Nan Wu

Epithelioid glioblastoma (EGBM, classified as glioblastoma, IDH wild type, grade 4 according to the fifth edition of the World Health Organization (WHO) Classification of Tumors of the Central Nervous System (CNS) (WHO CNS5)) is a highly aggressive malignancy, with a median progression-free survival (mPFS) of about 6 months in adults. The application of tumor-treating fields (TTFields, possessing anti-cancer capabilities via anti-mitotic effects) in the maintenance of temozolomide (TMZ) chemotherapy showed a benefit for prolonging the mPFS of newly diagnosed glioblastoma (GBM) for patients for up to 6.9 months in the EF-14 clinical trial (NCT00916409). However, studies focusing on the effect of TTFields in EGBM treatment are very limited due to the rarity of EGBM. Here, we have reported a case of a 28-year-old male (recurrent left-sided limb twitching for 1 month and dizziness for 1 week) diagnosed with EGBM. A right frontal lobe occupancy was detected by magnetic resonance imaging (MRI), and a total tumor resection was performed. Meanwhile, a postoperative histopathology test, including immunohistochemistry and molecular characterization, was conducted, and the results revealed a BRAF V600E mutation, no co-deletion of 1p and 19q, and negative O-6-methylguanine DNA methyltransferase (MGMT) promoter methylation. Then, chemoradiotherapy was conducted, and TTFields and TMZ were performed sequentially. Notably, a long-term PFS of 34 months and a Karnofsky Performance Scale (KPS) of 90 were achieved by the patient on TTFields combined with TMZ, whose average daily usage of TTFields was higher than 90%.

Introduction: Epithelioid glioblastoma (eGBM) is one of the rare glioblastoma (GBM) variants in the current World Health Organization (WHO) categorization of central nervous system (CNS) tumours. However, the diagnostic basis and molecular features of eGBM have not been clearly defined to date. In this study, we aimed to molecularly characterize these tumours.Methods: The clinicopathological, molecular, and immunohistochemical characteristics of 12 cases of eGBM were investigated.Results: The tumours were found to be made up of epithelioid and rhabdoid cells when examined under a microscope. Six cases (50%) harboured the BRAF V600E mutation, and NF1 mutation was detected in 2 eGBM cases (16.7%). CDKN2A/B homozygous deletion was seen in 5 cases (41.7%). TP53 mutation was recognized in 2 instances (16.7%), and TERT promoter mutation was recognized in 5 cases (41.7%).Discussion: eGBM is characterized by high molecular heterogeneity and has molecular overlaps between low-grade gliomas. Moreover, rather than being a variant or entity, the biological significance of the "epithelioid" appearance may be reduced to a simply morphological pattern. In order to target the proper treatment to suitable patients, molecular stratification via genome-wide molecular profiling will be crucial.

Rs-fMRI can provide rich information about functional processes in the brain with a large array of imaging parameters and is also suitable for investigating the biological processes in cerebral gliomas. We aimed to propose an imaging analysis method of RP-Rs-fMRIomics by adopting omics analysis on rs-fMRI with exhaustive regional parameters and subsequently estimating its feasibility on the prediction diagnosis of gliomas. In this retrospective study, preoperative rs-fMRI data were acquired from patients confirmed with diffuse gliomas (n = 176). A total of 420 features were extracted through measuring 14 regional parameters of rs-fMRI as much as available currently in 10 specific narrow frequency bins and three parts of gliomas. With a randomly split training and testing dataset (ratio 7:3), four classifiers were implemented to construct and optimize RP-Rs-fMRIomics models for predicting glioma grade, IDH status and Karnofsky Performance Status scores. The RP-Rs-fMRIomics models (AUROC 0.988, 0.905, 0.801) were superior to the corresponding traditional single rs-fMRI index (AUROC 0.803, 0.731, 0.632) in predicting glioma grade, IDH and survival. The RP-Rs-fMRIomics analysis, featuring high interpretability, was competitive for prediction of glioma grading, IDH genotype and prognosis. The method expanded the clinical application of rs-fMRI and also contributed a new imaging analysis for brain tumor research.