Models of fibrolamellar carcinomas, tools for evaluation of a new era of treatments - Song, Jinjia; Lu, Mengqi; He, Zhiying; Zhang, Wencheng (Frontiers in Immunology, 2024)
Fibrolamellar carcinoma (FLC) is a rare but fatal cancer that occurs primarily in young people. There are currently no known effective treatments, although several promising treatments appear to be in development. Genetic studies have confirmed that almost all FLC tumors have a fusion protein marker (DNAJB1-PRKACA) encoded by a fusion gene (DNAJB1-PRKACA); It is currently accepted as a diagnostic criterion for FLCs. Several research teams have established patient-derived xenograft (PDX) FLC models using immunocompromised animals as hosts and patient tissue samples (tumors or ascites) as primary sources for PDX-derived organoids. These FLC organoids are composed of FLC epithelia, endothelial progenitor cells, and stellate cells. CRISPR/Cas9 was used as a gene editing technique to modify mature hepatocytes to obtain ex vivo FLC-like cells expressing the fusion gene and/or other mutated genes associated with FLCs. Although these models simulate some but not all FLC features. Drug screening using these models has not proven effective in identifying clinically useful treatments. Genetic studies comparing FLCs to normal maturing endodermal cell lineages have shown that FLCs share genetic signatures not with hepatocytes, but with subpopulations of biliary tree stem cells (BTSCs), hepato/pancreatic stem/progenitor cells that consistently reside in peribiliary glands (PBGs) located in the biliary tree and are sources of stem cells for the formation and postnatal regeneration of the liver and pancreas. Therefore, it is expected that models of BTSCs, instead of hepatocytes may prove more useful. In this review, we summarize the status of the various FLC models and their features, applications, and limitations. They provide opportunities to understand the cause and characteristics of this deadly disease and are models from which effective treatments can be identified.