Abstract

Neoantigens are peptides derived from tumor-specific mutations, which are recognized by the immune system as foreign and can stimulate an immune response against cancer cells. Identifying these neoantigens is a crucial step in the development of personalized cancer immunotherapies, as they serve as targets for T-cell mediated immune responses. However, predicting which peptides from the tumor genome will bind effectively to major histocompatibility complex (MHC) molecules—key proteins that present antigens to immune cells—remains a significant challenge.

About This Material

This is a Hands-on Tutorial from the GTN which is usable either for individual self-study, or as a teaching material in a classroom.

Questions this will address

• What are neoantigens, and why are they significant in cancer immunotherapy?
• How can binding predictions and validation help distinguish strong and weak binders?
• What tools and techniques are commonly used for neoantigen identification and validation?

Learning Objectives

• Understand the process of neoantigen identification and the role of peptide binding predictions.
• Learn how to use IEDB to predict the binding affinity of peptides to MHC molecules.
• Gain practical experience using PepQuery to validate novel peptides from proteomics data.
• Distinguish between strong and weak binders based on predicted binding affinity.