Evidence map›Paper›PMID 41583479›Full record

ArticleFrontiers in immunology2025

Targeting the epidermal growth factor receptor using IgM antibodies: toward next generation cancer immunotherapy.

Kamolrat Somboon, Peter J Bond, Firdaus Samsudin

Abstract read
In one paragraph

Article in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Kamolrat SomboonBioinformatics Institute (BII), Agency for Science, Technology and Research (ASTAR), Singapore, Singapore.
Peter J BondBioinformatics Institute (BII), Agency for Science, Technology and Research (ASTAR), Singapore, Singapore.
Firdaus SamsudinBioinformatics Institute (BII), Agency for Science, Technology and Research (ASTAR), Singapore, Singapore.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Immunoglobulin G (IgG) monoclonal antibodies dominate current cancer immunotherapy but face challenges including resistance development, limited tumor penetration, and suboptimal avidity. In contrast, the pentameric or hexameric architecture of immunoglobulin M (IgM) offers up to twelve antigen-binding sites and potent complement activation, positioning IgM as a promising next-generation therapeutic scaffold. Here, we present integrative structural modeling and multiscale molecular dynamics simulations of IgM versions of Cetuximab and Matuzumab targeting the epidermal growth factor receptor (EGFR), a clinically validated oncogenic driver. Our analyses reveal that IgM antibodies maintain a rigid, glycan-stabilized Fc core while their Fab domains exhibit high mobility, enabling multivalent EGFR binding. Compared with IgG, IgM antibodies demonstrated enhanced binding avidity, prolonged receptor engagement, and slower dissociation kinetics. These properties suggest superior therapeutic durability and potential to overcome current limitations of IgG-based therapies. By providing mechanistic insight into how IgM isotypes can improve therapeutic engagement with tumor-associated antigens, our study supports the development of IgM antibodies as a new class of cancer immunotherapies.

Indexed as

Antibodies, Monoclonal, HumanizedAntineoplastic Agents, ImmunologicalCetuximabErbB ReceptorsImmunoglobulin MImmunotherapyNeoplasmsHumansImmunoglobulin GMolecular Dynamics SimulationProtein BindingAntibodies, Monoclonal, HumanizedAntineoplastic Agents, ImmunologicalCetuximabEGFR protein, humanErbB ReceptorsImmunoglobulin GImmunoglobulin MmatuzumabcancerCetuximabEGFRIgMMatuzumabmonoclonal antibody

Identifiers

PMID41583479
PMCPMC12827627

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Registered trials

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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.