Let-7 Inverts the Chemoresistance of Breast Tumor-Initiating Cells.

Abstract

Abstract Background: Cancers may arise from rare self-renewing highly tumorigenic “stem” cells, which are thought not only to be the source of the tumor, but also to be responsible for resistance to cancer therapy and subsequent tumor recurrence. Our preliminary data strongly suggest that let-7 is a master regulator of BT-IC self-renewal and multipotency. It is likely that let-7 regulates many other genes/pathways during BT-IC differentiation. However, we do not know whether let-7 might also regulate other putative aspects of “stemness” such as chemoresistance.Material and Methods: Quantified qRT-PCR was used to test the expression of let-7a in chemoresistant breast tumor tissue from patients, as well as the chemosensitive samples. The location of let-7a in primary breast cancer samples from patients with chemoresistance were compared to the samples without chemoresistance by in situ hybridization analysis.SK-3rd Cells, which is a cell line enriched in breast tumor-initiating cells, were cultured in suspension to form mammosphere which could be induced to differentiation with adhesive culture. Lentivirus-mediated let-7a transduction was used to increase the expression level of let-7a.Let-7 target gene expression (HRAS and HMGA2) was determined by qRT-PCR and western blot. The response of BT-ICs to chemotherapy was determined by MTT, Annexin V and Tunel.Results: The expression level of let-7a microRNA in chemoresistant patients were significantly lower than the patients without chemoresistance (P<0.05). The let-7a mimics can effectively enhance the expression of let-7a in mammospheric SK-3rd cells, and reduced the expression level of H-RAS and HMGA2 proteins, which are the targets of let-7. Mammospheric SK-3rd cells tranfected with let-7a mimics had a lower proliferation rate and a higher apoptosis rate under epirubicin treatment.Conclusion: Lack of expression of let-7 regulates BT-IC resistance to chemotherapy. Therefore, let-7a may be an effective maker to predict the response of tumor to chemotherapy. Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 1136.