No abstract

High-grade gliomas (HGG) are the most common primary brain malignancies and account for more than half of all malignant primary brain tumors. The new 2021 WHO classification divides adult HGG into four subtypes: grade 3 oligodendroglioma (1p/19 codeleted, IDH-mutant); grade 3 IDH-mutant astrocytoma; grade 4 IDH-mutant astrocytoma, and grade 4 IDH wild-type glioblastoma (GB). Radiotherapy (RT) and chemotherapy (CTX) are the current standard of care for patients with newly diagnosed HGG. Several clinically relevant molecular markers that assist in diagnosis and prognosis have recently been identified. The treatment for recurrent high-grade gliomas is not well defined and decision-making is usually based on prior strategies, as well as several clinical and radiological factors. Whereas the prognosis for GB is grim (5-year survival rate of 5–10%) outcomes for the other high-grade gliomas are typically better, depending on the molecular features of the tumor. The presence of neurological deficits and seizures can significantly impact quality of life.

No abstract

2042 Background: Malignant gliomas are heterogeneous diseases in genetic basis. The development of sequencing techniques, such as RNA-Sequencing, has identified many gene rearrangements encoding novel oncogenic fusions. Gene fusion discovery can potentially lead to the development of novel treatments, however studies of gene fusions in glioma remain limited. Methods: The GLIOCAT project studied 139 patient samples of newly diagnosed glioblastoma who had received the standard first-line treatment from 2004 to 2015, to identify gene fusion events from glioblastoma transcriptome data (RNA-Seq). The molecular subtype could be studied in 124 cases. RNA-Seq reads were mapped against the reference human genome with STAR-fusion version 0.7.0, specifically, with FusionInspector validate ( http://star-fusion.github.io ). Two other platforms, FusionHub ( https://fusionhub.persistent.co.in ) and Oncofuse ( www.unav.es/genetica/oncofuse.html ), were applied to eliminate false positives or previously described in healthy tissue and to predict of the oncogenic potential each fusion. Results: A total of61 patients showed 103 different fusions, a median of two fusions by sample. The majority of gene fusions were intrachromosomal and most frequently implied chromosome was 12 followed by 7. In addition, fusions were more common in patients with MGMT promoter methylation, TCGA classical subtype and 18 IGS subtype. There were no differences in age, sex, type of surgery or long survivors ( > 30 months). Ten fusions were already described in cancer, including three in gliomas (FRS2-KIF5A, EGFR-SEPT14 and FGFR3-TACC3). From the detected fusions, 22 of them included an oncogene or protooncogene. Conclusions: In our study, we report the landscape of gene fusions from a large data set of glioblastomas analyzed by RNA-seq. The majority of the fusions were private fusions. A minority of these recur in a low frequency but as many as a quarter of them included an oncogene or protooncogene. RNA-seq of GBM patient samples it is an important tool for the identification of patient-specific fusions that could drive personalized therapy. Furtherless, we will plan to validate this gene fusions.

No abstract