Evidence map›Paper›PMID 40502681›Full record

ReviewiScience2025

Complex regulatory network of programmed death-ligand 1 in cancer: Cancer immunomodulation from molecular mechanisms to clinical applications.

Yifei Zhang, Keyu Yin, Runsheng Ma, Yuxiao Sun, Longlong Wang, Detao Yin

Abstract readReview
In one paragraph

Review in iScience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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

6 authors.

Yifei ZhangDepartment of Thyroid Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Keyu YinDepartment of Human Anatomy, College of Basic Medical Sciences, Lanzhou University, Gansu, China.
Runsheng MaDepartment of Thyroid Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Yuxiao SunDepartment of Thyroid Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Longlong WangDepartment of Thyroid Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Detao YinDepartment of Thyroid Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Immune checkpoint therapy targeting PD-L1/PD-1 represents a key cancer treatment strategy. PD-L1 binds PD-1 on T cells, suppressing activation and enabling tumor immune escape. Although the blockade of the PD-L1/PD-1 pathway has demonstrated significant anti-tumor effects, the overall response rate remains suboptimal in solid tumors. Therefore, understanding the molecular mechanisms underlying PD-L1 deregulation is essential for enhancing the efficacy of PD-L1/PD-1 blockade therapies. As our comprehension of the regulatory mechanisms governing the PD-L1/PD-1 pathway continues to evolve, ongoing exploration of new immunotherapy targets remains critical. This article provides a comprehensive review of recent research concerning the regulation of PD-L1 expression. It encompasses aspects such as its structural characteristics, genomic alterations and rearrangements, epigenetic modifications, inflammatory signaling pathways, oncogenic signaling pathways, microRNA regulation, and post-translational modifications. Additionally, this article illustrates notable advancements and limitations regarding the application of PD-L1 as an immunotherapeutic target in current clinical settings.

Indexed as

CancerImmunology

Identifiers

PMID40502681
PMCPMC12152662

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.