Huang Ashley V, Kong Yali, Wang Kan, Brown Milton L, Mu David
Department of Biomedical and Translational Sciences, Macon & Joan Brock Virginia Health Sciences at Old Dominion University, Norfolk, VA 23507, USA.
Department of Internal Medicine, Macon & Joan Brock Virginia Health Sciences at Old Dominion University, Norfolk, VA 23507, USA.
Int J Mol Sci. 2025 Aug 17;26(16):7935. doi: 10.3390/ijms26167935.
Breast cancer is one of the most common cancers globally. Unfortunately, many patients with breast cancer develop resistance to chemotherapy and tumor recurrence, which is primarily driven by breast cancer stem cells (BCSCs). BCSCs behave like stem cells and can self-renew and differentiate into mature tumor cells, enabling the cancer to regrow and metastasize. Key markers like CD44 and aldehyde dehydrogenase-1 (ALDH1), along with pathways like Wingless-related integration site (Wnt), Notch, and Hedgehog, are critical to regulating this stem-like behavior of BCSCs and, thus, are being investigated as targets for various new therapies. This review summarizes marker-dependent strategies for targeting BCSCs and expands on the challenges for the development of anti-BCSC drugs. We explore cutting-edge approaches like artificial intelligence (AI)-driven drug discovery and urge readers to seriously consider biological clocks and chronotherapy as experimental variables in drug discovery. Collectively, the task of cancer researchers is to overcome the many hurdles targeting BCSCs if we hope to tangibly improve breast cancer treatment outcomes and reduce mortality.
乳腺癌是全球最常见的癌症之一。不幸的是,许多乳腺癌患者会对化疗产生耐药性并出现肿瘤复发,这主要是由乳腺癌干细胞(BCSCs)驱动的。BCSCs表现得像干细胞,能够自我更新并分化为成熟的肿瘤细胞,从而使癌症能够重新生长和转移。像CD44和醛脱氢酶-1(ALDH1)这样的关键标志物,以及无翅相关整合位点(Wnt)、Notch和Hedgehog等信号通路,对于调节BCSCs的这种干细胞样行为至关重要,因此正在作为各种新疗法的靶点进行研究。本综述总结了针对BCSCs的基于标志物的策略,并详述了抗BCSC药物开发面临的挑战。我们探索了如人工智能(AI)驱动的药物发现等前沿方法,并敦促读者认真考虑生物钟和时辰疗法作为药物发现中的实验变量。总体而言,如果我们希望切实改善乳腺癌治疗效果并降低死亡率,癌症研究人员的任务就是克服针对BCSCs的诸多障碍。