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Predictive biomarkers in PD-1/PD-L1 checkpoint blockade immunotherapy
Xiangjiao Meng1, Zhaoqin Huang2, Feifei Teng1
1Department of Radiation Oncology and Shandong Key Laboratory of Radiation Oncology, Shandong Cancer Hospital and Institute, Jinan, Shandong, China.
Cancer Treatment Reviews
|November 22, 2015
Summary
Predicting cancer immunotherapy response remains challenging. This review explores biomarkers beyond PD-L1 expression, including tumor-infiltrating cells and gene analysis, to identify patients who will benefit from programmed death 1 (PD-1)/programmed death ligand-1 (PD-L1) checkpoint blockades.
Area of Science:
- Immunotherapy
- Oncology
- Biomarker Discovery
Background:
- Programmed death 1 (PD-1)/programmed death ligand-1 (PD-L1) checkpoint blockade has revolutionized cancer immunotherapy, demonstrating significant clinical efficacy and durable responses.
- Despite successes, a substantial proportion of cancer patients do not respond to these therapies, necessitating improved patient selection strategies.
Purpose of the Study:
- To review and discuss predictive biomarkers for programmed death 1 (PD-1)/programmed death ligand-1 (PD-L1) pathway checkpoint blockades in cancer treatment.
- To highlight the limitations of current biomarkers like PD-L1 expression and explore novel approaches.
Main Methods:
- Literature review focusing on predictive biomarkers for PD-1/PD-L1 checkpoint blockade therapy.
- Analysis of existing data on PD-L1 expression, tumor-infiltrating immune cells, and gene-based markers.
Main Results:
- Programmed death ligand-1 (PD-L1) expression is a widely studied biomarker but suffers from low prediction accuracy and dynamic variability.
- Tumor microenvironment factors, including infiltrating immune cells and molecular signatures, alongside gene analysis (e.g., mutational landscape, mismatch-repair deficiency), show promise in predicting response.
- Current biomarkers are insufficient for accurate patient stratification, underscoring the need for further research.
Conclusions:
- Accurate identification of patients who will benefit from PD-1/PD-L1 checkpoint blockades requires exploring biomarkers beyond PD-L1.
- Tumor-infiltrating immune cells and genomic features represent promising avenues for improving predictive accuracy.
- Further preclinical and clinical studies are essential to validate novel biomarkers and integrate them into clinical practice for personalized cancer immunotherapy.
