1. Key Parameters of Tumor Epitope Immunogenicity Revealed Through a Consortium Approach Improve Neoantigen Prediction
- Author
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Zhiqin Huang, Pramod K. Srivastava, Song Liu, Jason A. Greenbaum, Dirk Jäger, Jiaqian Wang, Ognjen Milicevic, Willem-Jan Krebber, Barbara Schrörs, Sean Michael Boyle, Michal Bassani-Sternberg, Ana M. Mijalkovic Lazic, Amit A. Lugade, Kristen K. Dang, Han Si, Alessandro Sette, Jeffrey P. Ward, Irsan Kooi, Michael F. Princiotta, Begonya Comin-Anduix, Thierry Schuepbach, Pia Kvistborg, Julia Kodysh, William Chour, Vladimir B. Kovacevic, Jan H. Kessler, Ariella Sasson, Antoni Ribas, Brian Stevenson, Sriram Sridhar, Prateek Tanden, Robert D. Schreiber, Jason Perera, Kathleen C. F. Sheehan, Hira Rizvi, Sachet A. Shukla, Baikang Pei, Han Chang, Bo Li, Ion I. Mandoiu, Cristina Puig-Saus, Beatriz M. Carreno, Si Qiu, Jennifer M. Shelton, Patrick Jongeneel, Qiang Hu, Taha Merghoub, Matthew D. Hellmann, James P. Conway, Francisco Arcila, Ton N. Schumacher, Mathias Vormehr, Christopher A. Morehouse, Patrice Manning, Jonathon Blake, Pornpimol Charoentong, Angela Frentzen, Christopher A. Miller, Michael A. Kuziora, Bin Song, Lei Wei, Martin Löwer, Gabor Bartha, Justin Guinney, Niels Halama, Rolf Hilker, Yinong Sebastian, Veliborka Josipovic, Jason Harris, Geng Liu, Guilhem Richard, Arjun A. Rao, Nikola M. Skundric, Markus Mueller, Daniel K. Wells, Tatiana Shcheglova, Inka Zörnig, Weixuan Fu, John Sidney, Nadine Defranoux, Gabriela Steiner, Joseph D. Szustakowski, Arbel D. Tadmor, Maxim N. Artyomov, Jianmin Wang, George Coukos, Brandon W. Higgs, Milica R. Kojicic, Siranush Sarkizova, Daphne van Beek, Naibo Yang, Robert Ziman, Mignonette H. Macabali, Thomas Yu, Nicolas Guex, Nina Bhardwaj, Lorenzo F. Fanchi, Bjoern Peters, Christian Iseli, Song Wu, Maren Lang, Juliet Forman, Marit M. van Buuren, David Balli, Steven L. C. Ketelaars, Nir Hacohen, Ekaterina Esaulova, Maarten Slagter, Todd Creasy, Robert A. Petit, Yi-Hsiang Hsu, Ravi Gupta, Katie M. Campbell, Pascal Gellert, David Haussler, Jesse M. Zaretsky, Sofie R. Salama, Vanessa M. Hubbard-Lucey, Joel Greshock, Zeynep Kosaloglu Yalcin, Cornelis J. M. Melief, Priyanka Shah, Ioannis Xenarios, Nevena M. Ilic Raicevic, Andrew Lamb, Suchit Jhunjhunwala, Aly A. Khan, David Gfeller, James R. Heath, Richard Chen, Jia M. Chen, Alphonsus H. C. Ng, Elham Sherafat, Ana Belen Blazquez, Leo J. Lee, Beata Berent-Maoz, Cheryl Selinsky, Jasreet Hundal, Eduardo Cortes, Xengie Doan, Sahar Al Seesi, Adam Kolom, Fred Ramsdell, Nicolas Robine, and Andrew J. Rech
- Subjects
medicine.medical_treatment ,T cell ,Programmed Cell Death 1 Receptor ,No reference ,Sequencing data ,Computational biology ,Biology ,General Biochemistry, Genetics and Molecular Biology ,Epitope ,Cohort Studies ,Epitopes ,03 medical and health sciences ,0302 clinical medicine ,Antigens, Neoplasm ,Neoplasms ,Research community ,medicine ,Humans ,Alleles ,030304 developmental biology ,Antigen Presentation ,0303 health sciences ,Immunogenicity ,Reproducibility of Results ,Immunotherapy ,medicine.anatomical_structure ,Peptides ,030217 neurology & neurosurgery - 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.
- Published
- 2020