ArticleScientific reports2019
A library of Neo Open Reading Frame peptides (NOPs) as a sustainable resource of common neoantigens in up to 50% of cancer patients.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
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Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it, 32 citations in OpenAlex.
- Neoantigen prediction and computational perspectives towards clinical benefit: recommendations from the ESMO Precision Medicine Working Group.Annals of oncology : official journal of the European Society for Medical Oncology · 2020Pooled it
- Trial
- Review
- Computational identification of cross-reactive TCR epitopes with ARDitox.Journal of cancer research and clinical oncology · 2025Article
- Coordinated expression of retained introns and poison exons in renal cell carcinoma.Cell reports · 2025Article
- Bispecific T-cell engagers for the recruitment of T cells in solid tumors: a literature review.Immunotherapy advances · 2025Review
- Leveraging a powerful allogeneic dendritic cell line towards neoantigen-based cancer vaccines.Genes & cancer · 2023Article
- Development of antigen-prediction algorithm for personalized neoantigen vaccine using human leukocyte antigen transgenic mouse.Cancer science · 2022Article
- Review
- What's next in cancer immunotherapy? - The promise and challenges of neoantigen vaccination.Oncoimmunology · 2022Review
- Mutational signatures: emerging concepts, caveats and clinical applications.Nature reviews. Cancer · 2021Review
- Understanding small ORF diversity through a comprehensive transcription feature classification.DNA research : an international journal for rapid publication of reports on genes and genomes · 2021Review
- Article
- Review
- Neo-Antigen mRNA Vaccines.Vaccines · 2020Review
- Article
- Generation of multiepitope cancer vaccines based on large combinatorial libraries of survivin-derived mutant epitopes.Immunology · 2020Article
- Review
- Machine Learning for Cancer Immunotherapies Based on Epitope Recognition by T Cell Receptors.Frontiers in genetics · 2019Review
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Somatic mutations in cancer can result in neoantigens against which patients can be vaccinated. The quest for tumor specific neoantigens has yielded no targets that are common to all tumors, yet foreign to healthy cells. Single base pair substitutions (SNVs) at best can alter 1 amino acid which can result in a neoantigen; with the exception of rare site-specific oncogenic driver mutations (such as RAS) such mutations are private. Here, we describe a source of common neoantigens induced by frame shift mutations, based on analysis of 10,186 TCGA tumor samples. We find that these frame shift mutations can produce long neoantigens. These are completely new to the body, and indeed recent evidence suggests that frame shifts can be highly immunogenic. We report that many different frame shift mutations converge to the same small set of 3' neo open reading frame peptides (NOPs), all encoded by the Neo-ORFeome. We find that a fixed set of only 1,244 neo-peptides in as much as 30% of all TCGA cancer patients. For some tumor classes this is higher; e.g. for colon and cervical cancer, peptides derived from only ten genes (saturated at 90 peptides) can be applied to 39% of all patients. 50% of all TCGA patients can be achieved at saturation (using all those peptides in the library found more than once). A pre-fabricated library of vaccines (peptide, RNA or DNA) based on this set can provide off the shelf, quality certified, 'personalized' vaccines within hours, saving months of vaccine preparation. This is crucial for critically ill cancer patients with short average survival expectancy after diagnosis.
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