METHODS article
Front. Genet.
Sec. Computational Genomics
This article is part of the Research TopicFrom Graphs to Genes: Harnessing the Power of Machine Learning and BioengineeringView all articles
A Network-Based Discovery of Prognostic Markers in Recurrent IDH wild-type Gliomas
Provisionally accepted
- 1Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, United States
- 2Department of Biostatistics and Data Science, The University of Texas Health Science Center at Houston, Houston, United States
- 3Department of Pathology, University of Texas MD Anderson Cancer Center, Houston, United States
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Background: Isocitrate dehydrogenase wild-type (IDH wild-type) gliomas represents the most aggressive subtype of diffuse gliomas, characterized by therapeutic resistance and dismal prognosis. Despite advances in molecular classification, reliable prognostic biomarkers for these tumors remain limited, particularly for recurrent disease. This study aims to identify gene expression signatures associated with survival outcomes in recurrent IDH wild-type gliomas, with the goal of improving patient stratification and potential therapeutic targeting. Methods: We analyzed gene expression data from 180 recurrent IDH wild-type glioma samples from the Glioma Longitudinal AnalySiS (GLASS) Consortium. Using multiple computational approaches including a novel network-based method (netSurvival) and various survival analysis techniques, we identified genes associated with patient survival outcomes. Results: Our comprehensive analysis identify several gene expression markers that are associated with survival outcomes in recurrent IDH wild-type gliomas. Pathway enrichment analysis identified three significant pathways: FGFR3 signaling, nanoparticle-mediated receptor signaling, and MYCN transcriptional activation, highlighting receptor tyrosine kinase signaling and transcriptional dysregulation as key mechanisms. The AFT log normal model revealed that FN1, HIF3A, and EIF4B are associated with poorer survival (hazard ratios of 1.40, 1.49, and 1.54, respectively; p ¡ 0.05), while PTK2, CCND2, RAD51L3-RFFL, and MAX demonstrated protective effects (hazard ratios of 0.76, 0.78, 0.79, and 0.79, respectively; p < 0.05). Five genes (KIF5C, LINC00632, B4GALNT3, HIF3A, and RAD51L3-RFFL) show significant differential expression between primary and recurrent tumors, with four having established functional roles in glioma pathobiology. Conclusion: This study identifies a panel of gene expression markers with significant prognostic value in recurrent IDH wild-type gliomas. The differential impacts of these genes on survival outcomes provide insights into the biological heterogeneity underlying clinical behavior in these aggressive tumors. Particularly significant are the biomarkers associated with both survival outcomes and recurrence patterns, which may represent key drivers of disease progression. Sample et al. Running Title These findings represent an important step toward improved prognostic stratification and therapeutic targeting in IDH wild-type gliomas, addressing a critical unmet need in neuro-oncology.
Keywords: IDH wild-type glioma, Gene Expression, biomarkers, tumor recurrence, survival analysis, network
Received: 23 Jul 2025; Accepted: 27 Oct 2025.
Copyright: © 2025 Liu, Huse and Kannan. 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: Kasthuri Kannan, kasthuri@gmail.com
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