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- Title
Predicting MHC I restricted T cell epitopes in mice with NAP-CNB, a novel online tool.
- Authors
Wert-Carvajal, Carlos; Sánchez-García, Rubén; Macías, José R; Sanz-Pamplona, Rebeca; Pérez, Almudena Méndez; Alemany, Ramon; Veiga, Esteban; Sorzano, Carlos Óscar S.; Muñoz-Barrutia, Arrate
- Abstract
Lack of a dedicated integrated pipeline for neoantigen discovery in mice hinders cancer immunotherapy research. Novel sequential approaches through recurrent neural networks can improve the accuracy of T-cell epitope binding affinity predictions in mice, and a simplified variant selection process can reduce operational requirements. We have developed a web server tool (NAP-CNB) for a full and automatic pipeline based on recurrent neural networks, to predict putative neoantigens from tumoral RNA sequencing reads. The developed software can estimate H-2 peptide ligands, with an AUC comparable or superior to state-of-the-art methods, directly from tumor samples. As a proof-of-concept, we used the B16 melanoma model to test the system's predictive capabilities, and we report its putative neoantigens. NAP-CNB web server is freely available at http://biocomp.cnb.csic.es/NeoantigensApp/ with scripts and datasets accessible through the download section.
- Subjects
MAJOR histocompatibility complex; T cells; EPITOPES; CANCER immunotherapy; LABORATORY mice
- Publication
Scientific Reports, 2021, Vol 11, Issue 1, p1
- ISSN
2045-2322
- Publication type
Article
- DOI
10.1038/s41598-021-89927-5