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Published on: February 5, 2020
Biomarkers for Response to Anti-PD-1/Anti-PD-L1 Immune Checkpoint Inhibitors: A Large Meta-Analysis
Background:
Immune checkpoint inhibitors (ICIs) that block PD-1/PD-L1 have consistently demonstrated durable clinical activity across multiple histologies but have low overall response rates for many cancers-indicating that too few patients benefit from ICIs. Many studies have explored potential predictive biomarkers (eg, PD-1/PD-L1 expression, tumor mutational burden [TMB]), no consensus biomarker has been identified.
Methods:
This meta-analysis combined predictive accuracy metrics for various biomarkers, across multiple cancer types, to determine which biomarkers are most accurate for predicting ICI response. Data from 18,792 patients from 100 peer-reviewed studies that evaluated putative biomarkers for response to anti-PD-1/anti- PD-L1 treatment were meta-analyzed using bivariate linear mixed models. Biomarker performance was assessed based on the global area under the receiver operating characteristic curve (AUC) and 95% bootstrap confidence intervals.
Results:
PD-L1 immunohistochemistry, TMB, and multimodal biomarkers discriminated responders and nonresponders better than random assignment (AUCs >.50). Excluding multimodal biomarkers, these biomarkers correctly classified at least 50% of the responders (sensitivity 95% CIs, >.50). Notably, variation in biomarker performance was observed across cancer types.
Conclusions:
Although some biomarkers consistently performed better, heterogeneity in performance was observed across cancer types, and additional research is needed to identify highly accurate and precise biomarkers for widespread clinical use.
Insights
Predicting response to immune checkpoint inhibitors (ICIs) remains challenging. While PD-L1 expression and tumor mutational burden show promise, no single biomarker guarantees efficacy, necessitating further research for personalized cancer therapy.
Area of Science:
- Oncology
- Immunotherapy
- Biomarker Discovery
Background:
- Immune checkpoint inhibitors (ICIs) targeting PD-1/PD-L1 offer durable responses in various cancers but benefit a limited patient population.
- Identifying reliable predictive biomarkers for ICI response is crucial for optimizing treatment strategies.
Approach:
- A meta-analysis synthesized data from 100 studies involving 18,792 patients to evaluate biomarker accuracy for anti-PD-1/anti-PD-L1 therapy response.
- Bivariate linear mixed models assessed biomarker performance using the area under the receiver operating characteristic curve (AUC).
Key Points:
- PD-L1 immunohistochemistry, tumor mutational burden (TMB), and multimodal biomarkers demonstrated predictive accuracy above random chance (AUCs > 0.50).
- These biomarkers correctly classified over 50% of responders, though performance varied significantly across different cancer types.
Conclusions:
- While certain biomarkers show consistent performance, significant heterogeneity exists across cancer types.
- Further research is essential to develop highly accurate and precise biomarkers for routine clinical application in immunotherapy.
