Tumor neoantigenicity assessment with CSiN score incorporates clonality and immunogenicity to predict immunotherapy outcomes
- 21 February 2020
- journal article
- research article
- Published by American Association for the Advancement of Science (AAAS) in Science Immunology
- Vol. 5 (44)
- https://doi.org/10.1126/sciimmunol.aaz3199
Abstract
Lack of responsiveness to checkpoint inhibitors is a central problem in the modern era of cancer immunotherapy. Tumor neoantigens are critical targets of the host antitumor immune response, and their presence correlates with the efficacy of immunotherapy treatment. Many studies involving assessment of tumor neoantigens principally focus on total neoantigen load, which simplistically treats all neoantigens equally. Neoantigen load has been linked with treatment response and prognosis in some studies but not others. We developed a Cauchy-Schwarz index of Neoantigens (CSiN) score to better account for the degree of concentration of immunogenic neoantigens in truncal mutations. Unlike total neoantigen load determinations, CSiN incorporates the effect of both clonality and MHC binding affinity of neoantigens when characterizing tumor neoantigen profiles. By analyzing the clinical responses in 501 treated patients with cancer (with most receiving checkpoint inhibitors) and the overall survival of 1978 patients with cancer at baseline, we showed that CSiN scores predict treatment response to checkpoint inhibitors and prognosis in patients with melanoma, lung cancer, and kidney cancer. CSiN score substantially outperformed prior genetics-based prediction methods of responsiveness and fills an important gap in research involving assessment of tumor neoantigen burden.Keywords
Funding Information
- National Institutes of Health (R03 ES026397-01)
- National Institutes of Health (SPORE 1P50CA19651601)
- National Institutes of Health (CCSG 5P30CA142543)
- American Cancer Society (RSG-16-004-01-CCE)
- Cancer Prevention and Research Institute of Texas (CPRIT RP180319)
- Cancer Prevention Research Institute of Texas (CPRIT RP190208)
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