Identification Of Novel Breast Cancer Genes Based On Gene Expression Profiles And PPI Data

Breast cancer,one of the most common malignancies,is a threat to female health all over the world.However,the molecular mechanism of breast cancer has not been fully discovered yet.Triple-negative breast cancers comprise a very heterogeneous group of cancers difficult to treat.It is crucial to identify breast cancer-related genes,which could provide new biomarkers for breast cancer diagnosis as well as potential treatment targets.Here we used the mRMR(minimum redundancy-maximum relevance)method to select significant genes,and then mapped the tra nscripts of the genes on the protein-protein interaction network and traced the shortest path between each pair of two proteins.As a result,we identified 19 breast cancer-related genes whose betweenness were over 700.It is indicated by GO(Gene Ontology)enrichment analysis that transcription and oxygen level are very important in breast cancer.And it is indicated by pathway analysis that most of such 24 genes are enriched in prostate cancer,endocrine resistance,and pathways in cancer.It is anticipated that such 19 genes might be useful for diagnosis,prognosis and treatment for breast cancer.Besides,in this study,we also do the same pipeline for Triple-negative breast cancers.And we selected the same genes between breast cancer candidate genes and Triple-negative breast cancers candidate genes.In order to ensure the validity and precision of our results,we selected 248 proteins in PPI(protein-protein interaction)network randomly for shortest path tracing and repeated the procedure for 100 times.Then we picked up the same genes of these 100 results and remove them from our results.Finally,54 genes for Triple-negative breast cancers were selected as significant genes.This study proves the effectiveness of our methods,and provides some new ideas for the future research and diagnosis of breast cancer and triple negative breast cancer.