Cancer-associated fibroblasts (CAFs) in the tumor microenvironment have been associated with tumor progression in breast cancer. Although crosstalk between breast cancer cells and CAFs has been studied, the effect of CAFs on non-neoplastic breast epithelial cells is not fully understood to date. Here, we investigated the effect of CAFs on aggressive phenotypes in non-neoplastic MCF10A breast epithelial cells. CAFs induced epithelial-to-mesenchymal transition (EMT) and invasive phenotype in MCF10A cells. S100A8, a potential prognostic marker in several cancers, was markedly increased in MCF10A cells by CAFs. S100A8 was crucial for CAFs-induced invasive phenotype of MCF10A cells. Among cytokines increased by CAFs, interleukin (IL)-8 induced S100A8 through transcription factors p65 NF-κB and C/EBPβ. In a xenograft mouse model with MCF10A cells and CAFs, tumor was not developed, suggesting that coinjection with CAFs may not be sufficient for in vivo tumorigenicity of MCF10A cells. Xenograft mouse tumor models with MDA-MB-231 breast carcinoma cells provided an in vivo evidence for the effect of CAFs on breast cancer progression as well as a crucial role of IL-8 in tumor growth and S100A8 expression in vivo. Using a tissue microarray of human breast cancer, we showed that S100A8 expression was correlated with poor outcomes. S100A8 expression was more frequently detected in cancer-adjacent normal human breast tissues than in normal breast tissues. Together, this study elucidated a novel mechanism for the acquisition of invasive phenotype of non-neoplastic breast cells induced by CAFs, suggesting that targeting IL-8 and S100A8 may be an effective strategy against breast cancer.
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Sci Rep
December 2024
Department of Clinical Pharmacy, Baoshan Hospital Affiliated to, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
This study investigates the potential treatment of breast cancer utilizing Gentiana robusta King ex Hook. f. (QJ) through an integrated approach involving network pharmacology, molecular docking, and molecular dynamics simulation.
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December 2024
Department of Breast Surgery, Second Affiliated Hospital of Dalian Medical University, No. 467 Zhongshan Road, Shahekou District, Dalian, China.
Early prediction of patient responses to neoadjuvant chemotherapy (NACT) is essential for the precision treatment of early breast cancer (EBC). Therefore, this study aims to noninvasively and early predict pathological complete response (pCR). We used dynamic ultrasound (US) imaging changes acquired during NACT, along with clinicopathological features, to create a nomogram and construct a machine learning model.
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