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| 001 | 298907 | ||
| 005 | 20250407104341.0 | ||
| 024 | 7 | _ | |a 10.1016/j.stem.2025.01.002 |2 doi |
| 024 | 7 | _ | |a pmid:39938519 |2 pmid |
| 024 | 7 | _ | |a 1934-5909 |2 ISSN |
| 024 | 7 | _ | |a 1875-9777 |2 ISSN |
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| 037 | _ | _ | |a DKFZ-2025-00346 |
| 041 | _ | _ | |a English |
| 082 | _ | _ | |a 570 |
| 100 | 1 | _ | |a Peng, Tianping |b 0 |
| 245 | _ | _ | |a Individualized patient tumor organoids faithfully preserve human brain tumor ecosystems and predict patient response to therapy. |
| 260 | _ | _ | |a Amsterdam [u.a.] |c 2025 |b Elsevier |
| 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 1744015377_31488 |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 |
| 500 | _ | _ | |a DKFZ-ZMBH Alliance / #EA:A240# / HI-TRON / 2025 Apr 3;32(4):652-669.e11 |
| 520 | _ | _ | |a Tumor organoids are important tools for cancer research, but current models have drawbacks that limit their applications for predicting response to therapy. Here, we developed a fast, efficient, and complex culture system (IPTO, individualized patient tumor organoid) that accurately recapitulates the cellular and molecular pathology of human brain tumors. Patient-derived tumor explants were cultured in induced pluripotent stem cell (iPSC)-derived cerebral organoids, thus enabling culture of a wide range of human tumors in the central nervous system (CNS), including adult, pediatric, and metastatic brain cancers. Histopathological, genomic, epigenomic, and single-cell RNA sequencing (scRNA-seq) analyses demonstrated that the IPTO model recapitulates cellular heterogeneity and molecular features of original tumors. Crucially, we showed that the IPTO model predicts patient-specific drug responses, including resistance mechanisms, in a prospective patient cohort. Collectively, the IPTO model represents a major breakthrough in preclinical modeling of human cancers, which provides a path toward personalized cancer therapy. |
| 536 | _ | _ | |a 311 - Zellbiologie und Tumorbiologie (POF4-311) |0 G:(DE-HGF)POF4-311 |c POF4-311 |f POF IV |x 0 |
| 588 | _ | _ | |a Dataset connected to CrossRef, PubMed, , Journals: inrepo02.dkfz.de |
| 650 | _ | 7 | |a brain metastasis |2 Other |
| 650 | _ | 7 | |a glioblastoma |2 Other |
| 650 | _ | 7 | |a patient tumor organoid |2 Other |
| 650 | _ | 7 | |a predictive patient model |2 Other |
| 650 | _ | 7 | |a temozolomide |2 Other |
| 650 | _ | 7 | |a tumor heterogeneity |2 Other |
| 700 | 1 | _ | |a Ma, Xiujian |0 P:(DE-He78)88de8ba75b18dd92d742eb7eab04a1b3 |b 1 |e First author |
| 700 | 1 | _ | |a Hua, Wei |b 2 |
| 700 | 1 | _ | |a Wang, Changwen |0 P:(DE-He78)be724b82903aa397737196d8200edb30 |b 3 |
| 700 | 1 | _ | |a Chu, Youjun |b 4 |
| 700 | 1 | _ | |a Sun, Meng |b 5 |
| 700 | 1 | _ | |a Fermi, Valentina |b 6 |
| 700 | 1 | _ | |a Hamelmann, Stefan |0 P:(DE-He78)875b52cddc351d6eca86de4f404f4631 |b 7 |
| 700 | 1 | _ | |a Lindner, Katharina |0 P:(DE-He78)9c599f876c762bc78d289674c15ba4a5 |b 8 |
| 700 | 1 | _ | |a Shao, Chunxuan |0 P:(DE-He78)7e77b1ec44a0797f186de678c66f80a0 |b 9 |
| 700 | 1 | _ | |a Zaman, Julia |0 P:(DE-He78)786f582fd4178a697bb48213edd8aad4 |b 10 |
| 700 | 1 | _ | |a Tian, Weili |0 P:(DE-He78)013c1f7493419ce6a1a10fd28abb172b |b 11 |
| 700 | 1 | _ | |a Zhuo, Yue |0 P:(DE-He78)24e61e2f659895c9e6d595647a29bf36 |b 12 |
| 700 | 1 | _ | |a Harim, Yassin |0 P:(DE-He78)044b8e7cc52bce80fe9afd70f8f4d44e |b 13 |
| 700 | 1 | _ | |a Stöffler, Nadja |0 P:(DE-He78)79d514e9270d1a0c8b17992db50542f1 |b 14 |
| 700 | 1 | _ | |a Hammann, Linda |0 P:(DE-He78)6268906e54e5ca1f69e966a42d92bff7 |b 15 |
| 700 | 1 | _ | |a Xiao, Qungen |0 P:(DE-He78)4ddaf0b8a060cc0da9341ecef9ce161e |b 16 |
| 700 | 1 | _ | |a Jin, Xiaoliang |0 P:(DE-He78)ec03875913cf6c00f279fe768d4d7b5d |b 17 |
| 700 | 1 | _ | |a Warta, Rolf |b 18 |
| 700 | 1 | _ | |a Lotsch, Catharina |b 19 |
| 700 | 1 | _ | |a Zhuang, Xuran |b 20 |
| 700 | 1 | _ | |a Feng, Yuan |b 21 |
| 700 | 1 | _ | |a Fu, Minjie |b 22 |
| 700 | 1 | _ | |a Zhang, Xin |b 23 |
| 700 | 1 | _ | |a Zhang, Jinsen |b 24 |
| 700 | 1 | _ | |a Xu, Hao |b 25 |
| 700 | 1 | _ | |a Qiu, Fufang |b 26 |
| 700 | 1 | _ | |a Xie, Liqian |b 27 |
| 700 | 1 | _ | |a Zhang, Yi |b 28 |
| 700 | 1 | _ | |a Zhu, Wei |b 29 |
| 700 | 1 | _ | |a Du, Zunguo |b 30 |
| 700 | 1 | _ | |a Salgueiro, Lorena |0 P:(DE-HGF)0 |b 31 |
| 700 | 1 | _ | |a Schneider, Mark |b 32 |
| 700 | 1 | _ | |a Eichhorn, Florian |b 33 |
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| 700 | 1 | _ | |a Grinevich, Valery |b 36 |
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| 700 | 1 | _ | |a Xiang, Yangfei |b 41 |
| 700 | 1 | _ | |a Unterberg, Andreas |b 42 |
| 700 | 1 | _ | |a von Deimling, Andreas |0 P:(DE-He78)a8a10626a848d31e70cfd96a133cc144 |b 43 |
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| 700 | 1 | _ | |a Herold-Mende, Christel |b 45 |
| 700 | 1 | _ | |a Wu, Yonghe |b 46 |
| 700 | 1 | _ | |a Liu, Haikun |0 P:(DE-He78)76aeb2431f7458c9261e69c5420390c6 |b 47 |
| 700 | 1 | _ | |a Mao, Ying |b 48 |
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