TY - JOUR
T1 - Computational prediction of MHC anchor locations guides neoantigen identification and prioritization
AU - Xia, Huiming
AU - McMichael, Joshua
AU - Becker-Hapak, Michelle
AU - Onyeador, Onyinyechi C.
AU - Buchli, Rico
AU - McClain, Ethan
AU - Pence, Patrick
AU - Supabphol, Suangson
AU - Richters, Megan M.
AU - Basu, Anamika
AU - Ramirez, Cody A.
AU - Puig-Saus, Cristina
AU - Cotto, Kelsy C.
AU - Freshour, Sharon L.
AU - Hundal, Jasreet
AU - Kiwala, Susanna
AU - Goedegebuure, S. Peter
AU - Johanns, Tanner M.
AU - Dunn, Gavin P.
AU - Ribas, Antoni
AU - Miller, Christopher A.
AU - Gillanders, William E.
AU - Fehniger, Todd A.
AU - Griffith, Obi L.
AU - Griffith, Malachi
N1 - Publisher Copyright:
Copyright © 2023 The Authors, some rights reserved.
PY - 2023/4
Y1 - 2023/4
N2 - Neoantigens are tumor-specific peptide sequences resulting from sources such as somatic DNA mutations. Upon loading onto major histocompatibility complex (MHC) molecules, they can trigger recognition by T cells. Accurate neoantigen identification is thus critical for both designing cancer vaccines and predicting response to immunotherapies. Neoantigen identification and prioritization relies on correctly predicting whether the presenting peptide sequence can successfully induce an immune response. Because most somatic mutations are single-nucleotide variants, changes between wild-type and mutated peptides are typically subtle and require cautious interpretation. A potentially underappreciated variable in neoantigen prediction pipelines is the mutation position within the peptide relative to its anchor positions for the patient’s specific MHC molecules. Whereas a subset of peptide positions are presented to the T cell receptor for recognition, others are responsible for anchoring to the MHC, making these positional considerations critical for predicting T cell responses. We computationally predicted anchor positions for different peptide lengths for 328 common HLA alleles and identified unique anchoring patterns among them. Analysis of 923 tumor samples shows that 6 to 38% of neoantigen candidates are potentially misclassified and can be rescued using allele-specific knowledge of anchor positions. A subset of anchor results were orthogonally validated using protein crystallography structures. Representative anchor trends were experimentally validated using peptide-MHC stability assays and competition binding assays. By incorporating our anchor prediction results into neoantigen prediction pipelines, we hope to formalize, streamline, and improve the identification process for relevant clinical studies.
AB - Neoantigens are tumor-specific peptide sequences resulting from sources such as somatic DNA mutations. Upon loading onto major histocompatibility complex (MHC) molecules, they can trigger recognition by T cells. Accurate neoantigen identification is thus critical for both designing cancer vaccines and predicting response to immunotherapies. Neoantigen identification and prioritization relies on correctly predicting whether the presenting peptide sequence can successfully induce an immune response. Because most somatic mutations are single-nucleotide variants, changes between wild-type and mutated peptides are typically subtle and require cautious interpretation. A potentially underappreciated variable in neoantigen prediction pipelines is the mutation position within the peptide relative to its anchor positions for the patient’s specific MHC molecules. Whereas a subset of peptide positions are presented to the T cell receptor for recognition, others are responsible for anchoring to the MHC, making these positional considerations critical for predicting T cell responses. We computationally predicted anchor positions for different peptide lengths for 328 common HLA alleles and identified unique anchoring patterns among them. Analysis of 923 tumor samples shows that 6 to 38% of neoantigen candidates are potentially misclassified and can be rescued using allele-specific knowledge of anchor positions. A subset of anchor results were orthogonally validated using protein crystallography structures. Representative anchor trends were experimentally validated using peptide-MHC stability assays and competition binding assays. By incorporating our anchor prediction results into neoantigen prediction pipelines, we hope to formalize, streamline, and improve the identification process for relevant clinical studies.
UR - http://www.scopus.com/inward/record.url?scp=85152049697&partnerID=8YFLogxK
U2 - 10.1126/sciimmunol.abg2200
DO - 10.1126/sciimmunol.abg2200
M3 - Article
C2 - 37027480
AN - SCOPUS:85152049697
SN - 2470-9468
VL - 8
JO - Science immunology
JF - Science immunology
IS - 82
M1 - eabg2200
ER -