Evidence map›Paper›PMID 41496609›Full record

ArticleNuclear medicine communications2026

Preclinical evaluation of an antibody-based companion diagnostic for CD44v6 expressing cancer.

Maryam Oroujeni, Ram Kumar Selvaraju, Helena Persson, Leif Dahllund, Fredrik Y Frejd, Anja C L Mortensen

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In one paragraph

Article in Nuclear medicine communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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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

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Maryam OroujeniDepartment of Immunology, Genetics and Pathology.
Ram Kumar SelvarajuPreclinical PET-MRI Platform, Department of Medicinal Chemistry, Uppsala University, Uppsala.
Helena PerssonDrug Discovery and Development Platform, Science for Life Laboratories.
Leif DahllundDrug Discovery and Development Platform, Science for Life Laboratories.
Fredrik Y FrejdDepartment of Immunology, Genetics and Pathology.
Anja C L MortensenDepartment of Immunology, Genetics and Pathology.ORCID 0000-0002-6771-3289

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveDevelopment of companion diagnostics for targeted radionuclide therapy is critical, especially for full-size antibodies with prolonged circulation times. Engineering antibodies to modify their in-vivo pharmacokinetics, such as incorporating neonatal Fc receptor (FcRn)-binding mutations, can potentially enable earlier imaging timing and improved patient stratification. This study aimed to evaluate the impact of FcRn-binding mutations on the in-vitro binding characteristics and in-vivo biodistribution and imaging performance of a CD44v6-targeting full-size antibody, UU-40, labeled with different radionuclides, and to assess its potential as a companion diagnostic.

methodsThe study involved engineering UU-40 with LALA and IAHA mutations, evaluating specific binding, internalization, and affinity using in-vitro cell assays. Biodistribution and imaging studies [PET and single-photon emission computed tomography (SPECT)] were conducted in mice carrying human tumor xenografts in a dual-nuclide setting.

resultsThe FcRn mutations (LALA/IAHA) did not affect antibody specificity or affinity, which was target-specific and affinity remained in the subnanomolar range. Biodistribution studies demonstrated that the residualizing radiometal label ( 177 Lu) resulted in higher liver and spleen uptake compared with the nonresidualizing 125 I-label, leading to reduced tumor-to-organ ratios. Tumor uptake was higher in A431 xenografts, with peak accumulation at 24 h postinjection. SPECT and PET imaging confirmed superior contrast at later time points (~24 h) with 125 I-UU-40 LALA/IAHA , while earlier imaging with 68 Ga was hindered by increased nonspecific accumulation.

conclusionFcRn-binding mutations in full-size antibodies significantly alter their in-vivo pharmacokinetics without affecting binding affinity or specificity. Introducing these mutations enables earlier imaging time points, enhancing the potential for companion diagnostics in clinical settings.

Indexed as

Gene Expression Regulation, NeoplasticHyaluronan ReceptorsNeoplasmsAnimalsCell Line, TumorHistocompatibility Antigens Class IHumansMiceMutationReceptors, FcTissue DistributionTomography, Emission-Computed, Single-PhotonCD44v6 antigenFc receptor, neonatalHistocompatibility Antigens Class IHyaluronan ReceptorsReceptors, Fcantibody engineeringCD44v6companion diagnosticsneonatal Fc receptor mutationsPETradiolabeled antibodiessingle-photon emission computed tomography imaging

Identifiers

PMID41496609
PMCPMC12955976

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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.