Patient-derived models : Advanced tools for precision medicine in neuroblastoma
Aaltonen, Kristina LU ; Radke, Katarzyna LU ; Adamska, Aleksandra LU ; Seger, Alexandra LU
; Mañas, Adriana
LU
and Bexell, Daniel
LU
(2023)
In Frontiers in Oncology
12.
- Abstract
Neuroblastoma is a childhood cancer derived from the sympathetic nervous system. High-risk neuroblastoma patients have a poor overall survival and account for ~15% of childhood cancer deaths. There is thus a need for clinically relevant and authentic models of neuroblastoma that closely resemble the human disease to further interrogate underlying mechanisms and to develop novel therapeutic strategies. Here we review recent developments in patient-derived neuroblastoma xenograft models and in vitro cultures. These models can be used to decipher mechanisms of metastasis and treatment resistance, for drug screening, and preclinical drug testing. Patient-derived neuroblastoma models may also provide useful information about clonal... (More)
Neuroblastoma is a childhood cancer derived from the sympathetic nervous system. High-risk neuroblastoma patients have a poor overall survival and account for ~15% of childhood cancer deaths. There is thus a need for clinically relevant and authentic models of neuroblastoma that closely resemble the human disease to further interrogate underlying mechanisms and to develop novel therapeutic strategies. Here we review recent developments in patient-derived neuroblastoma xenograft models and in vitro cultures. These models can be used to decipher mechanisms of metastasis and treatment resistance, for drug screening, and preclinical drug testing. Patient-derived neuroblastoma models may also provide useful information about clonal evolution, phenotypic plasticity, and cell states in relation to neuroblastoma progression. We summarize current opportunities for, but also barriers to, future model development and application. Integration of patient-derived models with patient data holds promise for the development of precision medicine treatment strategies for children with high-risk neuroblastoma.
(Less)
- author
- Aaltonen, Kristina
LU
; Radke, Katarzyna
LU
; Adamska, Aleksandra
LU
; Seger, Alexandra
LU
; Mañas, Adriana
LU
and Bexell, Daniel
LU
- organization
- publishing date
- 2023-01-19
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- drug screening, neuroblastoma, patient-derived models, patient-derived xenograft, pediatric cancer, precision medicine, tumor organoids
- in
- Frontiers in Oncology
- volume
- 12
- article number
- 1085270
- publisher
- Frontiers Media S. A.
- external identifiers
-
- scopus:85147772149
- pmid:36776363
- ISSN
- 2234-943X
- DOI
- 10.3389/fonc.2022.1085270
- language
- English
- LU publication?
- yes
- id
- 0592b23e-00b5-4f6e-93aa-5f470a80a8d8
- date added to LUP
- 2023-02-23 14:36:11
- date last changed
- 2024-09-21 08:41:52
@article{0592b23e-00b5-4f6e-93aa-5f470a80a8d8,
abstract = {{<p>Neuroblastoma is a childhood cancer derived from the sympathetic nervous system. High-risk neuroblastoma patients have a poor overall survival and account for ~15% of childhood cancer deaths. There is thus a need for clinically relevant and authentic models of neuroblastoma that closely resemble the human disease to further interrogate underlying mechanisms and to develop novel therapeutic strategies. Here we review recent developments in patient-derived neuroblastoma xenograft models and in vitro cultures. These models can be used to decipher mechanisms of metastasis and treatment resistance, for drug screening, and preclinical drug testing. Patient-derived neuroblastoma models may also provide useful information about clonal evolution, phenotypic plasticity, and cell states in relation to neuroblastoma progression. We summarize current opportunities for, but also barriers to, future model development and application. Integration of patient-derived models with patient data holds promise for the development of precision medicine treatment strategies for children with high-risk neuroblastoma.</p>}},
author = {{Aaltonen, Kristina and Radke, Katarzyna and Adamska, Aleksandra and Seger, Alexandra and Mañas, Adriana and Bexell, Daniel}},
issn = {{2234-943X}},
keywords = {{drug screening; neuroblastoma; patient-derived models; patient-derived xenograft; pediatric cancer; precision medicine; tumor organoids}},
language = {{eng}},
month = {{01}},
publisher = {{Frontiers Media S. A.}},
series = {{Frontiers in Oncology}},
title = {{Patient-derived models : Advanced tools for precision medicine in neuroblastoma}},
url = {{http://dx.doi.org/10.3389/fonc.2022.1085270}},
doi = {{10.3389/fonc.2022.1085270}},
volume = {{12}},
year = {{2023}},
}