Identification of Novel Breast Cancer Genes based on Gene Expression Profiles and PPI Data

Background: Breast cancer is one of the most common malignancies, and a threat to female health all over the world. However, the molecular mechanism of breast cancer has not been fully discovered yet. Objective: It is crucial to identify breast cancer-related genes, which could provide new biomarker for breast cancer diagnosis as well as potential treatment targets. Methods: Here we used the minimum redundancy-maximum relevance (mRMR) method to select significant genes, then mapped the transcripts of the genes on the Protein-Protein Interaction (PPI) network and traced the shortest path between each pair of two proteins. Results: As a result, we identified 24 breast cancer-related genes whose betweenness were over 700. The GO enrichment analysis indicated that the transcription and oxygen level are very important in breast cancer. And the pathway analysis indicated that most of these 24 genes are enriched in prostate cancer, endocrine resistance, and pathways in cancer. Conclusion: We hope these 24 genes might be useful for diagnosis, prognosis and treatment for breast cancer.