Mutated neo-antigens in hepatocellular carcinoma
Background and rationale: Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death worldwide. Immunotherapeutic interventions may help at improving therapeutic outcome in HCC patients. Identification and immunological validation of specific mutated neo-antigens represents an essential knowledge. Hypothesis: The hypothesis of the present proposal is that identification and immunological validation of mutated neo-antigens specific to HCC will be essential to subsequently develop immunotherapy strategies for improved clinical outcome in HCC patients. Aims: The primary aim is the identification and immunological validation of mutated neo-antigens specific to HCC. Specific aims will be: 1) evaluate the mutational rate in HCC samples and predict the presentation of neo-epitopes by HLA-A2*01 allele; 2) assess the frequency of specific T cell response to such mutant epitopes in HCC patients, before and after treatment with checkpoint inhibitors (CI); 3) validate the immunogenicity of neo-epitopes in an HLA-transgenic mice and their therapeutic effect in a patient-derived xenograft (PDX) animal model; 4) identify mutated full-length proteins presented on the surface of HCC cancer cells; 5) develop MAbs to such mutated proteins and validate their specificity in vivo in a PDX animal model. Expected results and potential impact: The results of the proposed study will be the identification of HCC-specific target mutated neo-antigens (e.g. epitopes and proteins) and their immuological relevance in a PDX animal model and in HCC patients before and after CI treatment. Such results will have a potential extremely high impact, serving as a foundation for subsequent therapeutic strategies targeting HCC. Mutated neo-antigens will provide a source of immunogens to be used alone or in combination with wild-type antigens identified within the ongoing FP7-funded HEPAVAC project (Coordinator L. Buonaguro). The present HEPAMUT will complement and go far beyond HEPAVAC.
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This project has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No. 964264.