ArticleGenome biology2023
Comprehensive analysis of neoantigens derived from structural variation across whole genomes from 2528 tumors.
Article in Genome biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
- Current landscape and future directions of neoantigen vaccines: A new era of personalized cancer immunotherapy.Innovation (Cambridge (Mass.)) · 2026Review
- Neoantigen Targeting as a Novel Approach for Therapy-Resistant Tumors.Molecular diagnosis & therapy · 2026Review
- Decoding immunotherapy response through computational modeling.Nature communications · 2026Review
- Molecular origin, discovery, validation and application of neoantigens.Asian journal of pharmaceutical sciences · 2026Review
- SVNeoPP: A Workflow for Structural-Variant-Derived Neoantigen Prediction and Prioritization Using Multi-Omics Data.Biology · 2026Article
- CNNeoPP: a large language model-enhanced deep learning pipeline for personalized neoantigen prediction and liquid biopsy applications.Frontiers in immunology · 2026Article
- ImmunoNX: a robust bioinformatics workflow to support personalized neoantigen vaccine trials.ArXiv · 2025Article
- Engineering Anti-Tumor Immunity: An Immunological Framework for mRNA Cancer Vaccines.Vaccines · 2025Review
- NovumRNA: Accurate prediction of non-canonical tumor antigens from RNA sequencing data.iScience · 2025Article
- Personalizing DNA Cancer Vaccines.Journal of personalized medicine · 2025Review
- CDKN2A deletion is associated with immune desertification in diffuse pleural mesothelioma.Journal of experimental & clinical cancer research : CR · 2025Article
- Neoantigen load as a predictor of relapse in early-stage NSCLC: features that agonise and antagonise prognosis.Cancer immunology, immunotherapy : CII · 2025Article
- Computation strategies and clinical applications in neoantigen discovery towards precision cancer immunotherapy.Biomarker research · 2025Review
- SpatialSNV: A novel method for identifying and analyzing spatially resolved SNVs in tumor microenvironments.GigaScience · 2025Article
- Vaccine therapies for glioma: clinical frontiers and potential breakthrough.Frontiers in oncology · 2025Review
- Biomarkers to predict the benefits of immune‑checkpoint blockade‑based therapy in patients with malignant peritoneal mesothelioma (Review).Oncology letters · 2024Review
- Molecular targets and strategies in the development of nucleic acid cancer vaccines: from shared to personalized antigens.Journal of biomedical science · 2024Review
- Article
- Global research landscape and trends of cancer radiotherapy plus immunotherapy: A bibliometric analysis.Heliyon · 2024Article
- Enhancing the quality of panel-based tumor mutation burden assessment: a comprehensive study of real-world and in-silico outcomes.NPJ precision oncology · 2024Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundNeoantigens are critical for anti-tumor immunity and have been long-envisioned as promising therapeutic targets. However, current neoantigen analyses mostly focus on single nucleotide variations (SNVs) and indel mutations and seldom consider structural variations (SVs) that are also prevalent in cancer.
resultsHere, we develop a computational method termed NeoSV, which incorporates SV annotation, protein fragmentation, and MHC binding prediction together, to predict SV-derived neoantigens. Analysis of 2528 whole genomes reveals that SVs significantly contribute to the neoantigen repertoire in both quantity and quality. Whereas most neoantigens are patient-specific, shared neoantigens are identified with high occurrence rates in breast, ovarian, and gastrointestinal cancers. We observe extensive immunoediting on SV-derived neoantigens, especially on clonal events, which suggests their immunogenic potential. We also demonstrate that genomic alteration-related neoantigen burden, which integrates SV-derived neoantigens, depicts the tumor-immune interplay better than tumor neoantigen burden and may improve patient selection for immunotherapy.
conclusionsOur study fills the gap in the current neoantigen repertoire and provides a valuable resource for cancer vaccine development.
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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.