Background:C-Fos was initially described as oncogene, but was associated with favourable prognosis in ovarian cancer (OvCa) patients. The molecular and functional aspects underlying this effect are still unknown.Methods:Using stable transfectants of SKOV3 and OVCAR8 cells, proliferation, migration, invasion and apoptotic potential of c-FOS-overexpressing clones and controls were compared. Adherence to components of the extracellular matrix was analysed in static assays, and adhesion to E-selectin, endothelial and mesothelial cells in dynamic flow assays. The effect of c-FOS in vivo was studied after intraperitoneal injection of SKOV3 clones into SCID mice, and changes in gene expression were determined by microarray analysis.Results:Tumour growth after injection into SCID mice was strongly delayed by c-FOS overexpression, with reduction of lung metastases and circulating tumour cells. In vitro, c-FOS had only weak influence on proliferation and migration, but was strongly pro-apoptotic. Adhesion to components of the extracellular matrix (collagen I, IV) and to E-selectin, endothelial and mesothelial cells was significantly reduced in c-FOS-overexpressing OvCa cells. This corresponds to deregulation of adhesion proteins and glycosylation enzymes in microarray analysis.Conclusion:In addition to its known pro-apoptotic effect, c-FOS might influence OvCa progression by changing the adhesion of OvCa cells to peritoneal surfaces.
A novel computer model based on a discrete event simulation procedure describes quantitatively the processes underlying the metastatic cascade. Analytical functions describe the size of the primary tumor and the metastases, while a rate function models the intravasation events of the primary tumor and metastases. Events describe the behavior of the malignant cells until the formation of new metastases. The results of the computer simulations are in quantitative agreement with clinical data determined from a patient with hepatocellular carcinoma in the liver. The model provides a more detailed view on the process than a conventional mathematical model. In particular, the implications of interventions on metastasis formation can be calculated.
A simple and fast computational model to describe the dynamics of tumour growth and metastasis formation is presented. The model is based on the calculation of successive generations of tumour cells and enables one to describe biologically important entities like tumour volume, time point of 1st metastatic growth or number of metastatic colonies at a given time. The model entirely relies on the chronology of these successive events of the metastatic cascade. The simulation calculations were performed for two embedded growth models to describe the Gompertzian like growth behaviour of tumours. The initial training of the models was carried out using an analytical solution for the size distribution of metastases of a hepatocellular carcinoma. We then show the applicability of our models to clinical data from the Munich Cancer Registry. Growth and dissemination characteristics of metastatic cells originating from cells in the primary breast cancer can be modelled thus showing its ability to perform systematic analyses relevant for clinical breast cancer research and treatment. In particular, our calculations show that generally metastases formation has already been initiated before the primary can be detected clinically.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.