Temporal change of DNA methylation subclasses between matched newly diagnosed and recurrent glioblastoma.
Richard DrexlerRobin KhatriUlrich SchüllerAlicia EckhardtAlice RybaThomas SauvignyLasse DührsenMalte MohmeTammo RicklefsHelena BodeFabian HausmannTobias B HuberStefan BonnHannah VoßJulia E NeumannDana SilverbushVolker HovestadtMario L SuvàKatrin LamszusJens GemptManfred WestphalDieter H HeilandSonja HänzelmannFranz L RicklefsPublished in: Acta neuropathologica (2024)
The longitudinal transition of phenotypes is pivotal in glioblastoma treatment resistance and DNA methylation emerged as an important tool for classifying glioblastoma phenotypes. We aimed to characterize DNA methylation subclass heterogeneity during progression and assess its clinical impact. Matched tissues from 47 glioblastoma patients were subjected to DNA methylation profiling, including CpG-site alterations, tissue and serum deconvolution, mass spectrometry, and immunoassay. Effects of clinical characteristics on temporal changes and outcomes were studied. Among 47 patients, 8 (17.0%) had non-matching classifications at recurrence. In the remaining 39 cases, 28.2% showed dominant DNA methylation subclass transitions, with 72.7% being a mesenchymal subclass. In general, glioblastomas with a subclass transition showed upregulated metabolic processes. Newly diagnosed glioblastomas with mesenchymal transition displayed increased stem cell-like states and decreased immune components at diagnosis and exhibited elevated immune signatures and cytokine levels in serum. In contrast, tissue of recurrent glioblastomas with mesenchymal transition showed increased immune components but decreased stem cell-like states. Survival analyses revealed comparable outcomes for patients with and without subclass transitions. This study demonstrates a temporal heterogeneity of DNA methylation subclasses in 28.2% of glioblastomas, not impacting patient survival. Changes in cell state composition associated with subclass transition may be crucial for recurrent glioblastoma targeted therapies.
Keyphrases
- dna methylation
- newly diagnosed
- stem cells
- genome wide
- gene expression
- single cell
- mass spectrometry
- end stage renal disease
- cell therapy
- chronic kidney disease
- ejection fraction
- magnetic resonance
- peritoneal dialysis
- type diabetes
- high resolution
- magnetic resonance imaging
- adipose tissue
- combination therapy
- sensitive detection
- mesenchymal stem cells