Epitranscriptomic analysis reveals clinical and molecular signatures in glioblastoma
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....
Saved in:
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-04-01
|
| Series: | Acta Neuropathologica Communications |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s40478-025-01966-5 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850145390123286528 |
|---|---|
| author | Glaucia Maria de Mendonça Fernandes Wesley Wang Saman Seyed Ahmadian Daniel Jones Jing Peng Pierre Giglio Monica Venere José Javier Otero |
| author_facet | Glaucia Maria de Mendonça Fernandes Wesley Wang Saman Seyed Ahmadian Daniel Jones Jing Peng Pierre Giglio Monica Venere José Javier Otero |
| author_sort | Glaucia Maria de Mendonça Fernandes |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-c6a7c90ef4c64bc3a8a95ef6fef99508 |
| institution | OA Journals |
| issn | 2051-5960 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | BMC |
| record_format | Article |
| series | Acta Neuropathologica Communications |
| spelling | doaj-art-c6a7c90ef4c64bc3a8a95ef6fef995082025-08-20T02:28:07ZengBMCActa Neuropathologica Communications2051-59602025-04-0113111910.1186/s40478-025-01966-5Epitranscriptomic analysis reveals clinical and molecular signatures in glioblastomaGlaucia Maria de Mendonça Fernandes0Wesley Wang1Saman Seyed Ahmadian2Daniel Jones3Jing Peng4Pierre Giglio5Monica Venere6José Javier Otero7Departament of Cellular and Molecular Medicine, Florida International University Herbert Wertheim College of MedicineDepartment of Pathology, The Ohio State University Wexner Medical CenterDepartment of Pathology, The Ohio State University Wexner Medical CenterDepartment of Pathology, The Ohio State University Wexner Medical CenterCenter for Biostatistics, The Ohio State University College of MedicineDepartment of Neuro-oncology, The Ohio State University Wexner Medical CenterDepartment of Radiation Oncology, James Cancer Hospital and Comprehensive Cancer Center, The Ohio State University College of MedicineDepartament of Cellular and Molecular Medicine, Florida International University Herbert Wertheim College of MedicineAbstract 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.https://doi.org/10.1186/s40478-025-01966-5GlioblastomaProgression diseasePseudo-progressionNovel enhancementEpitranscriptome |
| spellingShingle | Glaucia Maria de Mendonça Fernandes Wesley Wang Saman Seyed Ahmadian Daniel Jones Jing Peng Pierre Giglio Monica Venere José Javier Otero Epitranscriptomic analysis reveals clinical and molecular signatures in glioblastoma Acta Neuropathologica Communications Glioblastoma Progression disease Pseudo-progression Novel enhancement Epitranscriptome |
| title | Epitranscriptomic analysis reveals clinical and molecular signatures in glioblastoma |
| title_full | Epitranscriptomic analysis reveals clinical and molecular signatures in glioblastoma |
| title_fullStr | Epitranscriptomic analysis reveals clinical and molecular signatures in glioblastoma |
| title_full_unstemmed | Epitranscriptomic analysis reveals clinical and molecular signatures in glioblastoma |
| title_short | Epitranscriptomic analysis reveals clinical and molecular signatures in glioblastoma |
| title_sort | epitranscriptomic analysis reveals clinical and molecular signatures in glioblastoma |
| topic | Glioblastoma Progression disease Pseudo-progression Novel enhancement Epitranscriptome |
| url | https://doi.org/10.1186/s40478-025-01966-5 |
| work_keys_str_mv | AT glauciamariademendoncafernandes epitranscriptomicanalysisrevealsclinicalandmolecularsignaturesinglioblastoma AT wesleywang epitranscriptomicanalysisrevealsclinicalandmolecularsignaturesinglioblastoma AT samanseyedahmadian epitranscriptomicanalysisrevealsclinicalandmolecularsignaturesinglioblastoma AT danieljones epitranscriptomicanalysisrevealsclinicalandmolecularsignaturesinglioblastoma AT jingpeng epitranscriptomicanalysisrevealsclinicalandmolecularsignaturesinglioblastoma AT pierregiglio epitranscriptomicanalysisrevealsclinicalandmolecularsignaturesinglioblastoma AT monicavenere epitranscriptomicanalysisrevealsclinicalandmolecularsignaturesinglioblastoma AT josejavierotero epitranscriptomicanalysisrevealsclinicalandmolecularsignaturesinglioblastoma |