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VENUS, a Novel Selection Approach to Improve the Accuracy of Neoantigens’ Prediction

Authors :
Simona Allocca
Linda Nocchi
Gabriella Cotugno
Guido Leoni
Rosa Bartolomeo
Irene Garzia
Elisa Scarselli
Fulvia Troise
Maria De Lucia
Elisa Micarelli
Anna Morena D'Alise
Armin Lahm
Alfredo Nicosia
Giuseppina Romano
Fabio Giovanni Tucci
Francesca Langone
Leoni, G.
D'Alise, A. M.
Tucci, F. G.
Micarelli, E.
Garzia, I.
De Lucia, M.
Langone, F.
Nocchi, L.
Cotugno, G.
Bartolomeo, R.
Romano, G.
Allocca, S.
Troise, F.
Nicosia, A.
Lahm, A.
Scarselli, E.
Source :
Vaccines, Vol 9, Iss 880, p 880 (2021), Vaccines; Volume 9; Issue 8; Pages: 880, Vaccines
Publication Year :
2021
Publisher :
MDPI AG, 2021.

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.

Details

Language :
English
Volume :
9
Issue :
880
Database :
OpenAIRE
Journal :
Vaccines
Accession number :
edsair.doi.dedup.....75ffa7fcbf1143b73bbcb33b19e27e04