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Updated: Mar 10, 2026
Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
Predictive biomarkers for checkpoint inhibitor-based immunotherapy
Geoffrey T Gibney1, Louis M Weiner1, Michael B Atkins1
1Lombardi Comprehensive Cancer Center, MedStar Georgetown University Hospital, Washington DC, USA.
Abstract:
The clinical development of checkpoint inhibitor-based immunotherapy has ushered in an exciting era of anticancer therapy. Durable responses can be seen in patients with melanoma and other malignancies. Although monotherapy with PD-1 or PD-L1 agents are typically well tolerated, the risk of immune-related adverse events increases with combination regimens. The development of predictive biomarkers is needed to optimise patient benefit, minimise risk of toxicities, and guide combination approaches. The greatest focus has been on tumour-cell PD-L1 expression. Although PD-L1 positivity enriches for populations with clinical benefit, PD-L1 testing alone is insufficient for patient selection in most malignancies. In this Review, we discuss the status of PD-L1 testing and explore emerging data on new biomarker strategies with tumour-infiltrating lymphocytes, mutational burden, immune gene signatures, and multiplex immunohistochemistry. Future development of an effective predictive biomarker for checkpoint inhibitor-based immunotherapy will integrate multiple approaches for optimal characterisation of the immune tumour microenvironment.
Insights
Checkpoint inhibitor immunotherapy offers durable responses but requires predictive biomarkers. Current PD-L1 testing is insufficient; integrating multiple biomarkers is key for optimizing cancer treatment and minimizing toxicity.
Area of Science:
- Oncology
- Immunology
- Biomarker Discovery
Background:
- Checkpoint inhibitor immunotherapy, including PD-1/PD-L1 agents, has transformed cancer treatment, yielding durable responses in various malignancies.
- While generally well-tolerated as monotherapy, combination regimens increase the risk of immune-related adverse events.
- Optimizing patient selection and minimizing toxicity necessitates the development of predictive biomarkers.
Purpose of the Study:
- To review the current status of PD-L1 testing for checkpoint inhibitor immunotherapy.
- To explore emerging biomarker strategies beyond PD-L1 expression.
- To highlight the need for integrated approaches in biomarker development.
Main Methods:
- Review of existing literature on PD-L1 testing and novel biomarker strategies.
- Discussion of data concerning tumour-infiltrating lymphocytes, mutational burden, immune gene signatures, and multiplex immunohistochemistry.
- Analysis of the limitations of PD-L1 testing alone for patient stratification.
Main Results:
- PD-L1 expression is a focus but insufficient alone for patient selection in most cancers.
- Emerging biomarkers like tumour-infiltrating lymphocytes and mutational burden show promise.
- Multiplex immunohistochemistry offers a way to characterize the immune microenvironment more comprehensively.
Conclusions:
- PD-L1 testing alone is inadequate for predicting response to checkpoint inhibitors.
- A combination of biomarkers, including immune cell infiltration and genetic factors, is required.
- Future strategies must integrate multiple approaches to accurately characterize the tumour immune microenvironment and guide therapy.
