An integrated database of experimentally validated major histocompatibility complex epitopes for antigen-specific cancer therapy.

cancer immunotherapy epitopes immunogenicity major histocompatibility complex

Journal

Antibody therapeutics
ISSN: 2516-4236
Titre abrégé: Antib Ther
Pays: United States
ID NLM: 101730822

Informations de publication

Date de publication:
Apr 2024
Historique:
received: 26 01 2024
revised: 18 04 2024
medline: 27 6 2024
pubmed: 27 6 2024
entrez: 27 6 2024
Statut: epublish

Résumé

Cancer immunotherapy represents a paradigm shift in oncology, offering a superior anti-tumor efficacy and the potential for durable remission. The success of personalized vaccines and cell therapies hinges on the identification of immunogenic epitopes capable of eliciting an effective immune response. Current limitations in the availability of immunogenic epitopes restrict the broader application of such therapies. A critical criterion for serving as potential cancer antigens is their ability to stably bind to the major histocompatibility complex (MHC) for presentation on the surface of tumor cells. To address this, we have developed a comprehensive database of MHC epitopes, experimentally validated for their MHC binding and cell surface presentation. Our database catalogs 451 065 MHC peptide epitopes, each with experimental evidence for MHC binding, along with detailed information on human leukocyte antigen allele specificity, source peptides, and references to original studies. We also provide the grand average of hydropathy scores and predicted immunogenicity for the epitopes. The database (MHCepitopes) has been made available on the web and can be accessed at https://github.com/jcm1201/MHCepitopes.git. By consolidating empirical data from various sources coupled with calculated immunogenicity and hydropathy values, our database offers a robust resource for selecting actionable tumor antigens and advancing the design of antigen-specific cancer immunotherapies. It streamlines the process of identifying promising immunotherapeutic targets, potentially expediting the development of effective antigen-based cancer immunotherapies.

Identifiants

pubmed: 38933532
doi: 10.1093/abt/tbae011
pii: tbae011
pmc: PMC11200702
doi:

Types de publication

Journal Article

Langues

eng

Pagination

177-186

Informations de copyright

© The Author(s) 2024. Published by Oxford University Press on behalf of Antibody Therapeutics.

Déclaration de conflit d'intérêts

C.C.C. was employed by the company Biomap, Inc. The remaining authors declare that the research was conducted without commercial or financial relationships that could be construed as a potential conflict of interest.

Auteurs

Satoru Kawakita (S)

Department of Precision Medicine, Terasaki Institute for Biomedical Innovation, Los Angeles, CA 90024, United States.

Aidan Shen (A)

Department of Precision Medicine, Terasaki Institute for Biomedical Innovation, Los Angeles, CA 90024, United States.

Cheng-Chi Chao (CC)

Department of Pipeline Development, Biomap, Inc., Palo Alto, CA 94303, United States.

Zhaohui Wang (Z)

Department of Precision Medicine, Terasaki Institute for Biomedical Innovation, Los Angeles, CA 90024, United States.

Siliangyu Cheng (S)

Quantitative and Computational Biology Department, University of Southern California, Los Angeles, CA 90089, United States.

Bingbing Li (B)

Autonomy Research Center for STEAHM (ARCS), California State University Northridge, Northridge, CA 91324, United States.

Chongming Jiang (C)

Department of Precision Medicine, Terasaki Institute for Biomedical Innovation, Los Angeles, CA 90024, United States.

Classifications MeSH