Predicting the HER2 status of breast cancer from basic histopathology data: an analysis of 1500 breast cancers as part of the HER2000 International Study

The tests that are currently available for the measurement of overexpression of the human epidermal growth factor-2 (HER2) in breast cancer have shown considerable problems in accuracy and interlaboratory reproducibility. Although these problems are partly alleviated by the use of validated, standardised 'kits', there may be considerable cost involved in their use. Prior to testing it may therefore be an advantage to be able to predict from basic pathology data whether a cancer is likely to overexpress HER2. In this study, we have correlated pathology features of cancers with the frequency of HER2 overexpression assessed by immunohistochemistry (IHC) using HercepTest (Dako). In addition, fluorescence in situ hybridisation (FISH) has been used to re-test the equivocal cancers and interobserver variation in assessing HER2 overexpression has been examined by a slide circulation scheme. Of the 1536 cancers, 1144 (74.5%) did not overexpress HER2. Unequivocal overexpression (3+ by IHC) was seen in 186 cancers (12%) and an equivocal result (2+ by IHC) was seen in 206 cancers (13%). Of the 156 IHC 3+ cancers for which complete data was available, 149 (95.5%) were ductal NST and 152 (97%) were histological grade 2 or 3. Only 1 of 124 infiltrating lobular carcinomas (0.8%) showed HER2 overexpression. None of the 49 'special types' of carcinoma showed HER2 overexpression. Re-testing by FISH of a proportion of the IHC 2+ cancers showed that only 25 (23%) of those assessable exhibited HER2 gene amplification, but 46 of the 47 IHC 3+ cancers (98%) were confirmed as showing gene amplification. Circulating slides for the assessment of HER2 score showed a moderate level of agreement between pathologists (kappa 0.4). As a result of this study we would advocate consideration of a triage approach to HER-2 testing. Infiltrating lobular and special types of carcinoma may not need to be routinely tested at presentation nor may grade 1 NST carcinomas in which only 1.4% have been shown to overexpress HER2. Testing of these carcinomas may be performed when HER2 status is required to assist in therapeutic or other clinical/prognostic decision-making. The highest yield of HER2 overexpressing carcinomas is seen in the grade 3 NST subgroup in which 24% are positive by IHC. (C) 2003 Elsevier Science Ltd. All rights reserved.

Capillaries within compartments: Microvascular interpretation of dynamic positron emission tomography data

Measurement of exchange of substances between blood and tissue has been a long-lasting challenge to physiologists, and considerable theoretical and experimental accomplishments were achieved before the development of the positron emission tomography (PET). Today, when modeling data from modern PET scanners, little use is made of earlier microvascular research in the compartmental models, which have become the standard model by which the vast majority of dynamic PET data are analysed. However, modern PET scanners provide data with a sufficient temporal resolution and good counting statistics to allow estimation of parameters in models with more physiological realism. We explore the standard compartmental model and find that incorporation of blood flow leads to paradoxes, such as kinetic rate constants being time-dependent, and tracers being cleared from a capillary faster than they can be supplied by blood flow. The inability of the standard model to incorporate blood flow consequently raises a need for models that include more physiology, and we develop microvascular models which remove the inconsistencies. The microvascular models can be regarded as a revision of the input function. Whereas the standard model uses the organ inlet concentration as the concentration throughout the vascular compartment, we consider models that make use of spatial averaging of the concentrations in the capillary volume, which is what the PET scanner actually registers. The microvascular models are developed for both single- and multi-capillary systems and include effects of non-exchanging vessels. They are suitable for analysing dynamic PET data from any capillary bed using either intravascular or diffusible tracers, in terms of physiological parameters which include regional blood flow. (C) 2003 Elsevier Ltd. All rights reserved.

Segmenting the market of West Australian senior tourists using an artificial neural network

Measuring perceptions of customers can be a major problem for marketers of tourism and travel services. Much of the problem is to determine which attributes carry most weight in the purchasing decision. Older travellers weigh many travel features before making their travel decisions. This paper presents a descriptive analysis of neural network methodology and provides a research technique that assesses the weighting of different attributes and uses an unsupervised neural network model to describe a consumer-product relationship. The development of this rich class of models was inspired by the neural architecture of the human brain. These models mathematically emulate the neurophysical structure and decision making of the human brain, and, from a statistical perspective, are closely related to generalised linear models. Artificial neural networks or neural networks are, however, nonlinear and do not require the same restrictive assumptions about the relationship between the independent variables and dependent variables. Using neural networks is one way to determine what trade-offs older travellers make as they decide their travel plans. The sample of this study is from a syndicated data source of 200 valid cases from Western Australia. From senior groups, active learner, relaxed family body, careful participants and elementary vacation were identified and discussed. (C) 2003 Published by Elsevier Science Ltd.

An EM-based Semi-Parametric Mixture Model Approach to the Regression Analysis of Competing-Risks Data

We consider a mixture model approach to the regression analysis of competing-risks data. Attention is focused on inference concerning the effects of factors on both the probability of occurrence and the hazard rate conditional on each of the failure types. These two quantities are specified in the mixture model using the logistic model and the proportional hazards model, respectively. We propose a semi-parametric mixture method to estimate the logistic and regression coefficients jointly, whereby the component-baseline hazard functions are completely unspecified. Estimation is based on maximum likelihood on the basis of the full likelihood, implemented via an expectation-conditional maximization (ECM) algorithm. Simulation studies are performed to compare the performance of the proposed semi-parametric method with a fully parametric mixture approach. The results show that when the component-baseline hazard is monotonic increasing, the semi-parametric and fully parametric mixture approaches are comparable for mildly and moderately censored samples. When the component-baseline hazard is not monotonic increasing, the semi-parametric method consistently provides less biased estimates than a fully parametric approach and is comparable in efficiency in the estimation of the parameters for all levels of censoring. The methods are illustrated using a real data set of prostate cancer patients treated with different dosages of the drug diethylstilbestrol. Copyright (C) 2003 John Wiley Sons, Ltd.

Effect of changing data collection parameters on statistical motor unit number estimates

The effect of number of samples and selection of data for analysis on the calculation of surface motor unit potential (SMUP) size in the statistical method of motor unit number estimates (MUNE) was determined in 10 normal subjects and 10 with amyotrophic lateral sclerosis (ALS). We recorded 500 sequential compound muscle action potentials (CMAPs) at three different stable stimulus intensities (10–50% of maximal CMAP). Estimated mean SMUP sizes were calculated using Poisson statistical assumptions from the variance of 500 sequential CMAP obtained at each stimulus intensity. The results with the 500 data points were compared with smaller subsets from the same data set. The results using a range of 50–80% of the 500 data points were compared with the full 500. The effect of restricting analysis to data between 5–20% of the CMAP and to standard deviation limits was also assessed. No differences in mean SMUP size were found with stimulus intensity or use of different ranges of data. Consistency was improved with a greater sample number. Data within 5% of CMAP size gave both increased consistency and reduced mean SMUP size in many subjects, but excluded valid responses present at that stimulus intensity. These changes were more prominent in ALS patients in whom the presence of isolated SMUP responses was a striking difference from normal subjects. Noise, spurious data, and large SMUP limited the Poisson assumptions. When these factors are considered, consistent statistical MUNE can be calculated from a continuous sequence of data points. A 2 to 2.5 SD or 10% window are reasonable methods of limiting data for analysis. Muscle Nerve 27: 320–331, 2003

Model-based clustering in gene expression microarrays: An application to breast cancer data

In microarray studies, the application of clustering techniques is often used to derive meaningful insights into the data. In the past, hierarchical methods have been the primary clustering tool employed to perform this task. The hierarchical algorithms have been mainly applied heuristically to these cluster analysis problems. Further, a major limitation of these methods is their inability to determine the number of clusters. Thus there is a need for a model-based approach to these. clustering problems. To this end, McLachlan et al. [7] developed a mixture model-based algorithm (EMMIX-GENE) for the clustering of tissue samples. To further investigate the EMMIX-GENE procedure as a model-based -approach, we present a case study involving the application of EMMIX-GENE to the breast cancer data as studied recently in van 't Veer et al. [10]. Our analysis considers the problem of clustering the tissue samples on the basis of the genes which is a non-standard problem because the number of genes greatly exceed the number of tissue samples. We demonstrate how EMMIX-GENE can be useful in reducing the initial set of genes down to a more computationally manageable size. The results from this analysis also emphasise the difficulty associated with the task of separating two tissue groups on the basis of a particular subset of genes. These results also shed light on why supervised methods have such a high misallocation error rate for the breast cancer data.

A modified Weibull distribution

A new lifetime distribution capable of modeling a bathtub-shaped hazard-rate function is proposed. The proposed model is derived as a limiting case of the Beta Integrated Model and has both the Weibull distribution and Type I extreme value distribution as special cases. The model can be considered as another useful 3-parameter generalization of the Weibull distribution. An advantage of the model is that the model parameters can be estimated easily based on a Weibull probability paper (WPP) plot that serves as a tool for model identification. Model characterization based on the WPP plot is studied. A numerical example is provided and comparison with another Weibull extension, the exponentiated Weibull, is also discussed. The proposed model compares well with other competing models to fit data that exhibits a bathtub-shaped hazard-rate function.

eMelanoBase: An online locus-specific variant database for familial melanoma

A proportion of melanoma,prone individuals in both familial and non,familial contexts has been shown to carry inactivating mutations in either CDKN2A or, rarely, CDK4. CDKN2A is a complex locus that encodes two unrelated proteins from alternately spliced transcripts that are read in different frames. The alpha transcript (exons 1a, 2, and 3) produces the p16INK4A cyclin-dependent kinase inhibitor, while the beta transcript (exons 1beta and 2) is translated as p14ARF, a stabilizing factor of p53 levels through binding to MDM2. Mutations in exon 2 can impair both polypeptides and insertions and deletions in exons 1alpha, 1beta, and 2, which can theoretically generate p16INK4A,p14ARF fusion proteins. No online database currently takes into account all the consequences of these genotypes, a situation compounded by some problematic previous annotations of CDKN2A related sequences and descriptions of their mutations. As an initiative of the international Melanoma Genetics Consortium, we have therefore established a database of germline variants observed in all loci implicated in familial melanoma susceptibility. Such a comprehensive, publicly accessible database is an essential foundation for research on melanoma susceptibility and its clinical application. Our database serves two types of data as defined by HUGO. The core dataset includes the nucleotide variants on the genomic and transcript levels, amino acid variants, and citation. The ancillary dataset includes keyword description of events at the transcription and translation levels and epidemiological data. The application that handles users' queries was designed in the model,view. controller architecture and was implemented in Java. The object-relational database schema was deduced using functional dependency analysis. We hereby present our first functional prototype of eMelanoBase. The service is accessible via the URL www.wmi.usyd.e, du.au:8080/melanoma.html.

Heritability of adult body height: A comparative study of twin cohorts in eight countries

A major component of variation in body height is due to genetic differences, but environmental factors have a substantial contributory effect. In this study we aimed to analyse whether the genetic architecture of body height varies between affluent western societies. We analysed twin data from eight countries comprising 30,111 complete twin pairs by using the univariate genetic model of the Mx statistical package. Body height and zygosity were self-reported in seven populations and measured directly in one population. We found that there was substantial variation in mean body height between countries; body height was least in Italy (177 cm in men and 163 cm in women) and greatest in the Netherlands (184 cm and 171 cm, respectively). In men there was no corresponding variation in heritability of body height, heritability estimates ranging from 0.87 to 0.93 in populations under an additive genes/unique environment (AE) model. Among women the heritability estimates were generally lower than among men with greater variation between countries, ranging from 0.68 to 0.84 when an additive genes/shared environment/unique environment (ACE) model was used. In four populations where an AE model fit equally well or better, heritability ranged from 0.89 to 0.93. This difference between the sexes was mainly due to the effect of the shared environmental component of variance, which appears to be more important among women than among men in our study populations. Our results indicate that, in general, there are only minor differences in the genetic architecture of height between affluent Caucasian populations, especially among men.

Zygosity Diagnosis in the Absence of Genotypic Data: An Approach Using Latent Class Analysis

For zygosity diagnosis in the absence of genotypic data, or in the recruitment phase of a twin study where only single twins from same-sex pairs are being screened, or to provide a test for sample duplication leading to the false identification of a dizygotic pair as monozygotic, the appropriate analysis of respondents' answers to questions about zygosity is critical. Using data from a young adult Australian twin cohort (N = 2094 complete pairs and 519 singleton twins from same-sex pairs with complete responses to all zygosity items), we show that application of latent class analysis (LCA), fitting a 2-class model, yields results that show good concordance with traditional methods of zygosity diagnosis, but with certain important advantages. These include the ability, in many cases, to assign zygosity with specified probability on the basis of responses of a single informant (advantageous when one zygosity type is being oversampled); and the ability to quantify the probability of misassignment of zygosity, allowing prioritization of cases for genotyping as well as identification of cases of probable laboratory error. Out of 242 twins (from 121 like-sex pairs) where genotypic data were available for zygosity confirmation, only a single case was identified of incorrect zygosity assignment by the latent class algorithm. Zygosity assignment for that single case was identified by the LCA as uncertain (probability of being a monozygotic twin only 76%), and the co-twin's responses clearly identified the pair as dizygotic (probability of being dizygotic 100%). In the absence of genotypic data, or as a safeguard against sample duplication, application of LCA for zygosity assignment or confirmation is strongly recommended.

Systematic characterization of mutations in yeast acetohydroxyacid synthase: Interpretation of herbicide-resistance data

Acetohydroxyacid synthase (AHAS, EC 4.1.3.18) catalyses the first step in branched-chain amino acid biosynthesis and is the target for sulfonylurea and imidazolinone herbicides, which act as potent and specific inhibitors. Mutants of the enzyme have been identified that are resistant to particular herbicides. However, the selectivity of these mutants towards various sulfonylureas and imidazolinones has not been determined systematically. Now that the structure of the yeast enzyme is known, both in the absence and presence of a bound herbicide, a detailed understanding of the molecular interactions between the enzyme and its inhibitors becomes possible. Here we construct 10 active mutants of yeast AHAS, purify the enzymes and determine their sensitivity to six sulfonylureas and three imidazolinones. An additional three active mutants were constructed with a view to increasing imidazolinone sensitivity. These three variants were purified and tested for their sensitivity to the imidazolinones only. Substantial differences are observed in the sensitivity of the 13 mutants to the various inhibitors and these differences are interpreted in terms of the structure of the herbicide-binding site on the enzyme.

A yield architecture framework to explain adaptation of pearl millet to environmental stress

Functional knowledge of the physiological basis of crop adaptation to stress is a prerequisite for exploiting specific adaptation to stress environments in breeding programs. This paper presents an analysis of yield components for pearl millet, to explain the specific adaptation of local landraces to stress environments in Rajasthan, India. Six genotypes, ranging from high-tillering traditional landraces to low-tillering open-pollinated modern cultivars, were grown in 20 experiments, covering a range of nonstress and drought stress patterns. In each experiment, yield components (particle number, grain number, 100 grain mass) were measured separately for main shoots, basal tillers, and nodal tillers. Under optimum conditions, landraces had a significantly lower grain yield than the cultivars, but no significant differences were observed at yield levels around 1 ton ha(-1). This genotype x environment interaction for grain yield was due to a difference in yield strategy, where landraces aimed at minimising the risk of a crop failure under stress conditions, and modem cultivars aimed at maximising yield potential under optimum conditions. A key aspect of the adaptation of landraces was the small size of the main shoot panicle, as it minimised (1) the loss of productive tillers during stem elongation; (2) the delay in anthesis if mid-season drought occurs; and (3) the reduction in panicle productivity of the basal tillers under stress. In addition, a low investment in structural panicle weight, relative to vegetative crop growth rate, promoted the production of nodal tillers, providing a mechanism to compensate for reduced basal tiller productivity if stress occurred around anthesis. A low maximum 100 grain mass also ensured individual grain mass was little affected by environmental conditions. The strategy of the high-tillering landraces carries a yield penalty under optimum conditions, but is expected to minimise the risk of a crop failure, particularly if mid-season drought stress occurs. The yield architecture of low-tillering varieties, by contrast, will be suited to end-of-season drought stress, provided anthesis is early. Application of the above adaptation mechanisms into a breeding program could enable the identification of plant types that match the prevalent stress patterns in the target environments. (C) 2003 E.J. van Oosterom. Published by Elsevier Science B.V. All rights reserved.

Data Mart para apoio ?? capacita????o em gest??o de pol??ticas p??blicas voltado para uma Escola de Administra????o P??blica

Este trabalho consiste num estudo de caso que se destina ao desenvolvimento de um Data Mart que possibilite a Escola Nacional de Administra????o P??blica ??? ENAP conhecer o perfil e o panorama geral da situa????o funcional dos servidores p??blicos federais que se capacitaram na Escola nos ??ltimos 7 anos. O aplicativo foi desenvolvido cruzando o banco de dados do sistema gerenciador dos cursos ministrados pela ENAP, onde est??o armazenadas informa????es sobre os alunos capacitados, os cursos realizados, os resultados alcan??ados, o perfil dos docentes e demais informa????es relativas ??s atividades da Escola, com os dados gerados pelo Sistema Integrado de Administra????o de Recursos Humanos ??? SIAPE, cuja extra????o de dados foi direcionada para os registros sobre a situa????o funcional, cargos, carreiras, fun????es, ??rg??os e alguns dados pessoais dos alunos, servidores p??blicos federais que se encontram registrados no SIAPE