循环肿瘤细胞（CTC）作为肿瘤转移的“种子细胞”，其数量、分子表型及功能状态与肿瘤进展、治疗反应和预后密切相关，是液体活检领域的重要研究对象。随着肿瘤精准治疗的发展，CTC检测已由单纯计数逐步转向分子分型和治疗决策支持。近年来，基于纳米多肽的新型CTC富集与分型平台逐渐兴起，依托多肽纳米磁珠介导的高效富集和多维度分子解析技术，可提升稀有CTC捕获能力，并为治疗相关靶点检测、疗效监测和耐药预警提供细胞学基础。中国国家纳米科学中心自主研发的纳米多肽CTC检测技术构建了兼具灵敏度、特异性和临床可及性的检测体系，推动CTC检测由“数量评估”迈向以分子分型和治疗决策支持为核心的2.0时代。本文重点阐述纳米多肽CTC检测平台的核心原理、关键技术突破及其在肿瘤精准生物治疗中的临床转化价值，并探讨其在标准化、成本控制、证据等级及伴随诊断转化方面面临的挑战，以期为优化肿瘤精准生物治疗策略提供参考。

Circulating tumor cells (CTCs), regarded as the “seed cells” of tumor metastasis, are closely associated with tumor progression, therapeutic response, and patient prognosis through changes in their abundance, molecular phenotypes, and functional states. With the development of precision oncology, CTC detection has gradually evolved from simple enumeration toward molecular subtyping and therapeutic decision support. In recent years, nanopeptide-based CTC enrichment and subtyping platforms have emerged as promising liquid biopsy technologies. By integrating peptide-functionalized magnetic nanobead-mediated enrichment with multidimensional molecular profiling, these platforms can improve the capture of rare CTCs and provide a cellular basis for therapeutic target detection, treatment monitoring, and early warning of drug resistance. The nanopeptide-based CTC detection technology developed by the National Center for Nanoscience and Technology, China (NCNST) has established a clinically accessible detection system with high sensitivity and specificity, promoting the transition of CTC detection from “quantitative assessment” to a 2.0 era centered on molecular subtyping and treatment decision support. This review focuses on the core principles, key technological breakthroughs, and clinical translational value of nanopeptide-based CTC detection platforms in precision cancer biotherapy, and discusses the challenges related to standardization, cost control, level of clinical evidence, and translation into companion diagnostics, to provide a reference for optimizing precision biotherapeutic strategies in oncology.

国家重点研发计划（2023YFC2507000）；国家自然科学基金（32471456）