The Efficacy of Etanercept As Anti-Breast Cancer Treatment Is Attenuated by Residing Macrophages Publisher Pubmed



Shirmohammadi E¹ ; Ebrahimi SES¹ ; Farshchi A² ; Salimi M³ Show Affiliations
Source: BMC Cancer Published:2020

Abstract

Background: Interaction between microenvironment and breast cancer cells often is not considered at the early stages of drug development leading to failure of many drugs at later clinical stages. Etanercept is a TNF-alpha inhibitor that has been investigated for potential antitumor effect in breast cancer with conflicting results. Methods: Secretome data on MDA-MB-231 cancer cell-line were from public repositories and subjected to gene enrichment analyses. Since MDA-MB-231 cells secrete high levels of Granulocyte-Monocyte Colony Stimulating Factor, which activates macrophages to promote tumor growth, the effect of macrophage co-culturing on anticancer efficacy of Etanercept in breast cancer was evaluated using the Boolean network modeling and in vitro experiments including invasion, cell cycle, Annexin PI, and tetrazolium based viability assays and NFKB activity. Results: The secretome profile of MDA-MB-231 cells was similar to the expression of genes following treatment of breast cancer cells with TNF-α. Accordingly, inhibition of TNF-α by Etanercept decreased MDA-MB-231 cell survival, induced apoptosis and cell cycle arrest in vitro and inhibited NFKB activation. The inhibitory effect of Etanercept on cell viability, cell cycle progression, invasion and induction of apoptosis decreased following co-culturing of the cancer cells with macrophages. The Boolean network modeling of the changes in the dynamics of intracellular signaling pathways revealed NFKB activation by secretome of macrophages, leading to a decreased efficacy of Etanercept, suggesting NFKB inhibition as an alternative approach to inhibit cancer cell growth in the presence of macrophage crosstalk. Conclusion: This study indicates that the effect of Etanercept may be influenced by residing macrophages in tumor microenvironment, and suggests a method to predict the effect of drugs in the presence of stromal cells to guide experimental designs in drug development. © 2020 The Author(s).