Recent advances in immunotherapy drugs, such as CTLA-4 and PD-1 blocking antibodies (immune checkpoint inhibitors), have highlighted the capacity of induced anti-tumor immune responses to yield improved survival for cancer patients ( Hellmann et al., 2018 Hodi et al., 2010 Larkin et al., 2019). NeoSplice provides a well-validated platform for prediction of TSA vaccine targets for future cancer antigen vaccine studies to evaluate the clinical efficacy of splice variant neoantigens. Lastly, we provide a comparison of NeoSplice against other splice variant prediction tools described in the literature. Through mass spectrometry analysis of the immunopeptidome of the K562.A2 cell line compared against a synthetic peptide reference of predicted splice variant neoantigens, we validated 4 of 37 predicted antigens corresponding to 3 of 17 unique splice junctions. NeoSplice demonstrates high sensitivity and precision (>80% on average across all splice variant classes) through in silico simulated RNA-seq data. In this study, we describe NeoSplice, a novel computational method for splice variant neoantigen prediction based on (i) prediction of tumor-specific k-mers from RNA-seq data, (ii) alignment of differentially expressed k-mers to the splice graph and (iii) inference of the variant transcript with MHC binding prediction.
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