Serum Extracellular Vesicle-Derived circHIPK3 and circSMARCA5 Are Two Novel Diagnostic Biomarkers for Glioblastoma Multiforme.
Michele StellaLuca FalzoneAngela CaponnettoGiuseppe GattusoCristina BarbagalloRosalia BattagliaFederica MirabellaGiuseppe BroggiRoberto AltieriFrancesco CertoRosario CaltabianoGiuseppe Maria Vincenzo BarbagalloPaolo MusumeciMarco RagusaCinzia Di PietroMassimo LibraMichele PurrelloDavide BarbagalloPublished in: Pharmaceuticals (Basel, Switzerland) (2021)
Glioblastoma multiforme (GBM) is the most frequent and deadly human brain cancer. Early diagnosis through non-invasive biomarkers may render GBM more easily treatable, improving the prognosis of this currently incurable disease. We suggest the use of serum extracellular vesicle (sEV)-derived circular RNAs (circRNAs) as highly stable minimally invasive diagnostic biomarkers for GBM diagnosis. EVs were isolated by size exclusion chromatography from sera of 23 GBM and 5 grade 3 glioma (GIII) patients, and 10 unaffected controls (UC). The expression of two candidate circRNAs (circSMARCA5 and circHIPK3) was assayed by droplet digital PCR. CircSMARCA5 and circHIPK3 were significantly less abundant in sEVs from GBM patients with respect to UC (fold-change (FC) of -2.15 and -1.92, respectively) and GIII (FC of -1.75 and -1.4, respectively). Receiver operating characteristic curve (ROC) analysis, based on the expression of sEV-derived circSMARCA5 and circHIPK3, allowed us to distinguish GBM from UC (area under the curve (AUC) 0.823 (0.667-0.979) and 0.855 (0.704 to 1.000), with a 95% confidence interval (CI), respectively). Multivariable ROC analysis, performed by combining the expression of sEV-derived circSMARCA5 and circHIPK3 with preoperative neutrophil to lymphocyte (NLR), platelet to lymphocyte (PLR) and lymphocyte to monocyte (LMR) ratios, three known diagnostic and prognostic GBM markers, allowed an improvement in the GBM diagnostic accuracy (AUC 0.901 (0.7912 to 1.000), 95% CI). Our data suggest sEV-derived circSMARCA5 and circHIPK3 as good diagnostic biomarkers for GBM, especially when associated with preoperative NLR, PLR and LMR.
Keyphrases
- poor prognosis
- minimally invasive
- peripheral blood
- end stage renal disease
- patients undergoing
- binding protein
- mass spectrometry
- machine learning
- newly diagnosed
- high throughput
- immune response
- prognostic factors
- peritoneal dialysis
- deep learning
- patient reported outcomes
- single cell
- high resolution
- artificial intelligence
- lymph node metastasis
- high speed