Evidence map›Paper›PMID 33028895›Full record

ArticleScientific reports2020

Modeling the dynamics of antibody-target binding in living tumors.

Yu Tang, Yanguang Cao

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.0field-weighted citation impact, top 20% 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

9 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
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  5. Physiological Considerations for ModelingFrontiers in pharmacology · 2022
    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

2 authors at 2 institutions in 1 country.

Yu TangDivision of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, 27599, USA.
Yanguang CaoDivision of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, 27599, USA. yanguang@unc.edu.
UNC Lineberger Comprehensive Cancer CenterUniversity of North Carolina at Chapel Hill · US

Funding

Optimizing antibody-based therapy through a system platform of pharmacokinetics-pharmacodynamics-immunodynamicsR35GM119661 · NIGMS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI CAO, YANGUANG · 2016 to 2020
$2.1M
NIGMS NIH HHS R35 GM119661NIH HHS GM119661
6 · The paper itself

Abstract

Antibodies have become an attractive class of therapeutic agents for solid tumors, mainly because of their high target selectivity and affinity. The target binding properties of antibodies are critical for their efficacy and toxicity. Our lab has developed a bioluminescence resonance energy transfer (BRET) imaging approach that directly supports the measurement of the binding dynamics between antibodies and their targets in the native tumor environment. In the present study, we have developed a spatially resolved computational model analyzing the longitudinal BRET imaging data of antibody-target binding and exploring the mechanisms of biphasic binding dynamics between a model antibody cetuximab and its target, the epidermal growth factor receptor (EGFR). The model suggested that cetuximab is bound differently to EGFR in the stroma-rich area than in stroma-poor regions, which was confirmed by immunofluorescence staining. Compared to the binding in vitro, cetuximab bound to EGFR to a "slower-but-tighter" degree in the living tumors. These findings have provided spatially resolved characterizations of antibody-target binding in living tumors and have yielded many mechanistic insights into the factors that affect antibody interactions with its targets and treatment efficacy.

Indexed as

Models, TheoreticalAnimalsAntibodies, MonoclonalBinding Sites, AntibodyCetuximabErbB ReceptorsHEK293 CellsHumansMice, NudeNeoplasmsXenograft Model Antitumor AssaysAntibodies, MonoclonalCetuximabErbB Receptors

Identifiers

PMID33028895
PMCPMC7542163
OpenAlexW3092444763

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.