DWI-Leibniz-Institute for Interactive Materials, Aachen, 52056, Germany.
Institute of Technical and Macromolecular Chemistry, RWTH Aachen University, Aachen, 52074, Germany.
Nat Commun. 2024 Sep 17;15(1):8172. doi: 10.1038/s41467-024-52416-0.
Nanocarriers (NCs) play a crucial role in delivering theranostic agents to tumors, making them a pivotal focus of research. However, the persistently low delivery efficiency of engineered NCs has been a significant challenge in the advancement of nanomedicine, stirring considerable debate. Transvascular transport is a critical pathway for NC delivery from vessels to tumors, yet a comprehensive understanding of the interactions between NCs and vascular systems remains elusive. In recent years, considerable efforts have been invested in elucidating the transvascular transport mechanisms of NCs, leading to promising advancements in tumor delivery and theranostics. In this context, we highlight various delivery mechanisms, including the enhanced permeability and retention effect, cooperative immune-driven effect, active transcytosis, and cell/bacteria-mediated delivery. Furthermore, we explore corresponding strategies aimed at enhancing transvascular transport of NCs for efficient tumor delivery. These approaches offer intriguing solutions spanning physicochemical, biological, and pharmacological domains to improve delivery and therapeutic outcomes. Additionally, we propose a forward-looking delivery framework that relies on advanced tumor/vessel models, high-throughput NC libraries, nano-bio interaction datasets, and artificial intelligence, which aims to guide the design of next-generation carriers and implementation strategies for optimized delivery.
纳米载体（NCs）在将治疗药物递送到肿瘤部位方面发挥着关键作用，因此成为研究的重点。然而，工程化 NCs 的递送效率一直很低，这是纳米医学发展的一个重大挑战，引发了广泛的争论。血管内转运是 NC 从血管向肿瘤递送的关键途径，但 NC 与血管系统之间的相互作用仍难以全面理解。近年来，人们投入了大量精力来阐明 NC 的跨血管转运机制，从而在肿瘤递送和治疗方面取得了有希望的进展。在这种情况下，我们强调了各种递送机制，包括增强的通透性和保留效应、协同免疫驱动效应、主动转胞作用和细胞/细菌介导的递送。此外，我们还探讨了相应的策略，旨在增强 NC 的跨血管转运，以实现高效的肿瘤递送。这些方法提供了有趣的解决方案，涵盖物理化学、生物和药理学领域，以改善递送和治疗效果。此外，我们提出了一个前瞻性的递送框架，该框架依赖于先进的肿瘤/血管模型、高通量的 NC 文库、纳米-生物相互作用数据集和人工智能，旨在指导下一代载体的设计和实施优化递送的策略。
