Evidence map›Paper›PMID 33224142›Full record

ArticleFrontiers in immunology2020

The Change of Soluble Programmed Cell Death-Ligand 1 in Glioma Patients Receiving Radiotherapy and Its Impact on Clinical Outcomes.

Xing-Chen Ding, Liang-Liang Wang, Yu-Fang Zhu, Yan-Dong Li, Shu-Lun Nie, Jia Yang, Hua Liang, Ralph R Weichselbaum, Jin-Ming Yu, Man Hu

Abstract read
In one paragraph

Article in Frontiers in immunology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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  7. Radiotherapy and immunology.The Journal of experimental medicine · 2024
    Review
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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

10 authors.

Xing-Chen DingDepartment of Oncology, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.
Liang-Liang WangDepartment of Radiation and Cellular Oncology, Ludwig Center for Metastasis Research, The University of Chicago, Chicago, IL, United States.
Yu-Fang ZhuDepartment of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.
Yan-Dong LiDepartment of Anesthesiology, Affiliated Hospital of Jining Medical University, Jinan, China.
Shu-Lun NieDepartment of Oncology, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.
Jia YangDepartment of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.
Hua LiangDepartment of Radiation and Cellular Oncology, Ludwig Center for Metastasis Research, The University of Chicago, Chicago, IL, United States.
Ralph R WeichselbaumDepartment of Radiation and Cellular Oncology, Ludwig Center for Metastasis Research, The University of Chicago, Chicago, IL, United States.
Jin-Ming YuDepartment of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.
Man HuDepartment of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The programmed cell death ligand 1 (PD-L1) plays a key role in glioma development. However, due to the specificity of glioma's anatomical position, the role of its expression as a tumor biomarker is limited. It has been proven that the levels of soluble programmed death-ligand 1 (sPD-L1) are associated with prognosis in many malignancies including glioma. However, the expression of sPD-L1 in glioma patients receiving radiotherapy (RT) remains unclear. The purpose of this study was to evaluate the concentration of sPD-L1 in the plasma of glioma patients before and after RT and to explore its relationship with clinical outcomes. Methods: Between October 2017 and September 2018, glioma patients treated with RT (30 ± 10 Gy, 2 Gy/f) were enrolled, and blood samples were collected before and after RT. We quantified the sPD-L1 levels by enzyme-linked immunosorbent assay (ELISA). The isocitrate dehydrogenase-1 (IDH-1) mutational status and Ki-67 expression of tumors were evaluated by immunohistochemistry. Glioma murine model were used to address whether circulating sPD-L1 molecules are directly targeted by an anti-PD-L1 antibody. The associations between sPD-L1 and clinical features were assessed with Pearson's or Spearman's correlation analysis. The progression-free survival (PFS) and overall survival (OS) were determined by the Kaplan-Meier method. Results: Sixty glioma patients were included, with a median age of 52 years. The proportions of grade I, II, III, and IV gliomas were 6.7%, 23.3%, 28.4%, and 41.6%, respectively. The baseline sPD-L1 levels were significantly associated with tumor grade, IDH-1 mutation status and Ki-67 expression. Using 14.35 pg/ml as the cutoff, significantly worse PFS and OS were both observed in patients with higher baseline levels of sPD-L1 ( Conclusion: This study reported that sPD-L1 might be a potential biomarker to predict the outcome in glioma patients receiving RT. The elevated level of sPD-L1 after RT suggested that the strategy of a combination of immune checkpoint inhibitors and RT might be promising for glioma patients, especially for those with IDH-1 mutations.

Indexed as

AdolescentAdultAgedB7-H1 AntigenBiomarkersBrain NeoplasmsCell Line, TumorFemaleGene Expression Regulation, NeoplasticGliomaHumansIsocitrate DehydrogenaseMaleMiddle AgedMutationSurvival AnalysisB7-H1 AntigenBiomarkersIsocitrate Dehydrogenaseclinical significancegliomaprognosisradiotherapysoluble programmed cell death-ligand 1

Identifiers

PMID33224142
PMCPMC7668030

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Registered trials

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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.