Perturbation of HSP Network in MCF-7 Breast Cancer Cell Line Triggers Inducible HSP70 Expression and Leads to Tumor Suppression

Background: Heat shock protein 70 (HSP70) is constitutively expressed in normal cells but aberrantly expressed in several types of tumor cells, helping their survival in extreme conditions. Thus, specific inhibition of HSP70 in tumor cells is a promising strategy in the treatment of cancer. HSP70 has a variety of isoforms in the cellular organelles and form different functions by coordinating and cooperating with cochaperones. Cancer cells overexpress HSPs during cell growth and proliferation and HSP network provides resistance against apoptosis. The present study aimed to evaluate quantitative changes in HSPs- and cancerassociated gene expressions and their interactions in the presence of 2-phenylethyenesulfonamide (PES) in MCF-7 cells. Methods: Antiproliferative activity of PES was evaluated using the XTT assay. Inducible HSP70 (HSP70i) levels in the PES-treated cells were determined using the ELISA kit. PCR Array was performed to assess the HSPs- and cancer-pathway focused gene expression profiling. Gene network analysis was performed using the X2K, yEd (V.3.18.1) programs, and web-based gene list enrichment analysis tool Enrichr. Results: The results demonstrated that PES exposure increased the amount of both HSP70i gene and protein expression surprisingly. However, the expression of HSP70 isoforms as well as other co-chaperones, and 17 cancer-associated genes decreased remarkably as expected. Additionally, interaction network analysis revealed a different mechanism; PES induction of HSP70i employs a cell cycle negative regulator, RB1, which is a tumor suppressor gene. Conclusion: PES treatment inhibited MCF-7 cell proliferation and changed several HSPs- and cancer-related gene expressions along with their interactions through a unique mechanism although it causes an interesting increase at HSP70i gene and protein expressions. RB1 gene expression may play an important role in this effect as revealed by the interaction network analysis.