Novel patient-derived preclinical models of liver cancer

Erin Bresnahan, Pierluigi Ramadori, Mathias Heikenwalder, Lars Zender, Amaia Lujambio

Research output: Contribution to journalReview articlepeer-review

46 Scopus citations

Abstract

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.

Original languageEnglish
Pages (from-to)239-249
Number of pages11
JournalJournal of Hepatology
Volume72
Issue number2
DOIs
StatePublished - Feb 2020

Keywords

  • Hepatocellular carcinoma
  • Humanised models
  • Liver cancer
  • Patient-derived organoids
  • Patient-derived xenografts

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