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Lymphocyte T Subsets and Outcome of Immune Checkpoint Inhibitors in Melanoma Patients: An Oncologist's Perspective on

Clara Martínez-Vila1,2,3, Europa Azucena González-Navarro4,5, Cristina Teixido5,6

  • 1Department of Medical Oncology, Althaia Xarxa Assistencial Universitària de Manresa, Dr. Joan Soler, 1-3, 08243 Manresa, Spain.

International Journal of Molecular Sciences
|September 14, 2024
PubMed

Insights

Quantifying T lymphocyte subsets in blood or tumors may identify patients who will respond to immune checkpoint inhibitors (ICI) for advanced melanoma. This could improve treatment selection for this deadly skin cancer.

Area of Science:

  • Oncology
  • Immunology
  • Dermatology

Background:

  • Melanoma incidence is rising, especially in Caucasians.
  • Immune checkpoint inhibitors (ICI) have improved melanoma treatment but are not effective for all patients.
  • Novel biomarkers are needed to predict response to ICI therapies.

Purpose of the Study:

  • To review existing data on T lymphocyte subsets as predictive biomarkers for advanced melanoma patients treated with ICI.
  • To evaluate the role of T lymphocyte distribution in peripheral blood and tumors for predicting ICI response.

Main Methods:

  • Systematic review of published literature.
  • Analysis of studies investigating T lymphocyte subsets (e.g., CD4+, CD8+, regulatory T cells) in melanoma patients.
  • Correlation of T cell distribution with response to anti-PD-1, anti-CTLA-4, and anti-LAG-3 therapies.

Main Results:

  • T lymphocyte subset distribution varies significantly between responders and non-responders to ICI.
  • Specific T cell profiles in peripheral blood and tumor microenvironment are associated with treatment outcomes.
  • BRAFV600 mutational status may influence the predictive value of certain T cell subsets.

Conclusions:

  • T lymphocyte subset quantification shows promise as a predictive biomarker for ICI therapy in advanced melanoma.
  • Further research is warranted to validate these findings and integrate T cell analysis into clinical decision-making.
  • Identifying ICI responders through immune profiling can optimize melanoma treatment strategies.
Keywords:
anti-CTLA-4anti-PD-1biomarkerslymphocyte T subsetsmelanoma

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