Biomarkers of response to immunotherapy in early stage non-small cell lung cancer

Matthieu Roulleaux Dugage1, Víctor Albarrán-Artahona2, Juan Carlos Laguna3

  • 1Department of Oncology, Hôpital Européen Georges Pompidou, AP-HP, Université Paris Cité, Paris, France; Laboratoire D'Immunomonitoring en Oncologie, INSERM US23, CNRS UMS 3655, Gustave Roussy, Villejuif, Île-de-France, France.

European Journal of Cancer (Oxford, England : 1990)
|March 24, 2023
PubMed

Insights

Immune-checkpoint inhibitors (ICIs) show promise in early non-small cell lung cancer (NSCLC) treatment, especially neoadjuvantly. Biomarkers are crucial for identifying patients who will benefit most from these immunotherapies.

Area of Science:

  • Oncology
  • Immunology
  • Pulmonology

Background:

  • Immune-checkpoint inhibitors (ICIs) targeting PD-1/PD-L1 have transformed advanced non-small cell lung cancer (NSCLC) care.
  • ICIs are being explored in early-stage NSCLC, including neoadjuvant settings, with promising pathological response and survival data.

Purpose of the Study:

  • To review the current landscape of ICI use in early NSCLC.
  • To identify existing and emerging biomarkers for predicting treatment response.
  • To discuss future directions for optimizing ICI therapy in early NSCLC.

Main Methods:

  • Review of current literature on neoadjuvant and adjuvant ICI therapy in early NSCLC.
  • Analysis of pathological response rates and survival data.
  • Evaluation of biomarkers such as PD-L1 expression, tumor mutational burden, and genetic mutations.

Main Results:

  • Neoadjuvant ICI monotherapy rarely achieves major pathological response rates above 40% in early NSCLC.
  • PD-L1 expression and tumor mutational burden show correlation with pathological response.
  • EGFR, STK11, and KEAP1 mutations are critical for treatment selection.

Conclusions:

  • While promising, neoadjuvant ICI therapy requires further data for paradigm shifts in early NSCLC.
  • Biomarker development is essential to personalize ICI treatment and improve outcomes.
  • Emerging biomarkers like ctDNA and TCR clonality hold future potential for patient selection and monitoring.

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