Background Glioblastoma is the most aggressive and common malignant primary brain tumor in adults. Many genetic, epigenetic and genomic mutations have been identified in this tumor, but no driving cause has been identified yet for glioblastoma pathogenesis. Autophagy has proved to be deregulated in different diseases such as cancer where it has a dual role, acting as a tumor suppression mechanism during the first steps of tumor development and promoting cancer cells survival in stablished tumors. Methods Here, we aimed to assess the potential association between several candidate polymorphisms in autophagy genes (ATG2B rs3759601, ATG16L1 rs2241880, ATG10 rs1864183, ATG5 rs2245214, NOD2 rs2066844 and rs2066845) and glioblastoma susceptibility. Results Our results showed a significant correlation between ATG2B rs3759601, ATG10 rs1864183 and NOD2 rs2066844 variants and higher risk to suffer glioblastoma. In addition, the relationship between the different clinical features listed in glioblastoma patients and candidate gene polymorphisms was also investigated, finding that ATG10 rs1864183 might be a promising prognosis factor for this tumor. Conclusions This is the first report evaluating the role of different variants in autophagy genes in modulating glioblastoma risk and our results emphasize the importance of autophagy in glioblastoma development.

Glioblastoma (GBM) represents one of the deadliest tumors owing to a lack of effective treatments. The adverse outcomes are worsened by high rates of treatment discontinuation, caused by the severe side effects of temozolomide (TMZ), the reference treatment. Therefore, understanding TMZ’s effects on GBM and healthy brain tissue could reveal new approaches to address chemotherapy side effects. In this context, we have previously demonstrated the membrane lipidome is highly cell type-specific and very sensitive to pathophysiological states. However, little remains known as to how membrane lipids participate in GBM onset and progression. Hence, we employed an ex vivo model to assess the impact of TMZ treatment on healthy and GBM lipidome, which was established through imaging mass spectrometry techniques. This approach revealed that bioactive lipid metabolic hubs (phosphatidylinositol and phosphatidylethanolamine plasmalogen species) were altered in healthy brain tissue treated with TMZ. To better understand these changes, we interrogated RNA expression and DNA methylation datasets of the Cancer Genome Atlas database. The results enabled GBM subtypes and patient survival to be linked with the expression of enzymes accounting for the observed lipidome, thus proving that exploring the lipid changes could reveal promising therapeutic approaches for GBM, and ways to ameliorate TMZ side effects.

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