Article a new epigenetic model to stratify glioma patients according to their immunosuppressive state

Maurizio Polano, Emanuele Fabbiani, Eva Adreuzzi, Federica Di Cintio, Luca Bedon, Davide Gentilini, Maurizio Mongiat, Tamara Ius, Mauro Arcicasa, Miran Skrap, Michele Dal Bo, Giuseppe Toffoli

Research output: Contribution to journalArticlepeer-review


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. Further-more, 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 tuned, trained, and evaluated both random forest and neural network classifiers on the resulting dataset. We found that a multi-layer perceptron network fed by the 338 probes selected by applying both expert choice and Boruta results in the best performance, achieving an out-of-sample accuracy of 82.8%, a Matthews correlation coefficient of 0.657, and an area under the ROC curve of 0.9. Based on the proposed model, we provided a method to stratify glioma patients according to their epigenomic state.

Original languageEnglish
Article number576
Pages (from-to)1-49
Number of pages49
Issue number3
Publication statusPublished - Mar 2021


  • Extracellular matrix
  • Genome-wide methyla-tion model
  • Glioma
  • Immunosuppression
  • Neural network
  • Tumor microenviroment

ASJC Scopus subject areas

  • Medicine(all)


Dive into the research topics of 'Article a new epigenetic model to stratify glioma patients according to their immunosuppressive state'. Together they form a unique fingerprint.

Cite this