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

Youngblood M. W., Duran D., Montejo J. D., Li C., Omay S. B., ÖZDUMAN K., ...More

JOURNAL OF NEUROSURGERY, vol.133, no.5, pp.1345-1354, 2020 (SCI-Expanded) identifier identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 133 Issue: 5
  • Publication Date: 2020
  • Doi Number: 10.3171/2019.8.jns191266
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, BIOSIS, EMBASE, MEDLINE
  • Page Numbers: pp.1345-1354
  • Keywords: meningioma, precision medicine, genomics, clinical correlations, machine learning, oncology, MUTATIONS, AKT1, GRADE, SMO, EPENDYMOMAS, EXPRESSION, GERMLINE, TRAF7, KLF4
  • Acibadem Mehmet Ali Aydinlar University Affiliated: Yes


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.