Background: Paclitaxel is widely used as an adjuvant therapy in the treatment of breast cancer, yet its effectiveness decreases due to resistance problems. We conducted the present study to identify the potential paclitaxel resistance biomarkers and therapeutic targets in breast cancer employing bioinformatics approach.
Methods: The present systematic bioinformatic study included a microarray data obtained from Gene Expression Omnibus database, which are respectively cell lines and tumor data from patients. We carried out Gene ontology, Kyoto Encyclopedia Genes, and Genome pathway enrichment analysis with The Database for Annotation, Visualization and Integrated. The protein-protein interaction network was analyzed with STRING-DB and visualized with Cytoscape. We confirmed of the reliability of the hub genes in paclitaxel sensitive and resistant breast cancer cells utilizing ONCOMINE. The prognostic value of the hub genes was evaluated using Kaplan-Meier survival curves.
Results: Gene ontology analysis revealed that differential expressed genes take part in cell adhesion, located in cellular component, and paly a negative role in the regulation of reactive oxygen species. The protein-protein interaction network analysis, confirmed with ONCOMINE and Kaplan Meier survival, revealed three hub genes (TIMP1, HK2 and IGFBP7). Kyoto Encyclopedia Genes and Genome pathway enrichment analysis revealed the regulation of HIF-1 signaling pathway. Kaplan Meier survival plot showed that patients with high mRNA of TIMP1, HK2, and IGFBP7 had significantly worse overall survival than those in the low expression level group.
Conclusion: TIMP1, HK2, and IGFBP7 are not only biomarkers, but also potential targets to circumvent paclitaxel resistance in breast cancer.