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Emerging predictors of the response to the blockade of immune checkpoints in cancer therapy

Xiaolei Li1,2, Wenhui Song3, Changshun Shao1

  • 1The First Affiliated Hospital of Soochow University and State Key Laboratory of Radiation Medicine and Radioprotection, Institutes for Translational Medicine, Soochow University, Suzhou, Jiangsu, 215123, China.

Cellular & Molecular Immunology
|July 14, 2018
PubMed

Insights

Predicting cancer immunotherapy success is crucial. This review covers biomarkers like gene expression and immune cell infiltration to identify patients who will benefit from checkpoint blockade therapy.

Area of Science:

  • Oncology
  • Immunology
  • Biomarker Discovery

Background:

  • Checkpoint blockade immunotherapy is a powerful cancer treatment, but its effectiveness varies significantly across cancer types and individuals.
  • Identifying patients likely to respond is essential for maximizing treatment benefits and minimizing toxicity.

Purpose of the Study:

  • To review the current landscape and advancements in predictive biomarkers for checkpoint blockade immunotherapy in cancer.
  • To highlight tools that aid in patient selection for immunotherapy and guide combination strategies.

Main Methods:

  • Review of existing literature on predictive biomarkers for cancer immunotherapy.
  • Analysis of various predictor types, including molecular and cellular markers.
  • Discussion of emerging trends and future directions in biomarker development.

Main Results:

  • Multiple predictors are emerging, focusing on checkpoint receptor ligand expression, tumor mutational burden, neoantigen and microsatellite instability, tumor-infiltrating immune cells, and peripheral blood biomarkers.
  • These predictors aim to stratify patients for immunotherapy efficacy.

Conclusions:

  • Predictive tools are vital for optimizing checkpoint blockade immunotherapy by enabling precise patient selection.
  • Continued research into novel biomarkers will enhance the efficacy and safety of cancer immunotherapy.
Keywords:
Cancer immunotherapyCheckpoint blockade immunotherapyPrecision oncologyPredictive biomarkers

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