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Recent efforts to design personalized cancer immunotherapies use predicted neoantigens.
To create a personalized cancer vaccine, strong-binding neoantigenic peptides are
computationally predicted from matched tumor-normal sequencing data, and then ranked
according to their predicted capability in stimulating a T cell response. These neoantigenic
peptides arise due to various changes in the somatic genome and identification and
characterization of these neoantigens is a critical step in designing these treatment
regimens. This is a cross-disciplinary challenge, involving genomics, proteomics,
immunology, and computational approaches.
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