FB2025_01 , released February 20, 2025
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Terrasi, A., Bertolini, I., Martelli, C., Gaudioso, G., Di Cristofori, A., Storaci, A.M., Formica, M., Bosari, S., Caroli, M., Ottobrini, L., Vaccari, T., Vaira, V. (2019). Specific V-ATPase expression sub-classifies IDHwt lower-grade gliomas and impacts glioma growth in vivo.  EBioMedicine 41(): 214--224.
FlyBase ID
FBrf0241903
Publication Type
Research paper
Abstract
Cancer cells use specific V-ATPase subunits to activate oncogenic pathways. Therefore, we investigated V-ATPase deregulation in aggressive gliomas and associated signaling. V-ATPase genes expression and associated pathways were analyzed in different series of glioma available from public databases, as well as in patients' cohort. Activation of pathways was analyzed at gene and protein expression levels. A genetic model of glioma in Drosophila melanogaster and mice with GBM patients-derived orthotopic xenografts were used as in vivo models of disease. GBM and recurrent gliomas display a specific V-ATPase signature. Such signature resolves the heterogeneous class of IDH-wild type lower-grade gliomas, identifying the patients with worse prognosis independently from clinical and molecular features (p = 0·03, by Cox proportional-hazards model). In vivo, V-ATPase subunits deregulation significantly impacts tumor growth and proliferation. At the molecular level, GBM-like V-ATPase expression correlates with upregulation of Homeobox genes. Our data identify a V-ATPase signature that accompanies glioma aggressiveness and suggest new entry points for glioma stratification and follow-up. FUND: This work was supported by Fondazione Cariplo (2014-1148 to VV), Fondazione IRCCS Ca' Granda, and Fondazione INGM Grant in Molecular Medicine 2014 (to VV).
PubMed ID
PubMed Central ID
PMC6441867 (PMC) (EuropePMC)
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    Language of Publication
    English
    Additional Languages of Abstract
    Parent Publication
    Publication Type
    Journal
    Abbreviation
    EBioMedicine
    Title
    EBioMedicine
    ISBN/ISSN
    2352-3964
    Data From Reference
    Alleles (4)
    Genes (4)
    Human Disease Models (1)
    Transgenic Constructs (4)