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Updated: Aug 13, 2026

Advances in Human Induced Pluripotent Stem Cell-Derived Chimeric Antigen Receptor-Expressing Natural Killer Cells
Published on: February 14, 2025
Dual-module aCAR-iCAR NK cells for solid tumors: cascade resistance mechanisms, AI-driven engineering, and precision
Chenru Ma1, Yafei Zhuang1, Songchen Han1
1Department of Radiation Oncology, Gansu Provincial People's Hospital, Lanzhou, Gansu, China.
None:
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.
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