Biomarker Research (Jun 2022)

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

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

DOI
https://doi.org/10.1186/s40364-022-00389-x
Journal volume & issue
Vol. 10, no. 1
pp. 1 – 17

Abstract

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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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