三阴性乳腺癌
亚型
乳腺癌
精密医学
医学
三重阴性
疾病
临床试验
仿形(计算机编程)
肿瘤科
癌症
计算生物学
生物信息学
内科学
计算机科学
生物
病理
程序设计语言
操作系统
作者
Song‐Yang Wu,Hai Wang,Zhi‐Ming Shao,Yi‐Zhou Jiang
标识
DOI:10.1007/s11427-020-1714-8
摘要
Triple-negative breast cancer (TNBC) remains the most aggressive cluster of all breast cancers, which is due to its rapid progression, high probabilities of early recurrence, and distant metastasis resistant to standard treatment. Following the advances in cancer genomics and transcriptomics that can illustrate the comprehensive profiling of this heterogeneous disease, it is now possible to identify different subclasses of TNBC according to both intrinsic signals and extrinsic microenvironment, which have a huge influence on predicting response to established therapies and picking up novel therapeutic targets for each cluster. In this review, we summarize basic characteristics and critical subtyping systems of TNBC, and particularly discuss newly found prospective targets and relevant medications, which were proved promising in clinical trials, thus shedding light on the future development of precision treatment strategies.
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