Dataset Information

Generation of combined hepatocellular-cholangiocarcinoma through transdifferentiation and dedifferentiation in p53-knockout mice.

ABSTRACT: The two principal histological types of primary liver cancers, hepatocellular carcinoma (HCC) and cholangiocarcinoma, can coexist within a tumor, comprising combined hepatocellular-cholangiocarcinoma (cHCC-CCA). Although the possible involvement of liver stem/progenitor cells has been proposed for the pathogenesis of cHCC-CCA, the cells might originate from transformed hepatocytes that undergo ductular transdifferentiation or dedifferentiation. We previously demonstrated that concomitant introduction of mutant HRAS^V12 (HRAS) and Myc into mouse hepatocytes induced dedifferentiated tumors that expressed fetal/neonatal liver genes and proteins. Here, we examine whether the phenotype of HRAS- or HRAS/Myc-induced tumors might be affected by the disruption of the Trp53 gene, which has been shown to induce biliary differentiation in mouse liver tumors. Hepatocyte-derived liver tumors were induced in heterozygous and homozygous p53-knockout (KO) mice by hydrodynamic tail vein injection of HRAS- or Myc-containing transposon cassette plasmids, which were modified by deleting loxP sites, with a transposase-expressing plasmid. The HRAS-induced and HRAS/Myc-induced tumors in the wild-type mice demonstrated histological features of HCC, whereas the phenotype of the tumors generated in the p53-KO mice was consistent with cHCC-CCA. The expression of fetal/neonatal liver proteins, including delta-like 1, was detected in the HRAS/Myc-induced but not in the HRAS-induced cHCC-CCA tissues. The dedifferentiation in the HRAS/Myc-induced tumors was more marked in the homozygous p53-KO mice than in the heterozygous p53-KO mice and was associated with activation of Myc and YAP and suppression of ERK phosphorylation. Our results suggest that the loss of p53 promotes ductular differentiation of hepatocyte-derived tumor cells through either transdifferentiation or Myc-mediated dedifferentiation.

SUBMITTER: Liu Y

PROVIDER: S-EPMC8353893 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:We explored the underlying mechanisms of differentiation, dedifferentiation, reprogramming and transdifferentiation (cell type switchings) from landscape and flux perspectives. Lineage reprogramming is a new regenerative method to convert a matured cell into another cell including direct transdifferentiation without undergoing a pluripotent cell state and indirect transdifferentiation with an initial dedifferentiation-reversion (reprogramming) to a pluripotent cell state. Each cell type is quantified by a distinct valley on the potential landscape with higher probability. We investigated three driving forces for cell fate decision making: stochastic fluctuations, gene regulation and induction, which can lead to cell type switchings. We showed that under the driving forces the direct transdifferentiation process proceeds from a differentiated cell valley to another differentiated cell valley through either a distinct stable intermediate state or a certain series of unstable indeterminate states. The dedifferentiation process proceeds through a pluripotent cell state. Barrier height and the corresponding escape time from the valley on the landscape can be used to quantify the stability and efficiency of cell type switchings. We also uncovered the mechanisms of the underlying processes by quantifying the dominant biological paths of cell type switchings on the potential landscape. The dynamics of cell type switchings are determined by both landscape gradient and flux. The flux can lead to the deviations of the dominant biological paths for cell type switchings from the naively expected landscape gradient path. As a result, the corresponding dominant paths of cell type switchings are irreversible. We also classified the mechanisms of cell fate development from our landscape theory: super-critical pitchfork bifurcation, sub-critical pitchfork bifurcation, sub-critical pitchfork with two saddle-node bifurcation, and saddle-node bifurcation. Our model showed good agreements with the experiments. It provides a general framework to explore the mechanisms of differentiation, dedifferentiation, reprogramming and transdifferentiation.

Project description:ObjectivesTo establish a nomogram based on preoperative laboratory study variables using least absolute shrinkage and selection operator (LASSO) regression for differentiating combined hepatocellular cholangiocarcinoma (cHCC) from intrahepatic cholangiocarcinoma (iCCA).MethodsWe performed a retrospective analysis of iCCA and cHCC patients who underwent liver resection. Blood signatures were established using LASSO regression, and then, the clinical risk factors based on the multivariate logistic regression and blood signatures were combined to establish a nomogram for a differential preoperative diagnosis between iCCA and cHCC. The differential accuracy ability of the nomogram was determined by Harrell's index (C-index) and decision curve analysis, and the results were validated using a validation set. Furthermore, patients were categorized into two groups according to the optimal cut-off values of the nomogram-based scores, and their survival differences were assessed using Kaplan-Meier curves.ResultsA total of 587 patients who underwent curative liver resection for iCCA or cHCC between January 2008 and December 2017 at West China Hospital were enrolled in this study. The cHCC score was based on the personalized levels of the seven laboratory study variables. On multivariate logistic analysis, the independent factors for distinguishing cHCC were age, sex, biliary duct stones, and portal hypertension, all of which were incorporated into the nomogram combined with the cHCC-score. The nomogram had a good discriminating capability, with a C-index of 0.796 (95% CI, 0.752-0.840). The calibration plot for distinguishing cHCC from iCCA showed optimal agreement between the nomogram prediction and actual observation in the training and validation sets. The decision curves indicated significant clinical usefulness.ConclusionThe nomogram showed good accuracy for the differential diagnosis between iCCA and cHCC preoperatively, and therapeutic decisions would improve if it was applied in clinical practice.

Dataset Information

Generation of combined hepatocellular-cholangiocarcinoma through transdifferentiation and dedifferentiation in p53-knockout mice.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets