A cell proliferation signature is a marker of extremely poor outcome in a subpopulation of breast cancer patients
A cell proliferation signature is a marker of extremely poor outcome in a subpopulation of breast cancer patients
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DOI：
10.1158/0008-5472.can-04-3953
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发表时间：
2005-05-15
期刊：
影响因子：
11.2
通讯作者：
Friend, S
中科院分区：
文献类型：
--
作者：
Dai, HY;van't Veer, L;Friend, S
乳腺癌由一组不同的亚型组成，尽管它们具有相似的组织学外观，但具有非常不同的转移潜力。鉴于大量女性被诊断患有乳腺癌，即使对于一小部分患者而言，能够识别生物驱动力也至关重要。在这里，我们发现，在以相对于其年龄而言雌激素受体表达相对较高的患者子集中，几乎完全由细胞周期基因组成的同质基因表达模式强烈预测了转移的发生（转移的5年比值比，24.0；95%置信区间，6.0-95.5）。这组基因的过度表达显然与极差的结果相关，贫困组的 10 年无转移概率仅为 24%，而良好组的 10 年无转移概率为 85%。相比之下，这种基因表达模式与其他患者亚群的结果相关性要小得多。这里描述的方法还说明了结合临床变量、生物学洞察力和机器学习来剖析生物复杂性的价值。我们在这里介绍的工作可能会为合理设计个性化治疗迈出关键一步。
Breast cancer comprises a group of distinct subtypes that despite having similar histologic appearances, have very different metastatic potentials. Being able to identify the biological driving force, even for a subset of patients, is crucially important given the large population of women diagnosed with breast cancer. Here, we show that within a subset of patients characterized by relatively high estrogen receptor expression for their age, the occurrence of metastases is strongly predicted by a homogeneous gene expression pattern almost entirely consisting of cell cycle genes (5-year odds ratio of metastasis, 24.0; 95% confidence interval, 6.0-95.5). Overexpression of this set of genes is clearly associated with an extremely poor outcome, with the 10-year metastasis-free probability being only 24% for the poor group, compared with 85% for the good group. In contrast, this gene expression pattern is much less correlated with the outcome in other patient subpopulations. The methods described here also illustrate the value of combining clinical variables, biological insight, and machine-learning to dissect biological complexity. Our work presented here may contribute a crucial step towards rational design of personalized treatment.