Predictive biomarkers for checkpoint inhibitor-based immunotherapy.

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.