The Cancer Epitope Database and Analysis Resource: A Blueprint for the Establishment of a New Bioinformatics Resource for Use by the Cancer Immunology Community

Koşaloğlu‐Yalçın, Zeynep; Blazeska, Nina; Carter, Hannah; Nielsen, Morten; Cohen, Ezra; Küfe, Donald; Conejo-Garcia, José R.; Robbins, Paul F.; Schoenberger, Stephen P.; Peters, Bjoern; Sette, Alessandro

doi:10.3389/fimmu.2021.735609

Cited by 12 publications

(9 citation statements)

References 82 publications

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“…Information is still not detail enough for readers to explore at a more specific. Therefore, we are looking forward to the blueprint mentioned in the CEDAR database ( Koşaloğlu-Yalçın et al, 2021 ). CEDAR was built based on IEDB ( Vita et al, 2019 ), including all cancer-specific epitope data from various T-cell and B-cell experiments, MHC-binding assays, and MHC ligandomics by MS.…”

Section: Discussionmentioning

confidence: 99%

“…However, this database does not contain invalid peptides and lacks clinically relevant data. The blueprint of the Cancer Epitope Database and Analysis Resource (CEDAR) database, proposed by Koşaloğlu-Yalçın et al (2021) , is based on the Immune Epitope Database (IEDB) and tries to collect more specific information and classify it in detail. The aforementioned databases focus on online information exploration but not on algorithm development.…”

Section: Introductionmentioning

confidence: 99%

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CAD v1.0: Cancer Antigens Database Platform for Cancer Antigen Algorithm Development and Information Exploration

Yu¹,

Wang²,

Kong

et al. 2022

Front. Bioeng. Biotechnol.

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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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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

CAD v1.0: Cancer Antigens Database Platform for Cancer Antigen Algorithm Development and Information Exploration

Yu¹,

Wang²,

Kong

et al. 2022

Front. Bioeng. Biotechnol.

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show abstract

“…Recently, a new specialized cancer epitope database has been developed to fill the gaps in cancer epitope prediction. The Cancer Epitope Database and Analysis Resource (CEDAR) [ 69 ] is envisioned as a complete bioinformatics resource that will give access to curated cancer epitope data, including mutant and non-mutated cancer epitopes, as well as bioinformatics tools for epitope and receptor research and prediction. The planned effort would expand on the IEDB.…”

Section: Immunoinformatics Approachmentioning

confidence: 99%

Immunoinformatics Approach for Epitope-Based Vaccine Design: Key Steps for Breast Cancer Vaccine

2022

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Vaccines are an upcoming medical intervention for breast cancer. By targeting the tumor antigen, cancer vaccines can be designed to train the immune system to recognize tumor cells. Therefore, along with technological advances, the vaccine design process is now starting to be carried out with more rational methods such as designing epitope-based peptide vaccines using immunoinformatics methods. Immunoinformatics methods can assist vaccine design in terms of antigenicity and safety. Common protocols used to design epitope-based peptide vaccines include tumor antigen identification, protein structure analysis, T cell epitope prediction, epitope characterization, and evaluation of protein‒epitope interactions. Tumor antigen can be divided into two types: tumor associated antigen and tumor specific antigen. We will discuss the identification of tumor antigens using high-throughput technologies. Protein structure analysis comprises the physiochemical, hydrochemical, and antigenicity of the protein. T cell epitope prediction models are widely available with various prediction parameters as well as filtering tools for the prediction results. Epitope characterization such as allergenicity and toxicity can be done in silico as well using allergenicity and toxicity predictors. Evaluation of protein‒epitope interactions can also be carried out in silico with molecular simulation. We will also discuss current and future developments of breast cancer vaccines using an immunoinformatics approach. Finally, although prediction models have high accuracy, the opposite can happen after being tested in vitro and in vivo. Therefore, further studies are needed to ensure the effectiveness of the vaccine to be developed. Although epitope-based peptide vaccines have the disadvantage of low immunogenicity, the addition of adjuvants can be a solution.

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“…Thus, intensive attention is given to strategies targeting neoantigens for the significant impact with other immunotherapy, such as the immune checkpoint inhibitor. Today, several algorithms are designed and optimized based on NGS and public databases, including dbPepNeo database ( www.biostatistics.online/dbPepNeo/ ) [ 202 ], TANTIGEN 2.0 database ( http://projects.met-hilab.org/tadb/ ) [ 203 ], Cancer Antigenic Peptide Database ( https://caped.icp.ucl.ac.be ), NEPdb [ 204 ], CEDAR or Cancer Epitope Database and Analysis Resource which led by La Jolla Institute for Immunology (LJI) and the project team are working to get CEDAR up and running [ 205 ], for predicting neoantigens in silico that motivates the development of cancer vaccines and other promising immunotherapy approaches.…”

Section: Conclusion and Prospectivementioning

confidence: 99%

“…ac. be), NEPdb [204], CEDAR or Cancer Epitope Database and Analysis Resource which led by La Jolla Institute for Immunology (LJI) and the project team are working to get CEDAR up and running [205], for predicting neoantigens in silico that motivates the development of cancer vaccines and other promising immunotherapy approaches.…”

Section: Conclusion and Prospectivementioning

confidence: 99%

Neoantigens and their clinical applications in human gastrointestinal cancers

et al. 2022

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Background Tumor-specific neoantigens are ideal targets for cancer immunotherapy. As research findings have proved, neoantigen-specific T cell activity is immunotherapy’s most important determinant. Main text There is sufficient evidence showing the role of neoantigens in clinically successful immunotherapy, providing a justification for targeting. Because of the significance of the pre-existing anti-tumor immune response for the immune checkpoint inhibitor, it is believed that personalized neoantigen-based therapy may be an imperative approach for cancer therapy. Thus, intensive attention is given to strategies targeting neoantigens for the significant impact with other immunotherapies, such as the immune checkpoint inhibitor. Today, several algorithms are designed and optimized based on Next-Generation Sequencing and public databases, including dbPepNeo, TANTIGEN 2.0, Cancer Antigenic Peptide Database, NEPdb, and CEDAR databases for predicting neoantigens in silico that stimulates the development of T cell therapies, cancer vaccine, and other ongoing immunotherapy approaches. Conclusions In this review, we deliberated the current developments in understanding and recognition of the immunogenicity of newly found gastrointestinal neoantigens as well as their functions in immunotherapies and cancer detection. We also described how neoantigens are being developed and how they might be used in the treatment of GI malignancies.

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The Cancer Epitope Database and Analysis Resource: A Blueprint for the Establishment of a New Bioinformatics Resource for Use by the Cancer Immunology Community

Cited by 12 publications

References 82 publications

CAD v1.0: Cancer Antigens Database Platform for Cancer Antigen Algorithm Development and Information Exploration

CAD v1.0: Cancer Antigens Database Platform for Cancer Antigen Algorithm Development and Information Exploration

Immunoinformatics Approach for Epitope-Based Vaccine Design: Key Steps for Breast Cancer Vaccine

Neoantigens and their clinical applications in human gastrointestinal cancers

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