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. 2025 Jan 12;27(1):195-208.
doi: 10.1093/neuonc/noae164.

Contemporary prognostic signatures and refined risk stratification of gliomas: An analysis of 4400 tumors

Hia S Ghosh  1 , Ruchit V Patel  1 , Eleanor Woodward  1 , Noah F Greenwald  2 , Varun M Bhave  1 , Eduardo A Maury  3   1 , Gregory Cello  1 , Samantha E Hoffman  1 , Yvonne Li  4   5 , Hersh Gupta  4   5 , Gilbert Youssef  4 , Liam F Spurr  6 , Jayne Vogelzang  7 , Mehdi Touat  8   9   4 , Frank Dubois  10   5 , Andrew D Cherniack  4   5 , Xiaopeng Guo  11 , Sherwin Tavakol  12   7 , Gino Cioffi  13 , Neal I Lindeman  14 , Azra H Ligon  14 , E Antonio Chiocca  1 , David A Reardon  15 , Patrick Y Wen  15 , David M Meredith  14 , Sandro Santagata  14 , Jill S Barnholtz-Sloan  16   13 , Keith L Ligon  14   7   5 , Rameen Beroukhim  17   15   5 , Wenya Linda Bi  1
Affiliations

Contemporary prognostic signatures and refined risk stratification of gliomas: An analysis of 4400 tumors

Hia S Ghosh et al. Neuro Oncol. .

Abstract

Background: With the significant shift in the classification, risk stratification, and standards of care for gliomas, we sought to understand how the overall survival of patients with these tumors is impacted by molecular features, clinical metrics, and treatment received.

Methods: We assembled a cohort of patients with histopathologically diagnosed glioma from The Cancer Genome Atlas (TCGA), Project Genomics Evidence Neoplasia Information Exchange, and Dana-Farber Cancer Institute/Brigham and Women's Hospital. This incorporated retrospective clinical, histological, and molecular data alongside a prospective assessment of patient survival.

Results: Of 4400 gliomas were identified: 2195 glioblastomas, 1198 IDH1/2-mutant astrocytomas, 531 oligodendrogliomas, 271 other IDH1/2-wild-type gliomas, and 205 pediatric-type glioma. Molecular classification updated 27.2% of gliomas from their original histopathologic diagnosis. Examining the distribution of molecular alterations across glioma subtypes revealed mutually exclusive alterations within tumorigenic pathways. Non-TCGA patients had significantly improved overall survival compared to TCGA patients, with 26.7%, 55.6%, and 127.8% longer survival for glioblastoma, IDH1/2-mutant astrocytoma, and oligodendroglioma, respectively (all P < .01). Several prognostic features were characterized, including NF1 alteration and 21q loss in glioblastoma, and EGFR amplification and 22q loss in IDH1/2-mutant astrocytoma. Leveraging the size of this cohort, nomograms were generated to assess the probability of overall survival based on patient age, the molecular features of a tumor, and the treatment received.

Conclusions: By applying modern molecular criteria, we characterize the genomic diversity across glioma subtypes, identify clinically applicable prognostic features, and provide a contemporary update on patient survival to serve as a reference for ongoing investigations.

Keywords: astrocytoma; glioma; molecular classification; oligodendroglioma; prognosis.

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Figures

Figure 1.
Figure 1.
Cohort overview. (A) Overview of constructing a pooled molecularly annotated glioma cohort. (B) Summary of the pooled glioma cohort.
Figure 2.
Figure 2.
Mutational signatures in glioma. (A) Mutational signatures of gliomas stratified by tumor subtype. Genes were filtered out of the comutation plot if alteration prevalence was low or if not involved in molecular glioma classification guidelines. (B) Molecular alterations within the same tumorigenic pathway were frequently mutually exclusive in glioma.
Figure 3.
Figure 3.
Genomic correlations in glioma subtypes. Heatmap of positively and inversely correlated genes for (A) glioblastoma, (B) IDH1/2-mutant astrocytoma, and (C) oligodendroglioma. (D) The genomic distance between grade 4 IDH1/2-mutant astrocytomas and glioblastoma was greater than the genomic distance within each glioma group. (E) Grade 4 IDH1/2-mutant astrocytoma were more genomically distinct from Grade 2/3 IDH1/2-mutant astrocytoma, with greater genomic separation compared to grade 2 and grade 3 IDH1/2-mutant astrocytoma or between grade 2 and grade 3 oligodendroglioma. P < .001 (***).
Figure 4.
Figure 4.
Overall survival and prognostic features in glioma subtypes. Kaplan–Meier curves demonstrate overall survival in the non-The Cancer Genome Atlas (TCGA) cohort exceeds that of the TCGA cohort for patients with newly diagnosed (A) glioblastoma, (C) IDH1/2-mutant astrocytoma, and (E) oligodendroglioma. Multivariate adjusted clinical and molecular features predictive of overall patient survival for newly diagnosed (B) glioblastoma, (D) IDH1/2-mutant astrocytoma, and (F) oligodendroglioma. Nomograms quantify the predicted probability of patient survival integrating clinical and molecular features for (G) glioblastoma and (H) IDH1/2-mutant astrocytoma.
Figure 5.
Figure 5.
Impact of age on survival and prognostic features. Kaplan–Meier curves for glioma overall survival stratified by age for (A) glioblastoma, (B) IDH1/2-mutant astrocytoma, and (C) oligodendroglioma. (D) Prevalence of glioma subtypes across age categories. (E) Prevalence of IDH1/2-mutation, MGMT-methylation, and chromosome 1p/19q codeletion across age categories. (F) Cooccurrence of MGMT-methylation with IDH1/2 mutation status. (G) Percent of gliomas assayed for MGMT-methylation stratified by IDH1/2 mutation status and tumor grade (high: grades 3–4, low: grades 1–2). P < .05 (*), P < .01 (**), P < .001 (***).
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