Mutational Landscape and Sensitivity to Immune Checkpoint Blockers.

Area of Science:

• Oncology
• Immunology
• Genomics

Background:

• Immunotherapy, particularly immune checkpoint blockers (ICB), has revolutionized cancer treatment, showing success even in non-immunogenic tumors.
• However, a substantial number of patients do not respond to ICB, highlighting the need for predictive biomarkers.
• Identifying patients likely to benefit from ICB is a major challenge in its development.

Purpose of the Study:

• To explore the role of tumor genomic landscape, mutational load, and neoantigens as predictive biomarkers for ICB response.
• To investigate the association between DNA repair defects and improved survival or clinical benefit from ICB.
• To emphasize the need for standardized analytical methods for genomic biomarkers in clinical implementation.

Main Methods:

• Review of recent publications linking tumor genomic features to ICB outcomes.
• Analysis of the relationship between DNA repair defects, genomic instability, mutational load, and neoantigens.
• Discussion on the integration of next-generation sequencing data for biomarker development.

Main Results:

• Tumor mutational load and neoantigens, influenced by DNA repair capacity and genomic instability, are potential determinants of ICB response.
• Defects in DNA repair machinery are associated with better survival and durable clinical benefit from ICB.
• Current next-generation sequencing data needs optimized analytical pipelines for reliable biomarker prediction.

Conclusions:

• Mutational load and neoantigens are promising predictive biomarkers for ICB therapy.
• Standardization and integration of sequencing data analysis are essential for clinical implementation of these biomarkers.
• Optimizing the measurement of these genomic parameters will enhance patient selection for immunotherapy.