Literature DB >> 28425064

A Pathway to Personalizing Therapy for Metastases Using Liver-on-a-Chip Platforms.

A S Khazali1, A M Clark1, A Wells2,3,4,5,6.   

Abstract

Metastasis accounts for most cancer-related deaths. The majority of solid cancers, including those of the breast, colorectum, prostate and skin, metastasize at significant levels to the liver due to its hemodynamic as well as tumor permissive microenvironmental properties. As this occurs prior to detection and treatment of the primary tumor, we need to target liver metastases to improve patients' outcomes. Animal models, while proven to be useful in mechanistic studies, do not represent the heterogeneity of human population especially in drug metabolism lack proper human cell-cell interactions, and this gap between animals and humans results in costly and inefficient drug discovery. This underscores the need to accurately model the human liver for disease studies and drug development. Further, the occurrence of liver metastases is influenced by the primary tumor type, sex and race; thus, modeling these specific settings will facilitate the development of personalized/targeted medicine for each specific group. We have adapted such all-human 3D ex vivo hepatic microphysiological system (MPS) (a.k.a. liver-on-a-chip) to investigate human micrometastases. This review focuses on the sources of liver resident cells, especially the iPS cell-derived hepatocytes, and examines some of the advantages and disadvantages of these sources. In addition, this review also examines other potential challenges and limitations in modeling human liver.

Entities:  

Keywords:  3D ex vivo hepatic microphysiological system (MPS); Embryonic stem cells (ES cells); Hepatocytes; Induced pluripotent stem cells (iPS cells); Liver metastasis; Liver sinusoidal endothelial cells (LSE cells); Non-parenchymal cells (NPC); Personalized/precision medicine

Mesh:

Year:  2017        PMID: 28425064      PMCID: PMC5484059          DOI: 10.1007/s12015-017-9735-3

Source DB:  PubMed          Journal:  Stem Cell Rev Rep        ISSN: 2629-3277            Impact factor:   5.739


  157 in total

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2.  Special Issue: Organs-on-Chips & 3D-Bioprinting Technologies for Personalized Medicine.

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