Differential localization of glioblastoma subtype: Implications on glioblastoma pathogenesis

Tyler C. Steed, Jeffrey M. Treiber, Kunal Patel, Valya Ramakrishnan, Alexander Merk, Amanda R. Smith, Bob S. Carter, Anders M. Dale, Lionel M.L. Chow, Clark C. Chen

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

Introduction: The subventricular zone (SVZ) has been implicated in the pathogenesis of glioblastoma. Whether molecular subtypes of glioblastoma arise from unique niches of the brain relative to the SVZ remains largely unknown. Here, we tested whether these subtypes of glioblastoma occupy distinct regions of the cerebrum and examined glioblastoma localization in relation to the SVZ. Methods: Pre-operative MR images from 217 glioblastoma patients from The Cancer Imaging Archive were segmented automatically into contrast enhancing (CE) tumor volumes using Iterative Probabilistic Voxel Labeling (IPVL). Probabilistic maps of tumor location were generated for each subtype and distances were calculated from the centroid of CE tumor volumes to the SVZ. Glioblastomas that arose in a Genetically Modified Murine Model (GEMM) model were also analyzed with regard to SVZ distance and molecular subtype. Results: Classical and mesenchymal glioblastomas were more diffusely distributed and located farther from the SVZ. In contrast, proneural and neural glioblastomas were more likely to be located in closer proximity to the SVZ. Moreover, in a GFAP-CreER; PtenloxP/loxP; Trp53loxP/loxP; Rb1loxP/loxP; Rbl1-/- GEMM model of glioblastoma where tumor can spontaneously arise in different regions of the cerebrum, tumors that arose near the SVZ were more likely to be of proneural subtype (p < 0.0001). Conclusions: Glioblastoma subtypes occupy different regions of the brain and vary in proximity to the SVZ. These findings harbor implications pertaining to the pathogenesis of glioblastoma subtypes.

Original languageEnglish (US)
Pages (from-to)24899-24907
Number of pages9
JournalOncotarget
Volume7
Issue number18
DOIs
StatePublished - May 1 2016

Keywords

  • Automatic tumor segmentation
  • Glioblastoma
  • MR imaging
  • Subtypes
  • Subventricular zone

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