ReviewOncoimmunology2016
Current tools for predicting cancer-specific T cell immunity.
Review in Oncoimmunology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
24 citing papers in PubMed, 51 citations in OpenAlex.
- Development of therapeutic cancer vaccines based on cancer immunity cycle.Frontiers of medicine · 2025Review
- Article
- Induction of cancer neoantigens facilitates development of clinically relevant models for the study of pancreatic cancer immunobiology.Cancer immunology, immunotherapy : CII · 2023Article
- A microfluidics-enabled automated workflow of sample preparation for MS-based immunopeptidomics.Cell reports methods · 2023Article
- Neoantigen-specific CD8 T cells with high structural avidity preferentially reside in and eliminate tumors.Nature communications · 2023Article
- The common HLA class I-restricted tumor-infiltrating T cell response in HPV16-induced cancer.Cancer immunology, immunotherapy : CII · 2023Article
- Advances of mRNA vaccine in tumor: a maze of opportunities and challenges.Biomarker research · 2023Review
- Peptide-based vaccine for cancer therapies.Frontiers in immunology · 2023Review
- A comprehensive analysis of the IEDB MHC class-I automated benchmark.Briefings in bioinformatics · 2022Article
- Comparison of HLA ligand elution data and binding predictions reveals varying prediction performance for the multiple motifs recognized by HLA-DQ2.5.Immunology · 2021Article
- A comprehensive review and performance evaluation of bioinformatics tools for HLA class I peptide-binding prediction.Briefings in bioinformatics · 2020Review
- High-Throughput Prediction of MHC Class I and II Neoantigens with MHCnuggets.Cancer immunology research · 2020Article
- Proteomics-inspired precision medicine for treating and understanding multiple myeloma.Expert review of precision medicine and drug development · 2020Article
- Identification and ranking of recurrent neo-epitopes in cancer.BMC medical genomics · 2019Article
- Footprints of antigen processing boost MHC class II natural ligand predictions.Genome medicine · 2018Article
- Pan-cancer analysis of neoepitopes.Scientific reports · 2018Article
- Systems Immunology: Learning the Rules of the Immune System.Annual review of immunology · 2018Review
- Personalized Clinical Decision Making Through Implementation of a Molecular Tumor Board: A German Single-Center Experience.JCO precision oncology · 2018Article
- Predicting Antigen Presentation-What Could We Learn From a Million Peptides?Frontiers in immunology · 2018Review
- Neoantigen prediction and the need for validation.Nature biotechnology · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Tumor exome and RNA sequencing data provide a systematic and unbiased view on cancer-specific expression, over-expression, and mutations of genes, which can be mined for personalized cancer vaccines and other immunotherapies. Of key interest are tumor-specific mutations, because T cells recognizing neoepitopes have the potential to be highly tumoricidal. Here, we review recent developments and technical advances in identifying MHC class I and class II-restricted tumor antigens, especially neoantigen derived MHC ligands, including in silico predictions, immune-peptidome analysis by mass spectrometry, and MHC ligand validation by biochemical methods on T cells.
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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.