Meduloblastoma pediatrikoaren pronostikorako markatzaile molekularren identifikazioa

  1. Frutos-Gallastegui, Begoña 1
  2. López-López, Elixabet 2
  3. Illarregi, Unai 1
  4. Bilbao-Aldaiturriaga, Nerea 3
  5. García-Ariza, Miguel 4
  6. Gutiérrez-Camino, Ángela 2
  7. Martín-Guerrero, Idoia 2
  1. 1 Genetika, Antropologia Fisikoa eta Animalien Fisiologia saila; Zientzia eta teknologia fakultatea; UPV/EHU
  2. 2 Genetika, Antropologia Fisikoa eta Animalien Fisiologia saila; Zientzia eta teknologia fakultatea; UPV/EHU Biocruces Osasun Ikerketako Institutua
  3. 3 Instituto Ginecológico y de Reproducción Asistida iGin
  4. 4 Biocruces Osasun Ikerketako Institutua Onkologia pediatrikoa, Gurutzetako Unibertsitate Hospitalea
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Revista:
Ekaia: Euskal Herriko Unibertsitateko zientzi eta teknologi aldizkaria

ISSN: 0214-9001

Año de publicación: 2021

Número: 40

Páginas: 51-76

Tipo: Artículo

DOI: 10.1387/EKAIA.21686 DIALNET GOOGLE SCHOLAR lock_openAcceso abierto editor

Otras publicaciones en: Ekaia: Euskal Herriko Unibertsitateko zientzi eta teknologi aldizkaria

Resumen

Medulloblastoma is a very heterogeneous malignancy at both clinical and molecular levels. In recent years, thanks to the development of massive and whole genome sequencing techniques, many specific mutations have been discovered within each medulloblastoma subtype. Therefore, this study aimed to design a panel of somatic mutations and genes to allow the early recognition of poor prognosis patients or those that will develop resistance to therapy. With this aim, a systematic review was performed to identify all information available in the literature regarding mutations in genes involved in the development of pediatric medulloblastoma. We searched in PubMed database using the keywords and subject terms (Medulloblastoma*) AND (“mutation*” OR “genetic alteration*” OR “genetic variation*”). The original search provided 588 records, from which 62 were finally selected. Out of the 197 identified genes found in those records, 21 showed mutational frequencies higher than 2% and 5 (TP53, CTNNB1, PTCH1, SUFU and KDM6A) could be useful at diagnosis because of their prognostic value or because they were specific of a single subtype. The analysis of these genes could help achieve more individualized therapies based on molecular profile.

Fuente de los datos: Dialnet