VENUS, a Novel Selection Approach to Improve the Accuracy of Neoantigens' Prediction
Guido Leoni, Anna Morena D'Alise, Fabio Giovanni Tucci, Elisa Micarelli, Irene Garzia, Maria De Lucia, Francesca Langone, Linda Nocchi, Gabriella Cotugno, Rosa Bartolomeo, Giuseppina Romano, Simona Allocca, Fulvia Troise, Alfredo Nicosia, Armin Lahm, Elisa Scarselli, Guido Leoni, Anna Morena D'Alise, Fabio Giovanni Tucci, Elisa Micarelli, Irene Garzia, Maria De Lucia, Francesca Langone, Linda Nocchi, Gabriella Cotugno, Rosa Bartolomeo, Giuseppina Romano, Simona Allocca, Fulvia Troise, Alfredo Nicosia, Armin Lahm, Elisa Scarselli
Abstract
Neoantigens are tumor-specific antigens able to induce T-cell responses, generated by mutations in protein-coding regions of expressed genes. Previous studies demonstrated that only a limited subset of mutations generates neoantigens in microsatellite stable tumors. We developed a method, called VENUS (Vaccine-Encoded Neoantigens Unrestricted Selection), to prioritize mutated peptides with high potential to be neoantigens. Our method assigns to each mutation a weighted score that combines the mutation allelic frequency, the abundance of the transcript coding for the mutation, and the likelihood to bind the patient's class-I major histocompatibility complex alleles. By ranking mutated peptides encoded by mutations detected in nine cancer patients, VENUS was able to select in the top 60 ranked peptides, the 95% of neoantigens experimentally validated including both CD8 and CD4 T cell specificities. VENUS was evaluated in a murine model in the context of vaccination with an adeno vector encoding the top ranked mutations prioritized in the MC38 cell line. Efficacy studies demonstrated anti tumoral activity of the vaccine when used in combination with checkpoint inhibitors. The results obtained highlight the importance of a combined scoring system taking into account multiple features of each tumor mutation to improve the accuracy of neoantigen prediction.
Keywords: MC38; VENUS; cancer vaccine; neoantigen; prediction.
Conflict of interest statement
A.M.D., F.G.T., E.M., G.C., R.B., F.T., G.R., F.L., M.D.L., L.N., I.G., A.L., E.S., are employees of Nouscom s.r.l. Some of the authors own shares of Nouscom A.G. G.L., A.L., A.N., and E.S. have a pending patent application (854-24 EP) related to the manuscript. A.L. and A.N. are inventors in a patent related to the manuscript (WO 2019/008111). No further conflicts of interests were disclosed by the other authors.
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