guest ::
| Home > External Publications > Vita Publications > PCLN-05. A BIOBANK OF PATIENT-DERIVED MOLECULARLY CHARACTERIZED ORTHOTOPIC PEDIATRIC BRAIN TUMOR MODELS FOR PRECLINICAL RESEARCH > print |
| Home > External Publications > Vita Publications > PCLN-05. A BIOBANK OF PATIENT-DERIVED MOLECULARLY CHARACTERIZED ORTHOTOPIC PEDIATRIC BRAIN TUMOR MODELS FOR PRECLINICAL RESEARCH > print |
| 001 | 294422 | ||
| 005 | 20241107160244.0 | ||
| 024 | 7 | _ | |a 10.1093/neuonc/noy059.574 |2 doi |
| 024 | 7 | _ | |a 1522-8517 |2 ISSN |
| 024 | 7 | _ | |a 1523-5866 |2 ISSN |
| 037 | _ | _ | |a DKFZ-2024-02251 |
| 041 | _ | _ | |a English |
| 082 | _ | _ | |a 610 |
| 100 | 1 | _ | |a Brabetz, Sebastian |b 0 |
| 245 | _ | _ | |a PCLN-05. A BIOBANK OF PATIENT-DERIVED MOLECULARLY CHARACTERIZED ORTHOTOPIC PEDIATRIC BRAIN TUMOR MODELS FOR PRECLINICAL RESEARCH |
| 260 | _ | _ | |a Oxford |c 2018 |b Oxford Univ. 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 1730991698_24841 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a ARTICLE |2 BibTeX |
| 336 | 7 | _ | |a JOURNAL_ARTICLE |2 ORCID |
| 336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
| 520 | _ | _ | |a Identification of multiple distinct subtypes of pediatric brain tumors raises the need for more and better preclinical models reflecting these subtypes. Orthotopic patient-derived xenograft (PDX) models generated by injection of human tumor cells into the brain of NSG mice offer the unique possibility to test novel substances in primary patient tissue in an in vivo environment. Extensive molecular characterization of PDX and matching primary tumor/blood are needed to see how well the PDX represents the original disease, to learn about targetable oncogenic drivers in each model, and to establish or confirm predictive biomarkers. In an ongoing world-wide effort we have generated and fully characterized thus far 130 PDX models reflecting 22 distinct molecular subtypes of pediatric brain tumors. PDX models always retain their molecular subtype as assessed by DNA methylation analysis and in the vast majority of cases also the mutations and copy number alterations when compared to their primary tumors. Most aggressive tumors, such as those having MYC(N) amplifications, are overrepresented in the cohort, but also subtypes which have not been available for preclinical testing before due to lack of genetically engineered mouse models or suitable cell lines are included. All models and corresponding molecular data will become available for the community for preclinical research. Our repertoire of PDX models and corresponding molecular characterizations allow researchers to find the right models for their specific scientific questions. It provides an unprecedented resource to study tumor biology and paves the way for improving treatment strategies for children with malignant brain tumors. |
| 588 | _ | _ | |a Dataset connected to CrossRef, Journals: inrepo02.dkfz.de |
| 700 | 1 | _ | |a Groebner, Susanne N |b 1 |
| 700 | 1 | _ | |a Jaeger, Natalie |b 2 |
| 700 | 1 | _ | |a Milde, Till |b 3 |
| 700 | 1 | _ | |a Ecker, Jonas |b 4 |
| 700 | 1 | _ | |a Selt, Florian |b 5 |
| 700 | 1 | _ | |a Witt, Olaf |b 6 |
| 700 | 1 | _ | |a Rusert, Jessica M |b 7 |
| 700 | 1 | _ | |a Koster, Jan |b 8 |
| 700 | 1 | _ | |a Leary, Sarah E |b 9 |
| 700 | 1 | _ | |a Li, Xiao-Nan |b 10 |
| 700 | 1 | _ | |a Wechsler-Reya, Robert J |b 11 |
| 700 | 1 | _ | |a Olson, James M |b 12 |
| 700 | 1 | _ | |a Pfister, Stefan M |b 13 |
| 700 | 1 | _ | |a Kool, Marcel |b 14 |
| 773 | _ | _ | |a 10.1093/neuonc/noy059.574 |g Vol. 20, no. suppl_2, p. i155 - i155 |0 PERI:(DE-600)2094060-9 |n suppl_2 |p i155 - i155 |t Neuro-Oncology |v 20 |y 2018 |x 1522-8517 |
| 915 | _ | _ | |a Nationallizenz |0 StatID:(DE-HGF)0420 |2 StatID |d 2023-10-24 |w ger |
| 915 | _ | _ | |a JCR |0 StatID:(DE-HGF)0100 |2 StatID |b NEURO-ONCOLOGY : 2022 |d 2023-10-24 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0200 |2 StatID |b SCOPUS |d 2023-10-24 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0300 |2 StatID |b Medline |d 2023-10-24 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0320 |2 StatID |b PubMed Central |d 2023-10-24 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0199 |2 StatID |b Clarivate Analytics Master Journal List |d 2023-10-24 |
| 915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0113 |2 StatID |b Science Citation Index Expanded |d 2023-10-24 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0150 |2 StatID |b Web of Science Core Collection |d 2023-10-24 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0160 |2 StatID |b Essential Science Indicators |d 2023-10-24 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1110 |2 StatID |b Current Contents - Clinical Medicine |d 2023-10-24 |
| 915 | _ | _ | |a IF >= 15 |0 StatID:(DE-HGF)9915 |2 StatID |b NEURO-ONCOLOGY : 2022 |d 2023-10-24 |
| 980 | 1 | _ | |a EXTERN4VITA |
| 980 | _ | _ | |a journal |
| 980 | _ | _ | |a EDITORS |
| 980 | _ | _ | |a I:(DE-He78)W510-20160331 |
| 980 | _ | _ | |a I:(DE-He78)W500-20160331 |
| Library | Collection | CLSMajor | CLSMinor | Language | Author |
|---|