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| 001 | 308493 | ||
| 005 | 20260119142654.0 | ||
| 024 | 7 | _ | |a 10.1016/j.ccell.2025.12.012 |2 doi |
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| 024 | 7 | _ | |a 1878-3686 |2 ISSN |
| 037 | _ | _ | |a DKFZ-2026-00133 |
| 041 | _ | _ | |a English |
| 082 | _ | _ | |a 610 |
| 100 | 1 | _ | |a Bernardi, Flavia |b 0 |
| 245 | _ | _ | |a Multiomic integration reveals tumoral heterogeneity of lipid dependence within lethal group 3 medulloblastoma. |
| 260 | _ | _ | |a Cambridge, Mass. |c 2026 |b Cell Press |
| 336 | 7 | _ | |a article |2 DRIVER |
| 336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
| 336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1768829147_2109350 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a ARTICLE |2 BibTeX |
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| 336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
| 500 | _ | _ | |a #DKTKZFB26# / #NCTZFB26# / epub |
| 520 | _ | _ | |a Medulloblastoma, the most common malignant brain tumor of childhood, exhibits significant biological complexity that demands deeper exploration. Here, we present a large multiomics dataset integrating data from 384 primary medulloblastoma patient samples across five omic layers: CpG methylome, transcriptome, proteome, phosphoproteome, and metabolome, paired with associated clinical metadata. Data integration revealed intertumoral heterogeneity of lipid metabolism across proteomic subtypes. Notably, while the MYC-FASN-SCD axis drives lipid biosynthesis, pathway inhibition elicits a compensatory escape mechanism in vivo through exogenous fatty acid uptake. Unexpectedly, we demonstrated that MYC triggers lipid storage, creating a unique dependency on lipid droplet-mitochondria communications to sustain tumor maintenance in vivo. Together, this comprehensive analysis reveals a targetable vulnerability downstream of MYC that constitutes a promising therapeutic approach to treat currently untreatable medulloblastoma subtypes. |
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| 650 | _ | 7 | |a lipid biosynthesis |2 Other |
| 650 | _ | 7 | |a lipid droplets |2 Other |
| 650 | _ | 7 | |a lipid oxidative stress |2 Other |
| 650 | _ | 7 | |a medulloblastoma |2 Other |
| 650 | _ | 7 | |a metabolomics |2 Other |
| 650 | _ | 7 | |a multiomics integration |2 Other |
| 650 | _ | 7 | |a pediatric cancer |2 Other |
| 650 | _ | 7 | |a phosphoproteomics |2 Other |
| 650 | _ | 7 | |a proteomics |2 Other |
| 650 | _ | 7 | |a transcriptomics |2 Other |
| 700 | 1 | _ | |a Torrejon, Jacob |b 1 |
| 700 | 1 | _ | |a Basili, Irene |b 2 |
| 700 | 1 | _ | |a Van Ommeren, Randy |b 3 |
| 700 | 1 | _ | |a Marsaud, Véronique |b 4 |
| 700 | 1 | _ | |a Yu, Hua |b 5 |
| 700 | 1 | _ | |a Talbot, Julie |b 6 |
| 700 | 1 | _ | |a Souphron, Judith |b 7 |
| 700 | 1 | _ | |a Indersie, Emilie |b 8 |
| 700 | 1 | _ | |a Forget, Antoine |b 9 |
| 700 | 1 | _ | |a Bonneau, Benjamin |b 10 |
| 700 | 1 | _ | |a Massiot, Alexane |b 11 |
| 700 | 1 | _ | |a Alcazar, Coralie |b 12 |
| 700 | 1 | _ | |a Figeac, Laurine |b 13 |
| 700 | 1 | _ | |a Bonerandi, Emma |b 14 |
| 700 | 1 | _ | |a Cancila, Gabriele |b 15 |
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| 700 | 1 | _ | |a Yadav, Navneesh |b 17 |
| 700 | 1 | _ | |a Mohanakrishnan, Dinesh |b 18 |
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