A New Epigenetic Model to Stratify Glioma Patients According to Their Immunosuppressive State.

ABSTRACT: Gliomas are the most common primary neoplasm of the central nervous system. A promising frontier in the definition of glioma prognosis and treatment is represented by epigenetics. Furthermore, in this study, we developed a machine learning classification model based on epigenetic data (CpG probes) to separate patients according to their state of immunosuppression. We considered 573 cases of low-grade glioma (LGG) and glioblastoma (GBM) from The Cancer Genome Atlas (TCGA). First, from gene expression data, we derived a novel binary indicator to flag patients with a favorable immune state. Then, based on previous studies, we selected the genes related to the immune state of tumor microenvironment. After, we improved the selection with a data-driven procedure, based on Boruta. Finally, we tun

SUBMITTER: Polano M 

PROVIDER: S-EPMC8001235 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature