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...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2024-12-01
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| Series: | Human Vaccines & Immunotherapeutics |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/21645515.2023.2300881 |
| _version_ | 1827382878696112128 |
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| author | Kai Xin Xiao Wei Jie Shao Fangjun Chen Qin Liu Baorui Liu |
| author_facet | Kai Xin Xiao Wei Jie Shao Fangjun Chen Qin Liu Baorui Liu |
| author_sort | Kai Xin |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-08T14:29:48Z |
| format | Article |
| id | doaj.art-21427348a2b64a0aa8bda443fd2b4be5 |
| institution | Directory Open Access Journal |
| issn | 2164-5515 2164-554X |
| language | English |
| last_indexed | 2024-03-08T14:29:48Z |
| publishDate | 2024-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Human Vaccines & Immunotherapeutics |
| spelling | doaj.art-21427348a2b64a0aa8bda443fd2b4be52024-01-12T12:23:17ZengTaylor & Francis GroupHuman Vaccines & Immunotherapeutics2164-55152164-554X2024-12-0120110.1080/21645515.2023.2300881Establishment of a novel tumor neoantigen prediction tool for personalized vaccine designKai Xin0Xiao Wei1Jie Shao2Fangjun Chen3Qin Liu4Baorui Liu5Department of Oncology, Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine, Nanjing, Jiangsu Province, ChinaDepartment of Pathology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu Province, ChinaDepartment of Oncology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu Province, ChinaDepartment of Oncology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu Province, ChinaDepartment of Oncology, Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine, Nanjing, Jiangsu Province, ChinaDepartment of Oncology, Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine, Nanjing, Jiangsu Province, ChinaABSTRACTThe 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.https://www.tandfonline.com/doi/10.1080/21645515.2023.2300881Cancer vaccineneoantigen predictiondeep learninggastric cancer |
| spellingShingle | Kai Xin Xiao Wei Jie Shao Fangjun Chen Qin Liu Baorui Liu Establishment of a novel tumor neoantigen prediction tool for personalized vaccine design Human Vaccines & Immunotherapeutics Cancer vaccine neoantigen prediction deep learning gastric cancer |
| title | Establishment of a novel tumor neoantigen prediction tool for personalized vaccine design |
| title_full | Establishment of a novel tumor neoantigen prediction tool for personalized vaccine design |
| title_fullStr | Establishment of a novel tumor neoantigen prediction tool for personalized vaccine design |
| title_full_unstemmed | Establishment of a novel tumor neoantigen prediction tool for personalized vaccine design |
| title_short | Establishment of a novel tumor neoantigen prediction tool for personalized vaccine design |
| title_sort | establishment of a novel tumor neoantigen prediction tool for personalized vaccine design |
| topic | Cancer vaccine neoantigen prediction deep learning gastric cancer |
| url | https://www.tandfonline.com/doi/10.1080/21645515.2023.2300881 |
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