Unraveling glioblastoma diversity: Insights into methylation subtypes and spatial relationships

Author:

Foltyn-Dumitru Martha12ORCID,Alzaid Haidar1ORCID,Rastogi Aditya12,Neuberger Ulf1,Sahm Felix34ORCID,Kessler Tobias56ORCID,Wick Wolfgang56ORCID,Bendszus Martin1ORCID,Vollmuth Philipp12ORCID,Schell Marianne12ORCID

Affiliation:

1. Department of Neuroradiology, Heidelberg University Hospital , Heidelberg , Germany

2. Section for Computational Neuroimaging, Department of Neuroradiology, Heidelberg University Hospital , Heidelberg , Germany

3. Department of Neuropathology, Heidelberg University Hospital , Heidelberg , Germany

4. Clinical Cooperation Unit Neuropathology, German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ) , Heidelberg , Germany

5. Department of Neurology and Neurooncology Program, Heidelberg University Hospital, Heidelberg University , Heidelberg , Germany

6. Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ) , Heidelberg , Germany

Abstract

Abstract Background The purpose of this study was to elucidate the relationship between distinct brain regions and molecular subtypes in glioblastoma (GB), focusing on integrating modern statistical tools and molecular profiling to better understand the heterogeneity of Isocitrate Dehydrogenase wild-type (IDH-wt) gliomas. Methods This retrospective study comprised 441 patients diagnosed with new IDH-wt glioma between 2009 and 2020 at Heidelberg University Hospital. The diagnostic process included preoperative magnetic resonance imaging and molecular characterization, encompassing IDH-status determination and subclassification, through DNA-methylation profiling. To discern and map distinct brain regions associated with specific methylation subtypes, a support-vector regression-based lesion-symptom mapping (SVR-LSM) was employed. Lesion maps were adjusted to 2 mm³ resolution. Significance was assessed with beta maps, using a threshold of P < .005, with 10 000 permutations and a cluster size minimum of 100 voxels. Results Of 441 initially screened glioma patients, 423 (95.9%) met the inclusion criteria. Following DNA-methylation profiling, patients were classified into RTK II (40.7%), MES (33.8%), RTK I (18%), and other methylation subclasses (7.6%). Between molecular subtypes, there was no difference in tumor volume. Using SVR-LSM, distinct brain regions correlated with each subclass were identified: MES subtypes were associated with left-hemispheric regions involving the superior temporal gyrus and insula cortex, RTK I with right frontal regions, and RTK II with 3 clusters in the left hemisphere. Conclusions This study linked molecular diversity and spatial features in glioblastomas using SVR-LSM. Future studies should validate these findings in larger, independent cohorts to confirm the observed patterns.

Funder

AI Health Innovation Cluster of the Heidelberg-Mannheim Health and Life Science Alliance

Physician-Scientist Program of Heidelberg University

Else Kröner Fresenius Foundation

Deutsche Forschungsgemeinschaft

Publisher

Oxford University Press (OUP)

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