ABSTRACT
Ovarian cancer is the most lethal cancer of the female reproductive system. In that regard, several epidemiological studies suggest that long-term exposure to estrogen could increase ovarian cancer risk, although its precise role remains controversial. To decipher a mechanism for this, we previously generated a mathematical model of how estrogen-mediated upregulation of the transcription factor, E2F6, upregulates the ovarian cancer stem/initiating cell marker, c-Kit, by epigenetic silencing the tumor suppressor miR-193a, and a competing endogenous (ceRNA) mechanism. In this study, we tested that previous mathematical model, showing that estrogen treatment of immortalized ovarian surface epithelial cells upregulated both E2F6 and c-KIT, but downregulated miR-193a. Luciferase assays further confirmed that microRNA-193a targets both E2F6 and c-Kit. Interestingly, ChIP-PCR and bisulphite pyrosequencing showed that E2F6 also epigenetically suppresses miR-193a, through recruitment of EZH2, and by a complex ceRNA mechanism in ovarian cancer cell lines. Importantly, cell line and animal experiments both confirmed that E2F6 promotes ovarian cancer stemness, whereas E2F6 or EZH2 depletion derepressed miR-193a, which opposes cancer stemness, by alleviating DNA methylation and repressive chromatin. Finally, 118 ovarian cancer patients with miR-193a promoter hypermethylation had poorer survival than those without hypermethylation. These results suggest that an estrogen-mediated E2F6 ceRNA network epigenetically and competitively inhibits microRNA-193a activity, promoting ovarian cancer stemness and tumorigenesis.
Subject(s)
E2F6 Transcription Factor/genetics , Neoplastic Stem Cells/pathology , Ovarian Neoplasms/genetics , RNA/genetics , Transcription, Genetic/genetics , Animals , Cell Line, Tumor , DNA Methylation/drug effects , DNA Methylation/genetics , Epigenesis, Genetic/drug effects , Epigenesis, Genetic/genetics , Epithelial Cells/drug effects , Epithelial Cells/pathology , Estrogens/adverse effects , Female , Genes, Tumor Suppressor/physiology , Humans , Mice , Mice, Inbred BALB C , Mice, Nude , Mice, SCID , MicroRNAs/genetics , Neoplastic Stem Cells/drug effects , Ovarian Neoplasms/etiology , Transcription, Genetic/drug effects , Up-Regulation/drug effects , Up-Regulation/geneticsABSTRACT
Accumulating data indicate that cancer stem cells contribute to tumor chemoresistance and their persistence alters clinical outcome. Our previous study has shown that ovarian cancer may be initiated by ovarian cancer initiating cells (OCIC) characterized by surface antigen CD44 and c-KIT (CD117). It has been experimentally demonstrated that a microRNA, namely miR-193a, targets c-KIT mRNA for degradation and could play a crucial role in ovarian cancer development. How miR-193a is regulated is poorly understood and the emerging picture is complex. To unravel this complexity, we propose a mathematical model to explore how estrogen-mediated up-regulation of another target of miR-193a, namely E2F6, can attenuate the function of miR-193a in two ways, one through a competition of E2F6 and c-KIT transcripts for miR-193a, and second by binding of E2F6 protein, in association with a polycomb complex, to the promoter of miR-193a to down-regulate its transcription. Our model predicts that this bimodal control increases the expression of c-KIT and that the second mode of epigenetic regulation is required to generate a switching behavior in c-KIT and E2F6 expressions. Additional analysis of the TCGA ovarian cancer dataset demonstrates that ovarian cancer patients with low expression of EZH2, a polycomb-group family protein, show positive correlation between E2F6 and c-KIT. We conjecture that a simultaneous EZH2 inhibition and anti-estrogen therapy can constitute an effective combined therapeutic strategy against ovarian cancer.
Subject(s)
Epigenesis, Genetic , MicroRNAs/genetics , Models, Genetic , Neoplastic Stem Cells/metabolism , Neoplastic Stem Cells/pathology , Ovarian Neoplasms/genetics , Ovarian Neoplasms/pathology , Base Sequence , Cell Line, Tumor , Databases, Genetic , E2F6 Transcription Factor/metabolism , Female , Gene Expression Regulation, Neoplastic , Gene Regulatory Networks , Humans , MicroRNAs/metabolism , Molecular Sequence Data , Proto-Oncogene Proteins c-kit/metabolism , Reproducibility of ResultsABSTRACT
This short article carefully formulate a simple SI model for a parasite-host interaction through the basic birth and death processes analysis. This model reveals and corrects an error in similar models studied recently by various authors. Complete mathematical investigation of this simple model shows that the host extinction dynamics can happen and the outcomes may depend on the initial conditions. We also present biological implications of our findings.
ABSTRACT
Experimental studies have shown that parasites can reduce host density and even drive host population to extinction. Conventional mathematical models for parasite-host interactions, while can address the host density reduction scenario, fail to explain such deterministic extinction phenomena. In order to understand the parasite induced host extinction, Ebert et al. (2000) formulated a plausible but ad hoc epidemiological microparasite model and its stochastic variation. The deterministic model, resembles a simple SI type model, predicts the existence of a globally attractive positive steady state. Their simulation of the stochastic model indicates that extinction of host is a likely outcome in some parameter regions. A careful examination of their ad hoc model suggests an alternative and plausible model assumption. With this modification, we show that the revised parasite-host model can exhibit the observed parasite induced host extinction. This finding strengthens and complements that of Ebert et al. (2000), since all continuous models are likely break down when all population densities are small. This extinction dynamics resembles that of ratio-dependent predator-prey models. We report here a complete global study of the revised parasite-host model. Biological implications and limitations of our findings are also presented.
Subject(s)
Ecosystem , Host-Parasite Interactions , Models, Biological , Parasites/growth & development , Animals , Conservation of Natural Resources , Parasitic Diseases, Animal , Population Dynamics , Stochastic ProcessesABSTRACT
While biological controls have been successfully and frequently implemented by nature and human, plausible mathematical models are yet to be found to explain the often observed deterministic extinctions of both pest and control agent in such processes. In this paper we study a three trophic level food chain model with ratio-dependent Michaelis-Menten type functional responses. We shall show that this model is rich in boundary dynamics and is capable of generating such extinction dynamics. Two trophic level Michaelis-Menten type ratio-dependent predator-prey system was globally and systematically analyzed in details recently. A distinct and realistic feature of ratio-dependence is its capability of producing the extinction of prey species, and hence the collapse of the system. Another distinctive feature of this model is that its dynamical outcomes may depend on initial populations levels. Theses features, if preserved in a three trophic food chain model, make it appealing for modelling certain biological control processes (where prey is a plant species, middle predator as a pest, and top predator as a biological control agent) where the simultaneous extinctions of pest and control agent is the hallmark of their successes and are usually dependent on the amount of control agent. Our results indicate that this extinction dynamics and sensitivity to initial population levels are not only preserved, but also enriched in the three trophic level food chain model. Specifically, we provide partial answers to questions such as: under what scenarios a potential biological control may be successful, and when it may fail. We also study the questions such as what conditions ensure the coexistence of all the three species in the forms of a stable steady state and limit cycle, respectively. A multiple attractor scenario is found.