Microsatellite Instability, Mismatch Repair, and Tumor Mutation Burden in Lung Cancer

Area of Science:

• Oncology
• Immunotherapy
• Biomarker Discovery

Background:

• The US FDA approved programmed death ligand 1 (PD-L1) as a companion diagnostic for immune checkpoint inhibitors (ICIs) in non-small cell lung cancer, improving patient survival.
• Selection of patients who will respond to ICIs remains a challenge, prompting investigation into additional predictive biomarkers.

Purpose of the Study:

• To review the role of PD-L1, microsatellite instability/mismatch repair deficiency (MSI/MMR), and tumor mutation burden (TMB) as predictive biomarkers for immunotherapy.
• To discuss the ongoing efforts in harmonizing testing methodologies and assay design for these biomarkers.
• To explore future directions, including novel biomarkers and artificial intelligence (AI), for optimizing immunotherapy eligibility determination.

Main Methods:

• Review of clinical data and existing literature on PD-L1, MSI/MMR, and TMB in cancer immunotherapy.
• Discussion of current challenges and ongoing research in biomarker standardization and implementation.
• Exploration of potential future algorithms integrating multiple biomarkers and AI.

Main Results:

• PD-L1, MSI/MMR, and TMB are established as independent predictive biomarkers for immunotherapy response.
• Clinical data support the utility of these biomarkers in patient selection for ICI therapy.
• Harmonization of testing and assay optimization are critical for reliable biomarker assessment.

Conclusions:

• PD-L1, MSI/MMR, and TMB are crucial for predicting immunotherapy efficacy.
• Future immunotherapy selection algorithms may integrate these established biomarkers with novel ones.
• Artificial intelligence holds promise for developing sophisticated algorithms to guide ICI selection based on complex genetic data.