التفاصيل البيبلوغرافية
| العنوان: |
Key Parameters of Tumor Epitope Immunogenicity Revealed Through a Consortium Approach Improve Neoantigen Prediction |
| المؤلفون: |
Wells, Daniel K., van Buuren, Marit M., Dang, Kristen K., Hubbard-Lucey, Vanessa M., Sheehan, Kathleen C. F., Campbell, Katie M., Lamb, Andrew, Ward, Jeffrey P., Sidney, John, Blazquez, Ana B., Rech, Andrew J., Zaretsky, Jesse M., Comin-Anduix, Begonya, Ng, Alphonsus H. C., Chour, William, Yu, Thomas V., Rizvi, Hira, Chen, Jia M., Manning, Patrice, Steiner, Gabriela M., Doan, Xengie C., Merghoub, Taha, Guinney, Justin, Kolom, Adam, Selinsky, Cheryl, Ribas, Antoni, Hellmann, Matthew D., Hacohen, Nir, Sette, Alessandro, Heath, James R., Bhardwaj, Nina, Ramsdell, Fred, Schreiber, Robert D., Schumacher, Ton N., Kvistborg, Pia, Defranoux, Nadine A., Khan, Aly A., Lugade, Amit, Mijalkovic Lazic, Ana M., Frentzen, Angela A. Elizabeth, Tadmor, Arbel D., Sasson, Ariella S., Rao, Arjun A., Pei, Baikang, Schrörs, Barbara, Berent-Maoz, Beata, Carreno, Beatriz M., Song, Bin, Peters, Bjoern, Li, Bo, Higgs, Brandon W., Stevenson, Brian J., Iseli, Christian, Miller, Christopher A., Morehouse, Christopher A., Melief, Cornelis J. M., Puig-Saus, Cristina, van Beek, Daphne, Balli, David, Gfeller, David, Haussler, David, Jäger, Dirk, Cortes, Eduardo, Esaulova, Ekaterina, Sherafat, Elham, Arcila, Francisco, Bartha, Gabor, Liu, Geng, Coukos, George, Richard, Guilhem, Chang, Han, Si, Han, Zörnig, Inka, Xenarios, Ioannis, Mandoiu, Ion, Kooi, Irsan, Conway, James P., Kessler, Jan H., Greenbaum, Jason A., Perera, Jason F., Harris, Jason, Hundal, Jasreet, Shelton, Jennifer M., Wang, Jianmin, Wang, Jiaqian, Greshock, Joel, Blake, Jonathon, Szustakowski, Joseph, Kodysh, Julia, Forman, Juliet, Wei, Lei, Lee, Leo J., Fanchi, Lorenzo F., Slagter, Maarten, Lang, Maren, Mueller, Markus, Lower, Martin, Vormehr, Mathias, Artyomov, Maxim N., Kuziora, Michael, Princiotta, Michael, Bassani-Sternberg, Michal, Macabali, Mignonette, Kojicic, Milica R., Yang, Naibo, Raicevic, Nevena M. Ilic, Guex, Nicolas, Robine, Nicolas, Halama, Niels, Skundric, Nikola M., Milicevic, Ognjen S., Gellert, Pascal, Jongeneel, Patrick, Charoentong, Pornpimol, Srivastava, Pramod K., Tanden, Prateek, Shah, Priyanka, Hu, Qiang, Gupta, Ravi, Chen, Richard, Petit, Robert, Ziman, Robert, Hilker, Rolf, Shukla, Sachet A., Al Seesi, Sahar, Boyle, Sean M., Qiu, Si, Sarkizova, Siranush, Salama, Sofie, Liu, Song, Wu, Song, Sridhar, Sriram, Ketelaars, Steven L. C., Jhunjhunwala, Suchit, Shcheglova, Tatiana, Schuepbach, Thierry, Creasy, Todd H., Josipovic, Veliborka, Kovacevic, Vladimir B., Fu, Weixuan, Krebber, Willem-Jan, Hsu, Yi-Hsiang, Sebastian, Yinong, Kosaloglu-Yalcin, Zeynep, Huang, Zhiqin |
| المصدر: |
Cell, 183(3), 818-834, (2020-10-29) |
| بيانات النشر: |
Cell Press |
| سنة النشر: |
2020 |
| المجموعة: |
Caltech Authors (California Institute of Technology) |
| مصطلحات موضوعية: |
immunotherapy, neoantigen, immunogenomics, epitope, TESLA, immunogenicity |
| الوصف: |
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. ; © 2020 Elsevier Inc. Received 30 March 2020, Revised 8 July 2020, Accepted 3 September 2020, Available online 9 October 2020. We thank all the subjects who contributed to this study through donation of tumor and blood samples, as well as the research staff at UCLA and MSKCC for sample collection and processing. We acknowledge Olga Malkova, Diane E. Bender, Likui Yang, and Tammi Vickery for their work on MHC I multimer binding assay and nucleic acid isolation and sequencing; Jeff Bluestone, Jeff Hammerbacher, Ansuman Satpathy, and Robert Vonderheide for helpful and supportive comments; and David Liu and Eliezer van Allen for help in obtaining access to published data. TESLA was conceived collaboratively between the Parker Institute for Cancer Immunotherapy (PICI) and the Cancer Research Institute (CRI), and primary financial support came from PICI, a not-for-profit ... |
| نوع الوثيقة: |
article in journal/newspaper |
| اللغة: |
unknown |
| العلاقة: |
https://doi.org/10.1016/j.cell.2020.09.015Test; oai:authors.library.caltech.edu:y57ap-h8p92; eprintid:106147; resolverid:CaltechAUTHORS:20201019-121956456 |
| DOI: |
10.1016/j.cell.2020.09.015 |
| الإتاحة: |
https://doi.org/10.1016/j.cell.2020.09.015Test |
| حقوق: |
info:eu-repo/semantics/openAccess ; Other |
| رقم الانضمام: |
edsbas.CDBCE0C1 |
| قاعدة البيانات: |
BASE |
