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ORIGINAL RESEARCH article

Front. Oncol.

Sec. Neuro-Oncology and Neurosurgical Oncology

MRI-Based Radiomic Clustering Identifies a Glioblastoma Subtype Enriched for Neural Stemness and Proliferative Programs

Provisionally accepted
Zhongyi  ZhangZhongyi Zhang1Yang  LiuYang Liu1Zhicong  ZhangZhicong Zhang2Tian  GuiTian Gui2Youhui  ChenYouhui Chen2Qian  ChenQian Chen1Xiufu  WuXiufu Wu1Li  SunLi Sun3Sujie  LiSujie Li3Shuyang  WeiShuyang Wei3*
  • 1Department of Neurosurgery, The Second Affiliated Hospital of Guilin Medical University, Guilin, China
  • 2Department of Operating Theatre, The Second Affiliated Hospital of Guilin Medical University, Guilin, China
  • 3Department of Neurosurgery, Affiliated Hospital of Guilin Medical University, Guilin, China

The final, formatted version of the article will be published soon.

Glioblastoma (GBM) is a highly aggressive brain tumor with a median survival of only 15 months. A major challenge in GBM management is the pronounced inter-and intratumoral heterogeneity, which complicates prognosis and therapy. Radiomics, the quantitative extraction of features from medical images, can capture this heterogeneity across the entire tumor volume, but the biological basis of radiographic phenotypes remains poorly understood. In this study, we integrated preoperative MRI-based radiomic stratification with multi-platform transcriptomics (bulk RNA-seq, single-cell RNA-seq, and spatial transcriptomics) in IDH-wildtype GBM patients. Unsupervised clustering of radiomic features identified four imaging subtypes; notably, Group 4 emerged as a high-risk subtype associated with significantly worse survival and a distinctive MRI pattern of peripheral contrast enhancement. Transcriptomic analyses revealed that Group 4 tumors were enriched in cell-cycle and proliferation markers and exhibited neural stem cell–like gene expression signatures. Single-cell profiling confirmed an elevated proportion of stem-like malignant cells in this subtype. Spatial transcriptomics further demonstrated that these proliferative, stem-like programs were localized predominantly to the tumor periphery, corresponding to the rim-enhancing regions on MRI. Finally, we identified the developmental transcription factor VAX2 as a candidate driver of the Group 4 gene network; functional assays showed that VAX2 promotes GBM cell proliferation in vitro. In summary, our findings link a radiomics-defined MRI phenotype to specific molecular programs and cell populations in GBM, suggesting that radiomic subtypes can serve as noninvasive biomarkers of tumor biology and highlighting potential therapeutic targets in aggressive, stem-like tumor cell populations.

Keywords: Radiogenomics 1, glioblastoma 2, Single-cell transcriptomics 3, Spatialtranscriptomics 4, Neural stem-like cells 5, Tumor heterogeneity 6

Received: 09 Jul 2025; Accepted: 03 Nov 2025.

Copyright: © 2025 Zhang, Liu, Zhang, Gui, Chen, Chen, Wu, Sun, Li and Wei. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Shuyang Wei, wei_shuyang1991@outlook.com

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