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Updated: Aug 7, 2026

Digital Spatial Profiling for Characterization of the Microenvironment in Adult-Type Diffusely Infiltrating Glioma
Published on: September 13, 2022
Towards a personalized perspective on gliomas: an epigenetic-immuno-inflammatory aging framework
Olga Vershinina1,2, Victoria Turubanova3,4, Claudio Franceschi2
1Research Center in Artificial Intelligence, Institute of Information Technologies, Mathematics and Mechanics, Lobachevsky State University, Nizhny Novgorod, Russia.
High-grade gliomas share molecular mechanisms with aging. Genes predicting glioma prognosis are also linked to aging, with similar expression changes during both processes, suggesting shared pathways.
Area of Science:
- Oncology
- Gerontology
- Molecular Biology
Background:
- High-grade gliomas are complex tumors.
- Understanding their biology requires considering the aging process.
- Shared molecular mechanisms between aging and glioma progression are hypothesized.
Purpose of the Study:
- To investigate the relationship between aging biomarkers and glioma characteristics.
- To explore the role of cellular senescence in glioma pathogenesis.
- To determine if accelerated aging is a universal hallmark of glioma aggressiveness.
Main Methods:
- Analysis of gene expression patterns.
- Utilizing mathematical models (biological clocks) to assess epigenetic and mitotic senescence via DNA methylation.
- Correlation of aging biomarkers with glioma subtype and patient survival.
Main Results:
- Genes predicting glioma subtype and survival are also aging biomarkers.
- Gene expression changes during aging parallel those in malignant transformation.
- Accelerated senescence is inherent to gliomas but varies by subtype and clock model.
- Accelerated aging is not a universal marker of glioma aggressiveness.
Conclusions:
- Glioma progression and aging share overlapping molecular mechanisms.
- Cellular senescence plays a key role in glioma growth control and therapeutic response.
- Further research is needed on the role of inflammaging and the potential for personalized treatment strategies based on cellular aging profiles.
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