Evidence map›Paper›PMID 37628671›Full record

ArticleGenes2023

The 3' Non-Coding Sequence Negatively Regulates PD-L1 Expression, and Its Regulators Are Systematically Identified in Pan-Cancer.

Zike Chen, Hui Pi, Wen Zheng, Xiaohong Guo, Conglin Shi, Zhiyang Wang, Jie Zhang, Xuanhao Qu, Lehan Liu, Haoliang Shen and 5 more

Open access · goldAbstract read
In one paragraph

Article in Genes, 2023. 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
0.9field-weighted citation impact, top 25% 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

3 citing papers in PubMed, 6 citations in OpenAlex.

  1. Review
  2. Review
  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

15 authors at 2 institutions in 1 country.

Zike ChenLaboratory of Medical Science, School of Medicine, Nantong University, Nantong 226001, China.
Hui PiDepartment of Pathophysiology, School of Medicine, Nantong University, Nantong 226001, China.
Wen ZhengDepartment of Pathogenic Biology, School of Medicine, Nantong University, Nantong 226001, China.
Xiaohong GuoDepartment of Pathogenic Biology, School of Medicine, Nantong University, Nantong 226001, China.
Conglin ShiDepartment of Pathogenic Biology, School of Medicine, Nantong University, Nantong 226001, China.
Zhiyang WangLaboratory of Medical Science, School of Medicine, Nantong University, Nantong 226001, China.
Jie ZhangLaboratory of Medical Science, School of Medicine, Nantong University, Nantong 226001, China.
Xuanhao QuLaboratory of Medical Science, School of Medicine, Nantong University, Nantong 226001, China.
Lehan LiuLaboratory of Medical Science, School of Medicine, Nantong University, Nantong 226001, China.
Haoliang ShenThe Intensive Care Unit, Affiliated Hospital of Nantong University, Nantong 226001, China.
Yang LuThe Intensive Care Unit, Affiliated Hospital of Nantong University, Nantong 226001, China.
Miaomiao ChenLaboratory of Medical Science, School of Medicine, Nantong University, Nantong 226001, China.
Weibing ZhangNantong Center for Disease Control and Prevention, Nantong 226001, China.
Rong SunLaboratory of Medical Science, School of Medicine, Nantong University, Nantong 226001, China.
Yihui FanLaboratory of Medical Science, School of Medicine, Nantong University, Nantong 226001, China.
Nantong University · CNAffiliated Hospital of Nantong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The 3'-untranslated region (3'-UTR) of PD-L1 is significantly longer than the coding sequences (CDSs). However, its role and regulators have been little studied. We deleted whole 3'-UTR region by CRISPR-Cas9. Prognostic analysis was performed using online tools. Immune infiltration analysis was performed using the Timer and Xcell packages. Immunotherapy response prediction and Cox regression was performed using the R software. MicroRNA network analysis was conducted by the Cytoscape software. The level of PD-L1 was significantly and dramatically up-regulated in cells after deleting the 3'-UTR. Additionally, we discovered a panel of 43 RNA-binding proteins (RBPs) whose expression correlates with PD-L1 in the majority of cancer cell lines and tumor tissues. Among these RBPs, PARP14 is widely associated with immune checkpoints, the tumor microenvironment, and immune-infiltrating cells in various cancer types. We also identified 38 microRNAs whose individual expressions are associated with PD-L1 across different cancers. Notably, miR-3139, miR-4761, and miR-15a-5p showed significant associations with PD-L1 in most cancer types. Furthermore, we revealed 21 m6A regulators that strongly correlate with PD-L1. Importantly, by combining the identified RBP and m6A regulators, we established an immune signature consisting of RBMS1, QKI, ZC3HAV1, and RBM38. This signature can be used to predict the responsiveness of cancer patients to immune checkpoint blockade treatment. We demonstrated the critical role of the 3'-UTR in the regulation of PD-L1 and identified a significant number of potential PD-L1 regulators across various types of cancer. The biomarker signature generated from our findings shows promise in predicting patient prognosis. However, further biological investigation is necessary to explore the potential of these PD-L1 regulators.

Indexed as

MicroRNAsNeoplasms3' Untranslated RegionsB7-H1 AntigenCell LineDNA-Binding ProteinsHumansRNA-Binding ProteinsTumor Microenvironment3' Untranslated RegionsB7-H1 AntigenDNA-Binding ProteinsMicroRNAsRBM38 protein, humanRBMS1 protein, humanRNA-Binding Proteins3′-untranslated region (3′-UTR)m6A regulatormiRNAsPD-L1RNA-binding proteins (RBPs)

Identifiers

PMID37628671
PMCPMC10454350
OpenAlexW4385795999

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.