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Molecular Characterization of Glioblastoma: Implications for Diagnosis and Personalized Treatment

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Pathology, Diagnostics, and Therapeutics".

Deadline for manuscript submissions: 20 June 2026 | Viewed by 508

Special Issue Editor


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Guest Editor
Department of Pharmacology and Cancer Biology, Duke University School of Medicine, Durham, NC 27710, USA
Interests: glioblastoma drug development using a precision medicine approach

Special Issue Information

Dear Colleagues,

Glioblastoma remains the most aggressive and lethal primary brain tumor in adults, with limited therapeutic options and poor survival rates. Recent advances in molecular profiling technologies have transformed our understanding of glioblastoma biology, leading to refined diagnostic criteria, identification of distinct molecular subtypes, and emergence of personalized treatment strategies.

This Special Issue of the International Journal of Molecular Sciences brings together a collection of submissions that highlight recent developments in the molecular characterization of glioblastoma, with a focus on its diagnostic, prognostic, and therapeutic implications. The topics covered include the integration of DNA methylation-based classifiers into diagnostic workflows, the role of comprehensive genomic profiling in detecting actionable mutations and gene fusions, and the utility of transcriptomic and proteomic signatures in subclassifying tumors. The collection also addresses challenges in clinical implementation, including tumor heterogeneity, evolving classification systems, and the need for CLIA-certified platforms. Collectively, these articles underscore the critical role of precision oncology in glioblastoma management and point toward a future where individualized therapy guided by molecular diagnostics may significantly improve patient outcomes.

Dr. Madan Mohan Kwatra
Guest Editor

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Keywords

  • glioblastoma
  • diagnosis
  • molecular characterization
  • personalized treatment

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Published Papers (1 paper)

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Research

25 pages, 14607 KB  
Article
A Synaptogenesis-Associated Histomorphologic Signature from H&E Whole-Slide Images Predicts Glioma Prognosis and Identifies EFNB2-Positive Malignant Cells as a Candidate Neuro-Glioma Communication Hub
by Xiaolong Wu, Dong Liu, Haoming Geng, Binghan Zhang, Huantong Diao, Yiqiang Zhou, Gang Song, Ye Cheng and Jiantao Liang
Int. J. Mol. Sci. 2026, 27(10), 4300; https://doi.org/10.3390/ijms27104300 - 12 May 2026
Viewed by 112
Abstract
Synaptogenesis-related neuron–glioma interactions are increasingly recognized in glioma, yet it remains unclear whether routine H&E morphology can capture these programs and improve prognostic stratification. We integrated H&E whole-slide images, transcriptomes, and clinical data from 434 TCGA gliomas. Deep learning and quantitative pathology yielded [...] Read more.
Synaptogenesis-related neuron–glioma interactions are increasingly recognized in glioma, yet it remains unclear whether routine H&E morphology can capture these programs and improve prognostic stratification. We integrated H&E whole-slide images, transcriptomes, and clinical data from 434 TCGA gliomas. Deep learning and quantitative pathology yielded an integrated histomorphologic feature set of 2678 features. Synaptogenesis-related activity was quantified using ssGSEA for ninety-eight synaptogenesis-related genes. In the training cohort, Spearman analysis identified 149 correlated histomorphologic features, which were refined to thirty-five by elastic net regularization. Seventeen prognostic candidates were entered into the MIME1 framework, and the most parsimonious model, Enet[0.1], retained fourteen non-zero-coefficient features to define the synaptogenesis-associated histomorphologic signature and construct the pathology-derived risk score (PRS). Multi-omic analyses, Human Protein Atlas validation, and single-nucleus RNA-seq were used to investigate the hub gene and its cellular context. PRS robustly stratified survival in both training and validation cohorts and remained an independent prognostic factor after adjustment for age and 2021 WHO CNS grade. High-risk tumors showed increased stromal and immune scores and enrichment of immune, adhesion, and phagosome-related pathways. EFNB2 emerged as the hub gene and was enriched in glioblastoma, and EFNB2-positive malignant cells displayed prominent communication with neurons, including EFNB2-EPHB1 signaling. Exploratory re-analysis of the myeloid compartment further showed that glioblastoma was enriched for suppressive TAM-like states relative to astrocytoma grade 2, supporting a shift toward a more tumor-associated and potentially immunosuppressive microenvironment. Routine H&E histomorphology can capture synaptogenesis-related molecular programs in glioma. The resulting PRS provides clinically relevant prognostic stratification, while EFNB2-positive malignant cells may represent a candidate hub for neuron–tumor communication within a remodeled tumor ecosystem. Full article
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