Zhang Yuhong, Wang Weidong
Department of Oncology, Clinical Medical College, Southwest Medical University, No. 319, Section 3, Zhongshan Road, Luzhou, 646099, Sichuan, China.
Department of Radiation Oncology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
J Transl Med. 2025 Apr 21;23(1):461. doi: 10.1186/s12967-025-06486-3.
Tumor subclones refer to distinct cell populations within the same tumor that possess different genetic characteristics. They play a crucial role in understanding tumor heterogeneity, evolution, and therapeutic resistance. The formation of tumor subclones is driven by several key mechanisms, including the inherent genetic instability of tumor cells, which facilitates the accumulation of novel mutations; selective pressures from the tumor microenvironment and therapeutic interventions, which promote the expansion of certain subclones; and epigenetic modifications, such as DNA methylation and histone modifications, which alter gene expression patterns. Major methodologies for studying tumor subclones include single-cell sequencing, liquid biopsy, and spatial transcriptomics, which provide insights into clonal architecture and dynamic evolution. Beyond their direct involvement in tumor growth and invasion, subclones significantly contribute to tumor heterogeneity, immune evasion, and treatment resistance. Thus, an in-depth investigation of tumor subclones not only aids in guiding personalized precision therapy, overcoming drug resistance, and identifying novel therapeutic targets, but also enhances our ability to predict recurrence and metastasis risks while elucidating the mechanisms underlying tumor heterogeneity. The integration of artificial intelligence, big data analytics, and multi-omics technologies is expected to further advance research in tumor subclones, paving the way for novel strategies in cancer diagnosis and treatment. This review aims to provide a comprehensive overview of tumor subclone formation mechanisms, evolutionary models, analytical methods, and clinical implications, offering insights into precision oncology and future translational research.
肿瘤亚克隆是指同一肿瘤内具有不同遗传特征的不同细胞群体。它们在理解肿瘤异质性、进化和治疗耐药性方面发挥着关键作用。肿瘤亚克隆的形成由多种关键机制驱动,包括肿瘤细胞固有的遗传不稳定性,这促进了新突变的积累;肿瘤微环境和治疗干预的选择压力,这促进了某些亚克隆的扩增;以及表观遗传修饰,如DNA甲基化和组蛋白修饰,它们改变基因表达模式。研究肿瘤亚克隆的主要方法包括单细胞测序、液体活检和空间转录组学,这些方法为克隆结构和动态进化提供了见解。除了直接参与肿瘤生长和侵袭外,亚克隆对肿瘤异质性、免疫逃逸和治疗耐药性也有显著贡献。因此,对肿瘤亚克隆的深入研究不仅有助于指导个性化精准治疗、克服耐药性和识别新的治疗靶点,还能提高我们预测复发和转移风险的能力,同时阐明肿瘤异质性的潜在机制。人工智能、大数据分析和多组学技术的整合有望进一步推动肿瘤亚克隆的研究,为癌症诊断和治疗的新策略铺平道路。本综述旨在全面概述肿瘤亚克隆的形成机制、进化模型、分析方法和临床意义,为精准肿瘤学和未来的转化研究提供见解。