Domain binding and isotype dictate the activity of anti-human OX40 antibodies

Jordana Griffiths1, Khiyam Hussain1, Hannah L Smith1

  • 1Antibody and Vaccine Group, Centre for Cancer Immunology, Cancer Sciences Unit, Faculty of Medicine, University of Southampton, Southampton, UK.

Abstract

Insights

Optimizing anti-OX40 antibody therapy involves understanding how isotype and epitope influence T-cell responses. This research reveals how to enhance anti-tumor effects by selecting the right antibody properties for specific tumor types.

Area of Science:

  • Immunology
  • Oncology
  • Pharmacology

Background:

  • Anti-OX40 monoclonal antibodies (mAbs) show anti-tumor effects via Treg deletion, but clinical responses are disappointing.
  • OX40 also has costimulatory T-cell effects, suggesting potential for therapeutic responses.
  • Optimal use of anti-human OX40 (hOX40) antibodies requires understanding agonism vs. depleting activity.

Purpose of the Study:

  • Investigate a novel panel of anti-hOX40 mAbs to optimize therapeutic benefit.
  • Determine how isotype and epitope influence the mechanism of action and efficacy of anti-hOX40 mAbs.
  • Understand the role of agonism versus depleting activity in therapeutic outcomes.

Main Methods:

  • Evaluated binding activity and in vitro activity of anti-hOX40 antibodies.
  • Assessed antibody performance in vivo using different isotypes and epitopes.
  • Analyzed T-cell responses, including Treg deletion and CD8+ T-cell expansion.

Main Results:

  • High-affinity antibodies bound epitopes across all four cysteine-rich domains of hOX40.
  • mIgG1 mAbs induced receptor agonism and CD8+ T-cell expansion; mIgG2a mAbs induced Treg deletion.
  • Membrane-proximal epitopes yielded more potent agonism; both isotypes showed therapeutic effects via distinct mechanisms.

Conclusions:

  • Isotype and epitope significantly modulate anti-hOX40 mAb therapy efficacy.
  • CD8+ T-cell expansion or Treg depletion can be selected based on tumor composition.
  • Understanding these mechanisms is vital for designing effective combination therapies to improve clinical outcomes.

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