Evidence map›Paper›PMID 42582347›Full record

ReviewFrontiers in immunology2026

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

Chenru Ma, Yafei Zhuang, Songchen Han, Shuping Li, Qiang Dai

Abstract readReview
In one paragraph

Review in Frontiers in immunology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Chenru Ma *Department of Radiation Oncology, Gansu Provincial People's Hospital, Lanzhou, Gansu, China.
Yafei Zhuang *Department of Radiation Oncology, Gansu Provincial People's Hospital, Lanzhou, Gansu, China.
Songchen HanDepartment of Radiation Oncology, Gansu Provincial People's Hospital, Lanzhou, Gansu, China.
Shuping LiDepartment of Radiation Oncology, Gansu Provincial People's Hospital, Lanzhou, Gansu, China.
Qiang DaiDepartment of Radiation Oncology, Gansu Provincial People's Hospital, Lanzhou, Gansu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Immunotherapy, AdoptiveKiller Cells, NaturalNeoplasmsReceptors, Chimeric AntigenAnimalsArtificial IntelligenceHumansTumor EscapeTumor MicroenvironmentReceptors, Chimeric AntigenaCAR-iCARartificial intelligenceCAR-NK cellscascade resistancedual-module CARNKG2A-HLA-Eprecision immunotherapytrogocytosis

Identifiers

PMID42582347
PMCPMC13457480

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.