Comparative Analysis of Predictive Biomarkers for PD-1/PD-L1 Inhibitors in Cancers: Developments and Challenges

Area of Science:

• Oncology
• Immunotherapy
• Biomarker Discovery

Background:

• Immune checkpoint inhibitors (ICIs) targeting programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1) have revolutionized cancer therapy, yielding durable responses in melanoma and non-small-cell lung cancer (NSCLC).
• However, only a subset of patients benefit from PD-1/PD-L1 blockade, and severe adverse events necessitate better patient selection.
• Current reliance on PD-L1 expression as a biomarker is limited, as negative expression does not exclude response, highlighting the need for alternative predictive markers.

Purpose of the Study:

• To review emerging data on novel biomarkers for predicting patient response to anti-PD-1/PD-L1 immunotherapy.
• To identify biomarkers that can optimize the selection of patients likely to benefit from ICI therapy.
• To address the limitations of current PD-L1 expression biomarker in predicting ICI efficacy.

Main Methods:

• Literature review of recent studies on biomarkers for ICI therapy.
• Analysis of data on tumor microenvironment and genomic signatures impacting ICI response.
• Examination of emerging biomarkers beyond PD-L1 expression.

Main Results:

• PD-L1 expression is an imperfect predictor of response to PD-1/PD-L1 inhibitors.
• Tumor microenvironment characteristics and genomic signatures influence ICI efficacy.
• Novel biomarkers are emerging with potential predictive value for ICI therapy.

Conclusions:

• Accurate prediction of patient response to ICIs remains a challenge.
• Beyond PD-L1, other factors like tumor microenvironment and genomic signatures are crucial for predicting ICI benefit.
• Further research into novel biomarkers is essential for optimizing ICI therapy and improving patient outcomes.