Evidence map›Paper›PMID 38665824›Full record

ReviewRSC medicinal chemistry2024

Beyond inhibition against the PD-1/PD-L1 pathway: development of PD-L1 inhibitors targeting internalization and degradation of PD-L1.

Jiazheng Guo, Fengyi Yu, Kuojun Zhang, Sheng Jiang, Xiangyu Zhang, Tianyu Wang

Open access · greenAbstract readReview
In one paragraph

Review in RSC medicinal chemistry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
3.0field-weighted citation impact, top 8% 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

7 citing papers in PubMed, 13 citations in OpenAlex.

  1. 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

6 authors at 1 institution in 1 country.

Jiazheng GuoSchool of Pharmacy, China Pharmaceutical University Nanjing 210009 China wangtianyu527@126.com.
Fengyi YuSchool of Pharmacy, China Pharmaceutical University Nanjing 210009 China wangtianyu527@126.com.
Kuojun ZhangSchool of Pharmacy, China Pharmaceutical University Nanjing 210009 China wangtianyu527@126.com.
Sheng JiangSchool of Pharmacy, China Pharmaceutical University Nanjing 210009 China wangtianyu527@126.com.
Xiangyu ZhangSchool of Pharmacy, China Pharmaceutical University Nanjing 210009 China wangtianyu527@126.com.
Tianyu WangSchool of Pharmacy, China Pharmaceutical University Nanjing 210009 China wangtianyu527@126.com.ORCID https://orcid.org/0009-0009-2688-5015
China Pharmaceutical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tumor cells hijack the programmed cell death protein-1 (PD-1)/programmed cell death ligand-1 (PD-L1) pathway to suppress the immune response through overexpressing PD-L1 to interact with PD-1 of T cells. With in-depth ongoing research, tumor-intrinsic PD-L1 is found to play important roles in tumor progression without interaction with PD-1 expressed on T cells, which provides an additional important target and therapeutic approach for development of PD-L1 inhibitors. Existing monoclonal antibody (mAb) drugs against the PD-1/PD-L1 pathway generally behave by conformationally blocking the interactions of PD-1 with PD-L1 on the cell surface. Beyond general inhibition of the protein-protein interaction (PPI), inhibitors targeting PD-L1 currently focus on the functional inhibition of the interaction between PD-1/PD-L1 and degradation of tumor-intrinsic PD-L1. This perspective will clarify the evolution of PD-L1 inhibitors and provide insights into the current development of PD-L1 inhibitors, especially targeting internalization and degradation of PD-L1.

Identifiers

PMID38665824
PMCPMC11042118
OpenAlexW4390077870

What OpenQuestion holds

Textmetadata
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.