AImmune - Artificial Intelligence Algorithm for Identification of Immunogenic Neoepitopes of Cancer to Predict and Boost Patient's Response to Immunotherapies.

Immunotherapy, Neoantigens, Neoepitopes, Next Generation Sequencing (NGS), Non Small Cell Lung Cancer, Personalized Neoantigen Cancer Vaccine

Cancer, Non Small Cell Lung Cancer, Neoepitopes, Neoantigens, Immunotherapy, Nivolumab, Ipilimumab, Atezolizumab, Neoantigen cancer vaccine, Personalized neoantigen cancer vaccine, FFPE, PBMC, Stool, Immuno-Oncology, Next generation sequencing (NGS)

The goal of the project is to develop and validate A.I.mmune technology. It performs complex analyses of patients' tumor and immune system state using data derived from next-generation sequencing of tumor and healthy tissue to identify cancer neoantigens, which are likely to elicit an immune response. A key challenge to be solved using the technology is to predict for each patient which neoepitopes are not only likely to bind to HLA or be presented on the tumor cell surface, but also will be recognized by the T-cell receptor and create the immunogenic response. The presence of such epitopes is required for immunotherapy by immune checkpoint inhibition to have an effect on the disease. Knowledge of those epitopes enables therapeutic strategies to boost the immune response by designing personalized cancer vaccines and adoptive cell therapies. The samples and data collected in this clinical study will be used for clinical validation of A.I.mmune technology. For all patients treated with immunotherapy (using anti-PD1 / anti-PDL1 and / or anti-CTLA-4 antibodies) peripheral blood samples (PBMC) and biopsy (FFPE) collection will be performed before treatment. Samples will be sequenced by next-generation sequencing platform. In parallel, the investigators will also collect samples of stool (one sample before the start of immunotherapy) and follow-up information of responses to treatment.

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