Optimizing preclinical pediatric low-grade glioma models for meaningful clinical translation
Pediatric low-grade gliomas (pLGGs) are the most common brain tumor in young children. While they are typically associated with good overall survival, children with these central nervous system tumors often experience chronic tumor- and therapy-related morbidities. Moreover, individuals with unresec...
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| Main Authors: | , , , , , , , , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
November 2023
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| In: |
Neuro-Oncology
Year: 2023, Volume: 25, Issue: 11, Pages: 1920-1931 |
| ISSN: | 1523-5866 |
| DOI: | 10.1093/neuonc/noad125 |
| Online Access: | Verlag, kostenfrei, Volltext: https://doi.org/10.1093/neuonc/noad125
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| Author Notes: | Till Milde, Jason Fangusaro, Michael J Fisher, Cynthia Hawkins, Fausto J Rodriguez, Uri Tabori, Olaf Witt, Yuan Zhu, and David H Gutmann |
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| 520 | |a Pediatric low-grade gliomas (pLGGs) are the most common brain tumor in young children. While they are typically associated with good overall survival, children with these central nervous system tumors often experience chronic tumor- and therapy-related morbidities. Moreover, individuals with unresectable tumors frequently have multiple recurrences and persistent neurological symptoms. Deep molecular analyses of pLGGs reveal that they are caused by genetic alterations that converge on a single mitogenic pathway (MEK/ERK), but their growth is heavily influenced by nonneoplastic cells (neurons, T cells, microglia) in their local microenvironment. The interplay between neoplastic cell MEK/ERK pathway activation and stromal cell support necessitates the use of predictive preclinical models to identify the most promising drug candidates for clinical evaluation. As part of a series of white papers focused on pLGGs, we discuss the current status of preclinical pLGG modeling, with the goal of improving clinical translation for children with these common brain tumors. | ||
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