Evidence map›Paper›PMID 35721177›Full record

ArticleFrontiers in pharmacology2022

Bafetinib Suppresses the Transcription of PD-L1 Through c-Myc in Lung

Xi Chen, Qianqian Du, Hongjie Guo, Qiaojun He, Bo Yang, Ling Ding

Abstract read
In one paragraph

Article in Frontiers in pharmacology, 2022. 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. Article
  2. 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

6 authors.

Xi ChenZhejiang Province Key Laboratory of Anti-Cancer Drug Research, Institute of Pharmacology and Toxicology, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.
Qianqian DuZhejiang Province Key Laboratory of Anti-Cancer Drug Research, Institute of Pharmacology and Toxicology, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.
Hongjie GuoZhejiang Province Key Laboratory of Anti-Cancer Drug Research, Institute of Pharmacology and Toxicology, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.
Qiaojun HeZhejiang Province Key Laboratory of Anti-Cancer Drug Research, Institute of Pharmacology and Toxicology, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.
Bo YangZhejiang Province Key Laboratory of Anti-Cancer Drug Research, Institute of Pharmacology and Toxicology, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.
Ling DingZhejiang Province Key Laboratory of Anti-Cancer Drug Research, Institute of Pharmacology and Toxicology, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Given the limitations of the existing antibody-based therapies, including immune-related adverse events, poor response rates, and intravenous route of dosing, small molecules inhibitors targeting PD-L1 are highly desirable. By cell-based screening, we found that tyrosine kinase inhibitor Bafetinib dramatically suppresses PD-L1 protein expression in a dose-dependent manner. In parallel, cell membrane PD-L1 is also reduced by Bafetinib. We confirm that Bafetinib doesn't affect the protein half-life of PD-L1 but significantly inhibits the transcription of PD-L1. Among the transcription factors that regulate PD-L1 expression, c-Myc is downregulated by Bafetinib. Bafetinib caused PD-L1 inhibition is abolished when c-Myc is knocked-down. Further, we identified that Bafetinib reduced c-Myc expression because of transcription inhibition. By using the CT26 tumor model, we further confirm that Bafetinib suppressed PD-L1 expression

Indexed as

bafetinibc-Myclung cancerPD-L1transcription

Identifiers

PMID35721177
PMCPMC9201485

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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.