ArticleFrontiers in bioengineering and biotechnology2022
CAD v1.0: Cancer Antigens Database Platform for Cancer Antigen Algorithm Development and Information Exploration.
Article in Frontiers in bioengineering and biotechnology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 12 citations in OpenAlex.
- Exploring and expanding the chemical multiverse of peptides.Chemical science · 2026Review
- Serial multiomics uncovers anti-glioblastoma responses not evident by routine clinical analyses.Science translational medicine · 2025Article
- Characterization of Tumor Antigens from Multi-omics Data: Computational Approaches and Resources.Genomics, proteomics & bioinformatics · 2025Review
- Computation strategies and clinical applications in neoantigen discovery towards precision cancer immunotherapy.Biomarker research · 2025Review
- TumorAgDB1.0: tumor neoantigen database platform.Database : the journal of biological databases and curation · 2025Article
- NeoTImmuML: a machine learning-based prediction model for human tumor neoantigen immunogenicity.Frontiers in immunology · 2025Article
- Tumor-Derived Antigenic Peptides as Potential Cancer Vaccines.International journal of molecular sciences · 2024Review
- Artificial intelligence and neoantigens: paving the path for precision cancer immunotherapy.Frontiers in immunology · 2024Review
- Evolution by innovation as a driving force to improve TCR-T therapies.Frontiers in oncology · 2023Review
- Artificial intelligence applied in neoantigen identification facilitates personalized cancer immunotherapy.Frontiers in oncology · 2022Review
Corrections and comments
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Authors and funding
11 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cancer vaccines have gradually attracted attention for their tremendous preclinical and clinical performance. With the development of next-generation sequencing technologies and related algorithms, pipelines based on sequencing and machine learning methods have become mainstream in cancer antigen prediction; of particular focus are neoantigens, mutation peptides that only exist in tumor cells that lack central tolerance and have fewer side effects. The rapid prediction and filtering of neoantigen peptides are crucial to the development of neoantigen-based cancer vaccines. However, due to the lack of verified neoantigen datasets and insufficient research on the properties of neoantigens, neoantigen prediction algorithms still need to be improved. Here, we recruited verified cancer antigen peptides and collected as much relevant peptide information as possible. Then, we discussed the role of each dataset for algorithm improvement in cancer antigen research, especially neoantigen prediction. A platform, Cancer Antigens Database (CAD, http://cad.bio-it.cn/), was designed to facilitate users to perform a complete exploration of cancer antigens online.
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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.