Molecular Biotechnology Center and Department of Genetics, Biology and Biochemistry, University of Turin, Turin, Italy.
PLoS One. 2011 Feb 28;6(2):e14737. doi: 10.1371/journal.pone.0014737.
The classification of breast cancer patients into risk groups provides a powerful tool for the identification of patients who will benefit from aggressive systemic therapy. The analysis of microarray data has generated several gene expression signatures that improve diagnosis and allow risk assessment. There is also evidence that cell proliferation-related genes have a high predictive power within these signatures.
We thus constructed a gene expression signature (the DM signature) using the human orthologues of 108 Drosophila melanogaster genes required for either the maintenance of chromosome integrity (36 genes) or mitotic division (72 genes).
The DM signature has minimal overlap with the extant signatures and is highly predictive of survival in 5 large breast cancer datasets. In addition, we show that the DM signature outperforms many widely used breast cancer signatures in predictive power, and performs comparably to other proliferation-based signatures. For most genes of the DM signature, an increased expression is negatively correlated with patient survival. The genes that provide the highest contribution to the predictive power of the DM signature are those involved in cytokinesis.
This finding highlights cytokinesis as an important marker in breast cancer prognosis and as a possible target for antimitotic therapies.
将乳腺癌患者分类为风险组为识别将从强化系统治疗中获益的患者提供了有力工具。微阵列数据分析生成了几种基因表达特征,可改善诊断并允许风险评估。还有证据表明,细胞增殖相关基因在这些特征中具有很高的预测能力。
因此,我们使用 108 个需要维持染色体完整性(36 个基因)或有丝分裂分裂(72 个基因)的黑腹果蝇(Drosophila melanogaster)的人类直系同源物构建了一个基因表达特征(DM 特征)。
DM 特征与现有特征的重叠最小,并且在 5 个大型乳腺癌数据集的生存预测中具有高度的预测性。此外,我们表明,DM 特征在预测能力方面优于许多广泛使用的乳腺癌特征,并且与其他基于增殖的特征相当。对于 DM 特征的大多数基因,表达增加与患者生存呈负相关。对 DM 特征预测能力贡献最大的基因是那些参与胞质分裂的基因。
这一发现强调了胞质分裂作为乳腺癌预后的一个重要标志物,并可能成为抗有丝分裂治疗的目标。