Establishment of a novel tumor neoantigen prediction tool for personalized vaccine design

ABSTRACTThe personalized neoantigen nanovaccine (PNVAC) platform for patients with gastric cancer we established previously exhibited promising anti-tumor immunoreaction. However, limited by the ability of traditional neoantigen prediction tools, a portion of epitopes failed to induce specific immun...

Full description

Saved in:
Bibliographic Details
Main Authors: Kai Xin (Author), Xiao Wei (Author), Jie Shao (Author), Fangjun Chen (Author), Qin Liu (Author), Baorui Liu (Author)
Format: Book
Published: Taylor & Francis Group, 2024-12-01T00:00:00Z.
Subjects:
Online Access:Connect to this object online.
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:ABSTRACTThe personalized neoantigen nanovaccine (PNVAC) platform for patients with gastric cancer we established previously exhibited promising anti-tumor immunoreaction. However, limited by the ability of traditional neoantigen prediction tools, a portion of epitopes failed to induce specific immune response. In order to filter out more neoantigens to optimize our PNVAC platform, we develop a novel neoantigen prediction model, NUCC. This prediction tool trained through a deep learning approach exhibits better neoantigen prediction performance than other prediction tools, not only in two independent epitope datasets, but also in a totally new epitope dataset we construct from scratch, including 25 patients with advance gastric cancer and 150 candidate mutant peptides, 13 of which prove to be neoantigen by immunogenicity test in vitro. Our work lay the foundation for the improvement of our PNVAC platform for gastric cancer in the future.
Item Description:10.1080/21645515.2023.2300881
2164-554X
2164-5515