{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Cornelissen FMG"],"funding":["Innovation Exchange Amsterdam/Amsterdam UMC","Clinical Center","Brain Tumour Charity","NIAID NIH HHS","The Brain Tumour Charity","NIH HHS","KWF Kankerbestrijding"],"pagination":["716-740"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11887679"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["19(3)"],"pubmed_abstract":["Glioblastoma (GB), the most common and aggressive brain tumor, demonstrates intrinsic resistance to current therapies, resulting in poor clinical outcomes. Cancer progression can be partially attributed to the deregulation of protein translation mechanisms that drive cancer cell growth. In this study, we present the translatome landscape of GB as a valuable data resource. Eight patient-derived GB sphere cultures (GSCs) were analyzed using ribosome profiling and messenger RNA (mRNA) sequencing. We investigated inter-cell-line differences through differential expression analysis at both the translatome and transcriptome levels. Translational changes post-radiotherapy were assessed at 30 and 60 min. The translation of non-coding RNAs (ncRNAs) was validated using in-house and public mass spect"],"journal":["Molecular oncology"],"pubmed_title":["The translatome of glioblastoma."],"pmcid":["PMC11887679"],"funding_grant_id":["488097","GN-000429","R01 AI100880","KWF‐4874","APCA-PoC-2017","KWF-4874","KWF-11038","KWF‐11038"],"pubmed_authors":["Ciputra E","Westerman BA","Murre C","Cornelissen FMG","He Z","Piersma SR","Noske D","Beumer-Chuwonpad A","Vandertop WP","Jimenez CR","de Haas RR"],"additional_accession":[]},"is_claimable":false,"name":"The translatome of glioblastoma.","description":"Glioblastoma (GB), the most common and aggressive brain tumor, demonstrates intrinsic resistance to current therapies, resulting in poor clinical outcomes. Cancer progression can be partially attributed to the deregulation of protein translation mechanisms that drive cancer cell growth. In this study, we present the translatome landscape of GB as a valuable data resource. Eight patient-derived GB sphere cultures (GSCs) were analyzed using ribosome profiling and messenger RNA (mRNA) sequencing. We investigated inter-cell-line differences through differential expression analysis at both the translatome and transcriptome levels. Translational changes post-radiotherapy were assessed at 30 and 60 min. The translation of non-coding RNAs (ncRNAs) was validated using in-house and public mass spect","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Mar","modification":"2026-05-15T03:19:05.339Z","creation":"2025-04-04T00:26:37.571Z"},"accession":"S-EPMC11887679","cross_references":{"pubmed":["39417309"],"doi":["10.1002/1878-0261.13743"]}}