Evidence map›Paper›PMID 35794161›Full record

ArticleScientific reports2022

PD-L1 regulates cell proliferation and apoptosis in acute myeloid leukemia by activating PI3K-AKT signaling pathway.

Fang Wang, Liqiong Yang, Mintao Xiao, Zhuo Zhang, Jing Shen, Songyot Anuchapreeda, Singkome Tima, Sawitree Chiampanichayakul, Zhangang Xiao

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.

0numbers the graph read from it
0cells of the map it votes in
48citing papers in PubMed
6.4field-weighted citation impact, top 2% 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

48 citing papers in PubMed, 76 citations in OpenAlex.

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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

9 authors at 3 institutions in 2 countries.

Fang Wang *Department of Medical Technology, Faculty of Associated Medical Sciences, Chiang Mai University, Chiang Mai, Thailand.
Liqiong Yang *Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, China.
Mintao XiaoLaboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, China.
Zhuo ZhangDepartment of Medical Technology, Faculty of Associated Medical Sciences, Chiang Mai University, Chiang Mai, Thailand.
Jing ShenLaboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, China.
Songyot AnuchapreedaDepartment of Medical Technology, Faculty of Associated Medical Sciences, Chiang Mai University, Chiang Mai, Thailand.
Singkome TimaDepartment of Medical Technology, Faculty of Associated Medical Sciences, Chiang Mai University, Chiang Mai, Thailand.
Sawitree ChiampanichayakulDepartment of Medical Technology, Faculty of Associated Medical Sciences, Chiang Mai University, Chiang Mai, Thailand. sawitree.chiampa@cmu.ac.th.
Zhangang XiaoLaboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, China. zhangangxiao@swmu.edu.cn.
Chiang Mai University · THSouthwest Medical University · CNFirst Affiliated Hospital of Sichuan Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As immune checkpoint inhibitors (ICIs) continue to advance, more evidence has emerged that anti-PD-1/PD-L1 immunotherapy is an effective treatment against cancers. Known as the programmed death ligand-1 (PD-L1), this co-inhibitory ligand contributes to T cell exhaustion by interacting with programmed death-1 (PD-1) receptor. However, cancer-intrinsic signaling pathways of the PD-L1 molecule are not well elucidated. Therefore, the present study aimed to evaluate the regulatory network of PD-L1 and lay the basis of successful use of anti-PD-L1 immunotherapy in acute myeloid leukemia (AML). Data for AML patients were extracted from TCGA and GTEx databases. The downstream signaling pathways of PD-L1 were identified via Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. The key PD-L1 related genes were selected by weighted gene co-expression network analysis (WGCNA), MCC algorithm and Molecular Complex Detection (MCODE). The CCK-8 assay was used to assess cell proliferation. Flow cytometry was used to determine cell apoptosis and cell cycle. Western blotting was used to identify the expression of the PI3K-AKT signaling pathway. PD-L1 was shown to be elevated in AML patients when compared with the control group, and high PD-L1 expression was associated with poor overall survival rate. The ECM-receptor interaction, as well as the PI3K-AKT signaling pathway, were important PD-L1 downstream pathways. All three analyses found eight genes (ITGA2B, ITGB3, COL6A5, COL6A6, PF4, NMU, AGTR1, F2RL3) to be significantly associated with PD-L1. Knockdown of PD-L1 inhibited AML cell proliferation, induced cell apoptosis and G2/M cell cycle arrest. Importantly, PD-L1 knockdown reduced the expression of PI3K and p-AKT, but PD-L1 overexpression increased their expression. The current study elucidates the main regulatory network and downstream targets of PD-L1 in AML, assisting in the understanding of the underlying mechanism of anti-PD-1/PD-L1 immunotherapy and paving the way for clinical application of ICIs in AML.

Indexed as

B7-H1 AntigenLeukemia, Myeloid, AcutePhosphatidylinositol 3-KinasesProto-Oncogene Proteins c-aktApoptosisCell ProliferationHumansProgrammed Cell Death 1 ReceptorSignal TransductionB7-H1 AntigenCD274 protein, humanPhosphatidylinositol 3-KinasesProgrammed Cell Death 1 ReceptorProto-Oncogene Proteins c-akt

Identifiers

PMID35794161
PMCPMC9259561
OpenAlexW4284889639

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.