Contemporary Prognostic Signatures and Refined Risk Stratification of Gliomas: An Analysis of 4,400 Tumors.

astrocytoma glioma molecular classification oligodendroglioma prognosis

Journal

Neuro-oncology
ISSN: 1523-5866
Titre abrégé: Neuro Oncol
Pays: England
ID NLM: 100887420

Informations de publication

Date de publication:
21 Aug 2024
Historique:
received: 21 04 2024
medline: 21 8 2024
pubmed: 21 8 2024
entrez: 20 8 2024
Statut: aheadofprint

Résumé

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. We assembled a cohort of patients with a histopathologically diagnosed glioma from The Cancer Genome Atlas, 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 prospective assessment of patient survival. 4,400 gliomas were identified: 2,195 glioblastoma, 1,198 IDH1/2-mutant astrocytoma, 531 oligodendroglioma, 271 other IDH1/2-wildtype glioma, 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<0.01). 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. 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.

Sections du résumé

BACKGROUND 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 METHODS
We assembled a cohort of patients with a histopathologically diagnosed glioma from The Cancer Genome Atlas, 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 prospective assessment of patient survival.
RESULTS RESULTS
4,400 gliomas were identified: 2,195 glioblastoma, 1,198 IDH1/2-mutant astrocytoma, 531 oligodendroglioma, 271 other IDH1/2-wildtype glioma, 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<0.01). 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 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.

Identifiants

pubmed: 39164213
pii: 7737688
doi: 10.1093/neuonc/noae164
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© The Author(s) 2024. Published by Oxford University Press on behalf of the Society for Neuro-Oncology.

Auteurs

Hia S Ghosh (HS)

Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.

Ruchit V Patel (RV)

Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.

Eleanor Woodward (E)

Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.

Noah F Greenwald (NF)

Stanford University, Palo Alto, California.

Varun M Bhave (VM)

Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.

Eduardo A Maury (EA)

Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
Harvard/MIT MD-PhD Program, Harvard Medical School, Boston, MA, USA.

Gregory Cello (G)

Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.

Samantha E Hoffman (SE)

Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.

Yvonne Li (Y)

Broad Institute of Harvard and MIT, Cambridge, Massachusetts.
Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts.

Hersh Gupta (H)

Broad Institute of Harvard and MIT, Cambridge, Massachusetts.
Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts.

Gilbert Youssef (G)

Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts.

Liam F Spurr (LF)

Department of Radiation and Cellular Oncology, University of Chicago Pritzker School of Medicine, Chicago, Illinois.

Jayne Vogelzang (J)

Department of Pathology, Dana-Farber Cancer Institute, Boston, Massachusetts.

Mehdi Touat (M)

Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts.
Department of Neurology, Brigham and Women's Hospital, Boston, Massachusetts.
Sorbonne Université, Inserm, CNRS, UMR S 1127, Institut du Cerveau, ICM, AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Service de Neurologie 2-Mazarin, Paris, France.

Frank Dubois (F)

Broad Institute of Harvard and MIT, Cambridge, Massachusetts.
Division of Cancer Biology, Dana-Farber Cancer Institute, Boston, Massachusetts.

Andrew D Cherniack (AD)

Broad Institute of Harvard and MIT, Cambridge, Massachusetts.
Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts.

Xiaopeng Guo (X)

Department of Neurosurgery, Peking Union Medical College Hospital, Beijing, China.

Sherwin Tavakol (S)

Department of Pathology, Dana-Farber Cancer Institute, Boston, Massachusetts.
Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma.

Gino Cioffi (G)

Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland.

Neal I Lindeman (NI)

Department of Pathology, Brigham and Women's Hospital, Boston, Massachusetts.

Azra H Ligon (AH)

Department of Pathology, Brigham and Women's Hospital, Boston, Massachusetts.

E Antonio Chiocca (EA)

Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.

David A Reardon (DA)

Center for Neuro-Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts.

Patrick Y Wen (PY)

Center for Neuro-Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts.

David Meredith (D)

Department of Pathology, Brigham and Women's Hospital, Boston, Massachusetts.

Sandro Santagata (S)

Department of Pathology, Brigham and Women's Hospital, Boston, Massachusetts.

Jill S Barnholtz-Sloan (JS)

Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland.
Center for Biomedical Informatics and Information Technology, National Cancer Institute, Bethesda, Maryland.

Keith L Ligon (KL)

Broad Institute of Harvard and MIT, Cambridge, Massachusetts.
Department of Pathology, Dana-Farber Cancer Institute, Boston, Massachusetts.
Department of Pathology, Brigham and Women's Hospital, Boston, Massachusetts.

Rameen Beroukhim (R)

Broad Institute of Harvard and MIT, Cambridge, Massachusetts.
Center for Neuro-Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts.
Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, Massachusetts.

Wenya Linda Bi (WL)

Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.

Classifications MeSH