Radioresistant triple-negative breast cancer cells release β-catenin containing extracellular vesicles to promote cancer stem cell activity of bystanders.

Abstract

Background: Triple-negative breast cancer (TNBC) frequently develops radioresistance, yet the mechanisms remain incompletely elucidated. This study is the first to investigate how β-catenin, transported by extracellular vesicles (EVs) from radioresistant TNBC cells, promotes radioresistance and enhances cancer stem cell (CSC) activity in recipient TNBC cells, offering a novel mechanism distinct from prior EV-related findings in other cancers. Methods and Results: A radioresistant cell line (231-RR) was developed from MDA-MB-231 cells, and EVs were isolated for characterization. EVs from 231-RR cells decreased radiosensitivity in parental MDA-MB-231 and two other TNBC cell lines (MDA-MB-468 and Hs578T), as shown by clonogenic assay. These EVs also enhanced CSC activity in MDA-MB-231 and Hs578T cells, demonstrated through primary and secondary mammosphere formation. The effects were nullified when using EVs from 231-RR cells treated with the EV secretion inhibitor GW4869. 231-RR-derived EVs showed elevated β-catenin levels and increased active β-catenin and stemness proteins (c-Myc, OCT4, SOX2) in recipient TNBC cells. The β-catenin inhibitor CCT-031374 prevented EV-mediated enhancement of radioresistance and CSC activity. Public data analysis from breast cancer patients revealed post-radiotherapy upregulation of the β-catenin pathway, with elevated CTNNB1, MYC, and CD44 expression, alongside reduced CDKN2A and CDH1 levels, supporting clinical relevance. Conclusions: This study uniquely demonstrates that EVs from radioresistant TNBC cells transfer β-catenin to confer radioresistance and enhance CSC activity in recipient cells, a mechanism not previously reported in TNBC. These findings suggest the potential of EV-β-catenin derived as a novel biomarker for predicting radiotherapy outcomes and recurrence risk in TNBC patients, pending development of sensitive detection methods.