Magnetic Resonance Imaging Reveals a Pronounced Treatment Response of a Isocitrate Dehydrogenase- and B-Raf Proto-Oncogene-Wildtype Epithelioid Glioblastoma

The Significance of BRAF Mutation in the Epithelioid Glioblastoma Subtype: A Systematic Literature Review and a Case Report with a Unique Intraventricular Topography

Epithelioid glioblastoma (E-GBM) is an exceedingly rare subtype of isocitrate dehydrogenase (IDH)-wildtype glioblastoma, first included in the WHO 2016 classification and characterized by a dominant population of epithelioid cells. Its histological and molecular defining features remain troublesome. The significance of BRAF mutations to pathological diagnosis and surgical outcome has drawn increasing attention given their promising potential for future adjuvant therapies. Herein, we describe a unique case of an E-GBM in the atrium of the left lateral ventricle and comprehensively analyze the importance of BRAF status in a cohort of 211 E-GBMs from the literature. Our patient was a 40-year-old man with occipital pain. His brain MRI revealed a large intraventricular tumor at the same location as a signal change found 10 years earlier with no additional follow-up. He underwent gross total tumor removal followed by conventional adjuvant treatment. Histopathological diagnosis was consistent with IDH-wildtype E-GBM WHO grade 4 with pleomorphic xanthoastrocytoma-like areas. BRAF p.V600 mutation was demonstrated in the tumoral genetic study. In the cohort analyzed, male patients predominated (63%), the median age was 32 years old, and the 5-year survival rate following diagnosis was 4.2%. BRAF mutations were found in 60.3% of the tumors overall, with this rate increasing to 78.3% in young adults (19-49 years, P < .001). Presence of BRAF mutations associated with tumor progression (P = .001), the event usually leading to death (P < .001). In conclusion, our study supports the importance of genetic BRAF p.V600 mutation analysis because its presence not only points to an E-GBM diagnosis but may also promote tumor progression.

Brain Tumor Characterization Using Radiogenomics in Artificial Intelligence Framework

Brain tumor characterization (BTC) is the process of knowing the underlying cause of brain tumors and their characteristics through various approaches such as tumor segmentation, classification, detection, and risk analysis. The substantial brain tumor characterization includes the identification of the molecular signature of various useful genomes whose alteration causes the brain tumor. The radiomics approach uses the radiological image for disease characterization by extracting quantitative radiomics features in the artificial intelligence (AI) environment. However, when considering a higher level of disease characteristics such as genetic information and mutation status, the combined study of "radiomics and genomics" has been considered under the umbrella of "radiogenomics". Furthermore, AI in a radiogenomics' environment offers benefits/advantages such as the finalized outcome of personalized treatment and individualized medicine. The proposed study summarizes the brain tumor's characterization in the prospect of an emerging field of research, i.e., radiomics and radiogenomics in an AI environment, with the help of statistical observation and risk-of-bias (RoB) analysis. The PRISMA search approach was used to find 121 relevant studies for the proposed review using IEEE, Google Scholar, PubMed, MDPI, and Scopus. Our findings indicate that both radiomics and radiogenomics have been successfully applied aggressively to several oncology applications with numerous advantages. Furthermore, under the AI paradigm, both the conventional and deep radiomics features have made an impact on the favorable outcomes of the radiogenomics approach of BTC. Furthermore, risk-of-bias (RoB) analysis offers a better understanding of the architectures with stronger benefits of AI by providing the bias involved in them.

Gliomas Infiltrating the Corpus Callosum: A Systematic Review of the Literature

Background: Gliomas infiltrating the corpus callosum (G-I-CC) majorly impact patient quality-of-life, but maximally safe tumor resection is challenging. We systematically reviewed the literature on G-I-CC. Methods: PubMed, EMBASE, Scopus, Web of Science, and Cochrane were searched following the PRISMA guidelines to include studies of patients with G-I-CC. Clinicopathological features, treatments, and outcomes were analyzed. Results: We included 52 studies comprising 683 patients. Most patients experienced headache (33%), cognitive decline (18.7%), and seizures (17.7%). Tumors mostly infiltrated the corpus callosum genu (44.2%) with bilateral extension (85.4%) into frontal (68.3%) or parietal (8.9%) lobes. Most G-I-CC were glioblastomas (84.5%) with IDH-wildtype (84.9%) and unmethylated MGMT promoter (53.5%). Resection (76.7%) was preferred over biopsy (23.3%), mostly gross-total (33.8%) and subtotal (32.5%). The tumor-infiltrated corpus callosum was resected in 57.8% of cases. Radiation was delivered in 65.8% of patients and temozolomide in 68.3%. Median follow-up was 12 months (range, 0.1−116). In total, 142 patients (31.8%) experienced post-surgical complications, including transient supplementary motor area syndrome (5.1%) and persistent motor deficits (4.3%) or abulia (2.5%). Post-treatment symptom improvement was reported in 42.9% of patients. No differences in rates of complications (p = 0.231) and symptom improvement (p = 0.375) were found in cases with resected versus preserved corpus callosum. Recurrences occurred in 40.9% of cases, with median progression-free survival of 9 months (0.1−72). Median overall survival was 10.7 months (range, 0.1−116), significantly longer in low-grade tumors (p = 0.013) and after resection (p < 0.001), especially gross-total (p = 0.041) in patients with high-grade tumors. Conclusions: G-I-CC show clinicopathological patterns comparable to other more frequent gliomas. Maximally safe resection significantly improves survival with low rates of persistent complications.

Clinicopathological characteristics and treatment outcomes of epithelioid glioblastoma

Epithelioid glioblastoma is a new variant of glioblastoma that has been recently recognized in the 2016 WHO classification of brain tumors. Given the rarity of epithelioid glioblastoma, the clinical characteristics, pathological features, radiological findings, and treatment outcomes are still not well characterized. Therefore, we identified eighty-four epithelioid glioblastoma cases to investigate these characteristics and identify the possible prognostic factors of survival. There were 55 male and 29 female patients with a mean age of 33.6 years. Headache (77.3%) was the most common clinical symptom, and other common symptoms included nausea or vomiting (34%), dizziness (20.5%), seizures (13.6%), and limb weakness (13.6%). Most lesions (88.1%) were located in cerebral lobes, especially in the frontal lobe and temporal lobe. One hundred percent of the patients were IDH1 wild-type (75/75) and INI-1 positive (58/58), and 57.3% (47/82) of patients harbored BRAF^V600E mutation. The median overall survival (OS) of all patients was 10.5 months. Patients who received chemotherapy (p = 0.006) or radiotherapy (p = 0.022) had a longer survival than patients who did not. In addition, the K-M curve showed that the BRAF^V600E mutation status was not associated with survival (p = 0.724). These findings may assist clinicians with better understanding and management of epithelioid glioblastoma.

Confirming Diagnosis and Effective Treatment for Rare Epithelioid Glioblastoma Variant: An Integrated Survival Analysis of the Literature

BACKGROUND

Epithelioid glioblastoma (eGBM) is a very rare histologic variant of glioblastoma that has not been studied in isolation and, therefore, its optimal management has been largely assumed, but not confirmed. The aim of this study was to analyze all reported cases describing the presentation and clinical features to better understand the clinical significance of this histologic diagnosis.

METHODS

A comprehensive literature search was conducted from 2005 to April 2019 identifying cases of eGBM that satisfied selection criteria for analysis. Survival was investigated using Kaplan-Meier estimations, and then univariate and multivariate logistic regression analyses for primary end point overall survival (OS) and second end point progression-free survival (PFS).

RESULTS

A total cohort of 59 eGBM cases from 28 articles were included for final analysis. Median age of patients at diagnosis was 30 years, with 29 (46%) female patients. When reported, 100% (37/37) cases were IDH1-wild-type and 63% (19/30) were positive for the BRAF V600E mutation by immunohistochemistry. Median OS and PFS were estimated to be 11.0 months (95% confidence interval, 6.5-13.0) and 7.0 months (95% confidence interval, 3.0-10.0), respectively. Surgical extent of resection, radiation therapy, and chemotherapy all predicted superior OS and PFS on multivariate analysis (P < 0.05). No biomarkers prognosticated survival.

CONCLUSIONS

These findings indicate that the histologic diagnosis of eGBM does not deviate from the clinical course of the broader glioblastoma diagnosis, despite being a unique histologic identity. These results argue against the temptation to deviate from the traditional management paradigm of surgery, radiation, and chemotherapy for glioblastoma based on this histology alone.