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Updated: Nov 16, 2025
Evaluation of Biomarkers in Glioma by Immunohistochemistry on Paraffin-Embedded 3D Glioma Neurosphere Cultures
Published on: January 9, 2019
Mutation-based clustering and classification analysis reveals distinctive age groups and age-related biomarkers for
Claire Jean-Quartier1, Fleur Jeanquartier2,3, Aydin Ridvan4
1Human-Centered AI Lab (Holzinger Group), Institute for Medical Informatics, Statistics and Documentation, Medical University Graz, Auenbruggerplatz 2/V, 8036, Graz, Austria.
Background:
Malignant brain tumor diseases exhibit differences within molecular features depending on the patient's age.
Methods:
In this work, we use gene mutation data from public resources to explore age specifics about glioma. We use both an explainable clustering as well as classification approach to find and interpret age-based differences in brain tumor diseases. We estimate age clusters and correlate age specific biomarkers.
Results:
Age group classification shows known age specifics but also points out several genes which, so far, have not been associated with glioma classification.
Conclusions:
We highlight mutated genes to be characteristic for certain age groups and suggest novel age-based biomarkers and targets.
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