ArticleNature communications2020
Predicting clinical benefit of immunotherapy by antigenic or functional mutations affecting tumour immunogenicity.
Article in Nature communications, 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 36 papers, 2 of them syntheses that pooled it.
What it found
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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
36 citing papers in PubMed, 2 syntheses or guidelines pooled it, 67 citations in OpenAlex.
- Prognostic significance of the CRAFITY score in hepatocellular carcinoma treated with immunotherapy: a systematic review and meta-analysis.BMC cancer · 2023Pooled it
- Early melanoma invasivity correlates with gut fungal and bacterial profiles.The British journal of dermatology · 2022Pooled it
- A single arm phase Ib/II trial of first-line pembrolizumab, trastuzumab and chemotherapy for advanced HER2-positive gastric cancer.Nature communications · 2022Trial
- Technical review of artificial intelligence in TCR-T therapy.Journal of the National Cancer Center · 2026Review
- Assessment of tumor mutation burden based on whole-exome sequencing of extracellular vesicle-derived DNA from bronchoalveolar lavage fluid in advanced non-small cell lung cancer treated with pembrolizumab: a prospective, multicenter, observational study.Translational lung cancer research · 2026Article
- The activity of immune checkpoint inhibitors in patients with recurrent cervical cancer developed in previously irradiated field: clinical and immunohistochemical investigations.Journal of gynecologic oncology · 2026Article
- B cell-reactive neoantigens boost antitumor immunity.Science advances · 2025Article
- Hallmarks of artificial intelligence contributions to precision oncology.Nature cancer · 2025Review
- Dual targeting of TIGIT and VISTA in non-small-cell lung cancer immunotherapy.EXCLI journal · 2025Review
- CapHLA: a comprehensive tool to predict peptide presentation and binding to HLA class I and class II.Briefings in bioinformatics · 2024Article
- Mutations in glioblastoma proteins do not disrupt epitope presentation and recognition, maintaining a specific CD8 T cell immune response potential.Scientific reports · 2024Article
- Advances in pediatric gliomas: from molecular characterization to personalized treatments.European journal of pediatrics · 2024Review
- GraphMHC: Neoantigen prediction model applying the graph neural network to molecular structure.PloS one · 2024Article
- GIHP: Graph convolutional neural network based interpretable pan-specific HLA-peptide binding affinity prediction.Frontiers in genetics · 2024Article
- Strategies to Overcome Hurdles in Cancer Immunotherapy.Biomaterials research · 2024Review
- Bifidobacterium affects antitumor efficacy of oncolytic adenovirus in a mouse model of melanoma.iScience · 2023Article
- DeepNeo: a webserver for predicting immunogenic neoantigens.Nucleic acids research · 2023Article
- MHC II immunogenicity shapes the neoepitope landscape in human tumors.Nature genetics · 2023Article
- Designing neoantigen cancer vaccines, trials, and outcomes.Frontiers in immunology · 2023Review
- Pan-sarcoma characterization of lncRNAs in the crosstalk of EMT and tumour immunity identifies distinct clinical outcomes and potential implications for immunotherapy.Cellular and molecular life sciences : CMLS · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Neoantigen burden is regarded as a fundamental determinant of response to immunotherapy. However, its predictive value remains in question because some tumours with high neoantigen load show resistance. Here, we investigate our patient cohort together with a public cohort by our algorithms for the modelling of peptide-MHC binding and inter-cohort genomic prediction of therapeutic resistance. We first attempt to predict MHC-binding peptides at high accuracy with convolutional neural networks. Our prediction outperforms previous methods in > 70% of test cases. We then develop a classifier that can predict resistance from functional mutations. The predictive genes are involved in immune response and EGFR signalling, whereas their mutation patterns reflect positive selection. When integrated with our neoantigen profiling, these anti-immunogenic mutations reveal higher predictive power than known resistance factors. Our results suggest that the clinical benefit of immunotherapy can be determined by neoantigens that induce immunity and functional mutations that facilitate immune evasion.
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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.