Evidence map›Paper›PMID 35444660›Full record

ArticleFrontiers in immunology2022

Discovery of Anti-PD-L1 Human Domain Antibodies for Cancer Immunotherapy.

Hao Liu, Yanli Liu, Zhen Zhao, Yuanke Li, Bahaa Mustafa, Zhijin Chen, Ashutosh Barve, Akshay Jain, Xiaolan Yao, Guangfu Li and 1 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.7field-weighted citation impact, top 17% 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

6 citing papers in PubMed, 12 citations in OpenAlex.

  1. Review
  2. Review
  3. Targeting PD-L1 in cholangiocarcinoma using nanovesicle-based immunotherapy.Molecular therapy : the journal of the American Society of Gene Therapy · 2024
    Article
  4. Review
  5. Review
  6. 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.

Hao LiuDivision of Pharmacology and Pharmaceutical Sciences, School of Pharmacy, University of Missouri-Kansas City, Kansas City, MO, United States.
Yanli LiuDivision of Pharmacology and Pharmaceutical Sciences, School of Pharmacy, University of Missouri-Kansas City, Kansas City, MO, United States.
Zhen ZhaoDivision of Pharmacology and Pharmaceutical Sciences, School of Pharmacy, University of Missouri-Kansas City, Kansas City, MO, United States.
Yuanke LiDivision of Pharmacology and Pharmaceutical Sciences, School of Pharmacy, University of Missouri-Kansas City, Kansas City, MO, United States.
Bahaa MustafaDivision of Pharmacology and Pharmaceutical Sciences, School of Pharmacy, University of Missouri-Kansas City, Kansas City, MO, United States.
Zhijin ChenDivision of Pharmacology and Pharmaceutical Sciences, School of Pharmacy, University of Missouri-Kansas City, Kansas City, MO, United States.
Ashutosh BarveDivision of Pharmacology and Pharmaceutical Sciences, School of Pharmacy, University of Missouri-Kansas City, Kansas City, MO, United States.
Akshay JainDivision of Pharmacology and Pharmaceutical Sciences, School of Pharmacy, University of Missouri-Kansas City, Kansas City, MO, United States.
Xiaolan YaoDepartment of Cell and Molecular Biology and Biochemistry, School of Biological and Chemical Sciences, University of Missouri-Kansas City, Kansas City, MO, United States.
Guangfu LiDepartment of Surgery, and Molecular Microbiology & Immunology, School of Medicine, University of Missouri, Columbia, MO, United States.
Kun ChengDivision of Pharmacology and Pharmaceutical Sciences, School of Pharmacy, University of Missouri-Kansas City, Kansas City, MO, United States.
University of Missouri–Kansas City · USUniversity of Missouri · US

Funding

Targeted delivery of PCBP2 siRNA for treating alcoholic liver fibrosisR01AA021510 · NIAAA · UNIVERSITY OF MISSOURI KANSAS CITY · PI CHENG, KUN · 2012 to 2022
$3.8M
Development of a targeted delivery platform for checkpoint inhibitorsR01CA231099 · NCI · UNIVERSITY OF MISSOURI KANSAS CITY · PI CHENG, KUN · 2018 to 2022
$1.8M
NCI NIH HHS R01 CA231099NIAAA NIH HHS R01 AA021510
6 · The paper itself

Abstract

Immunotherapy using monoclonal antibodies targeting the PD-1/PD-L1 interaction has shown enormous success for various cancers. Despite their encouraging results in clinics, antibody-based checkpoint inhibitors have several limitations, such as poor tumor penetration. To address these limitations of monoclonal antibodies, there is a growing interest in developing low-molecular-weight checkpoint inhibitors, such as antibody fragments. Several antibody fragments targeting PD-1/PD-L1 were recently discovered using phage libraries from camel or alpaca. However, animal-derived antibody fragments may elicit unwanted immune responses, which limit their therapeutic applications. For the first time, we used a human domain antibody phage library and discovered anti-human PD-L1 human single-domain antibodies (dAbs) that block the PD-1/PD-L1 interaction. Among them, the CLV3 dAb shows the highest affinity to PD-L1. The CLV3 dAb also exhibits the highest blocking efficacy of the PD-1/PD-L1 interaction. Moreover, the CLV3 dAb significantly inhibits tumor growth in mice implanted with CT26 colon carcinoma cells. These results suggest that CLV3 dAb can be potentially used as an anti-PD-L1 inhibitor for cancer immunotherapy.

Indexed as

Antineoplastic Agents, ImmunologicalColonic NeoplasmsSingle-Domain AntibodiesAnimalsAntibodies, MonoclonalB7-H1 AntigenHumansImmunotherapyMiceProgrammed Cell Death 1 ReceptorAntibodies, MonoclonalAntineoplastic Agents, ImmunologicalB7-H1 AntigenProgrammed Cell Death 1 ReceptorSingle-Domain Antibodiescheckpointhuman single-domain antibody (dAb)immunotherapyPD-L1phage display

Identifiers

PMID35444660
PMCPMC9013927
OpenAlexW4225811843

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.