Multi-omic integration of DNA methylation and gene expression data reveals molecular vulnerabilities in glioblastoma (processed data)

  1. Santamarina-Ojeda, Pablo 1
  2. Tejedor, Juan Ramón 2
  3. Pérez, Raúl F. 2
  4. López, Virginia 3
  5. Roberti, Annalisa 2
  6. Mangas, Cristina 3
  7. Fernández, Agustín F. 2
  8. Fraga, Mario F. 2
  1. 1 Health Research Institute of Asturias (ISPA)
  2. 2 Nanomaterials and Nanotechnology Research Centre (CINN-CSIC)
  3. 3 University Institute of Oncology of Asturias (IUOPA)
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Editor: Zenodo

Year of publication: 2023

Type: Dataset

CC BY 4.0

DOI: 10.5281/ZENODO.7380252 lock_openOpen access editor

Abstract

Glioblastoma multiforme (GBM) is one of the most aggressive types of cancer and exhibits profound genetic and epigenetic heterogeneity, making the development of an effective treatment a major challenge. The recent incorporation of molecular features into the diagnosis of GBM patients has led to an improved categorisation into various tumour subtypes with different prognoses and disease management. In this work, we have exploited the benefits of genome-wide multi-omic approaches to identify potential molecular vulnerabilities existing in GBM patients. Integration of gene expression and DNA methylation data from both bulk GBM and patient-derived GBM stem cell lines has revealed the presence of major sources of GBM variability, pinpointing subtype-specific tumour vulnerabilities amenable to pharmacological interventions. In this sense, inhibition of the AP1, SMAD3 and RUNX1 / RUNX2 pathways, in combination or not with the chemotherapeutic agent temozolomide, led to the subtype-specific impairment of tumour growth, particularly in the context of the aggressive, mesenchymal-like subtype. These results emphasize the involvement of these molecular pathways in the development of GBM and have potential implications for the development of personalized therapeutic approaches.