Evidence map›Paper›PMID 37313600›Full record

ArticleEssays in biochemistry2023

Tumour-associated macrophages as a potential target to improve natural killer cell-based immunotherapies.

Takanori Kitamura

Open access · hybridAbstract read
In one paragraph

Article in Essays in biochemistry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.0field-weighted citation impact, top 23% of its field
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

8 citing papers in PubMed, 6 citations in OpenAlex.

  1. Review
  2. Review
  3. Precision Oncology Framework Using Circulating Tumor Cells.International journal of molecular sciences · 2025
    Review
  4. Article
  5. Review
  6. Article
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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

1 author at 1 institution in 1 country.

Takanori KitamuraMRC Centre for Reproductive Health, The University of Edinburgh, Edinburgh, EH16 4TJ, United Kingdom.ORCID 0000-0003-2032-3918
MRC Centre for Reproductive Health · GB

Funding

Medical Research Council MR/N022556/1Medical Research Council MR/S006982/1
6 · The paper itself

Abstract

Adoptive transfer of natural killer (NK) cells has been proposed as a novel immunotherapy for malignant tumours resistant to current therapeutic modalities. Several clinical studies have demonstrated that the NK cell-infusion is well tolerated without severe side effects and shows promising results in haematological malignancies. However, patients with malignant solid tumours do not show significant responses to this therapy. Such disappointing results largely arise from the inefficient delivery of infused NK cells and the impairment of their functions in the tumour microenvironment (TME). Tumour-associated macrophages (TAMs) are the most abundant stromal cells in the TME of most solid tumours, and a high TAM density correlates with poor prognosis of cancer patients. Although our knowledge of the interactions between TAMs and NK cells is limited, many studies have indicated that TAMs suppress NK cell cytotoxicity against cancer cells. Therefore, blockade of TAM functions can be an attractive strategy to improve NK cell-based immunotherapies. On the other hand, macrophages are reported to activate NK cells under certain circumstances. This essay presents our current knowledge about mechanisms by which macrophages regulate NK cell functions and discusses possible therapeutic approaches to block macrophage-mediated NK cell suppression.

Indexed as

NeoplasmsTumor-Associated MacrophagesHumansImmunotherapyKiller Cells, NaturalTumor Microenvironmentcancerimmunotherapymacrophagenatural killer celltumor microenvironments

Identifiers

PMID37313600
PMCPMC10539946
OpenAlexW4380577106

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.