Evidence map›Paper›PMID 40726987›Full record

ReviewFrontiers in immunology2025

NK cell-based immunotherapy strategies for myeloid leukemia.

Lin Zhang, Yibo Zhao, Yan Dong, Xiuxing Jiang

Abstract readReview
In one paragraph

Review in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Article
  6. Review
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

4 authors.

Lin Zhang *Department of Pharmacy, Daping Hospital, Army Medical University, Chongqing, China.
Yibo Zhao *Department of Pharmacy, Daping Hospital, Army Medical University, Chongqing, China.
Yan DongDepartment of Oncology, Southwest Hospital, Army Medical University, Chongqing, China.
Xiuxing JiangFrontier Medical Training Brigade, Army Medical University, Xinjiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Myeloid leukemia (ML) is a clonal malignant disease with abnormal hematopoietic stem cells. With the emergence of novel immunotherapies, such as CAR-T, therapeutic outcomes in ML patients have improved, while significant challenges persist, including severe adverse events and disease recurrence. Natural killer cells (NK cells) are "natural killers" of the immune system that do not require antigen presentation and responsible for recognizing and destroying tumor cells. Some NK cells-based clinical experiments have been carried out and achieved remarkable results with lower side effects in ML. Crucially, within the ML microenvironment, NK cells frequently exhibit more severe functional exhaustion compared with T cells, characterized by impaired cytotoxicity, cytokine production, and proliferative capacity which limits anti-ML efficacy of NK cells. However, clinical studies utilizing NK cell-based therapies (e.g., adoptive transfer, CAR-NK cells) have demonstrated promising results with favorable safety profiles, underscoring their therapeutic potential. Therefore, developing more strategies based on NK cell is of great clinical significance for the treatment of ML. In this review, we systematically analysed the relationship between ML and NK cells, aiming to propose more novel protocols for NK cell expansion and persistence enhancement, establish evidence-based guidelines for next-generation NK cell-based immunotherapies in ML treatment.

Indexed as

ImmunotherapyImmunotherapy, AdoptiveKiller Cells, NaturalLeukemia, MyeloidAnimalsHumansReceptors, Chimeric AntigenTumor MicroenvironmentReceptors, Chimeric Antigenexhaustionimmunobiologymyeloid leukemiaNK celltherapeutic potential

Identifiers

PMID40726987
PMCPMC12301322

What OpenQuestion holds

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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.