ArticleActa neuropathologica communications2025
Epitranscriptomic analysis reveals clinical and molecular signatures in glioblastoma.
Article in Acta neuropathologica communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
1 citing paper in PubMed.
- Advanced deep learning strategies in nanopore RNA sequencing.RNA biology · 2026Review
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Authors and funding
8 authors.
Funding
Abstract
This study characterizes the glioblastoma (GB) epitranscriptomic landscape in patient who evolve to progressive disease (PD) or pseudo-progressive disease (psPD). Novel differences in N6-Methyladenosine (m6A) RNA methylation patterns between these groups are identified in the first biopsy. Retrospective data of patients that were eventually deemed to have progressive disease or pseudoprogressive disease was captured from the electronic health record, and RNA from the first resection specimen was utilized to evaluate N6-methyladenosine (m6A) biomarkers from FFPE samples. Molecular analysis of m6A methylation modified RNA employed ACA-based RNase MazF digestion. After Quantitative Normalization with ComBat to mitigate batch effects, we identifed differentially methylated transcripts and gene expression analyses, co-expression networks analyses with WGCNA, and subsequently performed gene set GO and KEGG enrichment analyses. Enrichments for metabolic biological processes and pathways were identified in our differential methylated transcripts and select module eigengene networks highlighted key co-expressed genes intricately tied to distinct phenotypes/traits in patients that would ultimately be deemed PD or psPD. Our study identified key genes and pathways modified by m6A RNA methylation associated with cell metabolism alterations, highlighting the importance of understanding m6A mechanisms leading to the oncometabolite accumulation governing PD versus psPD patients. Furthermore, these data indicate that epitranscriptomal differences between PD versus psPD are detected early in the disease course.
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Registered trials
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