Precision neuro-oncology for children: Time to gear up!
Abstract
Molecular profiling is central to pediatric precision oncology, yet only 15-20% of patients benefit from biology-guided treatments. This limitation underscores the urgent need for functional precision medicine, which interrogates therapeutic vulnerabilities using patient-derived models. Despite hurdles in establishing these models, such as limited biopsy material and technical screening barriers, recent advances in tumoroids, patient-derived xenografts and high-throughput platforms offer an unprecedented opportunity to bridge the translational gap. In this review, we describe the evolution of patient-derived models of ped iatric brain cancers, their current strengths and weaknesses and the technological innovations redefining the field. Together, these insights provide a road map for integrating functional data into clinical decision-making, ultimately aiming to 'cure more and heal better' children with brain tumors.
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BibTeX
@article{lafont2026precision,
title = {{Precision neuro-oncology for children: Time to gear up!}},
author = {Julie Lafont and Mathilde Kerhervé and Nicolas André and Marion Le Grand and Eddy Pasquier},
journal = {Trends in Cancer},
year = {2026},
month = nov,
doi = {10.1016/j.trecan.2026.06.001},
url = {https://hal.science/hal-05850736v1},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - JOUR
TI - Precision neuro-oncology for children: Time to gear up!
AU - Julie Lafont
AU - Mathilde Kerhervé
AU - Nicolas André
AU - Marion Le Grand
AU - Eddy Pasquier
PY - 2026
DA - 2026/11/03
JO - Trends in Cancer
DO - 10.1016/j.trecan.2026.06.001
UR - https://hal.science/hal-05850736v1
AB - Molecular profiling is central to pediatric precision oncology, yet only 15-20% of patients benefit from biology-guided treatments. This limitation underscores the urgent need for functional precision medicine, which interrogates therapeutic vulnerabilities using patient-derived models. Despite hurdles in establishing these models, such as limited biopsy material and technical screening barriers, recent advances in tumoroids, patient-derived xenografts and high-throughput platforms offer an unprecedented opportunity to bridge the translational gap. In this review, we describe the evolution of patient-derived models of ped iatric brain cancers, their current strengths and weaknesses and the technological innovations redefining the field. Together, these insights provide a road map for integrating functional data into clinical decision-making, ultimately aiming to 'cure more and heal better' children with brain tumors.
SN - 2405-8033
ER -