Abstract
Low-grade gliomas (LGG) are infiltrative primary brain tumors that in 70% of the cases undergo anaplastic transformation, deeply affecting prognosis. However, the timing of progression is heterogeneous. Recently, the tumor microenvironment (TME) has gained much attention either as prognostic factor or therapeutic target. Through the release of extracellular vesicles, the TME contributes to tumor progression by transferring bioactive molecules such as microRNA. The aim of the study was to take advantage of glioma-associated stem cells (GASC), an in vitro model of the glioma microenvironment endowed with a prognostic significance, and their released exosomes, to investigate the possible role of exosome miRNAs in favoring the anaplastic transformation of LGG. Therefore, by deep sequencing, we analyzed and compared the miRNA profile of GASC and exosomes obtained from LGG patients characterized by different prognosis. Results showed that exosomes presented a different signature, when compared to their cellular counterpart and that, although sharing several miRNAs, exosomes of patients with a bad prognosis, selectively expressed some miRNAs possibly responsible for the more aggressive phenotype. These findings get insights into the value of TME and exosomes as potential biomarkers for precision medicine approaches aimed at improving LGG prognostic stratification and therapeutic strategies.
Highlights
Adult diffuse low-grade gliomas (LGG) are classified and graded based on histological and molecular parameters according to the World Health Organization (WHO) classification of brain tumors [1]
We have identified a pro-migratory protein (SEMA-7A) able to promote the motility of glioma stem cells (GSC) in vitro, exposed on the surface of HGG-glioma-associated stem cells (GASC) exosomes [44]
Characterization of Exosomes Derived from LGG with Different Prognosis
Summary
Adult diffuse low-grade gliomas (LGG) are classified and graded based on histological and molecular parameters according to the World Health Organization (WHO) classification of brain tumors [1]. Even inside the same molecular group, there are differences in both risk and timing of malignant transformation. This makes it difficult to choose the therapeutic strategy, aimed at aggressively treating patients with a potentially more malignant neoplasm and avoiding adjuvant therapies to patients who could only progress after many years [3,4,9]. To refine the therapeutic approach towards personalized medicine, it is increasingly important to understand the molecular mechanisms driving the malignant evolution of LGG. Bai et at. compared the genomic landscape of
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