ArticlePharmaceutics2020
Evaluating the Therapeutic Efficacy of Mono- and Bivalent Affibody-Based Fusion Proteins Targeting HER3 in a Pancreatic Cancer Xenograft Model.
Article in Pharmaceutics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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.
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.
Who cites it
8 citing papers in PubMed, 14 citations in OpenAlex.
- Affibody-Drug Conjugates Targeting the Human Epidermal Growth Factor Receptor-3 Demonstrate Therapeutic Efficacy in Mice Bearing Low Expressing Xenografts.ACS pharmacology & translational science · 2024Article
- Surface-engineered bacteria in drug development.Microbial biotechnology · 2024Review
- Feasibility of Co-Targeting HER3 and EpCAM Using Seribantumab and DARPin-Toxin Fusion in a Pancreatic Cancer Xenograft Model.International journal of molecular sciences · 2023Article
- HER3 in cancer: from the bench to the bedside.Journal of experimental & clinical cancer research : CR · 2022Review
- Targeting Tumor Cells Overexpressing the Human Epidermal Growth Factor Receptor 3 with Potent Drug Conjugates Based on Affibody Molecules.Biomedicines · 2022Article
- Liver Endothelium Microenvironment Promotes HER3-mediated Cell Growth in Pancreatic Ductal Adenocarcinoma.Journal of cancer science and clinical therapeutics · 2022Article
- HER3 PET Imaging:Cancers · 2021Article
- PET and SPECT Imaging of the EGFR Family (RTK Class I) in Oncology.International journal of molecular sciences · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Human epidermal growth factor receptor 3 (HER3) has been increasingly scrutinized as a potential drug target since the elucidation of its role in mediating tumor growth and acquired therapy resistance. Affibody molecules are so-called scaffold proteins with favorable biophysical properties, such as a small size for improved tissue penetration and extravasation, thermal and chemical stability, and a high tolerance to modifications. Additionally, affibody molecules are efficiently produced in prokaryotic hosts or by chemical peptide synthesis. We have previously evaluated the biodistribution profiles of five mono- and bivalent anti-HER3 affibody molecules (designated as 3) fused to an albumin-binding domain (designated as A), 3A, 33A, 3A3, A33, and A3, that inhibit ligand-dependent phosphorylation. In the present study, we examined the therapeutic efficacy of the three most promising variants, 3A, 33A, and 3A3, in a direct comparison with the HER3-targeting monoclonal antibody seribantumab (MM-121) in a preclinical BxPC-3 pancreatic cancer model. Xenografted mice were treated with either an affibody construct or MM-121 and the tumor growth was compared to a vehicle group. Receptor occupancy was estimated by positron emission tomography/computed tomography (PET/CT) imaging using a HER3-targeting affibody imaging agent [
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Registered trials
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.