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

Miguel Lopez-Botet1, Carlos Vilches2,3, Aura Muntasell4,5,6

  • 1Department of Medicine and Life Sciences, University Pompeu Fabra, Barcelona, Spain.

Clinical Cancer Research : an Official Journal of the American Association for Cancer Research
|January 7, 2026
PubMed

Insights

Researchers are exploring the CD94/NKG2A-HLA-E pathway as a new target for cancer immunotherapy. Blocking this interaction or genetically modifying cells shows promise for improving treatments like adoptive NK cell therapy.

Area of Science:

  • Immunology
  • Oncology
  • Molecular Biology

Background:

  • Immune checkpoint blockers like PD1/PD-L1 and CTLA4 have advanced cancer immunotherapy.
  • The CD94/NKG2A inhibitory receptor, interacting with HLA-E, is a novel target of interest.
  • NKG2A is expressed on NK and T cell subsets, playing a role in immune regulation.

Purpose of the Study:

  • To review the biology of the CD94/NKG2A-HLA-E axis in cancer immunotherapy.
  • To discuss current therapeutic strategies targeting this axis.
  • To highlight challenges and future directions in targeting CD94/NKG2A.

Main Methods:

  • Review of preclinical and clinical data on CD94/NKG2A-HLA-E blockade.
  • Analysis of genetic engineering approaches for adoptive NK cell therapy.
  • Discussion of biomarker identification and clinical trial design.

Main Results:

  • Blocking the NKG2A-HLA-E interaction is effective in vitro and in preclinical models.
  • NKG2A+ CD8+ T cells infiltrate some solid tumors, suggesting therapeutic potential.
  • Clinical-grade monoclonal antibodies, such as monalizumab, targeting NKG2A are in development.
  • Genetic engineering of NK cells offers a strategy to enhance adoptive immunotherapies.

Conclusions:

  • The CD94/NKG2A-HLA-E axis represents a promising target for cancer immunotherapy.
  • Therapeutic strategies include antibody blockade and genetic modification of immune cells.
  • Future research should focus on predictive biomarkers, optimal clinical settings, and combination therapies.

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