Molecular Classification and Prognostic Features of Gliomas

Background Introduction

Glioma is the most common malignant brain tumor in adults, and its classification, risk stratification, and treatment standards have undergone significant changes in recent years. With the introduction of molecular markers, the classification system for gliomas has shifted from traditional histopathological classification to molecular classification. This transformation has not only improved the accuracy of predicting tumor behavior but also provided new insights for treatment selection and prognosis evaluation. However, despite the important role of molecular classification in the diagnosis and treatment of gliomas, systematic studies on the survival rates and prognostic features of patients with different molecular subtypes remain limited.

To address this gap, scientists from multiple research institutions collaborated on a large-scale study aimed at evaluating survival trends in glioma patients and identifying molecular features associated with prognosis by integrating molecular and clinical data. This study not only provides new insights into the molecular classification of gliomas but also offers practical prognostic tools for clinicians.

Source of the Paper

This paper was co-authored by scientists from several renowned research institutions, including Brigham and Women’s Hospital at Harvard Medical School, Dana-Farber Cancer Institute, and the Broad Institute of Harvard and MIT. The primary authors include Hia S. Ghosh, Ruchit V. Patel, and Wenya Linda Bi, among others. The study was published ahead of print on August 21, 2024, in the journal Neuro-Oncology, under the title “Contemporary Prognostic Signatures and Refined Risk Stratification of Gliomas: An Analysis of 4400 Tumors.”

Research Process and Results

1. Collection and Classification of Study Subjects

The research team collected data from 4,400 patients with histopathologically diagnosed gliomas from three datasets: Dana-Farber Cancer Institute/Brigham and Women’s Hospital (DFCI/BWH), Project Genomics Evidence Neoplasia Information Exchange (GENIE), and The Cancer Genome Atlas (TCGA). The median age of the patients was 52 years, with an age range of 0 to 94 years. Based on the 2021 World Health Organization (WHO) molecular classification criteria, these gliomas were divided into five subgroups: glioblastoma, IDH1/2-mutant astrocytoma, IDH1/2-mutant oligodendroglioma, pediatric-type glioma, and other IDH1/2-wild-type gliomas.

2. Molecular Classification Revises Histopathological Diagnoses

The study found that molecular classification significantly revised the original histopathological diagnoses in 27.2% of gliomas. For example, 87.4% of molecularly classified glioblastomas were consistent with their original diagnosis, while IDH1/2-mutant astrocytomas showed greater heterogeneity in their original diagnoses, with only 55.0% initially diagnosed as astrocytomas and 24.8% as glioblastomas. In contrast, IDH1/2-mutant oligodendrogliomas had higher diagnostic consistency, with 84.8% of cases initially diagnosed as oligodendrogliomas.

3. Distribution of Molecular Features and Prognostic Analysis

The research team further analyzed the distribution of molecular features across different glioma subtypes. The results showed that the most common molecular alterations in glioblastoma included whole chromosome 7 gain/chromosome 10 loss (7+/10-), while EGFR amplification was rare in IDH1/2-mutant astrocytomas but more common in high-grade tumors. Additionally, the study found that molecular alterations within tumorigenic pathways were mutually exclusive in different glioma subtypes. For example, alterations in EGFR and PDGFRA, MET, and other receptor tyrosine kinases (RTKs) rarely co-occurred.

4. Survival Analysis

The research team compared the survival rates of non-TCGA patients with those of TCGA patients. The results showed that the overall survival of non-TCGA patients was significantly higher than that of TCGA patients. Specifically, the median survival of glioblastoma patients in the non-TCGA cohort was 19.0 months, 26.7% higher than the 15.0 months observed in TCGA patients. The survival improvements for IDH1/2-mutant astrocytoma and oligodendroglioma patients in the non-TCGA cohort were even more pronounced, with increases of 55.6% and 127.8%, respectively.

5. Identification of Prognostic Features

Through multivariate analysis, the research team identified several molecular features associated with prognosis. For example, in glioblastoma, NF1 alterations and 21q loss were associated with poorer prognosis, while EGFR amplification and 22q loss showed negative prognostic impacts in IDH1/2-mutant astrocytomas. Additionally, the study found that heterozygous loss of CDKN2A/B had a similar prognostic impact as homozygous loss, suggesting that even partial loss of CDKN2A/B has prognostic value.

Conclusions and Significance

This study provides new insights into the molecular classification and prognostic evaluation of gliomas by integrating large-scale molecular and clinical data. The results demonstrate that molecular classification not only revises traditional histopathological diagnoses but also identifies molecular features closely associated with patient survival. These findings offer practical prognostic tools for clinicians and provide important references for future clinical trials and personalized treatment strategies.

Research Highlights

1. Revision of Molecular Classification: The study shows that molecular classification revised over 25% of the original histopathological diagnoses of gliomas, emphasizing the importance of molecular markers in glioma classification.
2. Significant Improvement in Survival Rates: The survival rates of non-TCGA patients were significantly higher than those of TCGA patients, indicating the positive impact of modern treatment methods and molecular diagnostic technologies on patient outcomes.
3. Identification of Prognostic Features: The study identified several molecular features associated with prognosis, such as NF1 alterations and EGFR amplification, providing new bases for clinical prognostic evaluation.

Additional Valuable Information

The study also found that age significantly impacts the prognosis of glioma patients, with older patients generally having lower survival rates. Additionally, the distribution of MGMT promoter methylation status was similar across age groups, but in IDH1/2-mutant gliomas, the methylation rate was significantly higher in older patients than in younger patients, suggesting that older patients may have biologically more favorable glioma subtypes.

This study not only provides new insights into the molecular classification and prognostic evaluation of gliomas but also lays an important foundation for future clinical research and personalized treatment strategies.