Evidence map›Paper›PMID 26368334›Full record

ArticleAnalytical chemistry2015

Quantification of epidermal growth factor receptor expression level and binding kinetics on cell surfaces by surface plasmon resonance imaging.

Fenni Zhang, Shaopeng Wang, Linliang Yin, Yunze Yang, Yan Guan, Wei Wang, Han Xu, Nongjian Tao

Abstract read
In one paragraph

Article in Analytical chemistry, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 106 papers.

0numbers the graph read from it
0cells of the map it votes in
106citing papers in PubMed
11.6field-weighted citation impact, top 1% 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

106 citing papers in PubMed, 207 citations in OpenAlex.

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  18. Enhancing NK cell-mediated tumor killing of B7-H6Molecular therapy. Oncology · 2025
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  19. Article
  20. Article

46 more citing papers are in PubMed but not listed here.

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

8 authors at 5 institutions in 2 countries.

Fenni ZhangCenter for Bioelectronics and Biosensors, Biodesign Institute, Arizona State University , Tempe, Arizona 85287, United States.
Shaopeng WangCenter for Bioelectronics and Biosensors, Biodesign Institute, Arizona State University , Tempe, Arizona 85287, United States.
Linliang YinCenter for Bioelectronics and Biosensors, Biodesign Institute, Arizona State University , Tempe, Arizona 85287, United States.
Yunze YangCenter for Bioelectronics and Biosensors, Biodesign Institute, Arizona State University , Tempe, Arizona 85287, United States.
Yan GuanCenter for Bioelectronics and Biosensors, Biodesign Institute, Arizona State University , Tempe, Arizona 85287, United States.
Wei WangState Key Laboratory of Analytical Chemistry for Life Science, School of Chemistry and Chemical Engineering, Nanjing University , Nanjing 210093, China.
Han XuAmgen Inc. , Thousand Oaks, California 91320, United States.
Nongjian TaoCenter for Bioelectronics and Biosensors, Biodesign Institute, Arizona State University , Tempe, Arizona 85287, United States.
Arizona State University · USBioElectronics (United States) · USAmgen (United States) · USChongqing University · CNNanjing University · CN

Funding

Quantitative label-free imaging of membrane protein interaction kinetics on cellsR01GM107165 · NIGMS · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI WANG, SHAOPENG · 2014 to 2021
$2.2M
Electrochemically-Enhanced Plasmonic Imaging for Quantitative ProteomicsR44GM106579 · NIGMS · BIOSENSING INSTRUMENT, INC. · PI LY, NGUYEN · 2013 to 2017
$1.9M
Nano-Oscillator Arrays for Sensitive Plasmonic Detection of Molecular Interactions and ReactionsR44GM126720 · NIGMS · BIOSENSING INSTRUMENT, INC. · PI LY, NGUYEN · 2018 to 2020
$1.6M
NIGMS NIH HHS 1R01GM107165-01A1NIGMS NIH HHS 1R44GM106579-01NIGMS NIH HHS R01 GM107165NIGMS NIH HHS R44 GM106579NIGMS NIH HHS R44 GM126720
6 · The paper itself

Abstract

Epidermal growth factor receptor (EGFR, also known as ErbB-1 or HER-1) is a membrane bound protein that has been associated with a variety of solid tumors and the control of cell survival, proliferation, and metabolism. Quantification of the EGFR expression level in cell membranes and the interaction kinetics with drugs are thus important for cancer diagnosis and treatment. Here we report mapping of the distribution and interaction kinetics of EGFR in their native environment with the surface plasmon resonance imaging (SPRi) technique. The monoclonal anti-EGFR antibody was used as a model drug in this study. The binding of the antibody to EGFR overexpressed A431 cells was monitored in real time, which was found to follow the first-order kinetics with an association rate constant (ka) and dissociation rate constant (kd) of (2.7 ± 0.6) × 10(5) M(-1) s(-1) and (1.4 ± 0.5) × 10(-4) s(-1), respectively. The dissociation constant (KD) was determined to be 0.53 ± 0.26 nM with up to seven-fold variation among different individual A431 cells. In addition, the averaged A431 cell surface EGFR density was found to be 636/μm(2) with an estimation of 5 × 10(5) EGFR per cell. Additional measurement also revealed that different EGFR positive cell lines (A431, HeLa, and A549) show receptor density dependent anti-EGFR binding kinetics. The results demonstrate that SPRi is a valuable tool for direct quantification of membrane protein expression level and ligand binding kinetics at single cell resolution. Our findings show that the local environment affects the drug-receptor interactions, and in situ measurement of membrane protein binding kinetics is important.

Indexed as

Antibodies, MonoclonalCell LineEquipment DesignErbB ReceptorsHeLa CellsHumansKineticsSurface Plasmon ResonanceAntibodies, MonoclonalEGFR protein, humanErbB Receptors

Identifiers

PMID26368334
PMCPMC4836855
OpenAlexW2265104901

What OpenQuestion holds

Textmetadata
LicenceTDM
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.