individual genes (CD68, DNAJB9, and CXCL12), tumor size, and the number of positive lymph nodes.

CONCLUSIONS

Our analysis leads to the unexpected and remarkable suggestion that ER, PR, and HER2 status, or molecular subtype classification, do not provide additional prognostic value when the values of the FGD3-SUSD3 and attractor metagenes are taken into consideration.

IMPACT

Our results suggest that BCAM's prognostic predictions show potential to outperform those resulting from existing breast cancer biomarker assays.

摘要

背景

Sage生物网络公司/全球癌症基因组学与蛋白质组学联盟(DREAM)乳腺癌预后挑战赛的获胜模型利用了几种分子特征,即吸引子元基因,以及由FGD3和SUSD3这两个基因的平均表达水平定义的另一个元基因。这是一项后续研究,旨在开发一种源自该模型并对其进行改进的乳腺癌预后检测方法。

方法

我们设计了一种特征选择工具,用于计算特征组合的预后评分,包括我们之前使用过的特征以及现有乳腺癌生物标志物检测中使用的特征,从而确定该检测的最佳特征选择。

结果

由此产生的检测方法称为BCAM(乳腺癌吸引子元基因),它普遍适用于乳腺癌的所有临床亚型和阶段,并且不使用任何乳腺癌分子亚型或激素状态信息,这些信息均未提供额外的预后价值。BCAM由几种分子特征组成:乳腺癌特异性的FGD3 - SUSD3元基因、多种癌症类型中存在的四个吸引子元基因(CIN、MES、LYM和END)、另外三个单独的基因(CD68、DNAJB9和CXCL12)、肿瘤大小以及阳性淋巴结数量。

结论

我们的分析得出了一个意外而显著的结论,即在考虑FGD3 - SUSD3和吸引子元基因的值时,雌激素受体(ER)、孕激素受体(PR)和人表皮生长因子受体2(HER2)状态或分子亚型分类并不能提供额外的预后价值。

影响

我们的结果表明,BCAM的预后预测有可能优于现有乳腺癌生物标志物检测的结果。

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