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

Glioblastoma (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 patients with GBM has led to an improved categorization 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 patients with GBM. 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 AP-1, 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.

Automated summary

Glioblastoma (GBM) is an aggressive and heterogeneous type of cancer, posing challenges in developing effective treatments. Incorporating molecular features into diagnosis has improved categorization of GBM subtypes, revealing subtype-specific vulnerabilities. By integrating gene expression and DNA methylation data, potential vulnerabilities in GBM patients were identified, implicating the AP-1, SMAD3, and RUNX1/RUNX2 pathways in tumor development. Inhibition of these pathways, with or without the chemotherapy agent temozolomide, led to impaired tumor growth, particularly in the aggressive, mesenchymal-like subtype. These findings have implications for personalized therapeutic approaches.