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Updated: Aug 19, 2026
Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
A clinical prognostic prediction of lymph node-negative breast cancer by gene expression profiles
1Department of Biostatistics, School of Public Health, Fudan University, Shanghai, 200032, People's Republic of China.
Purpose:
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).
Methods:
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.
Results:
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.
Conclusion:
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.
