The Analysis of Abnormal Gene Expression in Mammary Epithelium for Early Diagnosis of Breast Cancer / 天津医药

ABSTRACT

Objective To investigate the significance of abnormal gene in histologically normal mammary epithelial tissue for the early diagnosis of breast cancer. Methods Microarray technology was used to identify abnormal gene expres-sion and analyzed bioinformatics of normal mammary epithelial tissue in breast cancer patients and healthy normal control to establish a model for early diagnosis of breast cancer. The differentially expressed genes were screened by using signal path-way enrichment analysis. The accuracy (Ac), sensitivity (Sn) and specificity (Sp) were used to measure the prediction accura-cy of the different methods. Results The best prediction model was derived from the combination of differential genes en-riched from KEGG and BioCarta database. The number of differential expressed genes in three random created prediction models was reduced from 22 to 7, 14 to 3 and 18 to 4. However, the prediction accuracy was consistent with the model estab-lished from all of the differentially expressed genes, and the average accuracy of all models was 96.3%. Conclusion The prediction model can be simplified with the prediction accuracy unchanged, and thus facilitate the model apply to early diag-nosis and prevention of breast cancer.