Large-sequencing cancer genome projects have shown that tumors have thousands of molecular alterations and their frequency is highly heterogeneous. In such scenarios, physicians and oncologists ...routinely face lists of cancer genomic alterations where only a minority of them are relevant biomarkers to drive clinical decision-making. For this reason, the medical community agrees on the urgent need of methodologies to establish the relevance of tumor alterations, assisting in genomic profile interpretation, and, more importantly, to prioritize those that could be clinically actionable for cancer therapy.
We present PanDrugs, a new computational methodology to guide the selection of personalized treatments in cancer patients using the variant lists provided by genome-wide sequencing analyses. PanDrugs offers the largest database of drug-target associations available from well-known targeted therapies to preclinical drugs. Scoring data-driven gene cancer relevance and drug feasibility PanDrugs interprets genomic alterations and provides a prioritized evidence-based list of anticancer therapies. Our tool represents the first drug prescription strategy applying a rational based on pathway context, multi-gene markers impact and information provided by functional experiments. Our approach has been systematically applied to TCGA patients and successfully validated in a cancer case study with a xenograft mouse model demonstrating its utility.
PanDrugs is a feasible method to identify potentially druggable molecular alterations and prioritize drugs to facilitate the interpretation of genomic landscape and clinical decision-making in cancer patients. Our approach expands the search of druggable genomic alterations from the concept of cancer driver genes to the druggable pathway context extending anticancer therapeutic options beyond already known cancer genes. The methodology is public and easily integratable with custom pipelines through its programmatic API or its docker image. The PanDrugs webtool is freely accessible at http://www.pandrugs.org .
Abstract
This study investigates the contribution of external trunk morphology and posture to running performance in an evolutionary framework. It has been proposed that the evolution from primitive ...to derived features of torso shape involved changes from a mediolaterally wider into a narrower, and antero-posteriorly deeper into a shallower, more lightly built external trunk configuration, possibly in relation to habitat-related changes in locomotor and running behaviour. In this context we produced experimental data to address the hypothesis that medio-laterally narrow and antero-posteriorly shallow torso morphologies favour endurance running capacities. We used 3D geometric morphometrics to relate external 3D trunk shape of trained, young male volunteers (N = 27) to variation in running velocities during different workloads determined at 45–50%, 70% and 85% of heart rate reserve (HRR) and maximum velocity. Below 85% HRR no relationship existed between torso shape and running velocity. However, at 85% HRR and, more clearly, at maximum velocity, we found highly statistically significant relations between external torso shape and running performance. Among all trained subjects those with a relatively narrow, flat torso, a small thoracic kyphosis and a more pronounced lumbar lordosis achieved significantly higher running velocities. These results support the hypothesis that external trunk morphology relates to running performance. Low thoracic kyphosis with a flatter ribcage may affect positively respiratory biomechanics, while increased lordosis affects trunk posture and may be beneficial for lower limb biomechanics related to leg return. Assuming that running workload at 45–50% HRR occurs within aerobic metabolism, our results may imply that external torso shape is unrelated to the evolution of endurance running performance.
Central nervous system tumors (CNS) are the most frequent solid tumor in children. Causes of CNS tumors are mainly unknown and only 5% of the cases can be explained by genetic predisposition. We ...studied the effects of environmental exposure on the incidence of CNS tumors in children by subtype, according to exposure to industrial and/or urban environment, exposure to crops and according to socio-economic status of the child.
We carried out a population-based case-control study of CNS tumors in Spain, covering 714 incident cases collected from the Spanish Registry of Childhood Tumors (period 1996-2011) and 4284 controls, individually matched by year of birth, sex, and autonomous region of residence. We built a covariate to approximate the exposure to industrial and/or urban environment and a covariate for the exposure to crops (GCI) using the coordinates of the home addresses of the children. We used the 2001 Census to obtain information about socio-economic status (SES). We fitted logistic regression models to estimate odds ratios (ORs) and 95% confidence intervals (95%CIs).
The results for all CNS tumors showed an excess risk (OR = 1.37; 95%CI = 1.09-1.73) for SES, i.e., children living in the least deprived areas had 37% more risk of CNS tumor than children living in the most deprived areas. For GCI, an increase of 10% in crop surface in the 1-km buffer around the residence implied an increase of 22% in the OR (OR = 1.22; 95%CI = 1.15-1.29). Children living in the intersection of industrial and urban areas could have a greater risk of CNS tumors than children who live outside these areas (OR = 1.20; 95%CI = 0.82-1.77). Living in urban areas (OR = 0.90; 95%CI = 0.65-1.24) or industrial areas (OR = 0.96; 95%CI = 0.81-1.77) did not seem to increase the risk for all CNS tumors together. By subtype, Astrocytomas, Intracranial and intraspinal embryonal tumors, and other gliomas showed similar results.
Our results suggest that higher socioeconomic status and exposure to crops could increase the risk of CNS tumors in children.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Sleep apnea (OSA) is a common sleep disorder characterized by recurring breathing pauses during sleep caused by a blockage of the upper airway (UA). The altered UA structure or function in OSA ...speakers has led to hypothesize the automatic analysis of speech for OSA assessment. In this paper we critically review several approaches using speech analysis and machine learning techniques for OSA detection, and discuss the limitations that can arise when using machine learning techniques for diagnostic applications.
A large speech database including 426 male Spanish speakers suspected to suffer OSA and derived to a sleep disorders unit was used to study the clinical validity of several proposals using machine learning techniques to predict the apnea-hypopnea index (AHI) or classify individuals according to their OSA severity. AHI describes the severity of patients' condition. We first evaluate AHI prediction using state-of-the-art speaker recognition technologies: speech spectral information is modelled using supervectors or i-vectors techniques, and AHI is predicted through support vector regression (SVR). Using the same database we then critically review several OSA classification approaches previously proposed. The influence and possible interference of other clinical variables or characteristics available for our OSA population: age, height, weight, body mass index, and cervical perimeter, are also studied.
The poor results obtained when estimating AHI using supervectors or i-vectors followed by SVR contrast with the positive results reported by previous research. This fact prompted us to a careful review of these approaches, also testing some reported results over our database. Several methodological limitations and deficiencies were detected that may have led to overoptimistic results.
The methodological deficiencies observed after critically reviewing previous research can be relevant examples of potential pitfalls when using machine learning techniques for diagnostic applications. We have found two common limitations that can explain the likelihood of false discovery in previous research: (1) the use of prediction models derived from sources, such as speech, which are also correlated with other patient characteristics (age, height, sex,…) that act as confounding factors; and (2) overfitting of feature selection and validation methods when working with a high number of variables compared to the number of cases. We hope this study could not only be a useful example of relevant issues when using machine learning for medical diagnosis, but it will also help in guiding further research on the connection between speech and OSA.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Obstructive sleep apnea (OSA) is a common sleep disorder characterized by recurring breathing pauses during sleep caused by a blockage of the upper airway (UA). OSA is generally diagnosed through a ...costly procedure requiring an overnight stay of the patient at the hospital. This has led to proposing less costly procedures based on the analysis of patients’ facial images and voice recordings to help in OSA detection and severity assessment. In this paper we investigate the use of both image and speech processing to estimate the apnea-hypopnea index, AHI (which describes the severity of the condition), over a population of 285 male Spanish subjects suspected to suffer from OSA and referred to a Sleep Disorders Unit. Photographs and voice recordings were collected in a supervised but not highly controlled way trying to test a scenario close to an OSA assessment application running on a mobile device (i.e., smartphones or tablets). Spectral information in speech utterances is modeled by a state-of-the-art low-dimensional acoustic representation, called i-vector. A set of local craniofacial features related to OSA are extracted from images after detecting facial landmarks using Active Appearance Models (AAMs). Support vector regression (SVR) is applied on facial features and i-vectors to estimate the AHI.
Pluripotent stem cells (PSCs) transition between cell states in vitro, reflecting developmental changes in the early embryo. PSCs can be stabilized in the naive state by blocking extracellular ...differentiation stimuli, particularly FGF-MEK signalling. Here, we report that multiple features of the naive state in human and mouse PSCs can be recapitulated without affecting FGF-MEK signalling or global DNA methylation. Mechanistically, chemical inhibition of CDK8 and CDK19 (hereafter CDK8/19) kinases removes their ability to repress the Mediator complex at enhancers. CDK8/19 inhibition therefore increases Mediator-driven recruitment of RNA polymerase II (RNA Pol II) to promoters and enhancers. This efficiently stabilizes the naive transcriptional program and confers resistance to enhancer perturbation by BRD4 inhibition. Moreover, naive pluripotency during embryonic development coincides with a reduction in CDK8/19. We conclude that global hyperactivation of enhancers drives naive pluripotency, and this can be achieved in vitro by inhibiting CDK8/19 kinase activity. These principles may apply to other contexts of cellular plasticity.
This study sought to ascertain whether there might be excess lung cancer mortality among the population residing in the vicinity of Spanish paper and board industries which report their emissions to ...the European Pollutant Emission Register (EPER).
This was an ecological study that modelled the Standardised Mortality Ratio (SMR) for lung cancer in 8073 Spanish towns over the period 1994-2003. Population exposure to industrial pollution was estimated on the basis of distance from town of residence to pollution source. An exploratory, near-versus-far analysis was conducted, using mixed Poisson regression models and an analysis of the effect of municipal proximity within a 50-kilometre radius of each of the 18 installations.
Results varied for the different facilities. In two instances there was an increasing mortality gradient with proximity to the installation, though this was exclusively observed among men.
The study of cancer mortality in areas surrounding pollutant foci is a useful tool for environmental surveillance, and serves to highlight areas of interest susceptible to being investigated by ad hoc studies. Despite present limitations, recognition is therefore due to the advance represented by publication of the EPER and the study of pollutant foci.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
RAP1 is part of shelterin, the protective complex at telomeres. RAP1 also binds along chromosome arms, where it is proposed to regulate gene expression. To investigate the nontelomeric roles of RAP1 ...in vivo, we generated a RAP1 whole-body knockout mouse. These mice show early onset of obesity, which is more severe in females than in males. Rap1-deficient mice show accumulation of abdominal fat, hepatic steatosis, and high-fasting plasma levels of insulin, glucose, cholesterol, and alanine aminotransferase. Gene expression analyses of liver and visceral white fat from Rap1-deficient mice before the onset of obesity show deregulation of metabolic programs, including fatty acid, glucose metabolism, and PPARα signaling. We identify Pparα and Pgc1α as key factors affected by Rap1 deletion in the liver. We show that RAP1 binds to Pparα and Pgc1α loci and modulates their transcription. These findings reveal a role for a telomere-binding protein in the regulation of metabolism.
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•RAP1-deficient female mice develop obesity that is aggravated under a high-fat diet•RAP1 protects against obesity, insulin resistance, cardiopathies, and liver steatosis•RAP1 modulates the transcriptional regulation of metabolic pathways•RAP1 binds to Pparα and Pgc1α loci and modulates their transcription
Blasco and colleagues now show that RAP1 plays an important role in metabolism and identify PPARα and PGC1α as key mediators of RAP1 metabolic activities. Molecular defects seen in Rap1-deficient mice anticipate the onset of obesity, which is progressively aggravated with increasing age. Similar to Pparα- and Pgc1α-deficient mice, fat accumulation is more pronounced in Rap1-deficient females than in males, and they develop insulin resistance and hepatic steatosis, further supporting the idea that RAP1 and PPARα are in the same pathway of metabolism regulation.
Background: Placental tissue may furnish information on the exposure of both mother and fetus. Mercury (Hg), cadmium (Cd), and lead (Pb) are toxicants of interest in pregnancy because they are ...associated with alterations in child development. Objectives: The aim of this study was to summarize the available information regarding total Hg, Cd, and Pb levels in human placenta and possible related factors. Methods: We performed a systematic search of PubMed/MEDLINE, EMBASE, Lilacs, OSH, and Web of Science for original papers on total Hg, Cd, or Pb levels in human placenta that were published in English or Spanish (1976—2011). Data on study design, population characteristics, collection and analysis of placenta specimens, and main results were extracted using a standardized form. Results: We found a total of 79 papers (73 different studies). Hg, Cd, and Pb levels were reported in 24, 46, and 46 studies, respectively. Most studies included small convenience samples of healthy pregnant women. Studies were heterogeneous regarding populations selected, processing of specimens, and presentation of results. Hg concentrations > 50 ng/g were found in China (Shanghai), Japan, and the Faroe Islands. Cd levels ranged from 1.2 ng/g to 53 ng/g and were highest in the United States, Japan, and Eastern Europe. Pb showed the greatest variability, with levels ranging from 1.18 ng/g in China (Shanghai) to 500 ng/g in a polluted area of Poland. Conclusion: The use of the placenta as a biomarker to assess heavy metals exposure is not properly developed because of heterogeneity among the studies. International standardized protocols are needed to enhance comparability and increase the usefulness of this promising tissue in biomonitoring studies.
Asturias, an Autonomous Region in Northern Spain with a large industrial area, registers high lung cancer incidence and mortality. While this excess risk of lung cancer might be partially ...attributable to smoking habit and occupational exposure, the role of industrial and urban pollution also needs to be assessed. The objective was to ascertain the possible effect of air pollution, both urban and industrial, on lung cancer risk in Asturias.
This was a hospital-based case-control study covering 626 lung cancer patients and 626 controls recruited in Asturias and matched by ethnicity, hospital, age, and sex. Distances from the respective participants' residential locations to industrial facilities and city centers were computed. Using logistic regression, odds ratios (ORs) and 95% confidence intervals (95%CIs) for categories of distance to urban and industrial pollution sources were calculated, with adjustment for sex, age, hospital area, tobacco consumption, family history of cancer, and occupation.
Whereas individuals living near industries displayed an excess risk of lung cancer (OR = 1.49; 95%CI = 0.93-2.39), which attained statistical significance for small cell carcinomas (OR = 2.23; 95%CI = 1.01-4.92), residents in urban areas showed a statistically significant increased risk for adenocarcinoma (OR = 1.92; 95%CI = 1.09-3.38). In the Gijon health area, residents in the urban area registered a statistically significant increased risk of lung cancer (OR = 2.17; 95%CI = 1.25-3.76), whereas in the Aviles health area, no differences in risk were found by area of exposure.
This study provides further evidence that air pollution is a moderate risk factor for lung cancer.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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