Michael Newton - Academia.edu (original) (raw)

Papers by Michael Newton

Veterinary and Comparative Oncology, Feb 3, 2015

Serum alkaline phosphatase (ALP) concentration is a prognostic factor for osteosarcoma in multipl... more Serum alkaline phosphatase (ALP) concentration is a prognostic factor for osteosarcoma in multiple studies, although its biological significance remains incompletely understood. To determine whether gene expression patterns differed in osteosarcoma from patients with differing serum ALP concentrations, microarray analysis was performed on 18 primary osteosarcoma samples and six osteosarcoma cell lines from dogs with normal and increased serum ALP concentration. No differences in gene expression patterns were noted between tumours or cell lines with differing serum ALP concentration using a gene-specific two-sample t-test. Using a more sensitive empirical Bayes procedure, defective in cullin neddylation 1 domain containing 1 (DCUN1D1) was increased in both the tissue and cell lines of the normal ALP group. Using quantitative PCR (qPCR), differences in DCUN1D1 expression between the two groups failed to reach significance. The homogeneity of gene expression patterns of osteosarcoma associated differing serum ALP concentrations are consistent with previous studies suggesting serum ALP concentration is not associated with intrinsic differences of osteosarcoma cells.

Lecture notes in statistics, 1997

ABSTRACT

Veterinary and Comparative Oncology, Feb 16, 2015

An increased serum alkaline phosphatase concentration is known to be associated with a negative p... more An increased serum alkaline phosphatase concentration is known to be associated with a negative prognosis in canine and human osteosarcoma. To expand upon previous studies regarding the biological relevance of increased serum alkaline phosphatase as a negative prognostic factor, xenogeneic heterotopic transplants were performed using six canine primary osteosarcoma cell lines generated from patients with differing serum alkaline phosphatase concentrations (three normal and three increased). Three of the six cell lines were capable of generating tumours and tumour formation was independent of the serum alkaline phosphatase status of the cell line. Microarray analysis identified 379 genes as being differentially expressed between the tumourigenic and non-tumourigenic cell lines. Frizzled-6 was upregulated to the greatest extent (7.78-fold) in tumourigenic cell lines compared with non-tumourigenic cell lines. Frizzled-6, a coreceptor for Wnt ligands has been associated with enhanced tumour-initiating cells and poor prognosis for other tumours. The increased expression of frizzled-6 was confirmed by quantitative reverse transcription polymerase chain reaction (QPCR) and Western blot analysis. Additionally, the tumourigenic cell lines also had an increase in the percentage of side population cells compared with non-tumourigenic cell lines (5.89% versus 1.58%, respectively). There were no differences in tumourigenicity, frizzled-6 or percentage of side population cells noted between osteosarcoma cell lines generated from patients of differing serum alkaline phosphatase concentration. However, to our knowledge this is the first study to identified frizzled-6 as a possible marker of osteosarcoma cell populations with enhanced tumourigenicity and side population cells. Future work will focus on defining the role of frizzled-6 in osteosarcoma tumourigenesis and tumour-initiating cells.

Anticancer Research, Jul 30, 2018

Background/Aim: N-(4-hydroxyphenyl)retinamide (4-HPR) is a synthetic retinoid, less toxic than th... more Background/Aim: N-(4-hydroxyphenyl)retinamide (4-HPR) is a synthetic retinoid, less toxic than the parent alltrans retinoic acid (RA). Unlike RA, 4-HPR induces apoptosis in tumor cells. Because 4-HPR can hydrolyze to liberate RA, a potent human teratogen, the unhydrolyzable ketone analog of 4-HPR, 4-hydroxybenzylretinone (4-HBR) has been prepared and has been found to cause apoptosis in tumor cells and shrink carcinogen-induced rat mammary tumors as 4-HPR does. Herein, we examined the mechanism whereby 4-HPR and 4-HBR induce apoptosis and death in breast cancer cells. Materials and Methods: Gene expression profiling was conducted in MCF-7 cells over a 1.5-to 6-h time course and changes were validated by quantitative polymerase chain reaction (qPCR). Growth arrest and DNA damage-inducible protein 153 (GADD153 or C/EBP homologous protein, CHOP) was knocked down and the effect on 4-HPR-induced cell death and gene expression was assessed. 4-HPR synergy with tumor necrosis factor (TNF)-related apoptosis-inducing ligand (TRAIL or Apo2 ligand) was also examined. Results: Drug treatment induced increased expression of endoplasmic reticulum (ER) stress-related and pro-apoptotic genes. Gene expression changes were verified by qPCR in three invasive ductal breast carcinoma cell lines (MCF-7, T-47D, MDA-MB-231). GADD153 showed the largest increase in the microarray experiment; however, knockdown of GADD153 did not abrogate apoptosis and death. Genes related to the extrinsic pathway of apoptosis including a receptor for TRAIL, death receptor 5 (DR5), were up-regulated by drug treatment. A dose of 4-HPR that alone is ineffective in killing TRAIL-resistant MCF-7 cells, synergized with recombinant TRAIL to induce breast cancer cell death. Conclusion: 4-HPR and analogs might be useful in sensitizing tumor cells to death receptor agonists. N-(4-hydroxyphenyl)retinamide (4-HPR) and its nonhydrolyzable analog, 4-hydroxybenzylretinone (4-HBR), induce apoptosis and cell death in a variety of cell types including breast cancer, neuroblastoma and leukemia cells (1, 2). Both drugs are active in vivo and reduce the size and number of dimethylbenz[a]anthracene (DMBA)-induced mammary tumors in rats (3, 4). In vivo and in vitro studies on the effects of the non-hydrolyzable analog 4-HBR have supported that liberation of free retinoic acid (RA) from 4-HPR is not required to induce cell death (1). Earlier work has suggested that 4-HPR and 4-HBR act by similar mechanisms and that induction of endoplasmic reticulum (ER) stress plays a role in the ability of both compounds to induce cell death (2). 4-HPR induces apoptosis and death in many cancer cell types through activation of the intrinsic pathway, although the initiating event is unknown (5). In breast cancer cells, 4-HPR decreases levels of B-cell lymphoma 2 (BCL-2) (6) and results in the release of cytochrome c, activates caspase-3, and induces poly (ADP-ribose) polymerase (PARP) cleavage

Blood, Oct 1, 1993

topoiesis was neither large nor constant. With mathematical analyses, w e estimated that the prol... more topoiesis was neither large nor constant. With mathematical analyses, w e estimated that the proliferative potential of residual stem cells was much less than that of normal stem cells reduced in number by autologous transplantation (Abkowitz et al, Proc Natl Acad Sci USA 87:9062, 1990). There was no evidence for the regeneration of a normal stem cell reserve over time; rather, damage was most pronounced years after dimethylbusulfan exposure. These data may help explain the high clinical incidence of aplastic anemia and myelodysplasia after alkylating agent therapies.

Proceedings of the National Academy of Sciences of the United States of America, Nov 1, 1990

To test if hematopoiesis can be maintained by the sequential activation of stem-cell clones, we p... more To test if hematopoiesis can be maintained by the sequential activation of stem-cell clones, we performed autologous marrow transplantations with limited numbers of cells in cats heterozygous for the X chromosome-linked enzyme glucose-6-phosphate dehydrogenase (G6PD) and observed the G6PD phenotypes of erythroid and granulocyte/macrophage progenitors over time. The animals were the female offspring of Geoffroy male and domestic female cats. In repeated studies of marrow from control animals (n = 5) or experimental animals prior to transplantation (n = 3), the percent of progenitors with domestic-type G6PD did not vary. After transplantation, the peripheral blood counts, marrow morphologies, frequencies of progenitors, and progenitor cell cycle kinetics returned to normal. However, abrupt and significant fluctuations were seen in the G6PD type of progenitors from each cat during the 1-1.5 years of observation. These data cannot be explained if there were either a large or constant population ofactive stem cells and thus imply, in a large-animal system, that hematopoiesis was maintained through clonal succession. A stochastic model was developed to estimate the numbers of active clones and their mean lifetimes.

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The integrated likelihood (also called the marginal likelihood or the normalizing constant) is a ... more The integrated likelihood (also called the marginal likelihood or the normalizing constant) is a central quantity in Bayesian model selection and model averaging. It is defined as the integral over the parameter space of the likelihood times the prior density. The Bayes factor for model comparison and Bayesian testing is a ratio of integrated likelihoods, and the model weights in Bayesian model averaging are proportional to the integrated likelihoods. We consider the estimation of the integrated likelihood from posterior simulation output, aiming at a generic method that uses only the likelihoods from the posterior simulation iterations. The key is the harmonic mean identity, which says that the reciprocal of the integrated likelihood is equal to the posterior harmonic mean of the likelihood. The simplest estimator based on the identity is thus the harmonic mean of the likelihoods. While this is an unbiased and simulation-consistent estimator, its reciprocal can have infinite variance and so it is unstable in general. We describe two methods for stabilizing the harmonic mean estimator. In the first one, the parameter space is reduced in such a way that the modified estimator involves a harmonic mean of heavier-tailed densities, thus resulting in a finite variance estimator. The resulting estimator is stable. It is also self-monitoring, since it obeys the central limit theorem, and so confidence intervals are available. We discuss general conditions under which this reduction is applicable.

Journal of the American Statistical Association, Dec 1, 1995

Hematopoiesis is the body&amp;#39;s way of making the cellular constituents of blood. Oxy... more Hematopoiesis is the body&amp;#39;s way of making the cellular constituents of blood. Oxygen transport, response to infections, and control of bleeding are among the functions of different mature blood cells. These specific functions are acquired as cells mature in the bone marrow. Stem cells are the “master cells” at the top of this pedigree, having within them the capacity to

Applied statistics, Nov 29, 2005

Tumour multiplicity is a frequently measured phenotype in animal studies of cancer biology. Poiss... more Tumour multiplicity is a frequently measured phenotype in animal studies of cancer biology. Poisson variation of this measurement represents a biological and statistical reference point that is usually violated, even in highly controlled experiments, owing to sources of variation in the stochastic process of tumour formation. A recent experiment on murine intestinal tumours presented conditions which seem to generate Poisson-distributed tumour counts. If valid, this would support a claim about mechanisms by which the adenomatous polyposis coli gene is inactivated during tumour initiation. In considering hypothesis testing strategies, model choice and Bayesian approaches, we quantify the positive evidence favouring Poisson variation in this experiment. Statistical techniques used include likelihood ratio testing, the Bayes and Akaike information criteria, negative binomial modelling, reversible jump Markov chain Monte Carlo methods and posterior predictive checking. The posterior approximation that is based on the Bayes information criterion is found to be quite accurate in this small n casestudy.

Journal of the American Statistical Association, Dec 1, 2002

This article introduces a model-based statistical methodology for the analysis of copy-number var... more This article introduces a model-based statistical methodology for the analysis of copy-number variations in cancer genomes measured by comparative genomic hybridization. The methodology allows one to infer combinations of genomic aberrations associated with the cancer phenotype. The stochastic model conjoins two features of cancer biology to infuse some context into an otherwise unsupervised learning problem. It asserts random genomic instability in a potential progenitor cell, followed by selection into a tumor of the descending cell lineage if the lineage experiences certain ensembles of genomic aberration. Disease heterogeneity is reflected in the possibility of a network containing multiple ensembles. The network of ensembles is an identifiable parameter. By forming the sampling model conditionally on selection, statistical dependencies (both positive and negative) can be induced between aberrations, and the model entails heterogeneity in the marginal rate of occurrence of aberrations. A double-Pblya distribution is introduced as a prior over the network of ensembles, and Markov chain Monte Carlo is developed to enable posterior computation. As an example, the methodology is used to reanalyze genomic aberrations from 116 renal cell carcinomas. It produces posterior probabilities that any given aberration is relevant to oncogenesis, posterior probabilities that pairs of aberrations reside in a common ensemble, and a point estimate of the network of ensembles. The methodology provides a model-based clustering of all measured aberrations according to these estimated ensembles and a model-based clustering of tumors according to the probable ensembles of genomic aberration that they have experienced. Although it is formulated here to analyze aberrations in cancer genomes, the instability-selection-network model may provide an approach to modeling dependence in correlated binary data on various biological systems. Limitations and possible extensions of the methodology are discussed.

Mathematical medicine and biology, 1990

Haematopoiesis is the process by which progenitor cells differentiate into competent mature blood... more Haematopoiesis is the process by which progenitor cells differentiate into competent mature blood cells. Only those cells in the latter stages of haematopoiesis can be observed in vitro, so theories about the early stages of the process cannot be tested directly. Experimental data of bone marrow samples from Safari cats provides evidence for the clonal succession hypothesis of early haematopoiesis. In this paper, a hidden Markov model is constructed to quantify this support. Recursive updating techniques are derived and are used to calculate the likelihood and to construct fitted values for the model. Inference is based on multimodal likelihood surfaces.

Journal of the American Statistical Association, Sep 1, 1994

ABSTRACT A Monte Carlo algorithm is described that can be used in place of the nested bootstrap. ... more ABSTRACT A Monte Carlo algorithm is described that can be used in place of the nested bootstrap. It is particularly advantageous when there is a premium on the number of bootstrap samples, either because samples are hard to generate or because expensive computations are applied to each sample. This recycling algorithm is useful because it enables inference procedures like prepivoting and bootstrap iteration in models where nested bootstrapping is computationally impractical. Implementation of the recycling algorithm is quite straightforward. As a replacement of the double bootstrap, for example, bootstrap recycling involves two stages of sampling, as does the double bootstrap. The first stage of both algorithms is the same: simulate from the fitted model. In the second stage of recycling, one batch of samples is simulated from one measure; a measure dominating all the first-stage fits. These samples are recycled with each first-stage sample to yield estimated adjustments to the original inference procedure. Choice of this second-stage measure affects the efficiency of the recycling algorithm. Gains in efficiency are slight for the nonparametric bootstrap but can be substantial in parametric problems. Applications are given to testing with sparse contingency tables and to construction of likelihood-based confidence sets in a hidden Markov model from hematology.

Genetics, Oct 1, 1996

Markov chain Monte Carlo (MCMC) techniques are applied to simultaneously identify multiple quanti... more Markov chain Monte Carlo (MCMC) techniques are applied to simultaneously identify multiple quantitative trait loci (QTL) and the magnitude of their effects. Using a Bayesian approach a multi-locus model is fit to quantitative trait and molecular marker data, instead of fitting one locus at a time. The phenotypic trait is modeled as a linear function of the additive and dominance effects of the unknown QTL genotypes. Inference summaries for the locations of the QTL and their effects are derived from the corresponding marginal posterior densities obtained by integrating the likelihood, rather than by optimizing the joint likelihood surface. This is done using MCMC by treating the unknown QTL genotypes, and any missing marker genotypes, as augmented data and then by including these unknowns in the Markov chain cycle along with the unknown parameters. Parameter estimates are obtained as means of the corresponding marginal posterior densities. High posterior density regions of the marginal densities are obtained as confidence regions. We examine flowering time data from double haploid progeny of Brassica napus to illustrate the proposed method.

Biometrics, Dec 1, 2000

Cancerous tumor growth creates cells with abnormal DNA. Allelic-loss experiments identify genomic... more Cancerous tumor growth creates cells with abnormal DNA. Allelic-loss experiments identify genomic deletions in cancer cells, but sources of variation and intrinsic dependencies complicate inference about the location and effect of suppressor genes; such genes are the target of these experiments and are thought to be involved in tumor development. We investigate properties of an instability-selection model of allelic-loss data, including likelihood-based parameter estimation and hypothesis testing. By considering a special complete-data case, we derive an approximate calibration method for hypothesis tests of sporadic deletion. Parametric bootstrap and Bayesian computations are also developed. Data from three allelic-loss studies are reanalyzed to illustrate the methods.

ABSTRACT Thesis (Ph. D.)--University of Washington, 1991 The method of bootstrapping, which has t... more ABSTRACT Thesis (Ph. D.)--University of Washington, 1991 The method of bootstrapping, which has transformed the theory and practice of frequentist statistical inference, is applicable within the Bayesian paradigm. Rather than simulating data that might have been observed, this Bayesian extension, called the weighted likelihood bootstrap, involves simulating parameters corresponding to distributions that might have generated the observed data. The weighted likelihood bootstrap is an extension of earlier work by D. Rubin (Annals of Statistics, 1981) from purely nonparametric models into semi and fully parametric models for data. The resulting simulation, which is viewed as simply a Monte Carlo approximation to a posterior distribution of interest, has desirable asymptotic properties. This simulation method produces easily generated samples from a posterior under an effective prior which can be identified either exactly or approximately in certain models. The simulation is straightforward, requiring only an algorithm for maximum likelihood estimation. It is also closely related to frequentist bootstrapping procedures. The weighted likelihood bootstrap is applied to a wide variety of statistical models.The prepivoting procedure is studied in a general modeling framework and an efficient Monte Carlo algorithm, called bootstrap recycling, is introduced. This algorithm is shown to be simulation consistent; that is, it produces a closer approximation to the right answer as the amount of computing resources gets large. This new algorithm, which is an alternative to the iterated bootstrap, is applied to the likelihood ratio test of a sparse contingency table, and to the construction of likelihood based confidence sets in a complex stochastic model.

Canadian journal of statistics, Aug 20, 2020

The Columbus Ground segment is a very complex system with connections to USA (NASA), Russia (RSA)... more The Columbus Ground segment is a very complex system with connections to USA (NASA), Russia (RSA), ATV-CC and many user centers across Europe. Because of the many delays in the launch of the Columbus module to the ISS, the ground segment was used to support other activities between the ISS and centers in Europe, like the interim utilization, Eneide and Astrolab missions, among parallel activities such as simulations. This decision provided a good opportunity to test the systems and be prepared for the Columbus mission. On the other side now, after 2 years of Columbus operations, Col-CC is facing the issues that almost all the subsystems are running out of maintenance contracts, and in addition, the hardware and operating systems are aging. Some of the subsystems need an urgent update in order to ensure the required support to Columbus operations. That results in a new challenge of testing in parallel the new systems without affecting operations. It is important to note that Col-CC does not have a testing facility for most of the subsystem and is under a very complicated decision-making and financial structure that makes the maintenance of the current functionalities extremely complex. All of these factors combined with the budget and man power limitations makes the successful short history of the operations and the already start of the parallel migration an interesting defiance.

Statistical Modelling, Aug 1, 2017