Adipose MSCs Suppress MCF7 and MDA-MB-231 Breast Cancer Metastasis and EMT Pathways Leading to Dormancy via Exosomal-miRNAs Following Co-Culture Interaction

脂肪 MSCs 抑制 MCF7 和 MDA-MB-231 乳腺癌转移和 EMT 通路,通过共培养相互作用后外泌体-miRNA 导致细胞休眠

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作者:Norlaily Mohd Ali, Swee Keong Yeap, Wan Yong Ho, Lily Boo, Huynh Ky, Dilan Amila Satharasinghe, Sheau Wei Tan, Soon Keng Cheong, Hsien Da Huang, Kuan Chun Lan, Men Yee Chiew, Han Kiat Ong

Abstract

Globally, breast cancer is the most frequently diagnosed cancer in women, and it remains a substantial clinical challenge due to cancer relapse. The presence of a subpopulation of dormant breast cancer cells that survived chemotherapy and metastasized to distant organs may contribute to relapse. Tumor microenvironment (TME) plays a significant role as a niche in inducing cancer cells into dormancy as well as involves in the reversible epithelial-to-mesenchymal transition (EMT) into aggressive phenotype responsible for cancer-related mortality in patients. Mesenchymal stem cells (MSCs) are known to migrate to TME and interact with cancer cells via secretion of exosome- containing biomolecules, microRNA. Understanding of interaction between MSCs and cancer cells via exosomal miRNAs is important in determining the therapeutic role of MSC in treating breast cancer cells and relapse. In this study, exosomes were harvested from a medium of indirect co-culture of MCF7-luminal and MDA-MB-231-basal breast cancer cells (BCCs) subtypes with adipose MSCs. The interaction resulted in different exosomal miRNAs profiles that modulate essential signaling pathways and cell cycle arrest into dormancy via inhibition of metastasis and epithelial-to-mesenchymal transition (EMT). Overall, breast cancer cells displayed a change towards a more dormant-epithelial phenotype associated with lower rates of metastasis and higher chemoresistance. The study highlights the crucial roles of adipose MSCs in inducing dormancy and identifying miRNAs-dormancy related markers that could be used to identify the metastatic pattern, predict relapses in cancer patients and to be potential candidate targets for new targeted therapy.

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