Evidence map›Paper›PMID 40989721›Full record

ReviewImmunoTargets and therapy2025

Targeting ILT4 to Improve Immunotherapy Efficacy in Solid Tumour: From Bench to Bedside.

Aiqin Gao, Shuyun Wang, Yuping Sun

Abstract readReview
In one paragraph

Review in ImmunoTargets and therapy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Article
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

3 authors.

Aiqin Gao *Department of Thoracic Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, People's Republic of China.ORCID 0000-0003-1157-6104
Shuyun Wang *Phase I Clinical Trial Center, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, People's Republic of China.
Yuping SunPhase I Clinical Trial Center, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, People's Republic of China.ORCID 0000-0002-0804-6850

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Immunotherapy, especially immune checkpoint inhibitors (ICIs), has greatly changed the paradigm of cancer treatment in the past decade. However, the efficacy of ICIs in solid tumors is still limited. Even in patients with high PD-L1 expression, the response rate is less than 40%. The immunosuppressive tumour microenvironment (TME) represents a major cause of ICI hyporesponsiveness due to its inhibition on effective T-cell trafficking and immunity. Exploring novel immunotargets and developing combination therapeutics represent promising strategies to improve tumor response to immunotherapy. Immunoglobulin-like transcript (ILT) 4 is a classical inhibitory molecule in myeloid cells. Recently, ILT4 expression was discovered in tumour cells and multiple immunocytes in the TME, functionally inducing tumour growth, metastasis, and immune escape. Our group proposed ILT4 as a novel checkpoint molecule for tumour immunotherapy in 2018. In the past 5 years, translational research on ILT4 has made remarkable advances. Here, we update recent findings on ILT4 function in the TME, summarize the translational research on the development of therapeutic ILT4 antibodies, and highlight emerging clinical trial data supporting the role of ILT4 blockade in improving immunotherapy efficacy.

Indexed as

clinical trialsILT4immunosuppressionimmunotherapytranslational research

Identifiers

PMID40989721
PMCPMC12453052

What OpenQuestion holds

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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.