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PD-L1 Expression in NSCLC: Clouds in a Bright Sky.

Victoria Ferrari1, Jocelyn Gal2, Baharia Mograbi3

  • 1Antoine Lacassagne Center, Department of Medical Oncology, University Côte d'Azur, 33 Avenue de Valombrose, 06189 Nice, France.

International Journal of Molecular Sciences
|July 12, 2025
PubMed
Summary

Programmed Death-Ligand 1 (PD-L1) expression predicts immunotherapy response in lung cancer. However, its complex regulation and measurement challenges limit clinical utility, necessitating advanced biomarker strategies.

Keywords:
PD-L1gene expressionimmunotherapynon-small cell lung cancer

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Area of Science:

  • Oncology
  • Immunology
  • Molecular Biology

Background:

  • Programmed Death-Ligand 1 (PD-L1) is a key target for immune checkpoint inhibitors (CPIs) in cancer therapy.
  • Tumoral PD-L1 expression is a recognized, yet imperfect, predictor of CPI response, particularly in lung cancer.
  • PD-L1's role in immune resistance is linked to interferon-gamma upregulation by immune cells near tumor cells.

Purpose of the Study:

  • To review the molecular mechanisms regulating PD-L1 expression in lung cancer.
  • To discuss the limitations of PD-L1 as a predictive biomarker for CPI therapy.
  • To explore emerging multimodal/multi-omics biomarker strategies for patient selection.

Main Methods:

  • Literature review focusing on molecular mechanisms of PD-L1 expression.
  • Analysis of factors influencing PD-L1 modulation (oncogenic pathways, transcriptional/post-transcriptional regulation).
  • Discussion of measurement challenges (glycosylation, immunohistochemistry accuracy).

Main Results:

  • PD-L1 expression is modulated by multiple factors, leading to potential false positive/negative predictions.
  • PD-L1 levels can be unstable during cancer treatment (chemotherapy, TKIs), impacting predictive value.
  • Complex regulatory networks and measurement variability challenge PD-L1's sole reliance as a biomarker.

Conclusions:

  • Optimizing CPI therapy requires understanding PD-L1's complex regulation and limitations.
  • Multimodal and multi-omics biomarker approaches are emerging for improved patient selection.
  • Large-scale prospective studies are needed to validate comprehensive PD-L1-enriched biomarker strategies in lung cancer.