OncoImmunology · 2015 · 32 citations · 30 references
Life SciencesImmunologyOncologyCancer ImmunologyImmunotherapyTumor ImmunologyCancer GenomicsCancer ImmunotherapyNeoantigen ImmunologyT Cell Responses To TumorsTumor AntigensTumor-associated AntigensCancer NeoantigensHost Immune Response MarkersNeoantigen IdentificationPeptide Binding AffinityRna SequencingRna Sequencing (Rna-seq)Single-nucleotide VariantsTumor-specific Antigen Identification
A key to improving cancer immunotherapy will be the identification of tumor-specific "neoantigens" that arise from mutations and augment the resultant host immune response. In this study we identified single nucleotide variants (SNVs) by RNA sequencing of asbestos-induced murine mesothelioma cell lines AB1 and AB1-HA. Using the NetMHCpan 2.8 algorithm, the theoretical binding affinity of predicted peptides arising from high-confidence, exonic, non-synonymous SNVs was determined for the BALB/c strain. The immunoreactivity to 20 candidate mutation-carrying peptides of increased affinity and the corresponding wild-type peptides was determined using interferon-γ ELISPOT assays and lymphoid organs of non-manipulated tumor-bearing mice. A strong endogenous immune response was demonstrated to one of the candidate neoantigens, Uqcrc2; this response was detected in the draining lymph node and spleen. Antigen reactive cells were not detected in non-tumor bearing mice. The magnitude of the response to the Uqcrc2 neoantigen was similar to that of the strong influenza hemagglutinin antigen, a model tumor neoantigen. This work confirms that the approach of RNAseq plus peptide prediction and ELISPOT testing is sufficient to identify natural tumor neoantigens.
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The Sequence Alignment/Map format and SAMtools
Heng Li, Alec Wysoker, Tim Fennell et al. · Bioinformatics · 2009 · 67.5K citations · Full text
Fast and accurate short read alignment with Burrows–Wheeler transform
Heng Li, Richard Durbin · Bioinformatics · 2009 · 62.8K citations · Full text