IDH wild-type lower-grade gliomas with glioblastoma molecular features: a systematic review and meta-analysis

Variable screening and model construction for prognosis of elderly patients with lower-grade gliomas based on LASSO-Cox regression: a population-based cohort study

Background

This study aimed to identify prognostic factors for survival and develop a prognostic nomogram to predict the survival probability of elderly patients with lower-grade gliomas (LGGs).

Methods

Elderly patients with histologically confirmed LGG were recruited from the Surveillance, Epidemiology, and End Results (SEER) database. These individuals were randomly allocated to the training and validation cohorts at a 2:1 ratio. First, Kaplan-Meier survival analysis and subgroup analysis were performed. Second, variable screening of all 13 variables and a comparison of predictive models based on full Cox regression and LASSO-Cox regression analyses were performed, and the key variables in the optimal model were selected to construct prognostic nomograms for OS and CSS. Finally, a risk stratification system and a web-based dynamic nomogram were constructed.

Results

A total of 2307 elderly patients included 1220 males and 1087 females, with a median age of 72 years and a mean age of 73.30 ± 6.22 years. Among them, 520 patients (22.5%) had Grade 2 gliomas, and 1787 (77.5%) had Grade 3 gliomas. Multivariate Cox regression analysis revealed four independent prognostic factors (age, WHO grade, surgery, and chemotherapy) that were used to construct the full Cox model. In addition, LASSO-Cox regression analysis revealed five prognostic factors (age, WHO grade, surgery, radiotherapy, and chemotherapy), and a LASSO model was constructed. A comparison of the two models revealed that the LASSO model with five variables had better predictive performance than the full Cox model with four variables. Ultimately, five key variables based on LASSO-Cox regression were utilized to develop prognostic nomograms for predicting the 1-, 2-, and 5-year OS and CSS rates. The nomograms exhibited relatively good predictive ability and clinical utility. Moreover, the risk stratification system based on the nomograms effectively divided patients into low-risk and high-risk subgroups.

Conclusion

Variable screening based on LASSO-Cox regression was used to determine the optimal prediction model in this study. Prognostic nomograms could serve as practical tools for predicting survival probabilities, categorizing these patients into different mortality risk subgroups, and developing personalized decision-making strategies for elderly patients with LGGs. Moreover, the web-based dynamic nomogram could facilitate its use in the clinic.

Comparative analysis of molecular and histological glioblastomas: insights into prognostic variance

PURPOSE

Whether molecular glioblastomas (GBMs) identify with a similar dismal prognosis as a "classical" histological GBM is controversial. This study aimed to compare the clinical, molecular, imaging, surgical factors, and prognosis between molecular GBMs and histological GBMs.

METHODS

Retrospective chart and imaging review was performed in 983 IDH-wildtype GBM patients (52 molecular GBMs and 931 histological GBMs) from a single institution between 2005 and 2023. Propensity score-matched analysis was additionally performed to adjust for differences in baseline variables between molecular GBMs and histological GBMs.

RESULTS

Molecular GBM patients were substantially younger (58.1 vs. 62.4, P = 0.014) with higher rate of TERTp mutation (84.6% vs. 50.3%, P < 0.001) compared with histological GBM patients. Imaging showed higher incidence of gliomatosis cerebri pattern (32.7% vs. 9.2%, P < 0.001) in molecular GBM compared with histological GBM, which resulted in lesser extent of resection (P < 0.001) in these patients. The survival was significantly better in molecular GBM compared to histological GBM (median OS 30.2 vs. 18.4 months, P = 0.001). The superior outcome was confirmed in propensity score analyses by matching histological GBM to molecular GBM (P < 0.001).

CONCLUSION

There are distinct clinical, molecular, and imaging differences between molecular GBMs and histological GBMs. Our results suggest that molecular GBMs have a more favorable prognosis than histological GBMs.

Isocitrate Dehydrogenase 1/2 Wildtype Adult Astrocytoma with WHO Grade 2/3 Histological Features: Molecular Re-Classification, Prognostic Factors, Clinical Outcomes

BACKGROUND

Isocitrate Dehydrogenase 1/2 (IDH 1/2)-wildtype (WT) astrocytomas constitute a heterogeneous group of tumors and have undergone a series of diagnostic reclassifications over time. This study aimed to investigate molecular markers, clinical, imaging, and treatment factors predictive of outcomes in WHO grade 2/3 IDH-WT astrocytomas ('early glioblastoma').

METHODOLOGY

Patients with WHO grade 2/3 IDH-WT astrocytomas were identified from the hospital archives. They were cross-referenced with the electronic medical records systems, including neuroimaging. The expert neuro-pathology team retrieved data on molecular markers-MGMT, TERT, IDH, and EGFR. Tumors with a TERT mutation and/or EGFR amplification were reclassified as glioblastoma.

RESULTS

Fifty-four patients were identified. Sixty-three percent of the patients could be conclusively reclassified as glioblastoma based on either TERT mutation, EGFR amplification, or both. On imaging, 65% showed gadolinium enhancement on MRI. Thirty-nine patients (72%) received long-course radiotherapy, of whom 64% received concurrent chemotherapy. The median follow-up of the group was 16 months (range: 2-90), and the median overall survival (OS) was 17.3 months. The 2-year OS of the whole cohort was 31%. On univariate analysis, older age, worse performance status (PS), and presence versus absence of contrast enhancement on diagnostic MRI were statistically significant for poorer OS.

CONCLUSION

IDH-WT WHO grade 2/3 astrocytomas are a heterogeneous group of tumors with poor clinical outcomes. The majority can be reclassified as glioblastoma, based on current WHO classification criteria, but further understanding of the underlying biology of these tumors and the discovery of novel targeted agents are needed for better outcomes.

Patterns of T2-FLAIR discordance across a cohort of adult-type diffuse gliomas and deviations from the classic T2-FLAIR mismatch sign

PURPOSE

T2-FLAIR mismatch serves as a highly specific but insensitive marker for IDH-mutant (IDHm) astrocytoma with potential limitations in real-world application. We aimed to assess the utility of a broader definition of T2-FLAIR discordance across a cohort of adult-type diffuse lower-grade gliomas (LrGG) to see if specific patterns emerge and additionally examine factors determining deviation from the classic T2-FLAIR mismatch sign.

METHODS

Preoperative MRIs of non-enhancing adult-type diffuse LrGGs were reviewed. Relevant demographic, molecular, and MRI data were compared across tumor subgroups.

RESULTS

Eighty cases satisfied the inclusion criteria. Highest discordance prevalence and > 50% T2-FLAIR discordance volume were noted with IDHm astrocytomas (P < 0.001), while < 25% discordance volume was associated with oligodendrogliomas (P = 0.03) and IDH-wildtype (IDHw) LrGG (P = 0.004). "T2-FLAIR matched pattern" was associated with IDHw LrGG (P < 0.001) and small or minimal areas of discordance with oligodendrogliomas (P = 0.03). Sensitivity and specificity of classic mismatch sign for IDHm astrocytoma were 25.7% and 100%, respectively (P = 0.06). Retained ATRX expression and/or non-canonical IDH mutation (n = 10) emerged as a significant factor associated with absence of classic T2-FLAIR mismatch sign in IDHm astrocytomas (100%, P = 0.02) and instead had minimal discordance or matched pattern (40%, P = 0.04).

CONCLUSION

T2-FLAIR discordance patterns in adult-type diffuse LrGGs exist on a diverging but distinct spectrum of classic mismatch to T2-FLAIR matched patterns. Specific molecular markers may play a role in deviations from classic mismatch sign.

Prognostic and predictive biomarkers in central nervous system tumours: the molecular state of play

Central nervous system (CNS) tumours were one of the first cancer types to adopt and integrate molecular profiling into routine clinical diagnosis in 2016. The vast majority of these biomarkers, used to discriminate between tumour types, also offered prognostic information. With the advent of The Cancer Genome Atlas (TCGA) and other large genomic datasets, further prognostic sub-stratification was possible within tumour types, leading to increased precision in CNS tumour grading. This review outlines the evolution of the molecular landscape of adult CNS tumours, through the prism of World Health Organization (WHO) Classifications. We begin our journey in the pre-molecular era, where high-grade gliomas were divided into 'primary' and 'secondary' glioblastomas. Molecular alterations explaining these clinicopathological observations were the first branching points of glioma diagnostics, with the discovery of IDH1/2 mutations and 1p/19q codeletion. Subsequently, the rigorous characterisation of paediatric gliomas led to the unearthing of histone H3 alterations as a key event in gliomagenesis, which also had implications for young adult patients. Simultaneously, studies investigating prognostic biomarkers within tumour types were undertaken. Certain genomic phenotypes were found to portend unfavourable outcomes, for example, MYCN amplification in spinal ependymoma. The arrival of methylation profiling, having revolutionised the diagnosis of CNS tumours, now promises to bring increased prognostic accuracy, as has been shown in meningiomas. While MGMT promoter hypermethylation has remained a reliable biomarker of response to cytotoxic chemotherapy, targeted therapy in CNS tumours has unfortunately not had the success of other cancers. Therefore, predictive biomarkers have lagged behind the identification of prognostic biomarkers in CNS tumours. Emerging research from new clinical trials is cause for guarded optimism and may shift our conceptualisation of predictive biomarker testing in CNS tumours.

Pyrosequencing Analysis of O-6-Methylguanine-DNA Methyltransferase Methylation at Different Cut-Offs of Positivity Associated with Treatment Response and Disease-Specific Survival in Isocitrate Dehydrogenase-Wildtype Grade 4 Glioblastoma

The O-6-methylguanine-DNA methyltransferase (MGMT) gene is a critical guardian of genomic integrity. MGMT methylation in diffuse gliomas serves as an important determinant of patients' prognostic outcomes, more specifically in glioblastomas (GBMs). In GBMs, the absence of MGMT methylation, known as MGMT promoter unmethylation, often translates into a more challenging clinical scenario, tending to present resistance to chemotherapy and a worse prognosis. A pyrosequencing (PSQ) technique was used to analyze MGMT methylation status at different cut-offs (5%, 9%, and 11%) in a sample of 78 patients diagnosed with IDH-wildtype grade 4 GBM. A retrospective analysis was provided to collect clinicopathological and prognostic data. A statistical analysis was used to establish an association between methylation status and treatment response (TR) and disease-specific survival (DSS). The patients with methylated MGMT status experienced progressive disease rates of 84.6%, 80%, and 78.4% at the respective cut-offs of 5%, 9%, and 11%. The number was considerably higher when considering unmethylated patients, as all patients (100%), regardless of the cut-off, presented progressive disease. Regarding disease-specific survival (DSS), the Hazard Ratio (HR) was HR = 0.74 (0.45-1.24; p = 0.251); HR = 0.82 (0.51-1.33; p = 0.425); and HR = 0.79 (0.49-1.29; p = 0.350), respectively. Our study concludes that there is an association between MGMT unmethylation and worse TR and DSS. The 9% cut-off demonstrated a greater potential for patient survival as a function of time, which may shed light on the future need for standardization of MGMT methylation positivity parameters in PSQ.