Key parameters of tumor epitope immunogenicity revealed through a consortium approach improve neoantigen prediction Journal Article

   

Authors:	Wells, D. K.; van Buuren, M. M.; Dang, K. K.; Hubbard-Lucey, V. M.; Sheehan, K. C. F.; Campbell, K. M.; Lamb, A.; Ward, J. P.; Sidney, J.; Blazquez, A. B.; Rech, A. J.; Zaretsky, J. M.; Comin-Anduix, B.; Ng, A. H. C.; Chour, W.; Yu, T. V.; Rizvi, H.; Chen, J. M.; Manning, P.; Steiner, G. M.; Doan, X. C.; TheTumor Neoantigen Selection Alliance; Merghoub, T.; Guinney, J.; Kolom, A.; Selinsky, C.; Ribas, A.; Hellmann, M. D.; Hacohen, N.; Sette, A.; Heath, J. R.; Bhardwaj, N.; Ramsdell, F.; Schreiber, R. D.; Schumacher, T. N.; Kvistborg, P.; Defranoux, N. A.
Article Title:	Key parameters of tumor epitope immunogenicity revealed through a consortium approach improve neoantigen prediction
Abstract:	Many approaches to identify therapeutically relevant neoantigens couple tumor sequencing with bioinformatic algorithms and inferred rules of tumor epitope immunogenicity. However, there are no reference data to compare these approaches, and the parameters governing tumor epitope immunogenicity remain unclear. Here, we assembled a global consortium wherein each participant predicted immunogenic epitopes from shared tumor sequencing data. 608 epitopes were subsequently assessed for T cell binding in patient-matched samples. By integrating peptide features associated with presentation and recognition, we developed a model of tumor epitope immunogenicity that filtered out 98% of non-immunogenic peptides with a precision above 0.70. Pipelines prioritizing model features had superior performance, and pipeline alterations leveraging them improved prediction performance. These findings were validated in an independent cohort of 310 epitopes prioritized from tumor sequencing data and assessed for T cell binding. This data resource enables identification of parameters underlying effective anti-tumor immunity and is available to the research community. Genomic tumor sequencing data with matched measurements of tumor epitope immunogenicity allows for insights into the governing parameters of epitope immunogenicity and generation of models for effective neoantigen prediction. © 2020 Elsevier Inc.
Keywords:	cancer survival; unclassified drug; overall survival; sensitivity and specificity; binding affinity; antigen expression; t lymphocyte; biological marker; melanoma; data base; information processing; information retrieval; antigen presentation; immune response; immunotherapy; immunogenicity; antigen recognition; epitope; tumor immunity; validity; antigen binding; hla typing; predictive value; peripheral blood mononuclear cell; rna sequence; major histocompatibility antigen class 1; tesla; human; priority journal; article; rna sequencing; whole exome sequencing; neoantigen; immunogenomics; tumor epitope
Journal Title:	Cell
Volume:	183
Issue:	3
ISSN:	0092-8674
Publisher:	Cell Press
Date Published:	2020-10-29
Start Page:	818
End Page:	834.e13
Language:	English
DOI:	10.1016/j.cell.2020.09.015
PUBMED:	33038342
PROVIDER:	scopus
PMCID:	PMC7652061
DOI/URL:	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85094120480&doi=10.1016%2fj.cell.2020.09.015&partnerID=40&md5=b290029e6f07e0545ea564be585649f0
Notes:	Article -- Export Date: 1 December 2020 -- Source: Scopus

https://synapse.mskcc.org/synapse/works/has_related_data_chk/173135