Accounting for proximal variants improves neoantigen prediction. (January 2019)

• Record Type: Journal Article
• Authors: Hundal, Jasreet; Kiwala, Susanna; Feng, Yang-Yang; Liu, Connor; Govindan, Ramaswamy; Chapman, William; Uppaluri, Ravindra; Swamidass, S.; Griffith, Obi; Mardis, Elaine; Griffith, Malachi
• Is Part Of: Nature genetics. Volume 51:Number 1(2019)
• Page Start: 175
• Page End: 179
• Publication Date: 2019-01
• Subjects: Human genetics -- Periodicals; 576.505
• DOI: 10.1038/s41588-018-0283-9
• Languages: English
• ISSNs: 1061-4036

Abstract

Abstract Recent efforts to design personalized cancer immunotherapies use predicted neoantigens, but most neoantigen prediction strategies do not consider proximal (nearby) variants that alter the peptide sequence and may influence neoantigen binding. We evaluated somatic variants from 430 tumors to understand how proximal somatic and germline alterations change the neoantigenic peptide sequence and also affect neoantigen binding predictions. On average, 241 missense somatic variants were analyzed per sample. Of these somatic variants, 5% had one or more in-phase missense proximal variants. Without incorporating proximal variant correction for major histocompatibility complex class I neoantigen peptides, the overall false discovery rate (incorrect neoantigens predicted) and the false negative rate (strong-binding neoantigens missed) across peptides of lengths 8–11 were estimated as 0.069 (6.9%) and 0.026 (2.6%), respectively. Including patient-specific information about nearby somatic and germline alterations improves the accuracy of neoantigen prediction, potentially impacting cancer vaccine design.