Correlations between genomic subgroup and clinical features in a cohort of more than 3000 meningiomas.


Youngblood M., Duran D., Montejo J., Li C., Omay S., Özduman K. , ...More

Journal of neurosurgery, vol.133, pp.1345-1354, 2020 (Journal Indexed in SCI) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 133
  • Publication Date: 2020
  • Doi Number: 10.3171/2019.8.jns191266
  • Title of Journal : Journal of neurosurgery
  • Page Numbers: pp.1345-1354
  • Keywords: meningioma, precision medicine, genomics, clinical correlations, machine learning, oncology, MUTATIONS, AKT1, GRADE, SMO, EPENDYMOMAS, EXPRESSION, GERMLINE, TRAF7, KLF4

Abstract

OBJECTIVE Recent large-cohort sequencing studies have investigated the genomic landscape of meningiomas, identifying somatic coding alterations in NF2, SMARCB1, SMARCE1, TRAF7, KLF4, POLR2A, BAP1, and members of the PI3K and Hedgehog signaling pathways. Initial associations between clinical features and genomic subgroups have been described, including location, grade, and histology. However, further investigation using an expanded collection of samples is needed to confirm previous findings, as well as elucidate relationships not evident in smaller discovery cohorts.