ArticleHuman vaccines & immunotherapeutics2024
Establishment of a novel tumor neoantigen prediction tool for personalized vaccine design.
Article in Human vaccines & immunotherapeutics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed, 6 citations in OpenAlex.
- Neoantigen cancer vaccines for gastrointestinal tumors: opportunities and challenges.MedScience · 2026Review
- Current landscape and future directions of neoantigen vaccines: A new era of personalized cancer immunotherapy.Innovation (Cambridge (Mass.)) · 2026Review
- Mutant calreticulin-directed immunotherapies in myeloproliferative neoplasms.Blood neoplasia · 2026Review
- mRNA vaccines in oncology: personalized cancer immunization and neoantigen targeting.Molecular & cellular oncology · 2026Review
- Tumor Neoepitope-Based Vaccines: A Scoping Review on Current Predictive Computational Strategies.Vaccines · 2024Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.