A ZEB1-miR-375-YAP1 pathway regulates epithelial plasticity in prostate cancer.

MicroRNA-375 (miR-375) is frequently elevated in prostate tumors and cell-free fractions of patient blood, but its role in genesis and progression of prostate cancer is poorly understood. In this study, we demonstrated that miR-375 is inversely correlated with epithelial-mesenchymal transition signatures (EMT) in clinical samples and can drive mesenchymal-epithelial transition (MET) in model systems. Indeed, miR-375 potently inhibited invasion and migration of multiple prostate cancer lines. The transcription factor YAP1 was found to be a direct target of miR-375 in prostate cancer. Knockdown of YAP1 phenocopied miR-375 overexpression, and overexpression of YAP1 rescued anti-invasive effects mediated by miR-375. Furthermore, transcription of the miR-375 gene was shown to be directly repressed by the EMT transcription factor, ZEB1. Analysis of multiple patient cohorts provided evidence for this ZEB1-miR-375-YAP1 regulatory circuit in clinical samples. Despite its anti-invasive and anti-EMT capacities, plasma miR-375 was found to be correlated with circulating tumor cells in men with metastatic disease. Collectively, this study provides new insight into the function of miR-375 in prostate cancer, and more broadly identifies a novel pathway controlling epithelial plasticity and tumor cell invasion in this disease.

Circulating microRNAs predict biochemical recurrence in prostate cancer patients.

BACKGROUND: Circulating microRNAs (miRNAs) are emerging as promising biomarkers for prostate cancer. Here, we investigated the potential of these molecules to assist in prognosis and treatment decision-making. METHODS: MicroRNAs in the serum of patients who had experienced rapid biochemical recurrence (BCR) (n=8) or no recurrence (n=8) following radical prostatectomy (RP) were profiled using high-throughput qRT-PCR. Recurrence-associated miRNAs were subsequently quantitated by qRT-PCR in a validation cohort comprised of 70 patients with Gleason 7 cancers treated by RP, 31 of whom had undergone disease progression following surgery. The expression of recurrence-associated miRNAs was also examined in tumour tissue cohorts. RESULTS: Three miRNAs - miR-141, miR-146b-3p and miR-194 - were elevated in patients who subsequently experienced BCR in the screening study. MiR-146b-3p and miR-194 were also associated with disease progression in the validation cohort, as determined by log-rank tests and Cox proportional hazards regression. Multivariate analysis revealed that miR-146b-3p possessed prognostic information beyond standard clinicopathological parameters. Analysis of tissue cohorts revealed that miR-194 was robustly expressed in the prostate, elevated in metastases, and its expression in primary tumours was associated with a poor prognosis. CONCLUSION: Our study suggests that circulating miRNAs, measured at the time of RP, could be combined with current prognostic tools to predict future disease progression in men with intermediate risk prostate cancers.

A G matrix analogue to capture the cumulative effects of nongenetic inheritance.

The genetic variance-covariance (G) matrix describes the variances and covariances of genetic traits under strict genetic inheritance. Genetically expressed traits often influence trait expression in another via nongenetic forms of transmission and inheritance, however. The importance of non-genetic influences on phenotypic evolution is increasingly clear, but how genetic and nongenetic inheritance interact to determine the response to selection is not well understood. Here, we use the 'reachability matrix' - a key analytical tool of geometric control theory - to integrate both forms of inheritance, capturing how the consequences of generation-lagged maternal effects accumulate. Building on the classic Lande and Kirkpatrick model that showed how nongenetic (maternal) inheritance fundamentally alters the expected path of phenotypic evolution, we make novel inferences through decomposition of the reachability matrix. In particular, we quantify how nongenetic inheritance affects the distribution (orientation and shape) of ellipses of phenotypic change and how these distributions influence subsequent evolution. This interweaving of phenotypic means and variances accumulates generation by generation and is described analytically by the reachability matrix, which acts as an analogue of G when genetic and nongenetic inheritance both act.

Robust population management under uncertainty for structured population models.

Structured population models are increasingly used in decision making, but typically have many entries that are unknown or highly uncertain. We present an approach for the systematic analysis of the effect of uncertainties on long-term population growth or decay. Many decisions for threatened and endangered species are made with poor or no information. We can still make decisions under these circumstances in a manner that is highly defensible, even without making assumptions about the distribution of uncertainty, or limiting ourselves to discussions of single, infinitesimally small changes in the parameters. Suppose that the model (determined by the data) for the population in question predicts long-term growth. Our goal is to determine how uncertain the data can be before the model loses this property. Some uncertainties will maintain long-term growth, and some will lead to long-term decay. The uncertainties are typically structured, and can be described by several parameters. We show how to determine which parameters maintain long-term growth. We illustrate the advantages of the method by applying it to a Peregrine Falcon population. The U.S. Fish and Wildlife Service recently decided to allow minimal harvesting of Peregrine Falcons after their recent removal from the Endangered Species List. Based on published demographic rates, we find that an asymptotic growth rate lambda > 1 is guaranteed with 5% harvest rate up to 3% error in adult survival if no two-year-olds breed, and up to 11% error if all two-year-olds breed. If a population growth rate of 3% or greater is desired, the acceptable error in adult survival decreases to between 1% and 6% depending of the proportion of two-year-olds that breed. These results clearly show the interactions between uncertainties in different parameters, and suggest that a harvest decision at this stage may be premature without solid data on adult survival and the frequency of breeding by young adults.

Tea tree oil reduces histamine-induced oedema in murine ears.

OBJECTIVE: To examine the effect of topically applied tea tree oil (TTO) on histamine-induced oedema in the ears of mice. METHODS AND RESULTS: For BALB/c mice, 10 microl undiluted TTO applied immediately after, but not 30 min before intradermal injection of 600 microg histamine in 10 microl, significantly suppressed oedema development. TTO applied after histamine injection also suppressed histamine-induced oedema in C57/BL6 mice. TTO applied immediately after intradermal injection of compound 48/80 (200 microg in 10 microl saline) also significantly reduced ear swelling. TTO suppressed histamine-induced oedema to the same extent in capsaicin-treated (neuropeptide-depleted) and control mice which suggests that TTO does not inhibit histamine-induced oedema by regulating the activity of peripheral sensory neurons. Terpinen-4-ol, the major water-soluble component of TTO, was equivalent in potency to TTO in the suppression of histamine-induced ear swelling. CONCLUSION: Topical application of TTO, and in particular terpinen-4-ol, may be effective in controlling histamine-induced oedema often associated with Type I allergic immediate hypersensitivities.

cis-Urocanic acid stimulates neuropeptide release from peripheral sensory nerves.

Previous studies using an antibody to cis-urocanic acid and mast-cell-depleted mice implicated both cis-urocanic acid and mast cells in the mechanisms by which ultraviolet B light suppresses systemic contact hypersensitivity responses in mice. In the absence of a direct stimulatory effect of cis-urocanic acid on connective tissue mast cells, an indirect association was investigated. A blister induced in the rat hind footpad was used to examine the effects of slowly perfused cis-urocanic acid on cutaneous blood flow. cis-Urocanic acid but not trans-urocanic acid increased microvascular flow by a mechanism largely dependent on the combined activity of the neuropeptides, substance P and calcitonin gene-related peptide. Perfusion of cis-urocanic acid over the base of blisters induced in sensory-neuropeptide-depleted rats did not have any stimulatory effect above that seen with perfusion of cis-urocanic acid together with neuropeptide receptor antagonists in control rats. There was a small direct effect of cis-urocanic acid on microvascular blood flow. As both substance P and calcitonin gene-related peptide could directly degranulate connective tissue mast cells, this study suggests that cis-urocanic acid indirectly activates mast cells via its effects on peripheral terminals of unmyelinated primary afferent sensory nerves. cis-Urocanic-acid-induced neuropeptides may also contribute to ultraviolet-B-induced cutaneous inflammation and alterations to Langerhans cell activity.

Existence and learning of oscillations in recurrent neural networks.

In this paper we study a particular class of -node recurrent neural networks (RNN's). In the 3-node case we use monotone dynamical systems theory to show, for a well-defined set of parameters, that, generically, every orbit of the RNN is asymptotic to a periodic orbit. Then we investigate whether RNN's of this class can adapt their internal parameters so as to "learn" and then replicate autonomously (in feedback) certain external periodic signals. Our learning algorithm is similar to identification algorithms in adaptive control theory. The main feature of the algorithm is that global exponential convergence of parameters is guaranteed. We also obtain partial convergence results in the -node case.

Existence, learning, and replication of periodic motions in recurrent neural networks.

A class of recurrent neural networks is shown to possess a stable limit cycle. A gradient type algorithm is used to modify the parameters of the network so that it learns and replicates autonomously a time varying periodic signal. The results are applied to controlling the repetitive motion of a two-link robot manipulator.