Predicting methylation class from diffusely infiltrating adult gliomas using multimodality MRI data.

ABSTRACT:

Background

Radiogenomic studies of adult-type diffuse gliomas have used magnetic resonance imaging (MRI) data to infer tumor attributes, including abnormalities such as IDH-mutation status and 1p19q deletion. This approach is effective but does not generalize to tumor types that lack highly recurrent alterations. Tumors have intrinsic DNA methylation patterns and can be grouped into stable methylation classes even when lacking recurrent mutations or copy number changes. The purpose of this study was to prove the principle that a tumor's DNA-methylation class could be used as a predictive feature for radiogenomic modeling.

Methods

Using a custom DNA methylation-based classification model, molecular classes were assigned to diffuse gliomas in The Cancer Genome Atlas (TCGA) dat

SUBMITTER: Alom Z 

PROVIDER: S-EPMC10195196 | biostudies-literature | 2023 Jan-Dec

REPOSITORIES: biostudies-literature