ArticleCancer science2021
Neoantigen prediction in human breast cancer using RNA sequencing data.
Article in Cancer science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 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.
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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
21 citing papers in PubMed, 26 citations in OpenAlex.
- Review
- pVACtools v6: A comprehensive suite for neoantigen prediction, visualization, and therapy design.ArXiv · 2026Article
- ImmunoNX: a robust bioinformatics workflow to support personalized neoantigen vaccine trials.ArXiv · 2025Article
- Neoantigen-Driven Immunotherapy in Triple-Negative Breast Cancer: Emerging Strategies and Clinical Potential.Biomedicines · 2025Review
- RNA-DNA Differences: Mechanisms, Oxidative Stress, Transcriptional Fidelity, and Health Implications.Antioxidants (Basel, Switzerland) · 2025Review
- Advances in Therapeutic Cancer Vaccines, Their Obstacles, and Prospects Toward Tumor Immunotherapy.Molecular biotechnology · 2025Review
- Refined variant calling pipeline on RNA-seq data of breast cancer cell lines without matched-normal samples.BMC research notes · 2025Article
- Identification of BRCA new prognostic targets and neoantigen candidates from fusion genes.Discover oncology · 2024Article
- Tumor Neoepitope-Based Vaccines: A Scoping Review on Current Predictive Computational Strategies.Vaccines · 2024Article
- Targeting Neoantigens in Cancer: Possibilities and Opportunities in Breast Cancer.Antibodies (Basel, Switzerland) · 2024Review
- Tumor neoantigens and tumor immunotherapies.Aging medicine (Milton (N.S.W)) · 2024Review
- Full-length isoform concatenation sequencing to resolve cancer transcriptome complexity.BMC genomics · 2024Article
- MALAT1 promotes FOXA1 degradation by competitively binding to miR-216a-5p and enhancing neuroendocrine differentiation in prostate cancer.Translational oncology · 2024Article
- Proteogenomic analysis reveals RNA as a source for tumor-agnostic neoantigen identification.Nature communications · 2023Article
- Update Breast Cancer 2022 Part 5 - Early Stage Breast Cancer.Geburtshilfe und Frauenheilkunde · 2023Article
- Improvement in neoantigen prediction via integration of RNA sequencing data for variant calling.Frontiers in immunology · 2023Article
- The current advances of lncRNAs in breast cancer immunobiology research.Frontiers in immunology · 2023Review
- Update Breast Cancer 2022 Part 1 - Early Stage Breast Cancer.Geburtshilfe und Frauenheilkunde · 2022Article
- Development of antigen-prediction algorithm for personalized neoantigen vaccine using human leukocyte antigen transgenic mouse.Cancer science · 2022Article
- Engineering neoantigen vaccines to improve cancer personalized immunotherapy.International journal of biological sciences · 2022Review
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
Abstract
Neoantigens have attracted attention as biomarkers or therapeutic targets. However, accurate prediction of neoantigens is still challenging, especially in terms of its accuracy and cost. Variant detection using RNA sequencing (RNA-seq) data has been reported to be a low-accuracy but cost-effective tool, but the feasibility of RNA-seq data for neoantigen prediction has not been fully examined. In the present study, we used whole-exome sequencing (WES) and RNA-seq data of tumor and matched normal samples from six breast cancer patients to evaluate the utility of RNA-seq data instead of WES data in variant calling to detect neoantigen candidates. Somatic variants were called in three protocols using: (i) tumor and normal WES data (DNA method, Dm); (ii) tumor and normal RNA-seq data (RNA method, Rm); and (iii) combination of tumor RNA-seq and normal WES data (Combination method, Cm). We found that the Rm had both high false-positive and high false-negative rates because this method depended greatly on the expression status of normal transcripts. When we compared the results of Dm with those of Cm, only 14% of the neoantigen candidates detected in Dm were identified in Cm, but the majority of the missed candidates lacked coverage or variant allele reads in the tumor RNA. In contrast, about 70% of the neoepitope candidates with higher expression and rich mutant transcripts could be detected in Cm. Our results showed that Cm could be an efficient and a cost-effective approach to predict highly expressed neoantigens in tumor samples.
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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.