Modelling Epithelial Ovarian Cancer in Mice: Classical and Emerging Approaches.
epithelial ovarian cancer
genetically engineered mouse
high-grade serous
syngeneic models
Journal
International journal of molecular sciences
ISSN: 1422-0067
Titre abrégé: Int J Mol Sci
Pays: Switzerland
ID NLM: 101092791
Informations de publication
Date de publication:
07 Jul 2020
07 Jul 2020
Historique:
received:
09
06
2020
revised:
03
07
2020
accepted:
05
07
2020
entrez:
11
7
2020
pubmed:
11
7
2020
medline:
18
2
2021
Statut:
epublish
Résumé
High-grade serous epithelial ovarian cancer (HGSC) is the most aggressive subtype of epithelial ovarian cancer. The identification of germline and somatic mutations along with genomic information unveiled by The Cancer Genome Atlas (TCGA) and other studies has laid the foundation for establishing preclinical models with high fidelity to the molecular features of HGSC. Notwithstanding such progress, the field of HGSC research still lacks a model that is both robust and widely accessible. In this review, we discuss the recent advancements and utility of HGSC genetically engineered mouse models (GEMMs) to date. Further analysis and critique on alternative approaches to modelling HGSC considers technological advancements in somatic gene editing and modelling prototypic organs, capable of tumorigenesis, on a chip.
Identifiants
pubmed: 32645943
pii: ijms21134806
doi: 10.3390/ijms21134806
pmc: PMC7370285
pii:
doi:
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : Cancer Institute NSW
ID : 2017/ECF007
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