Clinical, molecular, and radiomic profile of gliomas with FGFR3-TACC3 fusions

Abstract

<jats:title>Abstract</jats:title> <jats:sec> <jats:title>Background</jats:title> <jats:p>Actionable fibroblast growth factor receptor 3 (FGFR3)–transforming acidic coiled-coil protein 3 fusions (F3T3) are found in approximately 3% of gliomas, but their characteristics and prognostic significance are still poorly defined. Our goal was to characterize the clinical, radiological, and molecular profile of F3T3 positive diffuse gliomas.</jats:p> </jats:sec> <jats:sec> <jats:title>Methods</jats:title> <jats:p>We screened F3T3 fusion by real-time (RT)-PCR and FGFR3 immunohistochemistry in a large series of gliomas, characterized for main genetic alterations, histology, and clinical evolution. We performed a radiological and radiomic case control study, using an exploratory and a validation cohort.</jats:p> </jats:sec> <jats:sec> <jats:title>Results</jats:title> <jats:p>We screened 1162 diffuse gliomas (951 unselected cases and 211 preselected for FGFR3 protein immunopositivity), identifying 80 F3T3 positive gliomas. F3T3 was mutually exclusive with IDH mutation (P &amp;lt; 0.001) and EGFR amplification (P = 0.01), defining a distinct molecular cluster associated with CDK4 (P = 0.04) and MDM2 amplification (P = 0.03). F3T3 fusion was associated with longer survival for the whole series and for glioblastomas (median overall survival was 31.1 vs 19.9 mo, P = 0.02) and was an independent predictor of better outcome on multivariate analysis.</jats:p> <jats:p>F3T3 positive gliomas had specific MRI features, affecting preferentially insula and temporal lobe, and with poorly defined tumor margins. F3T3 fusion was correctly predicted by radiomics analysis on both the exploratory (area under the curve [AUC] = 0.87) and the validation MRI (AUC = 0.75) cohort. Using Cox proportional hazards models, radiomics predicted survival with a high C-index (0.75, SD 0.04), while the model combining clinical, genetic, and radiomic data showed the highest C-index (0.81, SD 0.04).</jats:p> </jats:sec> <jats:sec> <jats:title>Conclusion</jats:title> <jats:p>F3T3 positive gliomas have distinct molecular and radiological features, and better outcome.</jats:p> </jats:sec>

Multi-Platform Classification of IDH-Wild-Type Glioblastoma Based on ERK/MAPK Pathway: Diagnostic, Prognostic and Therapeutic Implications

“…The largest subgroup, G1/EGFR↑, clustered closely with the G3/NF1 and G4/RAF subgroups, and more distantly with the G2/FGFR3 subgroup, in the molecular cluster#1. The G1/EGFR↑ subgroup showed the second-longest survival after the G2/FGFR3 subgroup, which was the subgroup with the longest survival, in concordance with a previous report [ 28 ]. The longest survivors of the cohort belonged to these two subgroups, with two survivors reaching 7 years, representing 2.2% of the IDH-wild-type cohort.…”

Comprehensive analysis of diverse low-grade neuroepithelial tumors with FGFR1 alterations reveals a distinct molecular signature of rosette-forming glioneuronal tumor

“…Notably, FGFR1 alterations are not commonly found in IDH-wildtype glioblastoma in adults, IDH-mutant astrocytoma, IDHmutant and 1p/19q-codeleted oligodendroglioma, H3.3 G34-mutant diffuse hemispheric glioma, ganglioglioma, polymorphous low-grade neuroepithelial tumor of the young (PLNTY), papillary glioneuronal tumor, myxoid glioneuronal tumor, multinodular and vacuolating neuronal tumor, diffuse leptomeningeal glioneuronal tumor (DLGNT), central neurocytoma, and ependymomas of any location or subtype [5,6,8,9,16,17,23,24,26,28,29]. However, fusions involving other FGFR genes are recurrently found in PLNTY (mostly involving FGFR2) and IDH-wildtype glioblastoma in adults (mostly involving FGFR3, typically with TACC3 as the fusion partner) [4,10,17,39]. Therefore, while the identification of an FGFR1 alteration in a CNS tumor of uncertain subtype may help to narrow the differential diagnosis and exclude certain tumor entities, this single genetic finding in and of itself does not enable precise classification.…”

Inflammation-Immunity-Nutrition Score: A Novel Prognostic Score for Patients with Resectable Colorectal Cancer

“…Therefore, to demonstrate the prognostic performances of indicators well, the AUCs and C-indices were calculated together. 24 , 25 Time-dependent ROC curves, time-AUC curves, decision curve analysis (DCA), Kaplan–Meier survival curves and Log rank tests were used to detect the prognostic performance of IINS. Compared with ordinary ROC curve, time-dependent ROC curve could observe the prognostic performance of indicator at a specific point in time after operation.…”