[Molecular predictors in immune oncology]

Area of Science:

• Oncology
• Immunology
• Biomarker Discovery

Background:

• Immune oncology (IO) therapies, particularly immune checkpoint inhibitors, are rapidly advancing.
• Identifying patients who will respond to IO treatment requires sophisticated biomarker approaches.

Purpose of the Study:

• To provide a comprehensive overview of current and emerging IO biomarker strategies.
• To discuss the evolving landscape of patient selection for IO therapies.

Main Methods:

• Review of current literature on IO biomarkers.
• Analysis of novel diagnostic-compatible biomarker strategies.
• Exploration of complex molecular predictors and combinatorial patient selection.

Main Results:

• Biomarker development in IO is dynamic, paralleling therapeutic advancements.
• Beyond checkpoint ligand/receptor expression, molecular predictors like tumor subtypes and mutational load are gaining importance.
• Emerging strategies involve combinatorial evaluation of multiple parameters for patient selection.

Conclusions:

• The field of IO biomarkers is rapidly evolving, necessitating a comprehensive understanding of available and emerging strategies.
• Advanced molecular biomarkers and combinatorial approaches are key to optimizing patient selection for IO therapies.