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From Data to Decision: Integrating Bioinformatics into Glioma Patient Stratification and Immunotherapy Selection
Ekaterina Sleptsova1, Olga Vershinina2,3, Mikhail Ivanchenko2,3
1Department of Genetics and Life Sciences, Sirius University, Sochi 354340, Russia.
International Journal of Molecular Sciences
|January 28, 2026
Summary
Bioinformatics tools refine glioma diagnosis and treatment by analyzing complex genomic and immune data. These computational methods aid in personalized therapy selection, particularly for immunotherapy, though clinical application is still developing.
Area of Science:
- Oncology
- Bioinformatics
- Genomics
Background:
- Gliomas exhibit significant heterogeneity, leading to variable treatment responses and driving the need for precise diagnostic and prognostic tools.
- Traditional treatment approaches for gliomas are often empirical due to their complexity.
Purpose of the Study:
- To review and comparatively analyze bioinformatic tools for glioma diagnosis, grading, and patient stratification.
- To highlight the role of bioinformatics in discovering novel biomarkers and therapeutic targets for gliomas.
- To assess computational models for predicting immunotherapy response in glioma patients.
Main Methods:
- Comparative analysis of software for whole-exome sequencing, DNA methylation, and transcriptomic data processing.
- Review of computational approaches for tumor mutational burden, immune microenvironment, and neoantigen identification.
- Evaluation of bioinformatics contributions to fundamental oncology research.
Main Results:
- Bioinformatic tools offer advanced capabilities for refining glioma diagnosis and grading.
- These tools facilitate the discovery of potential biomarker genes and drug targets.
- Integrative data analysis, including immune profiling, can predict immunotherapy efficacy in gliomas.
Conclusions:
- Comprehensive bioinformatic analysis supports the integration of immunotherapy into standard glioma treatment protocols for selected patients.
- Computational tools are crucial for advancing personalized medicine in glioma management.
- Despite significant progress, the clinical application of these bioinformatic tools is largely in the preclinical research stage.
Keywords:
astrocytomaexplainable artificial intelligenceglioblastoma (GBM)machine learningoligodendrogliomatumor microenvironmentMore Related Videos
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