GeneMCL in microarray analysis

Accurately and reliably identifying the actual number of clusters present with a dataset of gene expression profiles, when no additional information on cluster structure is available, is a problem addressed by few algorithms. GeneMCL transforms microarray analysis data into a graph consisting of nodes connected by edges, where the nodes represent genes, and the edges represent the similarity in expression of those genes, as given by a proximity measurement. This measurement is taken to be the Pearson correlation coefficient combined with a local non-linear rescaling step. The resulting graph is input to the Markov Cluster (MCL) algorithm, which is an elegant, deterministic, non-specific and scalable method, which models stochastic flow through the graph. The algorithm is inherently affected by any cluster structure present, and rapidly decomposes a graph into cohesive clusters. The potential of the GeneMCL algorithm is demonstrated with a 5730 gene subset (IGS) of the Van't Veer breast cancer database, for which the clusterings are shown to reflect underlying biological mechanisms. (c) 2005 Elsevier Ltd. All rights reserved.

Multiprobabilistic prediction in early medical diagnoses

This paper describes the methodology of providing multiprobability predictions for proteomic mass spectrometry data. The methodology is based on a newly developed machine learning framework called Venn machines. Is allows to output a valid probability interval. The methodology is designed for mass spectrometry data. For demonstrative purposes, we applied this methodology to MALDI-TOF data sets in order to predict the diagnosis of heart disease and early diagnoses of ovarian cancer and breast cancer. The experiments showed that probability intervals are narrow, that is, the output of the multiprobability predictor is similar to a single probability distribution. In addition, probability intervals produced for heart disease and ovarian cancer data were more accurate than the output of corresponding probability predictor. When Venn machines were forced to make point predictions, the accuracy of such predictions is for the most data better than the accuracy of the underlying algorithm that outputs single probability distribution of a label. Application of this methodology to MALDI-TOF data sets empirically demonstrates the validity. The accuracy of the proposed method on ovarian cancer data rises from 66.7 % 11 months in advance of the moment of diagnosis to up to 90.2 % at the moment of diagnosis. The same approach has been applied to heart disease data without time dependency, although the achieved accuracy was not as high (up to 69.9 %). The methodology allowed us to confirm mass spectrometry peaks previously identified as carrying statistically significant information for discrimination between controls and cases.

Radon in homes and risk of lung cancer: collaborative analysis of individual data from 13 European case-control studies

Objective: To determine the risk of lung cancer associated with exposure at home to the radioactive disintegration products of naturally Occurring radon gas. Design: Collaborative analysis of individual data from 13 case-control studies of residential radon and lung cancer. Setting Nine European countries. Subjects 7148 cases Of lung cancer and 14 208 controls. Main outcome measures: Relative risks of lung cancer and radon gas concentrations in homes inhabited during the previous 5-34 years measured in becquerels (radon disintegrations per second) per cubic incite (Bq/m(3)) Of household air. Results: The mean measured radon concentration in homes of people in tire control group was 97 Bq/m(3), with 11% measuring > 200 and 4% measuring > 400 Bq/m(3). For cases of lung cancer the mean concentration was 104 Bq/m(3). The risk of lung cancer increased by 8.4% (95% confidence interval 3.0% to 15.8%) per 100 Bq/m(3) increase in measured radon (P = 0.0007). This corresponds to an increase of 16% (5% to 31%) per 100 Bq/m(3) increase in usual radon-that is, after correction for the dilution caused by random uncertainties in measuring radon concentrations. The dose-response relation seemed to be linear with no threshold and remained significant (P=0.04) in analyses limited to individuals from homes with measured radon < 200 Bq/m(3). The proportionate excess risk did not differ significantly with study, age, sex, or smoking. In the absence of other causes of death, the absolute risks of lung cancer by age 75 years at usual radon concentrations of 0, 100, and 400 Bq/m(3) would be about 0.4%, 0.5%, and 0.7%, respectively, for lifelong non-smokers, and about 25 times greater (10%, 12%, and 16%) for cigarette smokers. Conclusions: Collectively, though not separately, these studies show appreciable hazards from residential radon, particularly for smokers and recent ex-smokers, and indicate that it is responsible for about 2% of all deaths from cancer in Europe.

A process for analysis of microarray comparative genomics hybridisation studies for bacterial genomes

Background: Microarray based comparative genomic hybridisation (CGH) experiments have been used to study numerous biological problems including understanding genome plasticity in pathogenic bacteria. Typically such experiments produce large data sets that are difficult for biologists to handle. Although there are some programmes available for interpretation of bacterial transcriptomics data and CGH microarray data for looking at genetic stability in oncogenes, there are none specifically to understand the mosaic nature of bacterial genomes. Consequently a bottle neck still persists in accurate processing and mathematical analysis of these data. To address this shortfall we have produced a simple and robust CGH microarray data analysis process that may be automated in the future to understand bacterial genomic diversity. Results: The process involves five steps: cleaning, normalisation, estimating gene presence and absence or divergence, validation, and analysis of data from test against three reference strains simultaneously. Each stage of the process is described and we have compared a number of methods available for characterising bacterial genomic diversity, for calculating the cut-off between gene presence and absence or divergence, and shown that a simple dynamic approach using a kernel density estimator performed better than both established, as well as a more sophisticated mixture modelling technique. We have also shown that current methods commonly used for CGH microarray analysis in tumour and cancer cell lines are not appropriate for analysing our data. Conclusion: After carrying out the analysis and validation for three sequenced Escherichia coli strains, CGH microarray data from 19 E. coli O157 pathogenic test strains were used to demonstrate the benefits of applying this simple and robust process to CGH microarray studies using bacterial genomes.

Parabens can enable hallmarks and characteristics of cancer in human breast epithelial cells: a review of the literature with reference to new exposure data and regulatory status

A framework for understanding the complexity of cancer development was established by Hanahan and Weinberg in their definition of the hallmarks of cancer. In this review, we consider the evidence that parabens can enable development in human breast epithelial cells of 4/6 of the basic hallmarks, 1/2 of the emerging hallmarks and 1/2 of the enabling characteristics. Hallmark 1: parabens have been measured as present in 99% of human breast tissue samples, possess oestrogenic activity and can stimulate sustained proliferation of human breast cancer cells at concentrations measurable in the breast. Hallmark 2: parabens can inhibit the suppression of breast cancer cell growth by hydroxytamoxifen, and through binding to the oestrogen-related receptor gamma (ERR) may prevent its deactivation by growth inhibitors. Hallmark 3: in the 10nM to 1M range, parabens give a dose-dependent evasion of apoptosis in high-risk donor breast epithelial cells. Hallmark 4: long-term exposure (>20weeks) to parabens leads to increased migratory and invasive activity in human breast cancer cells, properties which are linked to the metastatic process. Emerging hallmark: methylparaben has been shown in human breast epithelial cells to increase mTOR, a key regulator of energy metabolism. Enabling characteristic: parabens can cause DNA damage at high concentrations in the short term but more work is needed to investigate long-term low-doses of mixtures. The ability of parabens to enable multiple cancer hallmarks in human breast epithelial cells provides grounds for regulatory review of the implications of the presence of parabens in human breast tissue.

Peptides generated ex vivo from serum proteins by tumor-specific exopeptidases are not useful biomarkers in ovarian cancer

BACKGROUND: The serum peptidome may be a valuable source of diagnostic cancer biomarkers. Previous mass spectrometry (MS) studies have suggested that groups of related peptides discriminatory for different cancer types are generated ex vivo from abundant serum proteins by tumor-specific exopeptidases. We tested 2 complementary serum profiling strategies to see if similar peptides could be found that discriminate ovarian cancer from benign cases and healthy controls. METHODS: We subjected identically collected and processed serum samples from healthy volunteers and patients to automated polypeptide extraction on octadecylsilane-coated magnetic beads and separately on ZipTips before MALDI-TOF MS profiling at 2 centers. The 2 platforms were compared and case control profiling data analyzed to find altered MS peak intensities. We tested models built from training datasets for both methods for their ability to classify a blinded test set. RESULTS: Both profiling platforms had CVs of approximately 15% and could be applied for high-throughput analysis of clinical samples. The 2 methods generated overlapping peptide profiles, with some differences in peak intensity in different mass regions. In cross-validation, models from training data gave diagnostic accuracies up to 87% for discriminating malignant ovarian cancer from healthy controls and up to 81% for discriminating malignant from benign samples. Diagnostic accuracies up to 71% (malignant vs healthy) and up to 65% (malignant vs benign) were obtained when the models were validated on the blinded test set. CONCLUSIONS: For ovarian cancer, altered MALDI-TOF MS peptide profiles alone cannot be used for accurate diagnoses.

The survival advantage of milk and dairy consumption: An overview of evidence from cohort studies of vascular diseases, diabetes and cancer

Objectives: To conduct it detailed evaluation, with meta-analyses, of the published evidence on milk and dairy consumption and the incidence of vascular diseases and diabetes. Also to summarise the evidence on milk and dairy consumption and cancer reported by the World Cancer Research Fund and then to consider the relevance of milk and dairy consumption to survival in the UK, a typical Western community. Finally, published evidence on relationships with whole milk and fat-reduced milks was examined. Methods: Prospective cohort studies of vascular disease and diabetes with baseline data on milk or dairy consumption and a relevant disease outcome were identified by searching MEDLINE, and reference lists in the relevant published reports. Meta-analyses of relationships in these reports were conducted. The likely effect of milk and dairy consumption on survival was then considered, taking into account the results of published overviews of relationships of these foods with cancer. Results: From meta-analysis of 15 studies the relative risk of stroke and/or heart disease in subjects with high milk or dairy consumption was 0.84 (95% CI 0.76, 0,93) and 0.79 (0.75, 0.82) respectively, relative to the risk in those with low consumption. Four studies reported incident diabetes as an outcome, and the relative risk in the Subjects with the highest intake of milk or diary foods was 0.92 (0.86, 0.97). Conclusions: Set against the proportion of total deaths attributable to the life-threatening diseases in the UK, vascular disease, diabetes and cancer, the results of meta-analyses provide evidence of an overall survival advantage from the consumption of milk and dairy foods.

Relationship between milk consumption and prostate cancer: a short review

Epidemiological evidence based on both case–control and prospective cohort studies points to an overall positive relationship between consumption of milk/dairy products and the risk of developing prostate cancer. There are inconsistencies in the data, but taken together, the increased relative risk does not seem to be high. A number of mechanisms have been proposed to account for the relationship, with most attention being focused on the involvement of calcium/vitamin D, insulin-like growth factor-1 and oestrogens, although it is unlikely that a single factor in milk is implicated. In any event, any added risk of prostate cancer from increased milk consumption has to be set alongside other evidence, which shows that increased milk consumption can provide substantially reduced risk of coronary heart disease, stroke and colorectal cancer, particularly because cardiovascular disease accounts for vastly more deaths than prostate cancer (although the latter is of course restricted to men).

Mixture models for capture-recapture count data

The contribution investigates the problem of estimating the size of a population, also known as the missing cases problem. Suppose a registration system is targeting to identify all cases having a certain characteristic such as a specific disease (cancer, heart disease, ...), disease related condition (HIV, heroin use, ...) or a specific behavior (driving a car without license). Every case in such a registration system has a certain notification history in that it might have been identified several times (at least once) which can be understood as a particular capture-recapture situation. Typically, cases are left out which have never been listed at any occasion, and it is this frequency one wants to estimate. In this paper modelling is concentrating on the counting distribution, e.g. the distribution of the variable that counts how often a given case has been identified by the registration system. Besides very simple models like the binomial or Poisson distribution, finite (nonparametric) mixtures of these are considered providing rather flexible modelling tools. Estimation is done using maximum likelihood by means of the EM algorithm. A case study on heroin users in Bangkok in the year 2001 is completing the contribution.

The tagged microarray marker (TAM) method for high-throughput detection of single nucleotide and indel polymorphisms

The tagged microarray marker (TAM) method allows high-throughput differentiation between predicted alternative PCR products. Typically, the method is used as a molecular marker approach to determining the allelic states of single nucleotide polymorphisms (SNPs) or insertion-deletion (indel) alleles at genomic loci in multiple individuals. Biotin-labeled PCR products are spotted, unpurified, onto a streptavidin-coated glass slide and the alternative products are differentiated by hybridization to fluorescent detector oligonucleotides that recognize corresponding allele-specific tags on the PCR primers. The main attractions of this method are its high throughput (thousands of PCRs are analyzed per slide), flexibility of scoring (any combination, from a single marker in thousands of samples to thousands of markers in a single sample, can be analyzed) and flexibility of scale (any experimental scale, from a small lab setting up to a large project). This protocol describes an experiment involving 3,072 PCRs scored on a slide. The whole process from the start of PCR setup to receiving the data spreadsheet takes 2 d.

Comparison of the global gene expression profiles produced by methylparaben, n-butylparaben and 17 beta-oestradiol in MCF7 human breast cancer cells

Since the alkyl esters of p-hydroxybenzoic acid (parabens) can be measured intact in the human breast and possess oestrogenic properties, it has been suggested that they could contribute to an aberrant burden of oestrogen signalling in the human breast and so play a role in the rising incidence of breast cancer. However, although parabens have been shown to regulate a few single genes (reporter genes, pS2, progesterone receptor) in a manner similar to that of 17 beta-oestradiol, the question remains as to the full extent of the similarity in the overall gene profile induced in response to parabens compared with 17 beta-oestradiol. The GE-Amersham CodeLink 20 K human expression microarray system was used to profile the expression of 19881 genes in MCF7 human breast cancer cells following a 7-day exposure to 5 x 10(-4) m methylparaben, 10(-5) m n-butylparaben and 10(-8) m 17 beta-oestradiol. At these concentrations, the parabens gave growth responses in MCF7 cells of similar magnitude to 17 beta-oestradiol. The study identified genes which are upregulated or downregulated to a similar extent by methylparaben, n-butylparaben and 17 beta-oestradiol. However, the majority of genes were not regulated in the same way by all three treatments. Some genes responded differently to parabens from 17 beta-oestradiol, and furthermore, differences in expression of some genes could be detected even between the two individual parabens. Therefore, although parabens possess oestrogenic properties, their mimicry in terms of global gene expression patterns is not perfect and differences in gene expression profiles could result in consequences to the cells that are not identical to those following exposure to 17 beta-oestradiol. Copyright (c) 2006 John Wiley & Sons, Ltd.

Transcriptional profiling of the LPS induced NF-kappaB response in macrophages

BACKGROUND: Exposure of macrophages to bacterial products such as lipopolysaccharide (LPS) results in activation of the NF-kappaB transcription factor, which orchestrates a gene expression programme that underpins the macrophage-dependent immune response. These changes include the induction or repression of a wide range of genes that regulate inflammation, cell proliferation, migration and cell survival. This process is tightly regulated and loss of control is associated with conditions such as septic shock, inflammatory diseases and cancer. To study this response, it is important to have in vitro model systems that reflect the behaviour of cells in vivo. In addition, it is necessary to understand the natural differences that can occur between individuals. In this report, we have investigated and compared the LPS response in macrophage derived cell lines and peripheral blood mononuclear cell (PBMC) derived macrophages. RESULTS: Gene expression profiles were determined following LPS treatment of THP-1 cells for 1 and 4 hours. LPS significantly induced or repressed 72 out of 465 genes selected as being known or putative NF-kappaB target genes, which exhibited 4 temporal patterns of expression. Results for 34 of these genes, including several genes not previously identified as LPS target genes, were validated using real time PCR. A high correlation between microarray and real time PCR data was found. Significantly, the LPS induced expression profile of THP-1 cells, as determined using real time PCR, was found to be very similar to that of human PBMC derived macrophages. Interestingly, some differences were observed in the LPS response between the two donor PBMC macrophage populations. Surprisingly, we found that the LPS response in U937 cells was dramatically different to both THP-1 and PBMC derived macrophages. CONCLUSION: This study revealed a dynamic and diverse transcriptional response to LPS in macrophages, involving both the induction and repression of gene expression in a time dependent manner. Moreover, we demonstrated that the LPS induced transcriptional response in the THP-1 cell line is very similar to primary PBMC derived macrophages. Therefore, THP-1 cells represent a good model system for studying the mechanisms of LPS and NF-kappaB dependent gene expression.

Recorded quadrant incidence of female breast cancer in Great Britain suggests a disproportionate increase in the upper outer quadrant of the breast

Background: The upper outer quadrant (UOQ) of the breast is the most frequent site for incidence of breast cancel; but the reported disproportionate incidence in this quadrant appears to rise with year of publication. Materials and Methods: In order to determine whether this increasing incidence in the UOQ is an artifact of different study populations or is chronological, data have been analysed for annual quadrant incidence of female breast cancer recorded nationally in England and Wales between 1979 and 2000 and in Scotland between 1980 and 2001. Results: In England and Wales, the recorded incidence of female breast cancer in the UOQ rose front 47.9% in 1979 to 53.3% in 2000, and has done so linearly over tune with a con-elation coefficient R of +/- 0.71 +/- SD 0.01 (p < 0.001). Analysis of independent data front Scotland showed a similar trend in that recorded female breast cancer had also increased in the UOQ from 38.3% in 1980 to 54.7% in 2001, with a con-elation coefficient R for the linear annual increase of +0.80 +/- SD 0.03 (p < 0.001). Conclusion: These results are inconsistent with current views that the high level of UOQ breast cancer is due solely to a greater amount of target epithelial tissue in that region. Identification of the reasons for such a disproportionate site-specific increase could provide clues as to causative factors in breast cancer.

Endocrine disrupters and human health: Could oestrogenic chemicals in body care cosmetics adversely affect breast cancer incidence in women? A review of evidence and call for further research

In the decade that has elapsed since the suggestion that exposure of the foetal/developing male to environmental oestrogens could be the cause of subsequent reproductive and developmental effects in men, there has been little definitive research to provide conclusions to the hypothesis. Issues of exposure and low potency of environmental oestrogens may have reduced concerns. However, the hypothesis that chemicals applied in body care cosmetics (including moisturizers, creams, sprays or lotions applied to axilla or chest or breast areas) may be affecting breast cancer incidence in women presents a different case scenario, not least in the consideration of the exposure issues. The specific cosmetic type is not relevant but the chemical ingredients in the formulations and the application to the skin is important. The most common group of body care cosmetic formulation excipients, namely p-hydroxybenzoic acid esters or parabens, have been shown recently to be oestrogenic in vitro and in vivo and now have been detected in human breast tumour tissue, indicating absorption (route and causal associations have yet to be confirmed). The hypothesis for a link between oestrogenic ingredients in underarm and body care cosmetics and breast cancer is forwarded and reviewed here in terms of. data on exposure to body care cosmetics and parabens, including dermal absorption; paraben oestrogenicity; the role of oestrogen in breast cancer; detection of parabens in breast tumours; recent epidemiology studies of underarm cosmetics use and breast cancer; the toxicology database; the current regulatory status of parabens and regulatory toxicology data uncertainties. Notwithstanding the major public health issue of the causes of the rising incidence of breast cancer in women, this call for further research may provide the first evidence that environmental factors may be adversely affecting human health by endocrine disruption, because exposure to oestrogenic chemicals through application of body care products (unlike diffuse environmental chemical exposures) should be amenable to evaluation, quantification and control. The exposure issues are clear and the exposed population is large, and these factors should provide the necessary impetus to investigate this potential issue of public health. Copyright (C) 2004 John Wiley Sons, Ltd.

Serum proteomic abnormality predating screen detection of ovarian cancer

Ovarian cancer is characterized by vague, non-specific symptoms, advanced stage at diagnosis and poor overall survival. A nested case control study was undertaken on stored serial serum samples from women who developed ovarian cancer and healthy controls (matched for serum processing and storage conditions as well as attributes such as age) in a pilot randomized controlled trial of ovarian cancer screening. The unique feature of this study is that the women were screened for up to 7 years. The serum samples underwent prefractionation using a reversed-phase batch extraction protocol prior to MALDI-TOF MS data acquisition. Our exploratory analysis shows that combining a single MS peak with CA125 allows statistically significant discrimination at the 5% level between cases and controls up to 12 months in advance of the original diagnosis of ovarian cancer. Such combinations work much better than a single peak or CA125 alone. This paper demonstrates that mass spectra from the low molecular weight serum proteome carry information useful for early detection of ovarian cancer. The next step is to identify the specific biomarkers that make early detection possible.