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New insights into glioma frequency maps: From genetic and transcriptomic correlate to survival prediction

  • Hongbo Bao
  • , Peng Ren
  • , Liye Yi
  • , Zhonghua Lv
  • , Wencai Ding
  • , Chenlong Li
  • , Siyang Li
  • , Zhipeng Li
  • , Xue Yang
  • , Xia Liang*
  • , Peng Liang*
  • *Corresponding author for this work
  • Harbin Medical University
  • Harbin Institute of Technology
  • School of Life Science and Technology, Harbin Institute of Technology
  • The Second Affiliated Hospital of Harbin Medical University
  • The First Affiliated Hospital of Harbin Medical University

Research output: Contribution to journalArticlepeer-review

Abstract

Increasing evidence indicates that glioma topographic location is linked to the cellular origin, molecular alterations and genetic profile. This research aims to (a) reveal the underlying mechanisms of tumor location predilection in glioblastoma multiforme (GBM) and lower-grade glioma (LGG) and (b) leverage glioma location features to predict prognosis. MRI images from 396 GBM and 190 LGG (115 astrocytoma and 75 oligodendroglioma) patients were standardized to construct frequency maps and analyzed by voxel-based lesion-symptom mapping. We then investigated the spatial correlation between glioma distribution with gene expression in healthy brains. We also evaluated transcriptomic differences in tumor tissue from predilection and nonpredilection sites. Furthermore, we quantitively characterized tumor anatomical localization and explored whether it was significantly related to overall survival. Finally, we employed a support vector machine to build a survival prediction model for GBM patients. GBMs exhibited a distinct location predilection from LGGs. GBMs were nearer to the subventricular zone and more likely to be localized to regions enriched with synaptic signaling, whereas astrocytoma and oligodendroglioma tended to occur in areas associated with the immune response. Synapse, neurotransmitters and calcium ion channel-related genes were all activated in GBM tissues coming from predilection regions. Furthermore, we characterized tumor location features in terms of a series of tumor-to-predilection distance metrics, which were able to predict GBM 1-year survival status with an accuracy of 0.71. These findings provide new perspectives on our understanding of tumor anatomic localization. The spatial features of glioma are of great value in individual therapy and prognosis prediction.

Original languageEnglish
Pages (from-to)998-1012
Number of pages15
JournalInternational Journal of Cancer
Volume152
Issue number5
DOIs
StatePublished - 1 Mar 2023

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • GBM
  • LGG
  • frequency map
  • survival prediction
  • synapse

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