Comodularity and detection of co-communities

This paper introduces the notion of comodularity, to cocluster observations of bipartite networks into co-communities. The task of coclustering is to group together nodes of one type with nodes of another type, according to the interactions that are the most similar. The measure of comodularity is introduced to assess the strength of co-communities, as well as to arrange the representation of nodes and clusters for visualization, and to define an objective function for optimization. We demonstrate the usefulness of our proposed methodology on simulated data, and with examples from genomics and consumer-product reviews

Detection of epigenomic network community oncomarkers

In this paper we propose network methodology to infer prognostic cancer biomarkers based on the epigenetic pattern DNA methylation. Epigenetic processes such as DNA methylation reflect environmental risk factors, and are increasingly recognised for their fundamental role in diseases such as cancer. DNA methylation is a gene-regulatory pattern, and hence provides a means by which to assess genomic regulatory interactions. Network models are a natural way to represent and analyse groups of such interactions. The utility of network models also increases as the quantity of data and number of variables increase, making them increasingly relevant to large-scale genomic studies. We propose methodology to infer prognostic genomic networks from a DNA methylation-based measure of genomic interaction and association. We then show how to identify prognostic biomarkers from such networks, which we term “network community oncomarkers”. We illustrate the power of our proposed methodology in the context of a large publicly available breast cancer dataset

Single-cell Co-expression Subnetwork Analysis

Single-cell transcriptomic data have rapidly become very popular in genomic science. Genomic science also has a long history of using network models to understand the way in which genes work together to carry out specific biological functions. However, working with single-cell data presents major challenges, such as zero inflation and technical noise. These challenges require methods to be specifically adapted to the context of single-cell data. Recently, much effort has been made to develop the theory behind statistical network models. This has lead to many new models being proposed, and has provided a thorough understanding of the properties of existing models. However, a large amount of this work assumes binary-valued relationships between network nodes, whereas genomic network analysis is traditionally based on continuous-valued correlations between genes. In this paper, we assess several established methods for genomic network analysis, we compare ways that these methods can be adapted to the single-cell context, and we use mixture-models to infer binary-valued relationships based on gene-gene correlations. Based on these binary relationships, we find that excellent results can be achieved by using subnetwork analysis methodology popular amongst network statisticians. This methodology thereby allows detection of functional subnetwork modules within these single-cell genomic networks

Network models of stochastic processes in cancer

Complex systems which can be modelled as networks are ubiquitous. Well-known examples include social and economic networks, as well as many examples in cell biology such as gene regulatory and protein signalling networks. Many cell biological processes are inherently stochastic and non-stationary, and this is the perspective from which I have developed novel mathematical and computational statistical models, focusing particularly on network models. These models are primarily motivated by cell biological processes relating to DNA methylation and stem cell and cancer biology, but can be generalised to other systems and domains. I have used these and other models to identify and analyse novel DNA-based cancer biomarkers

Inference of tissue relative proportions of the breast epithelial cell types luminal progenitor, basal, and luminal mature

Single-cell analysis has revolutionised genomic science in recent years. However, due to cost and other practical considerations, single-cell analyses are impossible for studies based on medium or large patient cohorts. For example, a single-cell analysis usually costs thousands of euros for one tissue sample from one volunteer, meaning that typical studies using single-cell analyses are based on very few individuals. While single-cell genomic data can be used to examine the phenotype of individual cells, cell-type deconvolution methods are required to track the quantities of these cells in bulk-tissue genomic data. Hormone receptor negative breast cancers are highly aggressive, and are thought to originate from a subtype of epithelial cells called the luminal progenitor. In this paper, we show how to quantify the number of luminal progenitor cells as well as other epithelial subtypes in breast tissue samples using DNA and RNA based measurements. We find elevated levels of cells which resemble these hormone receptor negative luminal progenitor cells in breast tumour biopsies of hormone receptor negative cancers, as well as in healthy breast tissue samples from BRCA1 (FANCS) mutation carriers. We also find that breast tumours from carriers of heterozygous mutations in non-BRCA Fanconi Anaemia pathway genes are much more likely to be hormone receptor negative. These findings have implications for understanding hormone receptor negative breast cancers, and for breast cancer screening in carriers of heterozygous mutations of Fanconi Anaemia pathway genes

Corruption of the Intra-Gene DNA Methylation Architecture Is a Hallmark of Cancer

Epigenetic processes - including DNA methylation - are increasingly seen as having a fundamental role in chronic diseases like cancer. It is well known that methylation levels at particular genes or loci differ between normal and diseased tissue. Here we investigate whether the intra-gene methylation architecture is corrupted in cancer and whether the variability of levels of methylation of individual CpGs within a defined gene is able to discriminate cancerous from normal tissue, and is associated with heterogeneous tumour phenotype, as defined by gene expression. We analysed 270985 CpGs annotated to 18272 genes, in 3284 cancerous and 681 normal samples, corresponding to 14 different cancer types. In doing so, we found novel differences in intra-gene methylation pattern across phenotypes, particularly in those genes which are crucial for stem cell biology; our measures of intra-gene methylation architecture are a better determinant of phenotype than measures based on mean methylation level alone (K-S test [Formula: see text] in all 14 diseases tested). These per-gene methylation measures also represent a considerable reduction in complexity, compared to conventional per-CpG beta-values. Our findings strongly support the view that intra-gene methylation architecture has great clinical potential for the development of DNA-based cancer biomarkers

Epigenetic reprogramming of fallopian tube fimbriae in BRCA mutation carriers defines early ovarian cancer evolution

The exact timing and contribution of epigenetic reprogramming to carcinogenesis are unclear. Women harbouring BRCA1/2 mutations demonstrate a 30–40-fold increased risk of high-grade serous extra-uterine Müllerian cancers (HGSEMC), otherwise referred to as ‘ovarian carcinomas’, which frequently develop from fimbrial cells but not from the proximal portion of the fallopian tube. Here we compare the DNA methylome of the fimbrial and proximal ends of the fallopian tube in BRCA1/2 mutation carriers and non-carriers. We show that the number of CpGs displaying significant differences in methylation levels between fimbrial and proximal fallopian tube segments are threefold higher in BRCA mutation carriers than in controls, correlating with overexpression of activation-induced deaminase in their fimbrial epithelium. The differentially methylated CpGs accurately discriminate HGSEMCs from non-serous subtypes. Epigenetic reprogramming is an early pre-malignant event integral to BRCA1/2 mutation-driven carcinogenesis. Our findings may provide a basis for cancer-preventative strategies

Whole breast and regional nodal irradiation in prone versus supine position in left sided breast cancer

Background: Prone whole breast irradiation (WBI) leads to reduced heart and lung doses in breast cancer patients receiving adjuvant radiotherapy. In this feasibility trial, we investigated the prone position for whole breast + lymph node irradiation (WB + LNI). Methods: A new support device was developed for optimal target coverage, on which patients are positioned in a position resembling a phase from the crawl swimming technique (prone crawl position). Five left sided breast cancer patients were included and simulated in supine and prone position. For each patient, a treatment plan was made in prone and supine position for WB + LNI to the whole axilla and the unoperated part of the axilla. Patients served as their own controls for comparing dosimetry of target volumes and organs at risk (OAR) in prone versus in supine position. Results: Target volume coverage differed only slightly between prone and supine position. Doses were significantly reduced (P < 0.05) in prone position for ipsilateral lung (Dmean, D2, V5, V10, V20, V30), contralateral lung (Dmean, D2), contralateral breast (Dmean, D2 and for total axillary WB + LNI also V5), thyroid (Dmean, D2, V5, V10, V20, V30), oesophagus (Dmean and for partial axillary WB + LNI also D2 and V5), skin (D2 and for partial axillary WB + LNI V105 and V107). There were no significant differences for heart and humeral head doses. Conclusions: Prone crawl position in WB + LNI allows for good breast and nodal target coverage with better sparing of ipsilateral lung, thyroid, contralateral breast, contralateral lung and oesophagus when compared to supine position. There is no difference in heart and humeral head doses

The effect of prior statin use on 30-day mortality for patients hospitalized with community-acquired pneumonia

BACKGROUND: Recent studies suggest that HMG-CoA reductase inhibitors ("statins") may have beneficial effects for patients at risk for some types of infections. We examined the effect of prior outpatient use of statins on mortality for patients hospitalized with community-acquired pneumonia. METHODS: A retrospective cohort study conducted at two tertiary teaching hospitals. Eligible subjects were admitted with a diagnosis of, had a chest x-ray consistent with, and had a discharge ICD-9 diagnosis of pneumonia. Subjects were excluded if they were "comfort measures only" or transferred from another acute care hospital. Subjects were considered to be on a medication if they were taking it at the time of presentation. RESULTS: Data was abstracted on 787 subjects at the two hospitals. Mortality was 9.2% at 30-days and 13.6% at 90-days. At presentation 52% of subjects were low risk, 34% were moderate risk, and 14% were high risk based on the pneumonia severity index. In the multivariable regression analysis, after adjusting for potential confounders including a propensity score, the use of statins at presentation (odds ratio 0.36, 95% confidence interval 0.14–0.92) was associated with decreased 30-day mortality. DISCUSSION: Prior outpatient statin use was associated with decreased mortality in patients hospitalized with community-acquired pneumonia despite their use being associated with comorbid illnesses likely to contribute to increased mortality. Confirmatory studies are needed, as well as research to determine the mechanism(s) of this protective effect

The availability of novelty sweets within the high school fringe

Background Reducing sugar consumption is a primary focus of current global public health policy. Achieving 5% of total energy from free sugars will be difficult acknowledging the concentration of free sugars in sugar sweetened beverages, confectionery and as hidden sugars in many savoury items. The expansion of the novelty sweet market in the UK has significant implications for children and young adults as they contribute to dental caries, dental erosion and obesity. Objective To identify the most available types of novelty sweets within the high school fringe in Cardiff, UK and to assess their price range and where and how they were displayed in shops. Subjects and methods Shops within a ten minute walking distance around five purposively selected high schools in the Cardiff aea representing different levels of deprivation were visited. Shops in Cardiff city centre and three supermarkets were also visited to identify the most commonly available novelty sweets. Results The ten most popular novelty sweets identified in these scoping visits were (in descending order): Brain Licker, Push Pop, Juicy Drop, Lickedy Lips, Big Baby Pop, Vimto candy spray, Toxic Waste, Tango candy spray, Brain Blasterz Bitz and Mega Mouth candy spray. Novelty sweets were located on low shelves which were accessible to all age-groups in 73% (14 out of 19) of the shops. Novelty sweets were displayed in the checkout area in 37% (seven out of 19) shops. The price of the top ten novelty sweets ranged from 39p to £1. Conclusion A wide range of acidic and sugary novelty sweets were easily accessible and priced within pocket money range. Those personnel involved in delivering dental and wider health education or health promotion need to be aware of recent developments in children's confectionery. The potential effects of these novelty sweets on both general and dental health require further investigation