Recent advances in next-generation sequencing have enabled rapid and efficient evaluation of the mutational landscape of cancers. As a result, many cancer-specific neoantigens, which can generate antitumor cytotoxic T-cells inside tumors, have been identified. Previously, we reported a metastatic melanoma case with high tumor mutation burden, who obtained complete remission after anti-PD-1 therapy and surgical resection. The rib metastatic lesion, which was used for whole-exome sequencing and gene expression profiling in the HOPE project, showed upregulated expression of PD-L1 mRNA and a high single-nucleotide variants number of 2712. In the current study, we focused on a metastatic melanoma case and candidate epitopes among nonsynonymous mutant neoantigens of 1348 variants were investigated using a peptide-HLA binding algorithm, in vitro cytotoxic T-cell induction assay and HLA tetramer staining. Specifically, from mutant neoantigen data, a total of 21,066 9-mer mutant epitope candidates including a mutated amino acid anywhere in the sequence were applied to the NetMHC binding prediction algorithm. From in silico data, we identified the top 26 mutant epitopes with strong-binding capacity. A cytotoxic T-cell induction assay using 5 cancer patient-derived PBMCs revealed that the mutant ARMT1 peptide sequence (FYGKTILWF) with HLA-A*2402 restriction was an efficient neoantigen, which was detected at a frequency of approximately 0.04% in the HLA-A24 tetramer stain. The present success in identifying a novel mutant antigen epitope might be applied to clinical neoantigen screening in the context of an NGS-equipped medical facility for the development of the next-generation neoantigen cancer vaccines.
Keywords: Mutant neoantigen; Single nucleotide variant (SNV); Single-cell RNA sequencing; Tumor-infiltrating lymphocyte (TIL); Whole exome sequencing (WES).
Copyright © 2019 The Authors. Published by Elsevier B.V. All rights reserved.