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.
Keywords: HA, hemagglutinin; MCA, methylcholanthrene; NGS, next-generation sequencing; RNAseq; SNV, single nucleotide variant.; dLN, lymph node draining the tumor; epitope prediction; mesothelioma; neoantigen.