Atopic dermatitis-like disease and associated lethal myeloproliferative disorder arise from loss of Notch signaling in the murine skin.

BACKGROUND: The Notch pathway is essential for proper epidermal differentiation during embryonic skin development. Moreover, skin specific loss of Notch signaling in the embryo results in skin barrier defects accompanied by a B-lymphoproliferative disease. However, much less is known about the consequences of loss of Notch signaling after birth. METHODOLOGY AND PRINCIPAL FINDINGS: To study the function of Notch signaling in the skin of adult mice, we made use of a series of conditional gene targeted mice that allow inactivation of several components of the Notch signaling pathway specifically in the skin. We demonstrate that skin-specific inactivation of Notch1 and Notch2 simultaneously, or RBP-J, induces the development of a severe form of atopic dermatitis (AD), characterized by acanthosis, spongiosis and hyperkeratosis, as well as a massive dermal infiltration of eosinophils and mast cells. Likewise, patients suffering from AD, but not psoriasis or lichen planus, have a marked reduction of Notch receptor expression in the skin. Loss of Notch in keratinocytes induces the production of thymic stromal lymphopoietin (TSLP), a cytokine deeply implicated in the pathogenesis of AD. The AD-like associated inflammation is accompanied by a myeloproliferative disorder (MPD) characterized by an increase in immature myeloid populations in the bone marrow and spleen. Transplantation studies revealed that the MPD is cell non-autonomous and caused by dramatic microenvironmental alterations. Genetic studies demontrated that G-CSF mediates the MPD as well as changes in the bone marrow microenvironment leading to osteopenia. SIGNIFICANCE: Our data demonstrate a critical role for Notch in repressing TSLP production in keratinocytes, thereby maintaining integrity of the skin and the hematopoietic system.

Clinical trial substantiates the predictive value of O-6-methylguanine-DNA methyltransferase promoter methylation in glioblastoma patients treated with temozolomide.

PURPOSE: In the setting of a prospective clinical trial, we determined the predictive value of the methylation status of the O-6-methylguanine-DNA methyltransferase (MGMT) promoter for outcome in glioblastoma patients treated with the alkylating agent temozolomide. Expression of this excision repair enzyme has been associated with resistance to alkylating chemotherapy. EXPERIMENTAL DESIGN: The methylation status of MGMT in the tumor biopsies was evaluated in 38 patients undergoing resection for newly diagnosed glioblastoma and enrolled in a Phase II trial testing concomitant and adjuvant temozolomide and radiation. The epigenetic silencing of the MGMT gene was determined using methylation-specific PCR. RESULTS: Inactivation of the MGMT gene by promoter methylation was associated with longer survival (P = 0.0051; Log-rank test). At 18 months, survival was 62% (16 of 26) for patients testing positive for a methylated MGMT promoter but reached only 8% (1 of 12) in absence of methylation (P = 0.002; Fisher's exact test). In the presence of other clinically relevant factors, methylation of the MGMT promoter remains the only significant predictor (P = 0.017; Cox regression). CONCLUSIONS: This prospective clinical trial identifies MGMT-methylation status as an independent predictor for glioblastoma patients treated with a methylating agent. The association of the epigenetic inactivation of the DNA repair gene MGMT with better outcome in this homogenous cohort may have important implications for the design of future trials and supports efforts to deplete MGMT by O-6-benzylguanine, a noncytotoxic substrate of this enzyme.

Hierarchical modeling gave plausible estimates of associations between metabolic syndrome and components of antiretroviral therapy.

OBJECTIVE: Hierarchical modeling has been proposed as a solution to the multiple exposure problem. We estimate associations between metabolic syndrome and different components of antiretroviral therapy using both conventional and hierarchical models. STUDY DESIGN AND SETTING: We use discrete time survival analysis to estimate the association between metabolic syndrome and cumulative exposure to 16 antiretrovirals from four drug classes. We fit a hierarchical model where the drug class provides a prior model of the association between metabolic syndrome and exposure to each antiretroviral. RESULTS: One thousand two hundred and eighteen patients were followed for a median of 27 months, with 242 cases of metabolic syndrome (20%) at a rate of 7.5 cases per 100 patient years. Metabolic syndrome was more likely to develop in patients exposed to stavudine, but was less likely to develop in those exposed to atazanavir. The estimate for exposure to atazanavir increased from hazard ratio of 0.06 per 6 months' use in the conventional model to 0.37 in the hierarchical model (or from 0.57 to 0.81 when using spline-based covariate adjustment). CONCLUSION: These results are consistent with trials that show the disadvantage of stavudine and advantage of atazanavir relative to other drugs in their respective classes. The hierarchical model gave more plausible results than the equivalent conventional model.

Docetaxel and gemcitabine combination in 133 advanced soft-tissue sarcomas: a retrospective analysis.

Advanced soft-tissue sarcomas are usually resistant to cytotoxic agents such as doxorubicin and ifosfamide. Antitumor activity has been observed for gemcitabine and docetaxel combination. We conducted a retrospective study on 133 patients (58 males/75 females) with unresectable or metastatic soft-tissue sarcoma. The median age at diagnosis was 51.7 (18-82), with 76 patients with leiomoyosarcoma and 57 patients with other histological subtypes. The initial localizations were limb (44), uterine (32), retroperitoneal (23) and organs or bone (34). Patients received 900 mg/m2 of gemcitabine (days 1 and 8) over 90 min plus 100 mg/m2 of docetaxel (day 8), intravenously every 21 days. Gemcitabine/docetaxel combination was well tolerated with an overall response of 18.4% and with no clear statistical difference between leiomyosarcomas and other histological subtypes (24.2% versus 10.4% (p=0.06)). No difference was found between uterine soft-tissue sarcomas versus others. The median overall survival was 12.1 months (1-28). Better overall survival was correlated with leiomyosarcoma (p=0.01) and with the quality of the response, even for patients with stable disease (p<10(-4)). No statistical difference was found for the initial localization. Response to treatment and overall survival were better for patients in World Health Organization (WHO) performance status classification (PS) 0 at baseline versus patients in WHO PS-1, 2 or 3 (p=0.023 and p<10(-4), respectively). Gemcitabine/docetaxel combination was tolerable and demonstrated better response and survival for leiomyosarcoma, especially for patients in WHO PS-0 at baseline. For the other histological subtypes, the response was not encouraging, but the survival for patients in response or stable suggests further investigation.

Partial correlation : Network analysis

The final year project came to us as an opportunity to get involved in a topic which has appeared to be attractive during the learning process of majoring in economics: statistics and its application to the analysis of economic data, i.e. econometrics.Moreover, the combination of econometrics and computer science is a very hot topic nowadays, given the Information Technologies boom in the last decades and the consequent exponential increase in the amount of data collected and stored day by day. Data analysts able to deal with Big Data and to find useful results from it are verydemanded in these days and, according to our understanding, the work they do, although sometimes controversial in terms of ethics, is a clear source of value added both for private corporations and the public sector. For these reasons, the essence of this project is the study of a statistical instrument valid for the analysis of large datasets which is directly related to computer science: Partial Correlation Networks.The structure of the project has been determined by our objectives through the development of it. At first, the characteristics of the studied instrument are explained, from the basic ideas up to the features of the model behind it, with the final goal of presenting SPACE model as a tool for estimating interconnections in between elements in large data sets. Afterwards, an illustrated simulation is performed in order to show the power and efficiency of the model presented. And at last, the model is put into practice by analyzing a relatively large data set of real world data, with the objective of assessing whether the proposed statistical instrument is valid and useful when applied to a real multivariate time series. In short, our main goals are to present the model and evaluate if Partial Correlation Network Analysis is an effective, useful instrument and allows finding valuable results from Big Data.As a result, the findings all along this project suggest the Partial Correlation Estimation by Joint Sparse Regression Models approach presented by Peng et al. (2009) to work well under the assumption of sparsity of data. Moreover, partial correlation networks are shown to be a very valid tool to represent cross-sectional interconnections in between elements in large data sets.The scope of this project is however limited, as there are some sections in which deeper analysis would have been appropriate. Considering intertemporal connections in between elements, the choice of the tuning parameter lambda, or a deeper analysis of the results in the real data application are examples of aspects in which this project could be completed.To sum up, the analyzed statistical tool has been proved to be a very useful instrument to find relationships that connect the elements present in a large data set. And after all, partial correlation networks allow the owner of this set to observe and analyze the existing linkages that could have been omitted otherwise.

Radiotherapy and temozolomide for newly diagnosed glioblastoma: recursive partitioning analysis of the EORTC 26981/22981-NCIC CE3 phase III randomized trial.

PURPOSE: The European Organisation for Research and Treatment of Cancer and National Cancer Institute of Canada trial on temozolomide (TMZ) and radiotherapy (RT) in glioblastoma (GBM) has demonstrated that the combination of TMZ and RT conferred a significant and meaningful survival advantage compared with RT alone. We evaluated in this trial whether the recursive partitioning analysis (RPA) retains its overall prognostic value and what the benefit of the combined modality is in each RPA class. PATIENTS AND METHODS: Five hundred seventy-three patients with newly diagnosed GBM were randomly assigned to standard postoperative RT or to the same RT with concomitant TMZ followed by adjuvant TMZ. The primary end point was overall survival. The European Organisation for Research and Treatment of Cancer RPA used accounts for age, WHO performance status, extent of surgery, and the Mini-Mental Status Examination. RESULTS: Overall survival was statistically different among RPA classes III, IV, and V, with median survival times of 17, 15, and 10 months, respectively, and 2-year survival rates of 32%, 19%, and 11%, respectively (P < .0001). Survival with combined TMZ/RT was higher in RPA class III, with 21 months median survival time and a 43% 2-year survival rate, versus 15 months and 20% for RT alone (P = .006). In RPA class IV, the survival advantage remained significant, with median survival times of 16 v 13 months, respectively, and 2-year survival rates of 28% v 11%, respectively (P = .0001). In RPA class V, however, the survival advantage of RT/TMZ was of borderline significance (P = .054). CONCLUSION: RPA retains its prognostic significance overall as well as in patients receiving RT with or without TMZ for newly diagnosed GBM, particularly in classes III and IV.

Incidence and outcome of progressive multifocal leukoencephalopathy over 20 years of the Swiss HIV Cohort Study.

BACKGROUND: We investigated the incidence and outcome of progressive multifocal leukoencephalopathy (PML) in human immunodeficiency virus (HIV)-infected individuals before and after the introduction of combination antiretroviral therapy (cART) in 1996. METHODS: From 1988 through 2007, 226 cases of PML were reported to the Swiss HIV Cohort Study. By chart review, we confirmed 186 cases and recorded all-cause and PML-attributable mortality. For the survival analysis, 25 patients with postmortem diagnosis and 2 without CD4+ T cell counts were excluded, leaving a total of 159 patients (89 before 1996 and 70 during 1996-2007). RESULTS: The incidence rate of PML decreased from 0.24 cases per 100 patient-years (PY; 95% confidence interval [CI], 0.20-0.29 cases per 100 PY) before 1996 to 0.06 cases per 100 PY (95% CI, 0.04-0.10 cases per 100 PY) from 1996 onward. Patients who received a diagnosis before 1996 had a higher frequency of prior acquired immunodeficiency syndrome-defining conditions (P = .007) but similar CD4+ T cell counts (60 vs. 71 cells/microL; P = .25), compared with patients who received a diagnosis during 1996 or thereafter. The median time to PML-attributable death was 71 days (interquartile range, 44-140 days), compared with 90 days (interquartile range, 54-313 days) for all-cause mortality. The PML-attributable 1-year mortality rate decreased from 82.3 cases per 100 PY (95% CI, 58.8-115.1 cases per 100 PY) during the pre-cART era to 37.6 cases per 100 PY (95% CI, 23.4.-60.5 cases per 100 PY) during the cART era. In multivariate models, cART was the only factor associated with lower PML-attributable mortality (hazard ratio, 0.18; 95% CI, 0.07-0.50; P < .001), whereas all-cause mortality was associated with baseline CD4+ T cell count (hazard ratio per increase of 100 cells/microL, 0.52; 95% CI, 0.32-0.85; P = .010) and cART use (hazard ratio, 0.37; 95% CI, 0.19-0.75; P = .006). CONCLUSIONS: cART reduced the incidence and PML-attributable 1-year mortality, regardless of baseline CD4+ T cell count, whereas overall mortality was dependent on cART use and baseline CD4+ T cell count.

Social inequalities of functioning and perceived health in Switzerland: a representative cross-sectional analysis.

Many people worldwide live with a disability, i.e. limitations in functioning. The prevalence is expected to increase due to demographic change and the growing importance of non-communicable disease and injury. To date, many epidemiological studies have used simple dichotomous measures of disability, even though the WHO's International Classification of Functioning, Disability, and Health (ICF) provides a multi-dimensional framework of functioning. We aimed to examine associations of socio-economic status (SES) and social integration in 3 core domains of functioning (impairment, pain, limitations in activity and participation) and perceived health. We conducted a secondary analysis of representative cross-sectional data of the Swiss Health Survey 2007 including 10,336 female and 8,424 male Swiss residents aged 15 or more. Guided by a theoretical ICF-based model, 4 mixed effects Poisson regressions were fitted in order to explain functioning and perceived health by indicators of SES and social integration. Analyses were stratified by age groups (15-30, 31-54, ≥55 years). In all age groups, SES and social integration were significantly associated with functional and perceived health. Among the functional domains, impairment and pain were closely related, and both were associated with limitations in activity and participation. SES, social integration and functioning were related to perceived health. We found pronounced social inequalities in functioning and perceived health, supporting our theoretical model. Social factors play a significant role in the experience of health, even in a wealthy country such as Switzerland. These findings await confirmation in other, particularly lower resourced settings.

Early predictors of outcome in comatose survivors of ventricular fibrillation and non-ventricular fibrillation cardiac arrest treated with hypothermia: a prospective study

OBJECTIVES: Current indications for therapeutic hypothermia (TH) are restricted to comatose patients with cardiac arrest (CA) due to ventricular fibrillation (VF) and without circulatory shock. Additional studies are needed to evaluate the benefit of this treatment in more heterogeneous groups of patients, including those with non-VF rhythms and/or shock and to identify early predictors of outcome in this setting. DESIGN: Prospective study, from December 2004 to October 2006. SETTING: 32-bed medico-surgical intensive care unit, university hospital. PATIENTS: Comatose patients with out-of-hospital CA. INTERVENTIONS: TH to 33 +/- 1 degrees C (external cooling, 24 hrs) was administered to patients resuscitated from CA due to VF and non-VF (including asystole or pulseless electrical activity), independently from the presence of shock. MEASUREMENTS AND MAIN RESULTS: We hypothesized that simple clinical criteria available on hospital admission (initial arrest rhythm, duration of CA, and presence of shock) might help to identify patients who eventually survive and might most benefit from TH. For this purpose, outcome was related to these predefined variables. Seventy-four patients (VF 38, non-VF 36) were included; 46% had circulatory shock. Median duration of CA (time from collapse to return of spontaneous circulation [ROSC]) was 25 mins. Overall survival was 39.2%. However, only 3.1% of patients with time to ROSC > 25 mins survived, as compared to 65.7% with time to ROSC < or = 25 mins. Using a logistic regression analysis, time from collapse to ROSC, but not initial arrest rhythm or presence of shock, independently predicted survival at hospital discharge. CONCLUSIONS: Time from collapse to ROSC is strongly associated with outcome following VF and non-VF cardiac arrest treated with therapeutic hypothermia and could therefore be helpful to identify patients who benefit most from active induced cooling.

PAX3/FOXO1 fusion gene status is the key prognostic molecular marker in rhabdomyosarcoma and significantly improves current risk stratification.

PURPOSE: To improve the risk stratification of patients with rhabdomyosarcoma (RMS) through the use of clinical and molecular biologic data. PATIENTS AND METHODS: Two independent data sets of gene-expression profiling for 124 and 101 patients with RMS were used to derive prognostic gene signatures by using a meta-analysis. These and a previously published metagene signature were evaluated by using cross validation analyses. A combined clinical and molecular risk-stratification scheme that incorporated the PAX3/FOXO1 fusion gene status was derived from 287 patients with RMS and evaluated. RESULTS: We showed that our prognostic gene-expression signature and the one previously published performed well with reproducible and significant effects. However, their effect was reduced when cross validated or tested in independent data and did not add new prognostic information over the fusion gene status, which is simpler to assay. Among nonmetastatic patients, patients who were PAX3/FOXO1 positive had a significantly poorer outcome compared with both alveolar-negative and PAX7/FOXO1-positive patients. Furthermore, a new clinicomolecular risk score that incorporated fusion gene status (negative and PAX3/FOXO1 and PAX7/FOXO1 positive), Intergroup Rhabdomyosarcoma Study TNM stage, and age showed a significant increase in performance over the current risk-stratification scheme. CONCLUSION: Gene signatures can improve current stratification of patients with RMS but will require complex assays to be developed and extensive validation before clinical application. A significant majority of their prognostic value was encapsulated by the fusion gene status. A continuous risk score derived from the combination of clinical parameters with the presence or absence of PAX3/FOXO1 represents a robust approach to improving current risk-adapted therapy for RMS.

Steady-state global optimization of metabolic non-linear dynamic models through recasting into power-law canonical models

Background: Design of newly engineered microbial strains for biotechnological purposes would greatly benefit from the development of realistic mathematical models for the processes to be optimized. Such models can then be analyzed and, with the development and application of appropriate optimization techniques, one could identify the modifications that need to be made to the organism in order to achieve the desired biotechnological goal. As appropriate models to perform such an analysis are necessarily non-linear and typically non-convex, finding their global optimum is a challenging task. Canonical modeling techniques, such as Generalized Mass Action (GMA) models based on the power-law formalism, offer a possible solution to this problem because they have a mathematical structure that enables the development of specific algorithms for global optimization. Results: Based on the GMA canonical representation, we have developed in previous works a highly efficient optimization algorithm and a set of related strategies for understanding the evolution of adaptive responses in cellular metabolism. Here, we explore the possibility of recasting kinetic non-linear models into an equivalent GMA model, so that global optimization on the recast GMA model can be performed. With this technique, optimization is greatly facilitated and the results are transposable to the original non-linear problem. This procedure is straightforward for a particular class of non-linear models known as Saturable and Cooperative (SC) models that extend the power-law formalism to deal with saturation and cooperativity. Conclusions: Our results show that recasting non-linear kinetic models into GMA models is indeed an appropriate strategy that helps overcoming some of the numerical difficulties that arise during the global optimization task.

REGSTATTOOLS: freeware statistical tools for the analysis of disease population databases used in health and social studies

Background: The repertoire of statistical methods dealing with the descriptive analysis of the burden of a disease has been expanded and implemented in statistical software packages during the last years. The purpose of this paper is to present a web-based tool, REGSTATTOOLS http://regstattools.net intended to provide analysis for the burden of cancer, or other group of disease registry data. Three software applications are included in REGSTATTOOLS: SART (analysis of disease"s rates and its time trends), RiskDiff (analysis of percent changes in the rates due to demographic factors and risk of developing or dying from a disease) and WAERS (relative survival analysis). Results: We show a real-data application through the assessment of the burden of tobacco-related cancer incidence in two Spanish regions in the period 1995-2004. Making use of SART we show that lung cancer is the most common cancer among those cancers, with rising trends in incidence among women. We compared 2000-2004 data with that of 1995-1999 to assess percent changes in the number of cases as well as relative survival using RiskDiff and WAERS, respectively. We show that the net change increase in lung cancer cases among women was mainly attributable to an increased risk of developing lung cancer, whereas in men it is attributable to the increase in population size. Among men, lung cancer relative survival was higher in 2000-2004 than in 1995-1999, whereas it was similar among women when these time periods were compared. Conclusions: Unlike other similar applications, REGSTATTOOLS does not require local software installation and it is simple to use, fast and easy to interpret. It is a set of web-based statistical tools intended for automated calculation of population indicators that any professional in health or social sciences may require.

Angiogenic activity of breast cancer patients' monocytes reverted by combined use of systems modeling and experimental approaches.

Angiogenesis plays a key role in tumor growth and cancer progression. TIE-2-expressing monocytes (TEM) have been reported to critically account for tumor vascularization and growth in mouse tumor experimental models, but the molecular basis of their pro-angiogenic activity are largely unknown. Moreover, differences in the pro-angiogenic activity between blood circulating and tumor infiltrated TEM in human patients has not been established to date, hindering the identification of specific targets for therapeutic intervention. In this work, we investigated these differences and the phenotypic reversal of breast tumor pro-angiogenic TEM to a weak pro-angiogenic phenotype by combining Boolean modelling and experimental approaches. Firstly, we show that in breast cancer patients the pro-angiogenic activity of TEM increased drastically from blood to tumor, suggesting that the tumor microenvironment shapes the highly pro-angiogenic phenotype of TEM. Secondly, we predicted in silico all minimal perturbations transitioning the highly pro-angiogenic phenotype of tumor TEM to the weak pro-angiogenic phenotype of blood TEM and vice versa. In silico predicted perturbations were validated experimentally using patient TEM. In addition, gene expression profiling of TEM transitioned to a weak pro-angiogenic phenotype confirmed that TEM are plastic cells and can be reverted to immunological potent monocytes. Finally, the relapse-free survival analysis showed a statistically significant difference between patients with tumors with high and low expression values for genes encoding transitioning proteins detected in silico and validated on patient TEM. In conclusion, the inferred TEM regulatory network accurately captured experimental TEM behavior and highlighted crosstalk between specific angiogenic and inflammatory signaling pathways of outstanding importance to control their pro-angiogenic activity. Results showed the successful in vitro reversion of such an activity by perturbation of in silico predicted target genes in tumor derived TEM, and indicated that targeting tumor TEM plasticity may constitute a novel valid therapeutic strategy in breast cancer.

The use of beta-blockers is associated with the occurrence of acute kidney injury in severe alcoholic hepatitis.

BACKGROUND & AIMS: The beneficial effect of nonselective beta-blockers (NSBB) has recently been questioned in patients with end-stage cirrhosis. We analysed the impact of NSBB on outcomes in severe alcoholic hepatitis (AH). METHODS: This study was based on a prospective database of patients with severe, biopsy-proven AH. Patients admitted from July, 2006 to July, 2014 were retrospectively studied. Patients were divided into two groups (with and without NSBB) and assessed for the occurrence of Acute Kidney Injury (AKI) and transplant-free mortality during a 168-day follow-up period. RESULTS: One hundred thirty-nine patients were included, the mean Maddrey score was 71 ± 34 and 86 patients (61.9%) developed AKI. Forty-eight patients (34.5%) received NSBB. The overall 168-day transplant-free mortality was 50.5% (95%CI, 41.3-60.0%). The overall 168-day cumulative incidence of AKI was 61.9% (95%CI, 53.2-69.4%). When compared, patients with NSBB had a lower heart rate (65 ± 13 vs 92 ± 12, P < 0.0001) and a lower mean arterial pressure (MAP, 78 ± 3 vs 87 ± 5, P < 0.0001). Patients with NSBB had comparable MELD scores, Maddrey scores, and medical histories. The 168-day transplant-free mortality was 56.8% (95%CI, 41.3-69.7%) in patients with NSBB and 46.7% (95%CI, 35.0-57.6%) without NSBB (P = 0.25). The 168-day cumulative incidence of AKI was 89.6% (95%CI, 74.9-95.9%) with NSBB compared to 50.4% (95%CI: 39.0-60.7) for no NSBB (P = 0.0001). The independent factors predicting AKI were a higher MELD score and the presence of NSBB. CONCLUSIONS: The use of NSBB in patients with severe AH is independently associated with a higher cumulative incidence of AKI.

Overexpression of GPC6 and TMEM132D in Early Stage Ovarian Cancer Correlates with CD8+ T-Lymphocyte Infiltration and Increased Patient Survival.

Infiltration of cytotoxic T-lymphocytes in ovarian cancer is a favorable prognostic factor. Employing a differential expression approach, we have recently identified a number of genes associated with CD8+ T-cell infiltration in early stage ovarian tumors. In the present study, we validated by qPCR the expression of two genes encoding the transmembrane proteins GPC6 and TMEM132D in a cohort of early stage ovarian cancer patients. The expression of both genes correlated positively with the mRNA levels of CD8A, a marker of T-lymphocyte infiltration [Pearson coefficient: 0.427 (p = 0.0067) and 0.861 (p < 0.0001), resp.]. GPC6 and TMEM132D expression was also documented in a variety of ovarian cancer cell lines. Importantly, Kaplan-Meier survival analysis revealed that high mRNA levels of GPC6 and/or TMEM132D correlated significantly with increased overall survival of early stage ovarian cancer patients (p = 0.032). Thus, GPC6 and TMEM132D may serve as predictors of CD8+ T-lymphocyte infiltration and as favorable prognostic markers in early stage ovarian cancer with important consequences for diagnosis, prognosis, and tumor immunobattling.