Novel patient-derived preclinical models of liver cancer.
Hepatocellular carcinoma
Humanised models
Liver cancer
Patient-derived organoids
Patient-derived xenografts
Journal
Journal of hepatology
ISSN: 1600-0641
Titre abrégé: J Hepatol
Pays: Netherlands
ID NLM: 8503886
Informations de publication
Date de publication:
02 2020
02 2020
Historique:
received:
17
07
2019
revised:
24
09
2019
accepted:
28
09
2019
entrez:
20
1
2020
pubmed:
20
1
2020
medline:
8
7
2021
Statut:
ppublish
Résumé
Preclinical models of cancer based on the use of human cancer cell lines and mouse models have enabled discoveries that have been successfully translated into patients. And yet the majority of clinical trials fail, emphasising the urgent need to improve preclinical research to better interrogate the potential efficacy of each therapy and the patient population most likely to benefit. This is particularly important for liver malignancies, which lack highly efficient treatments and account for hundreds of thousands of deaths around the globe. Given the intricate network of genetic and environmental factors that contribute to liver cancer development and progression, the identification of new druggable targets will mainly depend on establishing preclinical models that mirror the complexity of features observed in patients. The development of new 3D cell culture systems, originating from cells/tissues isolated from patients, might create new opportunities for the generation of more specific and personalised therapies. However, these systems are unable to recapitulate the tumour microenvironment and interactions with the immune system, both proven to be critical influences on therapeutic outcomes. Patient-derived xenografts, in particular with humanised mouse models, more faithfully mimic the physiology of human liver cancer but are costly and time-consuming, which can be prohibitive for personalising therapies in the setting of an aggressive malignancy. In this review, we discuss the latest advances in the development of more accurate preclinical models to better understand liver cancer biology and identify paradigm-changing therapies, stressing the importance of a bi-directional communicative flow between clinicians and researchers to establish reliable model systems and determine how best to apply them to expanding our current knowledge.
Identifiants
pubmed: 31954489
pii: S0168-8278(19)30594-X
doi: 10.1016/j.jhep.2019.09.028
pii:
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
239-249Subventions
Organisme : NCI NIH HHS
ID : R37 CA230636
Pays : United States
Organisme : NCI NIH HHS
ID : P30 CA196521
Pays : United States
Informations de copyright
Copyright © 2019 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.