Epithelial-Mesenchymal Transition Status Of Circulating Tumor Cells In Breast Cancer And Its Clinical Relevance

CANCER BIOLOGY & MEDICINE(2020)

引用 15|浏览13
暂无评分
摘要
Objective Circulating tumor cells (CTCs) play a critical role in cancer metastasis, but their prevalence and significance remain unclear. This study attempted to track the epithelial-mesenchymal transition (EMT) status of CTCs in breast cancer patients and investigate their clinical relevance.Methods:In this study, the established negFACS-IF:E/M platform was applied to isolate rare CTCs and characterize their EMT status in breast cancer. A total of 89 breast cancer patients were recruited, including stage 0-III (n- 60) and late stage (n- 29) cases.Results: Using the negFACS-IF:E/M platform, it was found that in human epidermal growth factor receptor 2 (HER2)+ patients, mesenchymal CTCs usually exhibited a high percentage of HER2+ cells. Stage IV breast cancer patients had considerably more CTCs than stage 0-III patients. Among stage 0-III breast cancers, the HER2 subtype included a significantly higher percentage of mesenchymal and biphenotypic (epithelial and mesenchymal) CTCs than the luminal A or B subtypes. Among stage IV patients, CTCs were predominantly epithelial in cases with local recurrence and were more mesenchymal in cases with distant metastasis. By applying a support vector machine (SVM) algorithm, the EMT status of CTCs could distinguish between breast cancer cases with metastasis/local recurrence and those without recurrence.Conclusions: The negFACS-IF:E/M platform provides a flexible and generally acceptable method for the highly sensitive and specific detection of CTCs and their EMT traits in breast cancer. This study demonstrated that the EMT status of CTCs had high clinical relevance in breast cancer, especially in predicting the distant metastasis or local recurrence of breast cancer.
更多
查看译文
关键词
Circulating tumor cells,breast cancer,epithelial-to-mesenchymal transition,estrogen receptor/human epidermal growth factor receptor 2 expression,support vector machine algorithm
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要