An aqueous extract of Fagonia cretica induces DNA damage, cell cycle arrest and apoptosis in breast cancer cells via FOXO3a and p53 expression

Background - Plants have proved to be an important source of anti-cancer drugs. Here we have investigated the cytotoxic action of an aqueous extract of Fagonia cretica, used widely as a herbal tea-based treatment for breast cancer. Methodology/Principal Findings - Using flow cytometric analysis of cells labeled with cyclin A, annexin V and propidium iodide, we describe a time and dose-dependent arrest of the cell cycle in G0/G1 phase of the cell cycle and apoptosis following extract treatment in MCF-7 (WT-p53) and MDA-MB-231 (mutant-p53) human breast cancer cell lines with a markedly reduced effect on primary human mammary epithelial cells. Analysis of p53 protein expression and of its downstream transcription targets, p21 and BAX, revealed a p53 associated growth arrest within 5 hours of extract treatment and apoptosis within 24 hours. DNA double strand breaks measured as ?-H2AX were detected early in both MCF-7 and MDA-MB-231 cells. However, loss of cell viability was only partly due to a p53-driven response; as MDA-MB-231 and p53-knockdown MCF-7 cells both underwent cell cycle arrest and death following extract treatment. p53-independent growth arrest and cytotoxicity following DNA damage has been previously ascribed to FOXO3a expression. Here, in MCF-7 and MDA-MB-231 cells, FOXO3a expression was increased significantly within 3 hours of extract treatment and FOXO3 siRNA reduced the extract-induced loss of cell viability in both cell lines. Conclusions/Significance - Our results demonstrate for the first time that an aqueous extract of Fagonia cretica can induce cell cycle arrest and apoptosis via p53-dependent and independent mechanisms, with activation of the DNA damage response. We also show that FOXO3a is required for activity in the absence of p53. Our findings indicate that Fagonia cretica aqueous extract contains potential anti-cancer agents acting either singly or in combination against breast cancer cell proliferation via DNA damage-induced FOXO3a and p53 expression.

Thioredoxin and Jab1 control estrogen- and antiestrogen-mediated progression of the cell cycle through p27 interactions

A major problem with breast cancer treatment is the prevalence of antiestrogen resistance, be it de novo or acquired after continued use. Many of the underlying mechanisms of antiestrogen resistance are not clear, although estrogen receptor-mediated actions have been identified as a pathway that is blocked by antiestrogens. Selective estrogen receptor modulators (SERMs), such as tamoxifen, are capable of producing reactive oxygen species (ROS) through metabolic activation, and these ROS, at high levels, can induce irreversible growth arrest that is similar to the growth arrest incurred by SERMs. This suggests that SERM-mediated growth arrest may also be through ROS accumulation. Breast cancer receiving long-term antiestrogen treatment appears to adapt to this increased, persistent level of ROS. This, in turn, leads to the disruption of reversible redox signaling that involves redox-sensitive phosphatases and protein kinases and transcription factors. This has downstream consequences for apoptosis, cell cycle progression, and cell metabolism. For this dissertation, we explored if altering the ROS formed by tamoxifen also alters sensitivity of the drug in resistant cells. We explored an association with a thioredoxin/Jab1/p27 pathway, and a possible role of dysregulation of thioredoxin-mediated redox regulation contributing to the development of antiestrogen resistance in breast cancer. We used standard laboratory techniques to perform proteomic assays that showed cell proliferation, protein concentrations, redox states, and protein-protein interactions. We found that increasing thioredoxin reductase levels, and thus increasing the amount of reduced thioredoxin, increased tamoxifen sensitivity in previously resistant cells, as well as altered estrogen and tamoxifen-induced ROS. We also found that decreasing levels of Jab1 protein also increased tamoxifen sensitivity, and that the downstream effects showed a decrease p27 phosphorylation in both cases. We conclude that the chronic use of tamoxifen can lead to an increase in ROS that alters cell signaling and causing cell growth in the presence of tamoxifen, and that this resistant cell growth can be reversed with an alteration to the thioredoxin/Jab1 pathway.

The ciliary GTPase Arl13b regulates cell migration and cell cycle progression

Funding This work was supported by grants from British Council China (Sino-UK higher Education for PhD studies) to YD and CM, The Carnegie Trust for the Universities of Scotland (70190) and The NHS Grampian Endowment Funds (14/09) to BL, and National Natural Science Foundation of China (31528011) to BL and YD.

Commiphora gileadensis sap extract induces cell cycle-dependent death in immortalized keratinocytes and human dermoid carcinoma

We would like to dedicate this article to the memory of Professor Yoram Milner, who has passed away before this study was achieved. We are immeasurably indebted to him, professionally and personally. The study was supported by grants from the ICA Foundation and the Ministry of Science, Technology and Space.

MMSET deregulation affects cell cycle progression and adhesion regulons in t(4;14) myeloma plasma cells

BackgroundThe recurrent immunoglobulin translocation, t(4;14)(p16;q32) occurs in 15% of multiple myeloma patients and is associated with poor prognosis, through an unknown mechanism. The t(4;14) up-regulates fibroblast growth factor receptor 3 (FGFR3) and multiple myeloma SET domain (MMSET) genes. The involvement of MMSET in the pathogenesis of t(4;14) multiple myeloma and the mechanism or genes deregulated by MMSET upregulation are still unclear.Design and MethodsThe expression of MMSET was analyzed using a novel antibody. The involvement of MMSET in t(4;14) myelomagenesis was assessed by small interfering RNA mediated knockdown combined with several biological assays. In addition, the differential gene expression of MMSET-induced knockdown was analyzed with expression microarrays. MMSET gene targets in primary patient material was analyzed by expression microarrays.ResultsWe found that MMSET isoforms are expressed in multiple myeloma cell lines, being exclusively up-regulated in t(4;14)-positive cells. Suppression of MMSET expression affected cell proliferation by both decreasing cell viability and cell cycle progression of cells with the t(4;14) translocation. These findings were associated with reduced expression of genes involved in the regulation of cell cycle progression (e.g. CCND2, CCNG1, BRCA1, AURKA and CHEK1), apoptosis (CASP1, CASP4 and FOXO3A) and cell adhesion (ADAM9 and DSG2). Furthermore, we identified genes involved in the latter processes that were differentially expressed in t(4;14) multiple myeloma patient samples.ConclusionsIn conclusion, dysregulation of MMSET affects the expression of several genes involved in the regulation of cell cycle progression, cell adhesion and survival.

Cell cycle-coupled expansion of AR activity promotes cancer progression

The androgen receptor (AR) is required for prostate cancer (PCa) survival and progression, and ablation of AR activity is the first line of therapeutic intervention for disseminated disease. While initially effective, recurrent tumors ultimately arise for which there is no durable cure. Despite the dependence of PCa on AR activity throughout the course of disease, delineation of the AR-dependent transcriptional network that governs disease progression remains elusive, and the function of AR in mitotically active cells is not well understood. Analyzing AR activity as a function of cell cycle revealed an unexpected and highly expanded repertoire of AR-regulated gene networks in actively cycling cells. New AR functions segregated into two major clusters: those that are specific to cycling cells and retained throughout the mitotic cell cycle ('Cell Cycle Common'), versus those that were specifically enriched in a subset of cell cycle phases ('Phase Restricted'). Further analyses identified previously unrecognized AR functions in major pathways associated with clinical PCa progression. Illustrating the impact of these unmasked AR-driven pathways, dihydroceramide desaturase 1 was identified as an AR-regulated gene in mitotically active cells that promoted pro-metastatic phenotypes, and in advanced PCa proved to be highly associated with development of metastases, recurrence after therapeutic intervention and reduced overall survival. Taken together, these findings delineate AR function in mitotically active tumor cells, thus providing critical insight into the molecular basis by which AR promotes development of lethal PCa and nominate new avenues for therapeutic intervention.

Use of fluorescence lifetime imaging microscopy (FLIM) as a timer of cell cycle S phase

Incorporation of thymidine analogues in replicating DNA, coupled with antibody and fluorophore staining, allows analysis of cell proliferation, but is currently limited to monolayer cultures, fixed cells and end-point assays. We describe a simple microscopy imaging method for live real-time analysis of cell proliferation, S phase progression over several division cycles, effects of anti-proliferative drugs and other applications. It is based on the prominent (~ 1.7-fold) quenching of fluorescence lifetime of a common cell-permeable nuclear stain, Hoechst 33342 upon the incorporation of 5-bromo-2’-deoxyuridine (BrdU) in genomic DNA and detection by fluorescence lifetime imaging microscopy (FLIM). We show that quantitative and accurate FLIM technique allows high-content, multi-parametric dynamic analyses, far superior to the intensity-based imaging. We demonstrate its uses with monolayer cell cultures, complex 3D tissue models of tumor cell spheroids and intestinal organoids, and in physiological study with metformin treatment.

Multiscale analysis of protein functions and stochastic modelling of gene transcriptional regulatory networks

Genomic and proteomic analyses have attracted a great deal of interests in biological research in recent years. Many methods have been applied to discover useful information contained in the enormous databases of genomic sequences and amino acid sequences. The results of these investigations inspire further research in biological fields in return. These biological sequences, which may be considered as multiscale sequences, have some specific features which need further efforts to characterise using more refined methods. This project aims to study some of these biological challenges with multiscale analysis methods and stochastic modelling approach. The first part of the thesis aims to cluster some unknown proteins, and classify their families as well as their structural classes. A development in proteomic analysis is concerned with the determination of protein functions. The first step in this development is to classify proteins and predict their families. This motives us to study some unknown proteins from specific families, and to cluster them into families and structural classes. We select a large number of proteins from the same families or superfamilies, and link them to simulate some unknown large proteins from these families. We use multifractal analysis and the wavelet method to capture the characteristics of these linked proteins. The simulation results show that the method is valid for the classification of large proteins. The second part of the thesis aims to explore the relationship of proteins based on a layered comparison with their components. Many methods are based on homology of proteins because the resemblance at the protein sequence level normally indicates the similarity of functions and structures. However, some proteins may have similar functions with low sequential identity. We consider protein sequences at detail level to investigate the problem of comparison of proteins. The comparison is based on the empirical mode decomposition (EMD), and protein sequences are detected with the intrinsic mode functions. A measure of similarity is introduced with a new cross-correlation formula. The similarity results show that the EMD is useful for detection of functional relationships of proteins. The third part of the thesis aims to investigate the transcriptional regulatory network of yeast cell cycle via stochastic differential equations. As the investigation of genome-wide gene expressions has become a focus in genomic analysis, researchers have tried to understand the mechanisms of the yeast genome for many years. How cells control gene expressions still needs further investigation. We use a stochastic differential equation to model the expression profile of a target gene. We modify the model with a Gaussian membership function. For each target gene, a transcriptional rate is obtained, and the estimated transcriptional rate is also calculated with the information from five possible transcriptional regulators. Some regulators of these target genes are verified with the related references. With these results, we construct a transcriptional regulatory network for the genes from the yeast Saccharomyces cerevisiae. The construction of transcriptional regulatory network is useful for detecting more mechanisms of the yeast cell cycle.

Potential Landscape and Flux Framework of Nonequilibrium Networks: Robustness, Dissipation, and Coherence of Biochemical Oscillations

We established a theoretical framework for studying nonequilibrium networks with two distinct natures essential for characterizing the global probabilistic dynamics: the underlying potential landscape and the corresponding curl flux. We applied the idea to a biochemical oscillation network and found that the underlying potential landscape for the oscillation limit cycle has a distinct closed ring valley (Mexican hat-like) shape when the fluctuations are small. This global landscape structure leads to attractions of the system to the ring valley.

Robustness and dissipation of mitogen-activated protein kinases signal transduction network: Underlying funneled landscape against stochastic fluctuations

We uncovered the underlying energy landscape of the mitogen-activated protein kinases signal transduction cellular network by exploring the statistical natures of the Brownian dynamical trajectories. We introduce a dimensionless quantity: The robustness ratio of energy gap versus local roughness to measure the global topography of the underlying landscape. A high robustness ratio implies funneled landscape. The landscape is quite robust against environmental fluctuations and variants of the intrinsic chemical reaction rates.

Constraint-based analysis of gene interactions using restricted boolean networks and time-series data

Abstract Background A popular model for gene regulatory networks is the Boolean network model. In this paper, we propose an algorithm to perform an analysis of gene regulatory interactions using the Boolean network model and time-series data. Actually, the Boolean network is restricted in the sense that only a subset of all possible Boolean functions are considered. We explore some mathematical properties of the restricted Boolean networks in order to avoid the full search approach. The problem is modeled as a Constraint Satisfaction Problem (CSP) and CSP techniques are used to solve it. Results We applied the proposed algorithm in two data sets. First, we used an artificial dataset obtained from a model for the budding yeast cell cycle. The second data set is derived from experiments performed using HeLa cells. The results show that some interactions can be fully or, at least, partially determined under the Boolean model considered. Conclusions The algorithm proposed can be used as a first step for detection of gene/protein interactions. It is able to infer gene relationships from time-series data of gene expression, and this inference process can be aided by a priori knowledge available.

Identification of a Saccharomyces cerevisiae Gene that Is Required for G1 Arrest in Response to the Lipid Oxidation Product Linoleic Acid Hydroperoxide*

Reactive oxygen species cause damage to all of the major cellular constituents, including peroxidation of lipids. Previous studies have revealed that oxidative stress, including exposure to oxidation products, affects the progression of cells through the cell division cycle. This study examined the effect of linoleic acid hydroperoxide, a lipid peroxidation product, on the yeast cell cycle. Treatment with this peroxide led to accumulation of unbudded cells in asynchronous populations, together with a budding and replication delay in synchronous ones. This observed modulation of G1 progression could be distinguished from the lethal effects of the treatment and may have been due to a checkpoint mechanism, analogous to that known to be involved in effecting cell cycle arrest in response to DNA damage. By examining several mutants sensitive to linoleic acid hydroperoxide, the YNL099c open reading frame was found to be required for the arrest. This gene (designated OCA1) encodes a putative protein tyrosine phosphatase of previously unknown function. Cells lacking OCA1 did not accumulate in G1 on treatment with linoleic acid hydroperoxide, nor did they show a budding, replication, or Start delay in synchronous cultures. Although not essential for adaptation or immediate cellular survival, OCA1 was required for growth in the presence of linoleic acid hydroperoxide, thus indicating that it may function in linking growth, stress responses, and the cell cycle. Identification of OCA1 establishes cell cycle arrest as an actively regulated response to oxidative stress and will enable further elucidation of oxidative stress-responsive signaling pathways in yeast.