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The Consortium to Inform Molecular and Practical Approaches to CNS Tumor Taxonomy (cIMPACT-NOW) update 3 recommends that histologic grade II and III IDH-wildtype diffuse astrocytic gliomas that harbor EGFR amplification, the combination of whole chromosome 7 gain and whole chromosome 10 loss (7 + /10 −), or TERT promoter (pTERT) mutations should be considered as glioblastomas (GBM), World Health Organization grade IV. In this retrospective study, we examined the utility of molecular classification based on pTERT status and copy-number alterations (CNAs) in IDH-wildtype lower grade gliomas (LGGs, grade II, and III). The impact on survival was evaluated for the pTERT mutation and CNAs, including EGFR gain/amplification, PTEN loss, CDKN2A homozygous deletion, and PDGFRA gain/amplification. We analyzed 46 patients with IDH-wildtype/pTERT-mutant (mut) LGGs and 85 with IDH-wildtype/pTERT-wildtype LGGs. EGFR amplification and a combination of EGFR gain and PTEN loss (EGFR + /PTEN −) were significantly more frequent in pTERT-mut patients (p < 0.0001). Cox regression analysis showed that the pTERT mutation was a significant predictor of poor prognosis (hazard ratio [HR] 2.79, 95% confidence interval [CI] 1.55–4.89, p = 0.0008), but neither EGFR amplification nor EGFR + /PTEN − was an independent prognostic factor in IDH-wildtype LGGs. PDGFRA gain/amplification was a significant poor prognostic factor in IDH-wildtype/pTERT-wildtype LGGs (HR 2.44, 95% CI 1.09–5.27, p = 0.03, Cox regression analysis). The IDH-wildtype LGGs with either pTERT-mut or PDGFRA amplification were mostly clustered with GBM by DNA methylation analysis. Thus, our study suggests that analysis of pTERT mutation status is necessary and sufficient to diagnose IDH-wildtype diffuse astrocytic gliomas with molecular features of glioblastoma. The PDGFRA status may help further delineate IDH-wildtype/pTERT-wildtype LGGs. Methylation profiling showed that IDH-wildtype LGGs without molecular features of GBM were a heterogeneous group of tumors. Some of them did not fall into existing categories and had significantly better prognoses than those clustered with GBM. [ABSTRACT FROM AUTHOR]

Objective: Accumulating evidence from recent molecular diagnostic studies has indicated the prognostic significance of various genetic markers for patients with glioblastoma (GBM). To evaluate the impact of such genetic markers on prognosis, we retrospectively analyzed the outcomes of patients with IDH‐wildtype GBM in our institution. In addition, to assess the impact of bevacizumab (BEV) treatment, we compared overall survival (OS) between the pre‐ and post‐BEV eras. Methods: We analyzed the data of 100 adult patients (over 18 years old) with IDH‐wildtype GBM from our database between February 2006 and October 2018. Genetic markers, such as MGMT methylation status, EGFR amplification, CDKN2A homozygous deletion, and clinical factors were analyzed by evaluating the patients' OS. Results: CDKN2A homozygous deletion showed no significant impact on OS in patients with methylated MGMT status (p = 0.5268), whereas among patients with unmethylated MGMT status, there was a significant difference in OS between patients with and without CDKN2A homozygous deletion (median OS: 14.7 and 16.9 months, respectively, p = 0.0129). This difference was more evident in the pre‐BEV era (median OS: 10.1 and 15.6 months, respectively, p = 0.0351) but has become nonsignificant in the post‐BEV era (median OS: 16.0 and 16.9 months, respectively, p = 0.1010) due to OS improvement in patients with CDKN2A homozygous deletion. However, these findings could not be validated in The Cancer Genome Atlas cohort. Conclusions: MGMT and CDKN2A status subdivided our cohort into three race‐specific groups with different prognoses. Our findings indicate that BEV approval in Japan led to OS improvement exclusively for patients with concurrent unmethylated MGMT status and CDKN2A homozygous deletion. [ABSTRACT FROM AUTHOR]

We attempted to establish a magnetic resonance imaging (MRI)-based radiomic model for stratifying prognostic subgroups of newly diagnosed glioblastoma (GBM) patients and predicting O (6)-methylguanine-DNA methyltransferase promotor methylation (pMGMT-met) status of the tumor. Preoperative MRI scans from 201 newly diagnosed GBM patients were included in this study. A total of 489 texture features including the first-order feature, second-order features from 162 datasets, and location data from 182 datasets were collected. Supervised principal component analysis was used for prognostication and predictive modeling for pMGMT-met status was performed based on least absolute shrinkage and selection operator regression. 22 radiomic features that were correlated with prognosis were used to successfully stratify patients into high-risk and low-risk groups (p = 0.004, Log-rank test). The radiomic high- and low-risk stratification and pMGMT status were independent prognostic factors. As a matter of fact, predictive accuracy of the pMGMT methylation status was 67% when modeled by two significant radiomic features. A significant survival difference was observed among the combined high-risk group, combined intermediate-risk group (this group consists of radiomic low risk and pMGMT-unmet or radiomic high risk and pMGMT-met), and combined low-risk group (p = 0.0003, Log-rank test). Radiomics can be used to build a prognostic score for stratifying high- and low-risk GBM, which was an independent prognostic factor from pMGMT methylation status. On the other hand, predictive accuracy of the pMGMT methylation status by radiomic analysis was insufficient for practical use. [ABSTRACT FROM AUTHOR]

The diagnosis and prognostication of glioblastoma (GBM) remain to be solely dependent on histopathological findings and few molecular markers, despite the clinical heterogeneity in this entity. To address this issue, we investigated the prognostic impact of copy number alterations (CNAs) using two population-based IDH-wild-type GBM cohorts: an original Japanese cohort and a dataset from The Cancer Genome Atlas (TCGA). The molecular disproportions between these cohorts were dissected in light of cohort differences in GBM. The Japanese cohort was collected from cases registered in Kansai Molecular Diagnosis Network for CNS tumors (KNBTG). The somatic landscape around CNAs was analyzed for 212 KNBTG cases and 359 TCGA cases. Next, the clinical impacts of CNA profiles were investigated for 140 KNBTG cases and 152 TCGA cases treated by standard adjuvant therapy using temozolomide-based chemoradiation. The comparative profiling indicated unequal distribution of specific CNAs such as EGFR, CDKN2A, and PTEN among the two cohorts. Especially, the triple overlap CNAs in these loci (triple CNA) were much higher in frequency in TCGA (70.5%) than KNBTG (24.3%), and its prognostic impact was independently validated in both cohorts. The KNBTG cohort significantly showed better prognosis than the TCGA cohort (median overall survival 19.3 vs 15.6 months). This survival difference between the two cohorts completely resolved after subclassifying all cases according to the triple CNA status. The prognostic significance of triple CNA was identified in IDH-wild-type GBM. Distribution difference in prognostic CNA profiles potentially could cause survival differences across cohorts in clinical studies. [ABSTRACT FROM AUTHOR]