Evidence map›Paper›PMID 39217416›Full record

ArticleMolecular therapy : the journal of the American Society of Gene Therapy2024

High-throughput screening identifies ibuprofen as an sEV PD-L1 inhibitor for synergistic cancer immunotherapy.

Zhuo-Kun Chen, Shuo Zheng, Yan Long, Kui-Ming Wang, Bo-Lin Xiao, Jin-Bang Li, Wei Zhang, Heng Song, Gang Chen

Abstract read
In one paragraph

Article in Molecular therapy : the journal of the American Society of Gene Therapy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Drug repurposing in oncology: a path beyond the bottleneck.Medical oncology (Northwood, London, England) · 2025
    Review
  4. 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

9 authors.

Zhuo-Kun ChenState Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Wuhan University, Wuhan 430079, China.
Shuo ZhengCollege of Chemistry and Molecular Sciences, Wuhan University, Wuhan 430079, China.
Yan LongCollege of Chemistry and Molecular Sciences, Wuhan University, Wuhan 430079, China.
Kui-Ming WangState Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Wuhan University, Wuhan 430079, China.
Bo-Lin XiaoState Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Wuhan University, Wuhan 430079, China.
Jin-Bang LiState Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Wuhan University, Wuhan 430079, China.
Wei ZhangState Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Wuhan University, Wuhan 430079, China; Department of Oral and Maxillofacial Surgery, School & Hospital of Stomatology, Wuhan University, Wuhan 430079, China. Electronic address: wzhang88@whu.edu.cn.
Heng SongCollege of Chemistry and Molecular Sciences, Wuhan University, Wuhan 430079, China. Electronic address: hengsong@whu.edu.cn.
Gang ChenState Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Wuhan University, Wuhan 430079, China; Department of Oral and Maxillofacial Surgery, School & Hospital of Stomatology, Wuhan University, Wuhan 430079, China; TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan 430079, China; Frontier Science Center for Immunology and Metabolism, Wuhan University, Wuhan 430079, China. Electronic address: geraldchan@whu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Programmed death-ligand 1 (PD-L1) on tumor-derived small extracellular vesicles (sEVs) limits therapeutic effectiveness by interacting with the PD-1 receptor on host immune cells. Targeting the secretion of sEV PD-L1 has emerged as a promising strategy to enhance immunotherapy. However, the lack of small-molecule inhibitors poses a challenge for clinical translation. In this study, we developed a target and phenotype dual-driven high-throughput screening strategy that combined virtual screening with nanoflow-based experimental verification. We identified ibuprofen (IBP) as a novel inhibitor that effectively targeted sEV PD-L1 secretion. IBP disrupted the biogenesis and secretion of PD-L1

Indexed as

Antineoplastic Combined Chemotherapy ProtocolsB7-H1 AntigenEndosomal Sorting Complexes Required for TransportIbuprofenImmune Checkpoint InhibitorsNeoplasmsAdministration, CutaneousAnimalsCell LineDrug SynergismExtracellular VesiclesHead and Neck NeoplasmsHigh-Throughput Screening AssaysHumansMelanoma, ExperimentalMiceB7-H1 AntigenEndosomal Sorting Complexes Required for Transporthepatocyte growth factor-regulated tyrosine kinase substrateIbuprofenImmune Checkpoint InhibitorsPhosphoproteinsdrug repurposinghigh-throughput screeningimmunotherapysEV inhibitorssEV PD-L1synergistic cancer therapytargeted therapytumor-derived small extracellular vesicles

Identifiers

PMID39217416
PMCPMC11489553

What OpenQuestion holds

Textmetadata
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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.