MiR-1248: a new prognostic biomarker able to identify supratentorial hemispheric pediatric low-grade gliomas patients associated with progression

authors

  • Catanzaro Giuseppina
  • Besharat Zein Mersini
  • Carai Andrea
  • Jäger Natalie
  • Splendiani Elena
  • Colin Carole
  • Po Agnese
  • Chiacchiarini Martina
  • Citarella Anna
  • Gianno Francesca
  • Cacchione Antonella
  • Miele Evelina
  • Diomedi Camassei Francesca
  • Gessi Marco
  • Massimi Luca
  • Locatelli Franco
  • Jones David
  • Figarella‑branger Dominique
  • Pfister Stefan
  • Mastronuzzi Angela
  • Giangaspero Felice
  • Ferretti Elisabetta

keywords

  • Pediatric low-grade gliomas
  • MiR-1248
  • Prognostic biomarker
  • Tumour progression
  • Risk stratification
  • Personalized medicine

document type

ART

abstract

Background Pediatric low-grade gliomas (pLGGs), particularly incompletely resected supratentorial tumours, can undergo progression after surgery. However to date, there are no predictive biomarkers for progression. Here, we aimed to identify pLGG-specific microRNA signatures and evaluate their value as a prognostic tool. Methods We identified and validated supratentorial incompletey resected pLGG-specific microRNAs in independent cohorts from four European Pediatric Neuro-Oncology Centres. Results These microRNAs demonstrated high accuracy in differentiating patients with or without progression. Specifically, incompletely resected supratentorial pLGGs with disease progression showed significantly higher miR-1248 combined with lower miR-376a-3p and miR-888-5p levels than tumours without progression. A significant ( p < 0.001) prognostic performance for miR-1248 was reported with an area under the curve (AUC) of 1.00. We also highlighted a critical oncogenic role for miR-1248 in gliomas tumours. Indeed, high miR-1248 levels maintain low its validated target genes (CDKN1A (p21)/FRK/SPOP/VHL/MTAP) and consequently sustain the activation of oncogenic pathways. Conclusions Altogether, we provide a novel molecular biomarker able to successfully identify pLGG patients associated with disease progression that could support the clinicians in the decision-making strategy, advancing personalized medicine.

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