Differentially Expressed Genes Involved in Primary Resistance to Immunotherapy in Patients with Advanced-Stage

Luis Miguel Chinchilla-Tábora1, Juan Carlos Montero1,2, Luis Antonio Corchete3

  • 1Department of Pathology, Institute for Biomedical Research of Salamanca (IBSAL), University Hospital of Salamanca, University of Salamanca, 37007 Salamanca, Spain.

Insights

Researchers identified 24 gene expression variations predicting response to nivolumab immunotherapy in advanced lung cancer. These biomarkers can identify patients who benefit from immune checkpoint inhibitors and may impact overall survival.

Area of Science:

  • Oncology
  • Immunology
  • Genetics

Background:

  • Nivolumab is a standard treatment for advanced lung cancer, but many patients do not respond.
  • Primary resistance to nivolumab remains a significant clinical challenge.
  • Identifying predictive biomarkers is crucial for optimizing immunotherapy selection.

Purpose of the Study:

  • To identify gene expression profiles (GEP) associated with response to nivolumab in advanced non-small cell lung cancer (NSCLC).
  • To validate these GEP as predictive biomarkers for nivolumab treatment efficacy.
  • To assess the impact of identified gene expression markers on overall survival.

Main Methods:

  • Bronchoscopy tumor biopsies from NSCLC patients (responders and non-responders to nivolumab) were analyzed.
  • Differential gene expression of 760 immunotherapy-related genes was assessed using NanoString nCounter.
  • GEP signatures were validated in an independent cohort of 201 patients across various cancer types.

Main Results:

  • A signature of 24 dysregulated genes was identified, differentiating responders from non-responders.
  • Responder patients showed higher expression of genes including CXCL11, NT5E, KLRK1, CD3G, GZMA, IFNG, CD8A, and ITK.
  • Expression levels of ITK, NT5E, ITGAL, and CD8A were the strongest predictors of nivolumab response.
  • 13 of the 24 genes negatively impacted overall survival in a large NSCLC cohort.

Conclusions:

  • A specific gene expression profile in advanced NSCLC is strongly associated with response to nivolumab.
  • GEP classification can identify patients likely to benefit from immune checkpoint inhibitors (ICIs).
  • The identified biomarkers have potential for therapeutic decision-making and prognosis, warranting further clinical validation.

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