Evidence map›Paper›PMID 36031328›Full record

ArticleMolecular cancer therapeutics2022

Systemic Checkpoint Blockade by PD-L1 Single-Chain Antibody Confers Potent Antitumor Immunity and Long-term Survival.

Hong Wang, Vinayak Khattar, Jonathan A Hensel, Reading Ashton, Yun Lu, Anna G Sorace, Yong Wang, Jessy S Deshane, Joshua L Mieher, Champion Deivanayagam and 1 more

Open access · greenAbstract read
In one paragraph

Article in Molecular cancer therapeutics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.4field-weighted citation impact, top 37% 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

4 citing papers in PubMed, 4 citations in OpenAlex.

  1. Review
  2. Article
  3. Fibroblasts: invigorated targets in pre-metastatic niche formation.International journal of biological sciences · 2024
    Review
  4. Review
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

11 authors at 2 institutions in 1 country.

Hong WangDepartment of Pathology, The University of Alabama at Birmingham, Birmingham, Alabama.ORCID 0000-0001-5784-7876
Vinayak KhattarDepartment of Pathology, The University of Alabama at Birmingham, Birmingham, Alabama.ORCID 0000-0002-0483-7671
Jonathan A HenselDepartment of Pathology, The University of Alabama at Birmingham, Birmingham, Alabama.ORCID 0000-0003-1594-7013
Reading AshtonDepartment of Pathology, The University of Alabama at Birmingham, Birmingham, Alabama.ORCID 0000-0002-3708-758X
Yun LuDepartment of Radiology, The University of Alabama at Birmingham, Birmingham, Alabama.ORCID 0000-0002-4785-3401
Anna G SoraceDepartment of Radiology, The University of Alabama at Birmingham, Birmingham, Alabama.ORCID 0000-0002-3640-3966
Yong WangDepartment of Medicine, The University of Alabama at Birmingham, Birmingham, Alabama.ORCID 0000-0002-9206-6503
Jessy S DeshaneDepartment of Medicine, The University of Alabama at Birmingham, Birmingham, Alabama.ORCID 0000-0002-6761-5662
Joshua L MieherDepartment of Biochemistry and Molecular Genetics, The University of Alabama at Birmingham, Birmingham, Alabama.ORCID 0000-0003-4388-2392
Champion DeivanayagamDepartment of Biochemistry and Molecular Genetics, The University of Alabama at Birmingham, Birmingham, Alabama.ORCID 0000-0003-2972-1824
Selvarangan PonnazhaganDepartment of Pathology, The University of Alabama at Birmingham, Birmingham, Alabama.ORCID 0000-0001-5219-8379
University of Alabama at Birmingham · USMoffitt Cancer Center · US

Funding

XRAY CRYSTALLOGRAPHYP30CA013148 · NCI · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI Robert S Welner · 1985 to 2026
$165.9M
Project 5 Nano-micro Hybrid Fibrous Materials for Containment Removal and Site RemediationP42ES027723 · NIEHS · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI ANTONY, VEENA B. · 2020 to 2024
$6.7M
Targeted therapy for breast cancer with osteolytic bone damageR01CA184770 · NCI · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI PONNAZHAGAN, SELVARANGAN · 2015 to 2019
$1.7M
NCI NIH HHS P30 CA013148NCI NIH HHS R01 CA184770NIEHS NIH HHS P42 ES027723
6 · The paper itself

Abstract

Immune checkpoint inhibitors (ICI) are promising in adjuvant settings for solid tumors and hematologic malignancies. They are currently used in the treatment as mAbs in high concentrations, raising concerns of toxicity and adverse side effects. Among various checkpoint molecules, targeting the programmed cell death protein-1 (PD-1)-programmed death-ligand 1 (PD-L1) axis has garnered more clinical utility than others have. To develop a physiologically relevant and systemically stable level of ICIs from a one-time application by genetic antibody engineering, we endeavored using a nonpathogenic, replication-deficient recombinant adeno-associated vector (rAAV) expressing single-chain variable fragments (scFv) of PD-L1 antibody and tested in syngeneic mouse therapy models of MC38 colorectal and EMT6 breast tumors. Results of this study indicated a significant protection against PD-L1-mediated inhibition of CD8+ T-cell function, against the growth of primary and secondary tumors, and durable antitumor CTLs activity by adoptive CD8+ T-cell transfer. Stable maintenance of PD-L1 scFv in vivo resulted in an increase in PD-1- CD8+ T cells and a concomitant decrease in regulatory T cells, M2 macrophages, and myeloid-derived suppressor cells in the tumor microenvironment. Overall, these data demonstrate the potential of rAAV-PD-L1-scFv as an alternative to mAb targeting of PD-L1 for tumor therapy.

Indexed as

B7-H1 AntigenNeoplasmsAnimalsAntibodies, MonoclonalImmunotherapyMiceProgrammed Cell Death 1 ReceptorTumor MicroenvironmentAntibodies, MonoclonalB7-H1 AntigenCD274 protein, humanProgrammed Cell Death 1 Receptor

Identifiers

PMID36031328
PMCPMC9633566
OpenAlexW4293414870

What OpenQuestion holds

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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.