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Tumor neoantigenicity assessment with CSiN score incorporates clonality and immunogenicity to predict immunotherapy outcomes

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Science Immunology  21 Feb 2020:
Vol. 5, Issue 44, eaaz3199
DOI: 10.1126/sciimmunol.aaz3199

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Neoantigen Number Crunching

Immunotherapy with anti–PD-1 and other checkpoint inhibitors is an important cancer treatment modality, but improved biomarkers are needed to better predict which patients will respond. Current computational approaches that assess tumor immunogenicity by deep sequencing of tumor samples to count mutations and predict neoantigen epitopes are unable to factor in clonal variation within tumors. Lu et al. developed an algorithm to calculate CSiN score, a metric that also integrates the distribution of mutations among tumor clones. Testing of CSiN score against other indices of tumor neoantigen burden revealed improved correlations with outcome and prognosis in cohorts of patients with tumor types known to be immunogenic. Calculation of CSiN scores from tumor genomics data may assist in selection of patients most likely to benefit from cancer immunotherapy.

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