Breast cancer is a heterogeneous disease that is ranked as one of the most common cancers worldwide. Currently, although there are existing molecules such as progesterone receptor and estrogen receptor for breast cancer treatment, discovering more effective drug targets is still in urgent need. In this study, we have obtained six sequencing datasets of breast cancer from GEO database and identified a set of differentially expressed molecules, including 67 miRNAs and 133 genes. Function enrichment analysis by miRPathDB database indicated that targets of 11 miRNAs could be enriched in breast cancer pathway with a p-value ≤ .05. A special miRNA-gene interaction network was constructed for analysis of the progression of breast cancer. We then ranked the importance of each molecule (i.e. miRNA and gene) by their node centrality indexes in the network and selected the top 10% of molecules. The statistical analysis of these molecules showed three miRNAs (hsa-miR-1275, hsa-miR-2392, hsa-miR-3141) have significant effects on the prognosis and survival of patients. By searching for potential drugs in Drugbank database, we have identified four candidates (phenethyl isothiocyanate, amuvatinib, theophylline, trifluridine) for targeting these genes. In conclusion, we believe that these drugs and their analogs could be used in the targeted therapy of breast cancer in the future.
Read full abstract