ArticleNature biotechnology2018
Deep learning using tumor HLA peptide mass spectrometry datasets improves neoantigen identification.
Article in Nature biotechnology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07686744 (A Phase I Clinical Trial of Personalized Neoantigen Peptide Vaccine in Combination With Pembrolizumab for the Safety and Efficacy in Patients With Advanced, Recurrent or Refractory Renal Cell Carcinoma), which is not on this map. Cited by 152 papers, 4 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
A Phase I Clinical Trial of Personalized Neoantigen Peptide Vaccine in Combination With Pembrolizumab for the Safety and Efficacy in Patients With Advanced, Recurrent or Refractory Renal Cell Carcinoma
Who cites it
152 citing papers in PubMed, 4 syntheses or guidelines pooled it, 304 citations in OpenAlex.
- Transformers meets neoantigen detection: a systematic literature review.Journal of integrative bioinformatics · 2024Pooled it
- The current state and trends of immunotherapy research in lung cancer: a review and bibliometric analysis.Frontiers in oncology · 2024Pooled it
- Challenges targeting cancer neoantigens in 2021: a systematic literature review.Expert review of vaccines · 2021Pooled it
- 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
- Toward next-generation therapeutic HPV vaccines: A review on expanding the antigen repertoire and an integrated bioinformatics selection framework.Human vaccines & immunotherapeutics · 2026Review
- Cancer Vaccine Development: Toward Artificial Intelligence-Assisted Personalized Cell Membrane Nanovaccine.Small (Weinheim an der Bergstrasse, Germany) · 2026Review
- From Universal Aspiration to Precision Immunization: A Hypothesis Framework for Antigen-Defined, HLA-Restricted Cancer Vaccines.Vaccines · 2026Review
- The Ratio of Immunogenicity: A quantitative metric to identify highly immunogenic protein antigens to improve tissue-engineered biomaterials.Biomaterials · 2026Article
- Technical review of artificial intelligence in TCR-T therapy.Journal of the National Cancer Center · 2026Review
- Personalized cancer vaccines: bridging immune-oncology and precision medicine for advanced therapeutics.Signal transduction and targeted therapy · 2026Review
- AI-driven neoantigen identification: a comprehensive review from somatic variant calling to T cell recognition.Journal of translational medicine · 2026Review
- Personalized neoantigen-pulsed autologous dendritic cells in newly-diagnosed glioblastoma: a phase Ib trial.Nature communications · 2026Article
- AI-enabled virtual immunopeptidomics links quantitative neoantigen presentation to immunogenicity.bioRxiv : the preprint server for biology · 2026Article
- Article
- Neoantigen-based cancer vaccines: a mechanistic and clinical review of personalised melanoma immunotherapy.Frontiers in immunology · 2026Review
- Immunotherapy drug target identification using machine learning and patient-derived tumour explant validation.Nature machine intelligence · 2026Article
- AI-driven genotype-phenotype modeling: a framework integrating multi-modal single-cell genomics and reverse vaccinology forFrontiers in genetics · 2026Review
- Engineering Anti-Tumor Immunity: An Immunological Framework for mRNA Cancer Vaccines.Vaccines · 2025Review
- Innovations in cancer treatment as novel potential and the myth of personalized vaccines, immunotherapy, CRISPR/Cas9, and bacteriotherapy as promising therapeutic strategies.Discover oncology · 2025Review
- Alternative splicing: from tumorigenesis to neoantigen-mediated cancer immunotherapy.Biomarker research · 2025Review
92 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
39 authors at 11 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Neoantigens, which are expressed on tumor cells, are one of the main targets of an effective antitumor T-cell response. Cancer immunotherapies to target neoantigens are of growing interest and are in early human trials, but methods to identify neoantigens either require invasive or difficult-to-obtain clinical specimens, require the screening of hundreds to thousands of synthetic peptides or tandem minigenes, or are only relevant to specific human leukocyte antigen (HLA) alleles. We apply deep learning to a large (N = 74 patients) HLA peptide and genomic dataset from various human tumors to create a computational model of antigen presentation for neoantigen prediction. We show that our model, named EDGE, increases the positive predictive value of HLA antigen prediction by up to ninefold. We apply EDGE to enable identification of neoantigens and neoantigen-reactive T cells using routine clinical specimens and small numbers of synthetic peptides for most common HLA alleles. EDGE could enable an improved ability to develop neoantigen-targeted immunotherapies for cancer patients.
Identifiers
What OpenQuestion holds
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.