ArticleOncoimmunology2021
Immune-based mutation classification enables neoantigen prioritization and immune feature discovery in cancer immunotherapy.
Article in Oncoimmunology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 24 citations in OpenAlex.
- PredIG: an interpretable predictor of T-cell epitope immunogenicity.Genome medicine · 2025Article
- Shared neoantigens for cancer immunotherapy.Molecular therapy. Oncology · 2025Review
- Advances in the understanding and therapeutic manipulation of cancer immune responsiveness: a Society for Immunotherapy of Cancer (SITC) review.Journal for immunotherapy of cancer · 2025Review
- Stratifying ICIs-responsive tumor microenvironment in HCC: from parsing out immune-hypoxic crosstalk to clinically applicable MRI-radiomics models.British journal of cancer · 2024Article
- Molecular determinants of immunogenic cell death elicited by radiation therapy.Immunological reviews · 2024Review
- Conformational plasticity of RAS Q61 family of neoepitopes results in distinct features for targeted recognition.Nature communications · 2023Article
- Analysis of thymic generation of shared T-cell receptor α repertoire associated with recognition of tumor antigens shows no preference for neoantigens over wild-type antigens.Cancer medicine · 2023Article
- Therapeutic high affinity T cell receptor targeting a KRASNature communications · 2022Article
- Neoantigen Cancer Vaccines: Generation, Optimization, and Therapeutic Targeting Strategies.Vaccines · 2022Review
- Radiation therapy: An old dog learning new tricks.Methods in cell biology · 2022Article
- Modified immunoscore improves the prediction of progression-free survival in patients with non-muscle-invasive bladder cancer: A digital pathology study.Frontiers in oncology · 2022Article
- Neoantigen: A Promising Target for the Immunotherapy of Colorectal Cancer.Disease markers · 2022Review
- Beyond Tumor Mutation Burden: Tumor Neoantigen Burden as a Biomarker for Immunotherapy and Other Types of Therapy.Frontiers in oncology · 2021Review
- NEPdb: A Database of T-Cell Experimentally-Validated Neoantigens and Pan-Cancer Predicted Neoepitopes for Cancer Immunotherapy.Frontiers in immunology · 2021Article
Corrections and comments
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Authors and funding
13 authors at 4 institutions in 2 countries.
Funding
Abstract
Genetic mutations lead to the production of mutated proteins from which peptides are presented to T cells as cancer neoantigens. Evidence suggests that T cells that target neoantigens are the main mediators of effective cancer immunotherapies. Although algorithms have been used to predict neoantigens, only a minority are immunogenic. The factors that influence neoantigen immunogenicity are not completely understood. Here, we classified human neoantigen/neopeptide data into three categories based on their TCR-pMHC binding events. We observed a conservative mutant orientation of the anchor residue from immunogenic neoantigens which we termed the "NP" rule. By integrating this rule with an existing prediction algorithm, we found improved performance in neoantigen prioritization. To better understand this rule, we solved several neoantigen/MHC structures. These structures showed that neoantigens that follow this rule not only increase peptide-MHC binding affinity but also create new TCR-binding features. These molecular insights highlight the value of immune-based classification in neoantigen studies and may enable the design of more effective cancer immunotherapies.
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