Decoding the HLA-G peptide landscape for pancreatic cancer immunotherapy

Pancreatic cancer remains highly resistant to current immunotherapies, highlighting the need to identify new targets that allow the immune system to recognise and attack cancer cells. HLA-G, a non-classical HLA molecule found to be elevated in pancreatic cancer cell lines, may present peptides that could be targeted by new immunotherapies. However, the peptides presented by HLA-G are still poorly characterised, and their potential as therapeutic targets remains to be investigated. In this project, we will characterise the HLA-G peptide landscape to identify potential new targets for pancreatic cancer immunotherapy. We will use genetic engineering and CRISPR-Cas9 gene editing to generate specialised cell lines expressing individual HLA-G variants while removing endogenous HLA-G, allowing us to identify peptides specifically presented by each variant. We will then isolate HLA-G–peptide complexes using immunoprecipitation and analyse them by mass spectrometry to identify and characterise the bound peptides. To identify promising candidates, we will combine computational peptide-binding predictions with experimental validation, including flow cytometry-based binding assays and peptide-pulsing experiments. These approaches will help us determine which peptides are suitable for further investigation as potential immunotherapy targets. By identifying and characterising HLA-G-presented peptides, we aim to establish a foundation for future cancer therapies, including T-cell receptor (TCR)-based therapies, CAR-T cells and cancer vaccines.