Patients with lung cancer naturally raise immune responses against the malignant cells. Immune checkpoint blockers are able to activate these responses and cure a small percentage of these patients. Our consortium is currently producing and testing in patients a vaccine consisting of dendritic cells presenting a selection of patient-specific neo-epitopes to increase the percentage of responding patients. This proposal aims to improve neo-epitope selection for vaccine production. Current Next Generation Sequencing (NGS)-based neo-epitope prediction algorithms will be refined by adding mass spectrometry (MS) data and MSbased algorithms, which directly identify mutated peptides bound to Human Leucocyte Antigens (HLA). The proposal is heavily based on the world classexpertise of the proteomics research groups to improve MS technology and on the cross-fertilization between the different technologies: MS-based HLA binding peptides, NGS-based neo-epitope prediction, immune monitoring towards neo-epitopes and clinical responses. This proposal aims to optimize patient-specific therapeutic vaccination for cancer patients