ArticleCancer immunology, immunotherapy : CII2017
MuPeXI: prediction of neo-epitopes from tumor sequencing data.
Article in Cancer immunology, immunotherapy : CII, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 129 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
129 citing papers in PubMed, 1 synthesis or guideline pooled 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
- Preliminary clinical study of personalized neoantigen vaccine therapy for microsatellite stability (MSS)-advanced colorectal cancer.Cancer immunology, immunotherapy : CII · 2023Trial
- Neoantigen-specific CD8 T cell responses in the peripheral blood following PD-L1 blockade might predict therapy outcome in metastatic urothelial carcinoma.Nature communications · 2022Trial
- Neoantigen-reactive CD8+ T cells affect clinical outcome of adoptive cell therapy with tumor-infiltrating lymphocytes in melanoma.The Journal of clinical investigation · 2022Trial
- Evaluation of T-Cell Responses Against Shared Melanoma Associated Antigens and Predicted Neoantigens in Cutaneous Melanoma Patients Treated With the CSF-470 Allogeneic Cell Vaccine Plus BCG and GM-CSF.Frontiers in immunology · 2020Trial
- Cancer epitope prediction tools and analysis pipelines in CEDAR.Nucleic acids research · 2026Article
- AI-driven neoantigen identification: a comprehensive review from somatic variant calling to T cell recognition.Journal of translational medicine · 2026Review
- Advances in delivery technologies-powered cancer vaccines.Bioactive materials · 2026Review
- Repurposing public sarcoma multi-omics for neoantigen discovery.Cancer immunology, immunotherapy : CII · 2026Article
- ImmunoPepper: extracting personalized peptides from complex splicing graphs.Bioinformatics (Oxford, England) · 2026Article
- Artificial intelligence in peptide cancer vaccine design: from neoantigen discovery to immunogenicity prediction.Frontiers in genetics · 2026Review
- AI-powered mapping of tumor immunity for optimized mRNA vaccine engineering.Frontiers in oncology · 2026Review
- NeoGuider: neoepitope prediction using advanced feature engineering.Genome medicine · 2025Article
- Neoantigen-Driven Immunotherapy in Triple-Negative Breast Cancer: Emerging Strategies and Clinical Potential.Biomedicines · 2025Review
- Development of therapeutic cancer vaccines based on cancer immunity cycle.Frontiers of medicine · 2025Review
- Characterization of Tumor Antigens from Multi-omics Data: Computational Approaches and Resources.Genomics, proteomics & bioinformatics · 2025Review
- Computational methods and data resources for predicting tumor neoantigens.Briefings in bioinformatics · 2025Review
- The Landmark Series: Therapeutic Cancer Vaccine Strategies for Cold Tumors.Annals of surgical oncology · 2025Review
- Review
- Integration of proteomics profiling data to facilitate discovery of cancer neoantigens: a survey.Briefings in bioinformatics · 2025Review
69 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Personalization of immunotherapies such as cancer vaccines and adoptive T cell therapy depends on identification of patient-specific neo-epitopes that can be specifically targeted. MuPeXI, the mutant peptide extractor and informer, is a program to identify tumor-specific peptides and assess their potential to be neo-epitopes. The program input is a file with somatic mutation calls, a list of HLA types, and optionally a gene expression profile. The output is a table with all tumor-specific peptides derived from nucleotide substitutions, insertions, and deletions, along with comprehensive annotation, including HLA binding and similarity to normal peptides. The peptides are sorted according to a priority score which is intended to roughly predict immunogenicity. We applied MuPeXI to three tumors for which predicted MHC-binding peptides had been screened for T cell reactivity, and found that MuPeXI was able to prioritize immunogenic peptides with an area under the curve of 0.63. Compared to other available tools, MuPeXI provides more information and is easier to use. MuPeXI is available as stand-alone software and as a web server at http://www.cbs.dtu.dk/services/MuPeXI .
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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.