Genomic predictors of patterns of progression in glioblastoma and possible influences on radiation field design

Jordan A. Holmes, Anna K. Paulsson, Brandi R. Page, Lance D. Miller, Wennuan Liu, Jianfeng Xu, William H. Hinson, Glenn J. Lesser, Adrian W. Laxton, Stephen B. Tatter, Waldemar Debinski, Michael D. Chan

Research output: Contribution to journalArticle

Abstract

We present a retrospective investigation of the role of genomics in the prediction of central versus marginal disease progression patterns for glioblastoma (GBM). Between August 2000 and May 2010, 41 patients with GBM and gene expression and methylation data available were treated with radiotherapy with or without concurrent temozolomide. Location of disease progression was categorized as within the high dose (60 Gy) or low dose (46 Gy) volume. Samples were grouped into previously described TCGA genomic groupings: Mesenchymal (m), classical (c), proneural (pn), and neural (n); and were also classified by MGMT-Methylation status and G-Cimp methylation phenotype. Genomic groupings and methylation status were investigated as a possible predictor of disease progression in the high dose region, progression in the low dose region, and time to progression. Based on TCGA category there was no difference in OS (p = 0.26), 60 Gy progression (PN: 71 %, N: 60 %, M: 89 %, C: 83 %, p = 0.19), 46 Gy progression (PN: 57 %, N: 40 %, M: 61 %,C: 50 %, p = 0.8) or time to progression (PN: 9 months, N:15 months, M: 9 months, C: 7 months, p = 0.58). MGMT methylation predicted for improved OS (median 25 vs. 13 months, p = 0.01), improved DFS (median 13 vs. 8 months, p = 0.007) and decreased 60 Gy (p = 0.003) and 46 Gy (p = 0.006) progression. There was a cohort of MGMT methylated patients with late marginal disease progression (4/22 patients, 18 %). TCGA groups demonstrated no difference in survival or progression patterns. MGMT methylation predicted for a statistically significant decrease in in-field and marginal disease progression. There was a cohort of MGMT methylated patients with late marginal progression. Validations of these findings would have implications that could affect radiation field size.

Original languageEnglish (US)
Pages (from-to)447-453
Number of pages7
JournalJournal of neuro-oncology
Volume124
Issue number3
DOIs
StatePublished - Sep 30 2015
Externally publishedYes

Keywords

  • Genomics
  • Glioblastoma
  • Patterns of progression

ASJC Scopus subject areas

  • Oncology
  • Neurology
  • Clinical Neurology
  • Cancer Research

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  • Cite this

    Holmes, J. A., Paulsson, A. K., Page, B. R., Miller, L. D., Liu, W., Xu, J., Hinson, W. H., Lesser, G. J., Laxton, A. W., Tatter, S. B., Debinski, W., & Chan, M. D. (2015). Genomic predictors of patterns of progression in glioblastoma and possible influences on radiation field design. Journal of neuro-oncology, 124(3), 447-453. https://doi.org/10.1007/s11060-015-1858-2