Using the Epitranscriptome to Diagnose and Treat Gliomas

Diffuse gliomas are among the most common tumors of the central nervous system, with high morbidity and mortality and very limited therapeutic possibilities. The diffuse glioma are characterized by significant variability in terms of age at diagnosis, histological and molecular features, classification, ability to transform to a higher grade and/or to disseminate in the brain, response to treatment and patient outcome. One of the main challenges in the management of diffuse gliomas is related to tumor heterogeneity within the same subgroup. Establishing an accurate tumor classification is of paramount importance for selecting personalized therapy or avoiding unnecessary treatment. At present, the main diagnostic methods for detecting gliomas are based on histopathological features and mutation detection. Yet difficulties remain, due to tumor heterogeneity and sampling bias for tumors obtained from small biopsies. In particular, grade 2 (low-grade) and grade 3 (high-grade) gliomas cannot be easily distinguished, as intra-tumoral tumor grade heterogeneity is not uncommon in patients treated with extensive surgical resection. Another challenge in the field of gliomas is longitudinal monitoring of disease progression, which is currently mainly based on repeated brain Magnetic Resonance Imaging (MRI). New tools to detect tumor changes before the onset of imaging changes would be useful. Several genetic, epigenetic, metabolic and immunological profiles have been established for gliomas. Recently, the world of RiboNucleic Acid (RNA) has emerged as a promising area to explore for cancer therapy, especially since the (re)discovery of RNA chemical modifications. To date, more than 150 types of post-transcriptional modifications have been reported on various RNA molecules. This complex landscape of chemical marks embodies a new, invisible code that governs the post-transcriptional fate of RNA: stability, splicing, storage, translation.