Identification of Individual Cancer-Specific Somatic Mutations for Neoantigen-Based Immunotherapy of Lung Cancer

Abstract

Introduction: Two strategies for selecting neoantigens as targets for non-small cell lung cancer vaccines were compared: (1) an "off-the-shelf" approach starting with shared mutations extracted from global databases and (2) a personalized pipeline using whole-exome sequencing data on each patient's tumor.

Methods: The Catalogue of Somatic Mutations in Cancer database was used to create a list of shared missense mutations occurring in more than 1% of patients. These mutations were then assessed for predicted binding affinity to HLA alleles of 15 lung cancer patients, and potential neoantigens (pNeoAgs) for each patient were selected on this basis. In the personalized approach, pNeoAgs were selected from missense mutations detected by whole-exome sequencing of the patient's own samples.

Results: The list of shared mutations included 22 missense mutations for adenocarcinoma and 18 for squamous cell carcinoma (SCC), resulting in a median of 10 off-the-shelf pNeoAgs for each adenocarcinoma (range 5-13) and 9 (range 5-12) for each SCC. In contrast, a median of 59 missense mutations were identified by whole-exome sequencing (range 33-899) in adenocarcinoma and 164.5 (range 26-232) in SCC. This resulted in a median of 46 pNeoAgs (range 13-659) for adenocarcinoma and 95.5 (range 10-145) for SCC in the personalized set. We found that only one or two off-the-shelf pNeoAgs were included in the set of personalized pNeoAgs-and then in only three patients, with no overlap seen in the remaining 12 patients.

Conclusions: Use of an off-the-shelf pipeline is feasible but may not be satisfactory for most patients with non-small cell lung cancer. We recommend identifying personal mutations by comprehensive genome sequencing for developing neoantigen-targeted cancer immunotherapies.

Keywords: Exome; Genetic data bank; Immunotherapy; Missense mutation; Neoantigen.