251. Bioinformatic methods for cancer neoantigen prediction.
- Author
-
Boegel S, Castle JC, Kodysh J, O'Donnell T, and Rubinsteyn A
- Subjects
- Antigen Presentation immunology, High-Throughput Nucleotide Sequencing, Humans, Polymorphism, Single Nucleotide genetics, Antigens, Neoplasm immunology, Computational Biology methods, Neoplasms immunology
- Abstract
Tumor cells accumulate aberrations not present in normal cells, leading to presentation of neoantigens on MHC molecules on their surface. These non-self neoantigens distinguish tumor cells from normal cells to the immune system and are thus targets for cancer immunotherapy. The rapid development of molecular profiling platforms, such as next-generation sequencing, has enabled the generation of large datasets characterizing tumor cells. The simultaneous development of algorithms has enabled rapid and accurate processing of these data. Bioinformatic software tools encoding the algorithms can be strung together in a workflow to identify neoantigens. Here, with a focus on high-throughput sequencing, we review state-of-the art bioinformatic tools along with the steps and challenges involved in neoantigen identification and recognition., (© 2019 Elsevier Inc. All rights reserved.)
- Published
- 2019
- Full Text
- View/download PDF