1. Academic Validation
  2. The CD94/NKG2A-HLA-E Axis as a Target in Cancer Immunotherapy: A Critical Perspective

The CD94/NKG2A-HLA-E Axis as a Target in Cancer Immunotherapy: A Critical Perspective

  • Clin Cancer Res. 2026 Mar 16;32(6):1013-1019. doi: 10.1158/1078-0432.CCR-25-0447.
Miguel López-Botet 1 Carlos Vilches 2 3 Aura Muntasell 4 5 6
Affiliations

Affiliations

  • 1 Department of Medicine and Life Sciences, University Pompeu Fabra, Barcelona, Spain.
  • 2 Immunogenetics and Histocompatibility Lab, Instituto de Investigación Sanitaria Puerta de Hierro- Segovia de Arana, Majadahonda, Spain.
  • 3 Organización Nacional de Trasplantes , Ministerio de Sanidad, Madrid, Spain.
  • 4 Department of Cell Biology, Physiology and Immunology, Institute of Biotechnology and Biomedicine, Autonomous University of Barcelona, Bellaterra, Spain.
  • 5 Hospital del Mar Research Institute, Barcelona, Spain.
  • 6 Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Madrid, Spain.
Abstract

Successful clinical development of PD-1/PD-L1 and CTLA4 immune checkpoint blockers intensified the search for Other potential targets for Cancer Immunotherapy. Among them, the CD94/NKG2A inhibitory receptor displayed by NK cell and T-cell subsets, which specifically interacts with the nonclassic HLA-E class I molecule, has attracted special attention. Here, we provide an overview of basic concepts on the CD94/NKG2A-HLA-E axis biology relevant in the framework of ongoing Cancer Immunotherapy approaches in different scenarios. First, the effectiveness of blocking the NKG2A-HLA-E interaction in vitro and in preclinical models as well as the presence of infiltrating NKG2A+ CD8+ T cells in some solid tumors has led to the generation of clinical-grade NKG2A-specific monoclonal antibodies, pioneered by monalizumab, currently tested in clinical trials. Second, controlling NKG2A expression by genetic engineering constitutes a promising approach to improve advanced adoptive NK cell-based immunotherapies. Challenges include identifying predictive biomarkers of responsiveness, selecting appropriate clinical settings, and optimizing combinatorial regimens.

Figures
Products