Elucidating the role of the receptor tyrosine kinase Ror2 within the Wnt pathway and its contributions to renal cell carcinoma tumorigenesis

Ror2, an important mediator of Wnt signaling cascades, has been shown to be aberrantly expressed in RCC promoting cell migration, invasion, and tumor growth. In this work, our goal was to elucidate the role of Ror2 as a Wnt receptor within its contextual expression of RCC. Utilizing microarrays we examined gene expression in RCC tumors and found Ror2 was significantly correlated with expression of several Wnt signaling genes including the classical feedback target gene, Axin2. Subsequent analysis in RCC cells showed that Ror2 expression results in a poised state for canonical Wnt signaling through an increased signaling pool of beta-catenin, leading to an enhancement of target genes following Wnt3a stimulation. In addition, we utilized siRNA and dickkopf to inhibit LRP6 in order to show that Ror2 stabilization of beta-catenin was independent of LRP6 but required for the downstream response to Wnt3a. Finally, we also saw that the Ror2 kinase domain is required for stabilization of soluble beta-catenin and enhancement of canonical signaling. Due to Ror2's correlation with aggressive disease in several cancers we have aimed to examine its contributions to cell migration and tumor growth, and its potential as a prognostic biomarker for RCC. Utilizing RCC cells and human tumors we have shown that both MMP2 and SFRP2 exhibit a significant correlation with Ror2. We show that Ror2 expression results in increased cell migration that is dependent upon an intact Ror2 kinase domain. We also examined the effects of Ror2 overexpression in xenografts and found that Ror2 expression results in increased tumor growth and vascularity. To ascertain the potential of Ror2 as a prognostic biomarker we first examined Ror2 expression in relation to the ccA and ccB molecular subtypes in RCC tumors, finding that Ror2 expression was significantly higher in ccB. Finally we assessed Ror2's potential as an independent prognostic biomarker for RCC; we show that high Ror2 expression correlates with increased tumor growth and significant reduction in overall survival. These results exhibit Ror2's potential as a prognostic biomarker and therapeutic target for RCC.Doctor of Philosoph

New Approaches To Photometric Redshift Prediction Via Gaussian Process Regression In The Sloan Digital Sky Survey

Expanding upon the work of Way and Srivastava 2006 we demonstrate how the use of training sets of comparable size continue to make Gaussian process regression (GPR) a competitive approach to that of neural networks and other least-squares fitting methods. This is possible via new large size matrix inversion techniques developed for Gaussian processes (GPs) that do not require that the kernel matrix be sparse. This development, combined with a neural-network kernel function appears to give superior results for this problem. Our best fit results for the Sloan Digital Sky Survey (SDSS) Main Galaxy Sample using u,g,r,i,z filters gives an rms error of 0.0201 while our results for the same filters in the luminous red galaxy sample yield 0.0220. We also demonstrate that there appears to be a minimum number of training-set galaxies needed to obtain the optimal fit when using our GPR rank-reduction methods. We find that morphological information included with many photometric surveys appears, for the most part, to make the photometric redshift evaluation slightly worse rather than better. This would indicate that most morphological information simply adds noise from the GP point of view in the data used herein. In addition, we show that cross-match catalog results involving combinations of the Two Micron All Sky Survey, SDSS, and Galaxy Evolution Explorer have to be evaluated in the context of the resulting cross-match magnitude and redshift distribution. Otherwise one may be misled into overly optimistic conclusions.Comment: 32 pages, ApJ in Press, 2 new figures, 1 new table of comparison methods, updated discussion, references and typos to reflect version in Pres

Bayesian hierarchical clustering for studying cancer gene expression data with unknown statistics

Clustering analysis is an important tool in studying gene expression data. The Bayesian hierarchical clustering (BHC) algorithm can automatically infer the number of clusters and uses Bayesian model selection to improve clustering quality. In this paper, we present an extension of the BHC algorithm. Our Gaussian BHC (GBHC) algorithm represents data as a mixture of Gaussian distributions. It uses normal-gamma distribution as a conjugate prior on the mean and precision of each of the Gaussian components. We tested GBHC over 11 cancer and 3 synthetic datasets. The results on cancer datasets show that in sample clustering, GBHC on average produces a clustering partition that is more concordant with the ground truth than those obtained from other commonly used algorithms. Furthermore, GBHC frequently infers the number of clusters that is often close to the ground truth. In gene clustering, GBHC also produces a clustering partition that is more biologically plausible than several other state-of-the-art methods. This suggests GBHC as an alternative tool for studying gene expression data. The implementation of GBHC is available at https://sites. google.com/site/gaussianbhc

Infinite factorization of multiple non-parametric views

Combined analysis of multiple data sources has increasing application interest, in particular for distinguishing shared and source-specific aspects. We extend this rationale of classical canonical correlation analysis into a flexible, generative and non-parametric clustering setting, by introducing a novel non-parametric hierarchical mixture model. The lower level of the model describes each source with a flexible non-parametric mixture, and the top level combines these to describe commonalities of the sources. The lower-level clusters arise from hierarchical Dirichlet Processes, inducing an infinite-dimensional contingency table between the views. The commonalities between the sources are modeled by an infinite block model of the contingency table, interpretable as non-negative factorization of infinite matrices, or as a prior for infinite contingency tables. With Gaussian mixture components plugged in for continuous measurements, the model is applied to two views of genes, mRNA expression and abundance of the produced proteins, to expose groups of genes that are co-regulated in either or both of the views. Cluster analysis of co-expression is a standard simple way of screening for co-regulation, and the two-view analysis extends the approach to distinguishing between pre- and post-translational regulation

Haemoglobin mass and running time trial performance after recombinant human erythropoietin administration in trained men

<p>Recombinant human erythropoietin (rHuEpo) increases haemoglobin mass (Hbmass) and maximal oxygen uptake (v˙ O2 max).</p> <p>Purpose: This study defined the time course of changes in Hbmass, v˙ O2 max as well as running time trial performance following 4 weeks of rHuEpo administration to determine whether the laboratory observations would translate into actual improvements in running performance in the field.</p> <p>Methods: 19 trained men received rHuEpo injections of 50 IUNkg21 body mass every two days for 4 weeks. Hbmass was determined weekly using the optimized carbon monoxide rebreathing method until 4 weeks after administration. v˙ O2 max and 3,000 m time trial performance were measured pre, post administration and at the end of the study.</p> <p>Results: Relative to baseline, running performance significantly improved by ,6% after administration (10:3061:07 min:sec vs. 11:0861:15 min:sec, p,0.001) and remained significantly enhanced by ,3% 4 weeks after administration (10:4661:13 min:sec, p,0.001), while v˙ O2 max was also significantly increased post administration (60.765.8 mLNmin21Nkg21 vs. 56.066.2 mLNmin21Nkg21, p,0.001) and remained significantly increased 4 weeks after rHuEpo (58.065.6 mLNmin21Nkg21, p = 0.021). Hbmass was significantly increased at the end of administration compared to baseline (15.261.5 gNkg21 vs. 12.761.2 gNkg21, p,0.001). The rate of decrease in Hbmass toward baseline values post rHuEpo was similar to that of the increase during administration (20.53 gNkg21Nwk21, 95% confidence interval (CI) (20.68, 20.38) vs. 0.54 gNkg21Nwk21, CI (0.46, 0.63)) but Hbmass was still significantly elevated 4 weeks after administration compared to baseline (13.761.1 gNkg21, p<0.001).</p> <p>Conclusion: Running performance was improved following 4 weeks of rHuEpo and remained elevated 4 weeks after administration compared to baseline. These field performance effects coincided with rHuEpo-induced elevated v˙ O2 max and Hbmass.</p&gt

Accelerating MCMC Algorithms

Markov chain Monte Carlo algorithms are used to simulate from complex statistical distributions by way of a local exploration of these distributions. This local feature avoids heavy requests on understanding the nature of the target, but it also potentially induces a lengthy exploration of this target, with a requirement on the number of simulations that grows with the dimension of the problem and with the complexity of the data behind it. Several techniques are available towards accelerating the convergence of these Monte Carlo algorithms, either at the exploration level (as in tempering, Hamiltonian Monte Carlo and partly deterministic methods) or at the exploitation level (with Rao-Blackwellisation and scalable methods).Comment: This is a survey paper, submitted WIREs Computational Statistics, to with 6 figure

Receptor Tyrosine Kinase-like Orphan Receptor 2 (Ror2) Expression Creates a Poised State of Wnt Signaling in Renal Cancer

Expression of the receptor tyrosine kinase-like orphan receptor 2 (Ror2) has been identified in an increasing array of tumor types and is known to play a role as an important mediator of Wnt signaling cascades. In this study, we aimed to clarify Ror2 interactions with the Wnt pathways within the context of renal cell carcinoma (RCC). An examination of Ror2 expression in primary human RCC tumors showed a significant correlation with several Wnt signaling genes, including the classical feedback target gene Axin2. We provide evidence that Ror2 expression results in a partially activated state for canonical Wnt signaling through an increased signaling pool of β-catenin, leading to an enhancement of downstream target genes following Wnt3a stimulation in both renal and renal carcinoma-derived cells. Additionally, inhibition of low-density lipoprotein receptor-related protein 6 (LRP6) with either siRNA or dickkopf decreased the response to Wnt3a stimulation, but no change was seen in the increased β-catenin pool associated with Ror2 expression, suggesting that LRP6 cofactor recruitment is necessary for a Wnt3a-induced signal but that it does not participate in the Ror2 effect on β-catenin signaling. These results highlight a new role for Ror2 in conveying a tonic signal to stabilize soluble β-catenin and create a poised state of enhanced responsiveness to Wnt3a exogenous signals in RCC

Search for W~1Z~2\widetilde{W}_1\widetilde{Z}_2 Production via Trilepton Final States in ppˉp\bar{p} collisions at s=1.8\sqrt{s}=1.8 TeV

We have searched for associated production of the lightest chargino, $\widetilde{W}_1$, and next-to-lightest neutralino, $\widetilde{Z}_2$, of the Minimal Supersymmetric Standard Model in $p\bar{p}$ collisions at \mbox{$\sqrt{s}$ = 1.8 TeV} using the \D0 detector at the Fermilab Tevatron collider. Data corresponding to an integrated luminosity of 12.5$\pm 0.7$ \ipb were examined for events containing three isolated leptons. No evidence for $\widetilde{W}_1\widetilde{Z}_2$ pair production was found. Limits on $\sigma(\widetilde{W}_1\widetilde{Z}_2)$Br$(\widetilde{W}_1\to l\nu\widetilde{Z}_1)$Br$(\widetilde{Z}_2\to l\bar{l}\widetilde{Z}_1)$ are presented.Comment: 17 pages (13 + 1 page table + 3 pages figures). 3 PostScript figures will follow in a UUEncoded, gzip'd, tar file. Text in LaTex format. Submitted to Physical Review Letters. Replace comments - Had to resumbmit version with EPSF directive

Measurement of the Top Quark Mass Using Dilepton Events

The D0 collaboration has performed a measurement of the top quark mass based on six candidate events for the process t tbar -> b W+ bbar W-, where the W bosons decay to e nu or mu nu. This sample was collected during an exposure of the D0 detector to an integrated luminosity of 125 pb^-1 of sqrt(s)=1.8 TeV p-pbar collisions. We obtain mt = 168.4 +- 12.3 (stat) +- 3.7 (sys) GeV/c^2, consistent with the measurement obtained using single-lepton events. Combination of the single-lepton and dilepton results yields mt = 172.0 +- 7.5 GeV/c^2.Comment: 12 pages, 3 figure