Mathematical model of a telomerase transcriptional regulatory network developed by cell-based screening: analysis of inhibitor effects and telomerase expression mechanisms

Cancer cells depend on transcription of telomerase reverse transcriptase (TERT). Many transcription factors affect TERT, though regulation occurs in context of a broader network. Network effects on telomerase regulation have not been investigated, though deeper understanding of TERT transcription requires a systems view. However, control over individual interactions in complex networks is not easily achievable. Mathematical modelling provides an attractive approach for analysis of complex systems and some models may prove useful in systems pharmacology approaches to drug discovery. In this report, we used transfection screening to test interactions among 14 TERT regulatory transcription factors and their respective promoters in ovarian cancer cells. The results were used to generate a network model of TERT transcription and to implement a dynamic Boolean model whose steady states were analysed. Modelled effects of signal transduction inhibitors successfully predicted TERT repression by Src-family inhibitor SU6656 and lack of repression by ERK inhibitor FR180204, results confirmed by RT-QPCR analysis of endogenous TERT expression in treated cells. Modelled effects of GSK3 inhibitor 6-bromoindirubin-3′-oxime (BIO) predicted unstable TERT repression dependent on noise and expression of JUN, corresponding with observations from a previous study. MYC expression is critical in TERT activation in the model, consistent with its well known function in endogenous TERT regulation. Loss of MYC caused complete TERT suppression in our model, substantially rescued only by co-suppression of AR. Interestingly expression was easily rescued under modelled Ets-factor gain of function, as occurs in TERT promoter mutation. RNAi targeting AR, JUN, MXD1, SP3, or TP53, showed that AR suppression does rescue endogenous TERT expression following MYC knockdown in these cells and SP3 or TP53 siRNA also cause partial recovery. The model therefore successfully predicted several aspects of TERT regulation including previously unknown mechanisms. An extrapolation suggests that a dominant stimulatory system may programme TERT for transcriptional stability

DBSolve Optimum: a software package for kinetic modeling which allows dynamic visualization of simulation results

<p>Abstract</p> <p>Background</p> <p>Systems biology research and applications require creation, validation, extensive usage of mathematical models and visualization of simulation results by end-users. Our goal is to develop novel method for visualization of simulation results and implement it in simulation software package equipped with the sophisticated mathematical and computational techniques for model development, verification and parameter fitting.</p> <p>Results</p> <p>We present mathematical simulation workbench DBSolve Optimum which is significantly improved and extended successor of well known simulation software DBSolve5. Concept of "dynamic visualization" of simulation results has been developed and implemented in DBSolve Optimum. In framework of the concept graphical objects representing metabolite concentrations and reactions change their volume and shape in accordance to simulation results. This technique is applied to visualize both kinetic response of the model and dependence of its steady state on parameter. The use of the dynamic visualization is illustrated with kinetic model of the Krebs cycle.</p> <p>Conclusion</p> <p>DBSolve Optimum is a user friendly simulation software package that enables to simplify the construction, verification, analysis and visualization of kinetic models. Dynamic visualization tool implemented in the software allows user to animate simulation results and, thereby, present them in more comprehensible mode. DBSolve Optimum and built-in dynamic visualization module is free for both academic and commercial use. It can be downloaded directly from <url>http://www.insysbio.ru</url>.</p

Identification of androgen-selective androgen-response elements in the human aquaporin-5 and Rad9 genes

The AR (androgen receptor) is known to influence the expression of its target genes by binding to different sets of AREs (androgen-response elements) in the DNA. One set consists of the classical steroid-response elements which are partial palindromic repeats of the 5'-TGTTCT-3' steroid-receptor monomer-binding element. The second set contains motifs that are AR-specific and that are proposed to be partial direct repeats of the same motif. On the basis of this assumption, we used an in silico approach to identify new androgen-selective AREs in the regulatory regions of known androgen-responsive genes. We have used an extension of the NUBIScan algorithm to screen a collection of 85 known human androgen-responsive genes compiled from literature and database searches. We report the evaluation of the most promising hits resulting from this computational search by in vitro DNA-binding assays using full-size ARs and GRs (glucocorticoid receptors) as well as their isolated DBDs (DNA-binding domains). We also describe the ability of some of these motifs to confer androgen-, but not glucocorticoid-, responsiveness to reporter-gene expression. The elements found in the aquaporin-5 and the Rad9 (radiation-sensitive 9) genes showed selective AR versus GR binding in band-shift assays and a strong activity and selectivity in functional assays, both as isolated elements and in their original contexts. Our data indicate the validity of the hypothesis that selective AREs are recognizable as direct 5'-TGTTCT-3' repeats, and extend the list of currently known selective elements

Wild-type but not mutant androgen receptor inhibits expression of the hTERT telomerase subunit: a novel role of AR mutation for prostate cancer development

Androgens play a central role in prostate development and prostate cancer proliferation. Induction of telomerase is an early event in prostate carcinogenesis and is considered as a marker for both primary tumors and metastases. Interestingly, several reports suggest that telomerase activity is regulated by androgens in vivo. Here, we show that the wild-type (WT) human androgen receptor (AR) inhibits the expression of the human telomerase reverse transcriptase (hTERT) and telomerase activity via inhibition of hTERT promoter activity in the presence of androgen receptor agonists. However, pure androgen antagonists failed to repress hTERT transcription. The androgen-mediated repression of hTERT is abrogated in a human prostate cancer cell line exhibiting hormone-dependent growth, which expresses a mutant AR (T877A) frequently occurring in prostate cancer. We reveal that this single amino acid exchange is sufficient for the lack of transrepression. Interestingly, chromatin immunoprecipitation data suggest that, in contrast to the WT AR, the mutant AR is recruited less efficiently to the hTERT promoter in vivo, indicating that loss of transrepression results from reduced chromatin recruitment. Thus, our findings suggest that the WT AR inhibits expression of hTERT, which is indicative of a protective mechanism, whereas the T877A mutation of AR not only broadens the ligand spectrum of the receptor but abrogates this inhibitory mechanism in prostate cancer cells. This novel role of AR mutations in prostate cancer development suggests the benefit to a search for new AR antagonists that inhibit transactivation but allow transrepression

Loss of androgen receptor binding to selective androgen response elements causes a reproductive phenotype in a knockin mouse model

Androgens influence transcription of their target genes through the activation of the androgen receptor (AR) that subsequently interacts with specific DNA motifs in these genes. These DNA motifs, called androgen response elements (AREs), can be classified in two classes: the classical AREs, which are also recognized by the other steroid hormone receptors; and the AR-selective AREs, which display selectivity for the AR. For in vitro interaction with the selective AREs, the androgen receptor DNA-binding domain is dependent on specific residues in its second zinc-finger. To evaluate the physiological relevance of these selective elements, we generated a germ-line knockin mouse model, termed SPARKI (SPecificity-affecting AR KnockIn), in which the second zinc-finger of the AR was replaced with that of the glucocorticoid receptor, resulting in a chimeric protein that retains its ability to bind classical AREs but is unable to bind selective AREs. The reproductive organs of SPARKI males are smaller compared with wild-type animals, and they are also subfertile. Intriguingly, however, they do not display any anabolic phenotype. The expression of two testis-specific, androgen-responsive genes is differentially affected by the SPARKI mutation, which is correlated with the involvement of different types of response elements in their androgen responsiveness. In this report, we present the first in vivo evidence of the existence of two functionally different types of AREs and demonstrate that AR-regulated gene expression can be targeted based on this distinction