SynthesisAnnals of oncology : official journal of the European Society for Medical Oncology2020
Neoantigen prediction and computational perspectives towards clinical benefit: recommendations from the ESMO Precision Medicine Working Group.
Synthesis in Annals of oncology : official journal of the European Society for Medical Oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 104 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
104 citing papers in PubMed, 1 synthesis or guideline pooled it, 148 citations in OpenAlex.
- Transformers meets neoantigen detection: a systematic literature review.Journal of integrative bioinformatics · 2024Pooled it
- Characteristics of clinical trials for non-small cell lung cancer therapeutic vaccines registered on ClinicalTrials.gov.Frontiers in immunology · 2022Trial
- Artificial intelligence for translational personalized neoantigen cancer vaccine development.Journal of biomedical science · 2026Review
- Review
- Advances in Therapeutic Melanoma Vaccines (2010-2025).Vaccines · 2026Review
- The landscape of genitourinary cancer vaccines: clinical advances and future opportunities.Journal of advanced research · 2026Review
- TransBindpMHCI: a transformer-based model for pan-specific MHC-I peptide binding prediction.BMC bioinformatics · 2026Article
- Tumor Microenvironment in Neuroblastoma and Immunotherapeutic Approaches: Towards More Effective Treatment.Cancers · 2026Review
- Targeting Telomerase in Cancer: Vaccine-Based Strategies, Clinical Evidence, and Synergy with Immunotherapy.Diseases (Basel, Switzerland) · 2026Review
- CNNeoPP: a large language model-enhanced deep learning pipeline for personalized neoantigen prediction and liquid biopsy applications.Frontiers in immunology · 2026Article
- Head and neck cancer therapeutic vaccines: a review.Frontiers in oncology · 2026Review
- Quantum medicine: A quantum-mechanical framework for redox biology, disease and precision medicine.Clinical and translational medicine · 2026Review
- ImmunoNX: a robust bioinformatics workflow to support personalized neoantigen vaccine trials.ArXiv · 2025Article
- PredIG: an interpretable predictor of T-cell epitope immunogenicity.Genome medicine · 2025Article
- Beyond single biomarkers: multi-omics strategies to predict immunotherapy outcomes in blood cancers.Clinical and experimental medicine · 2025Review
- NovumRNA: Accurate prediction of non-canonical tumor antigens from RNA sequencing data.iScience · 2025Article
- Personalizing DNA Cancer Vaccines.Journal of personalized medicine · 2025Review
- THLANet: A deep learning framework for predicting TCR-pHLA binding in immunotherapy applications.PLoS computational biology · 2025Article
- A comprehensive proteogenomic pipeline for neoantigen discovery to advance personalized cancer immunotherapy.Nature biotechnology · 2025Article
- Characterization of Tumor Antigens from Multi-omics Data: Computational Approaches and Resources.Genomics, proteomics & bioinformatics · 2025Review
44 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
15 authors at 10 institutions in 5 countries.
Funding
Abstract
backgroundThe use of next-generation sequencing technologies has enabled the rapid identification of non-synonymous somatic mutations in cancer cells. Neoantigens are mutated peptides derived from somatic mutations not present in normal tissues that may result in the presentation of tumour-specific peptides capable of eliciting antitumour T-cell responses. Personalised neoantigen-based cancer vaccines and adoptive T-cell therapies have been shown to prime host immunity against tumour cells and are under clinical trial development. However, the optimisation and standardisation of neoantigen identification, as well as its delivery as immunotherapy are needed to increase tumour-specific T-cell responses and, thus, the clinical efficacy of current cancer immunotherapies.
methodsIn this recommendation article, launched by the European Society for Medical Oncology (ESMO), we outline and discuss the available framework for neoantigen prediction and present a systematic review of the current scientific evidence.
resultsA number of computational pipelines for neoantigen prediction are available. Most of them provide peptide major histocompatibility complex (MHC) binding affinity predictions, but more recent approaches incorporate additional features like variant allele fraction, gene expression, and clonality of mutations. Neoantigens can be predicted in all cancer types with high and low tumour mutation burden, in part by exploiting tumour-specific aberrations derived from mutational frameshifts, splice variants, gene fusions, endogenous retroelements and other tumour-specific processes that could yield more potently immunogenic tumour neoantigens. Ongoing clinical trials will highlight those cancer types and combinations of immune therapies that would derive the most benefit from neoantigen-based immunotherapies.
conclusionsImproved identification, selection and prioritisation of tumour-specific neoantigens are needed to increase the scope of benefit from cancer vaccines and adoptive T-cell therapies. Novel pipelines are being developed to resolve the challenges posed by high-throughput sequencing and to predict immunogenic neoantigens.
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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.