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Methods behind neoantigen prediction for personalized anticancer vaccines.
Godazandeh, Kiyana; Van Olmen, Lies; Van Oudenhove, Lore; Lefever, Steve; Bogaert, Cedric; Fant, Bruno.
  • Godazandeh K; myNEO, Ghent, Belgium.
  • Van Olmen L; myNEO, Ghent, Belgium.
  • Van Oudenhove L; myNEO, Ghent, Belgium.
  • Lefever S; myNEO, Ghent, Belgium.
  • Bogaert C; myNEO, Ghent, Belgium.
  • Fant B; myNEO, Ghent, Belgium. Electronic address: bruno@myneo.me.
Methods Cell Biol ; 183: 161-186, 2024.
Article en En | MEDLINE | ID: mdl-38548411
ABSTRACT
Next to conventional cancer therapies, immunotherapies such as immune checkpoint inhibitors have broadened the cancer treatment landscape over the past decades. Recent advances in next generation sequencing and bioinformatics technologies have made it possible to identify a patient's own immunogenic neoantigens. These cancer neoantigens serve as important targets for personalized immunotherapy which has the benefit of being more active and effective in targeting cancer cells. This paper is a step-by-step guide discussing the different analyses and challenges encountered during in-silico neoantigen prediction. The protocol describes all the tools and steps required for the identification of immunogenic neoantigens.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Vacunas contra el Cáncer / Neoplasias Límite: Humans Idioma: En Año: 2024 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Vacunas contra el Cáncer / Neoplasias Límite: Humans Idioma: En Año: 2024 Tipo del documento: Article