Mutation-based clustering and classification analysis reveals distinctive age groups and age-related biomarkers for glioma

Published in
on
Claire Jean-Quartier, Fleur Jeanquartier, Aydin Ridvan, Matthias Kargl, Tica Mirza, Tobias Stangl, Robi Markaĉ, Mauro Jurada & Andreas Holzinger
Mutationbased clustering.JPG

Abstract

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.