Untangling the ATR-CHEK1 network for prognostication, prediction and therapeutic target validation in breast cancer

Background: ATR-Chk1 signalling network is critical for genomic stability. ATR-Chk1 may be deregulated in breast cancer and have prognostic, predictive and therapeutic significance. Patients and methods: We investigated ATR and phosphorylated CHK1Ser345 protein (pChk1) expression in 1712 breast cancers (Nottingham Tenovus series). ATR and Chk1 mRNA were evaluated in 1950 breast cancers (METABRIC cohort). Pre-clinically, biological consequences of ATR gene knockdown or ATR inhibition by small molecule inhibitor (VE-821) were investigated in MCF-7 and MDA-MB-231 breast cancer cell lines and in non-tumorigenic breast epithelial cells (MCF10A). Results: High ATR and high cytoplasmic pChk1 expression was significantly associated with higher tumour stage, higher mitotic index, pleomorphism and lymphovascular invasion. In univariate analysis, high ATR and high cytoplasmic pChk1 protein expression was associated with shorter breast cancer specific survival (BCSS). In multivariate analysis, high ATR remains an independent predictor of adverse outcome. At the mRNA level, high Chk1 remains associated with aggressive phenotypes including lymph node positivity, high grade, Her-2 overexpression, triple-negative phenotype and molecular classes associated with aggressive behaviour and shorter survival.. Pre-clinically, Chk1 phosphorylation at serine 345 following replication stress (induced by gemcitabine or hydroxyurea treatment) was impaired in ATR knockdown and in VE-821 treated breast cancer cells. Doxycycline inducible knockdown of ATR suppressed growth, which was restored when ATR was re-expressed. Similarly, VE-821 treatment resulted in a dose dependent suppression of cancer cell growth and survival (MCF7 and MDA-MB-231) but had no effect on non-tumorigenic breast epithelial cells (MCF10A). Conclusions: We provides evidence that ATR and Chk1 are promising biomarkers and rational drug target for personalized therapy in breast cancer

Semiconductor nanostructure quantum ratchet for high efficiency solar cells

Conventional solar cell efficiencies are capped by the ~31% Shockley–Queisser limit because, even with an optimally chosen bandgap, some red photons will go unabsorbed and the excess energy of the blue photons is wasted as heat. Here we demonstrate a “quantum ratchet” device that avoids this limitation by inserting a pair of linked states that form a metastable photoelectron trap in the bandgap. It is designed both to reduce non-radiative recombination, and to break the Shockley–Queisser limit by introducing an additional “sequential two photon absorption” (STPA) excitation channel across the bandgap. We realise the quantum ratchet concept with a semiconductor nanostructure. It raises the electron lifetime in the metastable trap by ~104, and gives a STPA channel that increases the photocurrent by a factor of ~50%. This result illustrates a new paradigm for designing ultra-efficient photovoltaic devices

PedGenie: meta genetic association testing in mixed family and case-control designs

<p>Abstract</p> <p>Background-</p> <p>PedGenie software, introduced in 2006, includes genetic association testing of cases and controls that may be independent or related (nuclear families or extended pedigrees) or mixtures thereof using Monte Carlo significance testing. Our aim is to demonstrate that PedGenie, a unique and flexible analysis tool freely available in Genie 2.4 software, is significantly enhanced by incorporating meta statistics for detecting genetic association with disease using data across multiple study groups.</p> <p>Methods-</p> <p>Meta statistics (chi-squared tests, odds ratios, and confidence intervals) were calculated using formal Cochran-Mantel-Haenszel techniques. Simulated data from unrelated individuals and individuals in families were used to illustrate meta tests and their empirically-derived p-values and confidence intervals are accurate, precise, and for independent designs match those provided by standard statistical software.</p> <p>Results-</p> <p>PedGenie yields accurate Monte Carlo p-values for meta analysis of data across multiple studies, based on validation testing using pedigree, nuclear family, and case-control data simulated under both the null and alternative hypotheses of a genotype-phenotype association.</p> <p>Conclusion-</p> <p>PedGenie allows valid combined analysis of data from mixtures of pedigree-based and case-control resources. Added meta capabilities provide new avenues for association analysis, including pedigree resources from large consortia and multi-center studies.</p

Critical research gaps and translational priorities for the successful prevention and treatment of breast cancer

INTRODUCTION Breast cancer remains a significant scientific, clinical and societal challenge. This gap analysis has reviewed and critically assessed enduring issues and new challenges emerging from recent research, and proposes strategies for translating solutions into practice. METHODS More than 100 internationally recognised specialist breast cancer scientists, clinicians and healthcare professionals collaborated to address nine thematic areas: genetics, epigenetics and epidemiology; molecular pathology and cell biology; hormonal influences and endocrine therapy; imaging, detection and screening; current/novel therapies and biomarkers; drug resistance; metastasis, angiogenesis, circulating tumour cells, cancer 'stem' cells; risk and prevention; living with and managing breast cancer and its treatment. The groups developed summary papers through an iterative process which, following further appraisal from experts and patients, were melded into this summary account. RESULTS The 10 major gaps identified were: (1) understanding the functions and contextual interactions of genetic and epigenetic changes in normal breast development and during malignant transformation; (2) how to implement sustainable lifestyle changes (diet, exercise and weight) and chemopreventive strategies; (3) the need for tailored screening approaches including clinically actionable tests; (4) enhancing knowledge of molecular drivers behind breast cancer subtypes, progression and metastasis; (5) understanding the molecular mechanisms of tumour heterogeneity, dormancy, de novo or acquired resistance and how to target key nodes in these dynamic processes; (6) developing validated markers for chemosensitivity and radiosensitivity; (7) understanding the optimal duration, sequencing and rational combinations of treatment for improved personalised therapy; (8) validating multimodality imaging biomarkers for minimally invasive diagnosis and monitoring of responses in primary and metastatic disease; (9) developing interventions and support to improve the survivorship experience; (10) a continuing need for clinical material for translational research derived from normal breast, blood, primary, relapsed, metastatic and drug-resistant cancers with expert bioinformatics support to maximise its utility. The proposed infrastructural enablers include enhanced resources to support clinically relevant in vitro and in vivo tumour models; improved access to appropriate, fully annotated clinical samples; extended biomarker discovery, validation and standardisation; and facilitated cross-discipline working. CONCLUSIONS With resources to conduct further high-quality targeted research focusing on the gaps identified, increased knowledge translating into improved clinical care should be achievable within five years

The prevalence of obesity in children with autism: a secondary data analysis using nationally representative data from the National Survey of Children's Health

<p>Abstract</p> <p>Background</p> <p>The prevalence of childhood obesity has increased dramatically in the last two decades and numerous efforts to understand, intervene on, and prevent this significant threat to children's health are underway for many segments of the pediatric population. Understanding the prevalence of obesity in populations of children with developmental disorders is an important undertaking, as the factors that give rise to obesity may not be the same as for typically developing children, and because prevention and treatment efforts may need to be tailored to meet their needs and the needs of their families. The goal of the current study was to estimate the prevalence of obesity in children and adolescents with autism.</p> <p>Methods</p> <p>This study was a secondary data analysis of cross-sectional nationally representative data collected by telephone interview of parents/guardians on 85,272 children ages 3-17 from the 2003-2004 National Survey of Children's Health (NSCH). Autism was determined by response to the question, "Has a doctor or health professional ever told you that your child has autism?" Children and adolescents were classified as obese accordingto CDC guidelines for body mass index (BMI) for age and sex.</p> <p>Results</p> <p>The prevalence of obesity in children with autism was 30.4% compared to 23.6% of children without autism (p = .075). The unadjusted odds of obesity in children with autism was 1.42 (95% confidence interval (CI): 1.00, 2.02, p = .052) compared to children without autism.</p> <p>Conclusions</p> <p>Based on US nationally representative data, children with autism have a prevalence of obesity at least as high as children overall. These findings suggest that additional research is warranted to understand better the factors that influence the development of obesity in this population of children.</p

Metastatic melanoma in an esophagus demonstrating Barrett esophagus with high grade dysplasia

BACKGROUND: Metastatic melanoma involving the esophagus is rare; the occurrence of metastatic melanoma in a background of Barrett esophagus is rarer still. We report a case of an 80 year-old male who presented to our institution for workup of Barrett esophagus with high-grade dysplasia and who proved to have metastatic melanoma occurring in the background of Barrett esophagus, the first report of this kind, to our knowledge, in the English literature. CASE PRESENTATION: An 80 year-old Caucasian male was diagnosed at an outside institution with Barrett’s esophagus with high grade dysplasia and presented to our institution for therapy. The patient underwent endoscopic mucosal resection using a band ligation technique of an area of nodularity within the Barrett esophagus. Microscopic examination demonstrated extensive Barrett esophagus with high-grade dysplasia as well as a second tumor which was morphologically different from the surrounding high-grade dysplasia and which was positive for S-100, HMB 45 and Melan-A on immunohistochemistry, consistent with melanoma. Further workup of the patient demonstrated multiple radiologic lesions consistent with metastases. Molecular studies demonstrated that the melanoma was positive for the 1799T>A (V600E) mutation in the BRAF gene. The overall features of the tumor were most consistent with metastatic melanoma occurring in a background of Barrett esophagus with high-grade dysplasia. CONCLUSION: This case demonstrates a unique intersection between a premalignant condition (Barrett esophagus with high grade dysplasia) and a separate malignancy (melanoma). This report also shows the utility of molecular testing to support the hypothesis of primary versus metastatic disease in melanoma

Three Ways of Combining Genotyping and Resequencing in Case-Control Association Studies

We describe three statistical results that we have found to be useful in case-control genetic association testing. All three involve combining the discovery of novel genetic variants, usually by sequencing, with genotyping methods that recognize previously discovered variants. We first consider expanding the list of known variants by concentrating variant-discovery in cases. Although the naive inclusion of cases-only sequencing data would create a bias, we show that some sequencing data may be retained, even if controls are not sequenced. Furthermore, for alleles of intermediate frequency, cases-only sequencing with bias-correction entails little if any loss of power, compared to dividing the same sequencing effort among cases and controls. Secondly, we investigate more strongly focused variant discovery to obtain a greater enrichment for disease-related variants. We show how case status, family history, and marker sharing enrich the discovery set by increments that are multiplicative with penetrance, enabling the preferential discovery of high-penetrance variants. A third result applies when sequencing is the primary means of counting alleles in both cases and controls, but a supplementary pooled genotyping sample is used to identify the variants that are very rare. We show that this raises no validity issues, and we evaluate a less expensive and more adaptive approach to judging rarity, based on group-specific variants. We demonstrate the important and unusual caveat that this method requires equal sample sizes for validity. These three results can be used to more efficiently detect the association of rare genetic variants with disease