美国帕克癌症免疫疗法研究所Nadine A. Defranoux、Daniel K. Wells等研究人员合作通过联合体方法揭示出肿瘤表位免疫原性的关键参数，并改善了新抗原的预测。相关论文于2020年10月9日在线发表在《细胞》杂志上。
Title: Key Parameters of Tumor Epitope Immunogenicity Revealed Through a Consortium Approach Improve Neoantigen Prediction
Author: Daniel K. Wells, Marit M. van Buuren, Kristen K. Dang, Vanessa M. Hubbard-Lucey, Kathleen C.F. Sheehan, Katie M. Campbell, Andrew Lamb, Jeffrey P. Ward, John Sidney, Ana B. Blazquez, Andrew J. Rech, Jesse M. Zaretsky, Begonya Comin-Anduix, Alphonsus H.C. Ng, William Chour, Thomas V. Yu, Hira Rizvi, Jia M. Chen, Patrice Manning, Gabriela M. Steiner, Xengie C. Doan, Aly A. Khan, Amit Lugade, Ana M. Mijalkovic Lazic, Angela A. Elizabeth Frentzen, Arbel D. Tadmor, Ariella S. Sasson, Arjun A. Rao, Baikang Pei, Barbara Schrrs, Beata Berent-Maoz, Beatriz M. Carreno, Bin Song, Bjoern Peters, Bo Li, Brandon W. Higgs, Brian J. Stevenson, Christian Iseli, Christopher A. Miller, Christopher A. Morehouse, Cornelis J.M. Melief, Cristina Puig-Saus, Daphne van Beek, David Balli, David Gfeller, David Haussler, Dirk Jger, Eduardo Cortes, Ekaterina Esaulova, Elham Sherafat, Francisco Arcila, Gabor Bartha, Geng Liu, George Coukos, Guilhem Richard, Han Chang, Han Si, Inka Zrnig, Ioannis Xenarios, Ion Mandoiu, Irsan Kooi, James P. Conway, Jan H. Kessler, Jason A. Greenbaum, Jason F. Perera, Jason Harris, Jasreet Hundal, Jennifer M. Shelton, Jianmin Wang, Jiaqian Wang, Joel Greshock, Jonathon Blake, Joseph Szustakowski, Julia Kodysh, Juliet Forman, Lei Wei, Leo J. Lee, Lorenzo F. Fanchi, Maarten Slagter, Maren Lang, Markus Mueller, Martin Lower, Mathias Vormehr, Maxim N. Artyomov, Michael Kuziora, Michael Princiotta, Michal Bassani-Sternberg, Mignonette Macabali, Milica R. Kojicic, Naibo Yang, Nevena M. Ilic Raicevic, Nicolas Guex, Nicolas Robine, Niels Halama, Nikola M. Skundric, Ognjen S. Milicevic, Pascal Gellert, Patrick Jongeneel, Pornpimol Charoentong, Pramod K. Srivastava, Prateek Tanden, Priyanka Shah, Qiang Hu, Ravi Gupta, Richard Chen, Robert Petit, Robert Ziman, Rolf Hilker, Sachet A. Shukla, Sahar Al Seesi, Sean M. Boyle, Si Qiu, Siranush Sarkizova, Sofie Salama, Song Liu
Issue&Volume: 2020-10-09
Abstract: Many approaches to identify therapeutically relevant neoantigens couple tumor sequencingwith bioinformatic algorithms and inferred rules of tumor epitope immunogenicity.However, there are no reference data to compare these approaches, and the parametersgoverning tumor epitope immunogenicity remain unclear. Here, we assembled a globalconsortium wherein each participant predicted immunogenic epitopes from shared tumorsequencing data. 608 epitopes were subsequently assessed for T cell binding in patient-matchedsamples. By integrating peptide features associated with presentation and recognition,we developed a model of tumor epitope immunogenicity that filtered out 98% of non-immunogenicpeptides with a precision above 0.70. Pipelines prioritizing model features had superiorperformance, and pipeline alterations leveraging them improved prediction performance.These findings were validated in an independent cohort of 310 epitopes prioritizedfrom tumor sequencing data and assessed for T cell binding. This data resource enablesidentification of parameters underlying effective anti-tumor immunity and is availableto the research community.
DOI: 10.1016/j.cell.2020.09.015
Source: https://www.cell.com/cell/fulltext/S0092-8674(20)31156-9