ArticleCell2020
Key Parameters of Tumor Epitope Immunogenicity Revealed Through a Consortium Approach Improve Neoantigen Prediction.
Article in Cell, 2020. 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 356 papers.
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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
356 citing papers in PubMed.
- Exome sequencing shows same pattern of clonal tumor mutational burden, intratumor heterogenicity and clonal neoantigen between autologous tumor and Vigil product.Scientific reports · 2025Trial
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- Toward next-generation therapeutic HPV vaccines: A review on expanding the antigen repertoire and an integrated bioinformatics selection framework.Human vaccines & immunotherapeutics · 2026Review
- Neoantigen cancer vaccines for gastrointestinal tumors: opportunities and challenges.MedScience · 2026Review
- Predicting Neoantigen Immunogenicity frombioRxiv : the preprint server for biology · 2026Article
- Cancers modulate processing and presentation of p53 neoantigens to evade T cell detection.Immunity · 2026Article
- Current landscape and future directions of neoantigen vaccines: A new era of personalized cancer immunotherapy.Innovation (Cambridge (Mass.)) · 2026Review
- From Universal Aspiration to Precision Immunization: A Hypothesis Framework for Antigen-Defined, HLA-Restricted Cancer Vaccines.Vaccines · 2026Review
- Current and future therapies for triple-negative breast cancer.Journal of hematology & oncology · 2026Review
- Artificial intelligence in oncology: linking biological discovery to clinical utility.Molecular cancer · 2026Review
- T-cell receptor repertoires against HLA class I-restricted minor histocompatibility antigens are highly diverse with a small subset of public clonotypes.Journal for immunotherapy of cancer · 2026Article
- Past achievements and future perspectives of personalized vaccines and the role of dendritic cells.Immunologic research · 2026Review
- Take Five: harmonization in personalized cancer vaccines for cancer immunotherapy.Experimental & molecular medicine · 2026Review
- Highlight of 2025: From binding prediction to molecular design-computational advances in TCR-pMHC prediction and targeting.Immunology and cell biology · 2026Review
- Technical review of artificial intelligence in TCR-T therapy.Journal of the National Cancer Center · 2026Review
- Quantum convolutional HLA immunogenic peptide prediction (Q-CHIPP): Next-generation neoantigen prediction with quantum neural network.Science advances · 2026Article
- Differential T cell clonal dynamics underlie outcomes to frontline chemoimmunotherapy in advanced gastric cancer.Cell reports. Medicine · 2026Article
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- Cancer epitope prediction tools and analysis pipelines in CEDAR.Nucleic acids research · 2026Article
- In vivo engineering tumor cells to a universal "all-in-one" cancer vaccine with full antigen spectrum.Science advances · 2026Article
296 more citing papers are in PubMed but not listed here.
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Authors and funding
37 authors.
Funding
Abstract
Many approaches to identify therapeutically relevant neoantigens couple tumor sequencing with bioinformatic algorithms and inferred rules of tumor epitope immunogenicity. However, there are no reference data to compare these approaches, and the parameters governing tumor epitope immunogenicity remain unclear. Here, we assembled a global consortium wherein each participant predicted immunogenic epitopes from shared tumor sequencing data. 608 epitopes were subsequently assessed for T cell binding in patient-matched samples. By integrating peptide features associated with presentation and recognition, we developed a model of tumor epitope immunogenicity that filtered out 98% of non-immunogenic peptides with a precision above 0.70. Pipelines prioritizing model features had superior performance, and pipeline alterations leveraging them improved prediction performance. These findings were validated in an independent cohort of 310 epitopes prioritized from tumor sequencing data and assessed for T cell binding. This data resource enables identification of parameters underlying effective anti-tumor immunity and is available to the research community.
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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.