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Immune checkpoint inhibitors: recent progress and potential biomarkers
Pramod Darvin1, Salman M Toor1, Varun Sasidharan Nair1
1Cancer Research Center, Qatar Biomedical Research Institute, College of Science and Engineering, Hamad Bin Khalifa University, Qatar Foundation, Doha, Qatar.
Experimental & Molecular Medicine
|December 15, 2018
Summary
Predictive biomarkers are crucial for optimizing cancer immunotherapy. This review discusses biomarkers for immune checkpoint inhibitors like PD-1/PD-L1 and CTLA-4 to improve patient selection and treatment outcomes.
Area of Science:
- Oncology
- Immunology
- Pharmacology
Background:
- Cancer progression involves immune suppression via immune checkpoints.
- Immune checkpoint inhibitors (ICIs) like anti-PD-1/PD-L1 and anti-CTLA-4 have revolutionized cancer therapy.
- Despite benefits, low response rates and immune-related adverse events necessitate predictive biomarkers.
Purpose of the Study:
- To review existing and potential predictive biomarkers for anti-PD-1/PD-L1 and anti-CTLA-4 therapies.
- To highlight the importance of biomarkers in patient selection and treatment decision-making for ICIs.
- To discuss strategies for developing more reliable predictive biomarkers.
Main Methods:
- Literature review of studies on immune checkpoint inhibitors and predictive biomarkers.
- Analysis of various biomarker categories including immune cells, PD-L1 expression, neoantigens, and genetic/epigenetic signatures.
- Discussion of current challenges and future directions in biomarker development.
Main Results:
- Several biomarkers, including immune cell infiltration, PD-L1 expression, neoantigens, and genetic/epigenetic factors, show potential in predicting ICI response.
- These biomarkers can inform patient selection for ICI therapy.
- Challenges remain in developing universally applicable and highly accurate predictive biomarkers.
Conclusions:
- Predictive biomarkers are essential for enhancing the efficacy and safety of cancer immune checkpoint inhibitor therapy.
- Further research is needed to refine and validate biomarkers for improved patient stratification.
- Development of robust biomarkers will optimize clinical decision-making and patient outcomes in ICI treatment.
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