Evidence map›Paper›PMID 39007146›Full record

ReviewFrontiers in immunology2024

Advances in CAR-NK cell therapy for hematological malignancies.

Rui Yang, Yun Yang, Rui Liu, Yiwen Wang, Ruoyu Yang, Aili He

Abstract readReview
In one paragraph

Review in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

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  15. Are monocytes a preferable option to develop myeloid cell-based therapies for solid tumors?Journal of experimental & clinical cancer research : CR · 2025
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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

6 authors.

Rui YangDepartment of Hematology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Yun YangDepartment of Hematology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Rui LiuDepartment of Hematology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Yiwen WangDepartment of Hematology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Ruoyu YangDepartment of Hematology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Aili HeDepartment of Hematology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chimeric antigen receptor T (CAR-T) cell therapy has revolutionized the treatment of hematological malignancies, demonstrably improving patient outcomes and prognosis. However, its application has introduced new challenges, such as safety concerns, off-target toxicities, and significant costs. Natural killer (NK) cells are crucial components of the innate immune system, capable of eliminating tumor cells without prior exposure to specific antigens or pre-activation. This inherent advantage complements the limitations of T cells, making CAR-NK cell therapy a promising avenue for hematological tumor immunotherapy. In recent years, preclinical and clinical studies have yielded preliminary evidence supporting the safety and efficacy of CAR-NK cell therapy in hematological malignancies, paving the way for future advancements in immunotherapy. This review aims to succinctly discuss the characteristics, significant therapeutic progress, and potential challenges associated with CAR-NK cell therapy.

Indexed as

Hematologic NeoplasmsImmunotherapy, AdoptiveKiller Cells, NaturalReceptors, Chimeric AntigenAnimalsHumansReceptors, Chimeric AntigenCAR-NKchimeric antigen receptorhematological malignanciesimmunotherapyNK cells

Identifiers

PMID39007146
PMCPMC11239349

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.