Jiang Dingfeng, Zhao Naiqing
Department of Biostatistics, School of Public Health, Fudan University, Shanghai, 200032, People's Republic of China.
J Cancer Res Clin Oncol. 2006 Sep;132(9):579-87. doi: 10.1007/s00432-006-0108-6. Epub 2006 Jun 8.
To set up a method by use of gene expression data to predict the prognosis of breast cancer patients on the basis of genes as few as possible, but maintaining the accuracy of prediction, we reanalyze the data from van't Veer et al. (Nature 415:530-536, 2002) and van de Vijver et al. (N Engl J Med 347:1999-2009, 2002).
A three-step method based on re-sampling strategy is employed to select the prognostic genes. And based on these genes, a predictive approach is established. Validation sets are used to testify the predictive power of the prognostic genes.
We have discovered 13 genes as the most informative ones to predict the clinical outcomes of breast cancer patients with lymph node-negative. The validation results show the robust performances of these genes. And the results of further analysis illustrate the significant association of the prediction to the time of metastases and overall survival.
Our predictive approach is useful in prognosis prediction for breast cancer patients with lymph node-negative. The gene markers provide valuable information for the progression of breast cancer and suggest potential target genes for treating the cancer.
为了建立一种利用基因表达数据来预测乳腺癌患者预后的方法,在尽可能少的基因基础上保持预测准确性,我们重新分析了范特·韦尔等人(《自然》415:530 - 536,2002年)以及范德·维杰弗等人(《新英格兰医学杂志》347:1999 - 2009,2002年)的数据。
采用基于重采样策略的三步法来选择预后基因。并基于这些基因建立一种预测方法。使用验证集来验证预后基因的预测能力。
我们发现了13个基因是预测淋巴结阴性乳腺癌患者临床结局最具信息价值的基因。验证结果显示了这些基因的稳健性能。进一步分析的结果表明该预测与转移时间和总生存期有显著关联。
我们的预测方法对于淋巴结阴性乳腺癌患者的预后预测是有用的。这些基因标志物为乳腺癌的进展提供了有价值的信息,并提示了治疗该癌症的潜在靶基因。