Lauss Martin, Kriegner Albert, Vierlinger Klemens, Visne Ilhami, Yildiz Ahmet, Dilaveroglu Erkan, Noehammer Christa
Austrian Research Centers GmbH, Molecular Diagnostics, Seibersdorf, Austria.
Breast Cancer Res Treat. 2008 Jul;110(2):235-44. doi: 10.1007/s10549-007-9716-3. Epub 2007 Sep 26.
Extensive efforts have been undertaken to discover genes relevant for breast cancer prognosis. Yet, in current opinion, with little overlap in findings. We aimed to reanalyze molecular prediction of breast cancer recurrence.
From 44 published gene lists relevant for breast cancer prognosis, we extracted 374 genes, which, besides other quality criteria, are recorded at least twice. From eight published microarray datasets, a single dataset of 1,067 breast cancer patients was created, using transformation to 'probability of expression' scale. For recurrence analysis, the Cox proportional hazards model was applied.
The 374 genes, termed '374 Gene Set', are highly enriched in cell cycle genes. The '374 Gene Set' is significantly associated with breast cancer recurrence (p = 2 x 10(-12), log-rank test) in the meta set of 1,067 patients, showing an estimated Hazard Ratio of recurrence for the 'poor' prognosis group compared to the 'good' prognosis group of 2.03 (95% confidence interval, 1.66-2.48). Notably, the '374 Gene Set' is significantly associated with recurrence in untreated patients. In multivariate analysis, including the standard histopathological parameters, only tumor size and the '374 Gene Set' remain independent predictors of recurrence. External validation further confirmed the prognostic relevance of the gene set (253 patients, p = 0.001, log-rank test).
The '374 Gene Set' comprises a molecular basis of metastatic breast cancer progression. Starting from this gene set it might be possible to construct a clinically relevant classifier, which then again needs to be validated.
人们已经付出了巨大努力来发现与乳腺癌预后相关的基因。然而，目前看来，研究结果之间几乎没有重叠。我们旨在重新分析乳腺癌复发的分子预测。
从44个已发表的与乳腺癌预后相关的基因列表中，我们提取了374个基因，这些基因除了其他质量标准外，至少被记录了两次。从八个已发表的微阵列数据集中，通过转换为“表达概率”量表，创建了一个包含1067名乳腺癌患者的单一数据集。对于复发分析，应用了Cox比例风险模型。
这374个基因，称为“374基因集”，在细胞周期基因中高度富集。在1067名患者的元数据集中，“374基因集”与乳腺癌复发显著相关（p = 2×10⁻¹²，对数秩检验），显示“预后不良”组与“预后良好”组相比，复发的估计风险比为2.03（95%置信区间，1.66 - 2.48）。值得注意的是，“374基因集”与未治疗患者的复发显著相关。在多变量分析中，包括标准组织病理学参数，只有肿瘤大小和“374基因集”仍然是复发的独立预测因素。外部验证进一步证实了该基因集的预后相关性（253名患者，p = 0.001，对数秩检验）。
“374基因集”构成了转移性乳腺癌进展的分子基础。从这个基因集出发，有可能构建一个临床相关的分类器，然后再次需要进行验证。
