CAR-NK cells to treat patients with cancer: a systematic scoping review of published studies and registered clinical trials
Bibliographic record
Abstract
INTRODUCTION: Chimeric antigen-receptor natural killer cells (CAR-NKs) offer a promising allogeneic immune effector cell therapy to treat malignant diseases. A systematic review is needed to understand the scope of current clinical studies and registered active trials to identify aspects of study design and cell product characterization that could accelerate greater clinical adoption. METHODS: A systematic review of all publications (to January 25, 2025) and registered clinical trials (to June 21, 2024) was conducted. We extracted information on study design, patient characteristics, outcome measures, and cell product characterization. RESULTS: A total of 150 patients in ten studies published between 2018 and 2025 were identified. Hematologic malignancies were examined most frequently (n = 6 studies). All published studies were uncontrolled, and only four reported on more than three patients. CAR-NK products were most frequently derived from the NK-92 cell line (four studies), umbilical cord blood (three studies), induced pluripotent stem cells (one study), or not reported (two studies). Considerable heterogeneity was observed regarding CAR-NK cell manufacturing methods and dosing. Complete response rates for patients with B cell lymphomas ranged from 25-85%, depending on lymphoma subtype. Responses were durable with median response not reached in the largest study and durable remission at 1-year in 70% of responders in a second study. Adverse events were uncommon with no cases of grade 3 or higher cytokine release syndrome and no cases of immune effector-cell mediated neurotoxicity or graft versus host disease reported. Among the 50 registered trials identified (n=2102 subjects to be enrolled), hematological malignancies (n = 34; 68%) were the most common diseases examined. CONCLUSIONS: The clinical outcomes and low adverse event rates following CAR-NK therapy in published studies are encouraging. Larger controlled trials are needed to confirm the safety and efficacy of CAR-NK therapy. We anticipate the completion of several such trials in the coming years.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.058 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.009 |
| Bibliometrics | 0.016 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".