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用于实体瘤的双模块 aCAR-iCAR NK 细胞:级联耐药机制、AI 驱动工程化改造与精准分层

英文原题:Dual-module aCAR-iCAR NK cells for solid tumors: cascade resistance mechanisms, AI-driven engineering, and precision stratification.

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Dual-module aCAR-iCAR NK cells for solid tumors: cascade resistance mechanisms, AI-driven engineering, and precision stratification.

PubMed 2026/07/28(内容时间) Front Immunol Q1 · IF 7(JCR 2025)

研究概要

嵌合抗原受体工程化自然杀伤(CAR-NK)细胞已成为癌症免疫治疗中一种有前景的现货型平台,在早期临床试验中展现出良好的安全性,并在复发/难治性(R/R)血液系统恶性肿瘤中显示出强效抗肿瘤活性。

中文摘要

嵌合抗原受体工程化自然杀伤(CAR-NK)细胞已成为一种有前景的现货型肿瘤免疫治疗平台,在早期临床试验中表现出良好的安全性,并在复发/难治性(R/R)血液系统恶性肿瘤中显示出强效抗肿瘤活性。然而,其在实体瘤中的临床疗效仍因相互关联的耐药机制而受到严重限制。在本综述中,我们系统剖析了CAR-NK治疗在实体瘤中失败的病理基础,并提出一个整合性级联耐药框架,该框架界定了三个核心瓶颈:肿瘤微环境(TME)介导的功能耗竭、非自然杀伤(NK)细胞适配型嵌合抗原受体(CAR)的结构缺陷,以及胞啃作用驱动的免疫逃逸。我们进一步阐明了NK 细胞2组成员A-人类白细胞抗原E(NKG2A-HLA-E)免疫检查点轴与细胞间黏附分子1/淋巴细胞功能相关抗原1(ICAM-1/LFA-1)黏附通路在该级联模型中的情境依赖性调控作用,并对所有机制性结论的证据强度进行了明确分层。以激活-抑制双模块CAR(aCAR-iCAR)系统为核心,我们总结了其设计原则、临床前验证现状以及缓解级联耐药的潜力,并明确区分了基于杀伤细胞免疫球蛋白样受体(KIR)的(1级证据)与基于NKG2A的(2-3级证据)抑制性CAR骨架。随后,我们勾勒了一个端到端的人工智能(AI)驱动的理性设计框架,涵盖靶点筛选、结构优化和信号平衡校准,并引入 AI-纳米共生体(AI-nanosymbiont)概念作为外源性协同策略,以应对 TME 递送障碍。基于实体瘤的分子异质性,我们提出一个四亚型精准分层框架,以将肿瘤特征与定制化治疗方案相匹配,并总结了核心转化挑战,包括生产制造限制、监管空白和安全性考量。总体而言,本综述为针对实体瘤的下一代 CAR-NK 开发提供了一个平衡的、循证分级的理论框架,并为未来的机制和临床研究产生了可检验的假设。

展开英文摘要原文

Chimeric antigen receptor-engineered natural killer (CAR-NK) cells have emerged as a promising off-the-shelf platform for cancer immunotherapy, with a favorable safety profile in early clinical trials and potent antitumor activity demonstrated in relapsed/refractory (R/R) hematologic malignancies. However, their clinical efficacy in solid tumors remains severely limited by interconnected resistance mechanisms. In this review, we systematically dissect the pathological basis of CAR-NK therapy failure in solid tumors and propose an integrative cascade resistance framework that delineates three core bottlenecks: tumor microenvironment (TME)-mediated functional exhaustion, structural defects of non-natural killer (NK)-cell-adapted chimeric antigen receptors (CARs), and trogocytosis-driven immune escape. We further characterize the context-dependent regulatory roles of the natural killer group 2 member A-human leukocyte antigen E (NKG2A-HLA-E) immune checkpoint axis and the intercellular adhesion molecule 1/lymphocyte function-associated antigen 1 (ICAM-1/LFA-1) adhesion pathway within this cascade model, with clear stratification of evidence strength across all mechanistic conclusions. Centered on the activating-inhibitory dual-module CAR (aCAR-iCAR) system, we summarize its design principles, preclinical validation status, and potential to mitigate cascade resistance, with explicit distinction between killer cell immunoglobulin-like receptor (KIR)-based (Level 1 evidence) and NKG2A-based (Level 2-3 evidence) inhibitory CAR backbones. We then outline an end-to-end artificial intelligence (AI)-driven rational design framework covering target screening, structural optimization, and signaling balance calibration, and introduce the AI-nanosymbiont concept as an exogenous synergistic strategy to address TME delivery barriers. Building on the molecular heterogeneity of solid tumors, we propose a four-subtype precision stratification framework to match tumor features with tailored therapeutic regimens, and summarize core translational challenges including manufacturing constraints, regulatory gaps, and safety considerations. Overall, this review provides a balanced, evidence-graded theoretical framework for next-generation CAR-NK development against solid tumors, and generates testable hypotheses for future mechanistic and clinical investigations.

论文信息

作者
Ma C、Zhuang Y、Han S、Li S、Dai Q
单位
Department of Radiation Oncology, Gansu Provincial People's Hospital, Lanzhou, Gansu, China.China
文献类型
综述
期刊
Frontiers in immunology2026
原文标识
PubMed 42582347 · DOI 10.3389/fimmu.2026.1863734