Multiplicity: an organizing principle for cancers and somatic mutations

<p>Abstract</p> <p>Background</p> <p>With the advent of whole-genome analysis for profiling tumor tissue, a pressing need has emerged for principled methods of organizing the large amounts of resulting genomic information. We propose the concept of multiplicity measures on cancer and gene networks to organize the information in a clinically meaningful manner. Multiplicity applied in this context extends Fearon and Vogelstein's multi-hit genetic model of colorectal carcinoma across multiple cancers.</p> <p>Methods</p> <p>Using the Catalogue of Somatic Mutations in Cancer (COSMIC), we construct networks of interacting cancers and genes. Multiplicity is calculated by evaluating the number of cancers and genes linked by the measurement of a somatic mutation. The Kamada-Kawai algorithm is used to find a two-dimensional minimum energy solution with multiplicity as an input similarity measure. Cancers and genes are positioned in two dimensions according to this similarity. A third dimension is added to the network by assigning a maximal multiplicity to each cancer or gene. Hierarchical clustering within this three-dimensional network is used to identify similar clusters in somatic mutation patterns across cancer types.</p> <p>Results</p> <p>The clustering of genes in a three-dimensional network reveals a similarity in acquired mutations across different cancer types. Surprisingly, the clusters separate known causal mutations. The multiplicity clustering technique identifies a set of causal genes with an area under the ROC curve of 0.84 versus 0.57 when clustering on gene mutation rate alone. The cluster multiplicity value and number of causal genes are positively correlated via Spearman's Rank Order correlation (<it>r_s</it>(8) = 0.894, Spearman's <it>t </it>= 17.48, <it>p </it>< 0.05). A clustering analysis of cancer types segregates different types of cancer. All blood tumors cluster together, and the cluster multiplicity values differ significantly (Kruskal-Wallis, <it>H </it>= 16.98, <it>df </it>= 2, <it>p </it>< 0.05).</p> <p>Conclusion</p> <p>We demonstrate the principle of multiplicity for organizing somatic mutations and cancers in clinically relevant clusters. These clusters of cancers and mutations provide representations that identify segregations of cancer and genes driving cancer progression.</p

Probabilistic fire spread forecast as a management tool in an operational setting

Background: An approach to predict fire growth in an operational setting, with the potential to be used as a decision-support tool for fire management, is described and evaluated. The operational use of fire behaviour models has mostly followed a deterministic approach, however, the uncertainty associated with model predictions needs to be quantified and included in wildfire planning and decision-making process during fire suppression activities. We use FARSITE to simulate the growth of a large wildfire. Probabilistic simulations of fire spread are performed, accounting for the uncertainty of some model inputs and parameters. Deterministic simulations were performed for comparison. We also assess the degree to which fire spread modelling and satellite active fire data can be combined, to forecast fire spread during large wildfires events. Results: Uncertainty was propagated through the FARSITE fire spread modelling system by randomly defining 100 different combinations of the independent input variables and parameters, and running the correspondent fire spread simulations in order to produce fire spread probability maps. Simulations were initialized with the reported ignition location and with satellite active fires. The probabilistic fire spread predictions show great potential to be used as a fire management tool in an operational setting, providing valuable information regarding the spatial–temporal distribution of burn probabilities. The advantage of probabilistic over deterministic simulations is clear when both are compared. Re-initializing simulations with satellite active fires did not improve simulations as expected. Conclusion: This information can be useful to anticipate the growth of wildfires through the landscape with an associated probability of occurrence. The additional information regarding when, where and with what probability the fire might be in the next few hours can ultimately help minimize the negative environmental, social and economic impacts of these firesinfo:eu-repo/semantics/publishedVersio

Thermal properties comparison of hybrid CF/FF and BF/FF cyanate ester-based composites

[EN] Insights within thermal expansion, conductivity, and decomposition dependencies with temperature on symmetrical and unsymmetrical layered carbon (CF) or basalt (BF) fabrics in combination with flax fibers (FF) were approached. Driven by commercial application and environmental concerns, the paper draws attention on a modified formula of cyanate ester with a common epoxy resin under an optimized ratio of 70:30 (vol%) as well as on the hybrid reinforcements stacking sequences. Synergetic effects were debated in terms of the CF and BF stacking sequences and corresponding volume fraction followed by comparisons with values predicted by the deployment of hybrid mixtures rules (RoHM/iRoHM). CF hybrid architectures revealed enhanced effective thermophysical properties over their BF counterparts and both over the FF-reinforced polymer composite considered as a reference. Thermal conductivities spread between 0.116 and 0.299 W m-1 K-1 from room temperature up to 250 C on all hybrid specimens, giving rise to an insulator character. Concerning the coefficient of thermal expansion, CF hybrid architectures disclosed values of 1.236 10-6 K-1 and 3.102 10-6 K-1 compared with BF affine exhibiting 4.794 10-6 K-1 and 6.245 10-6 K-1, respectively, with an increase in their volume fraction.The corresponding author gratefully acknowledges the financial assistance of German Academic Exchange Service-DAAD that enabled and supported the internship with Fraunhofer Research Institution for Polymeric Materials and Composites-PYCO, Germany. Many thanks go to Dr. Christian Dreyer and Dr. Maciej Gwiazda for the resin formula and access to the composite manufacturing technology.Motoc, DL.; Ferrándiz Bou, S.; Balart, R. (2018). Thermal properties comparison of hybrid CF/FF and BF/FF cyanate ester-based composites. 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Role of BRCA gene dysfunction in breast and ovarian cancer predisposition

Tumor suppressor genes that perform apparently generic cellular functions nonetheless cause tissue-specific syndromes in the human population when they are mutated in the germline. The two major hereditary breast/ovarian cancer predisposition genes, BRCA1 and BRCA2, appear to participate in a common pathway that is involved in the control of homologous recombination and in the maintenance of genomic integrity. How might such functions translate into the specific suppression of cancers of the breast and ovarian epithelia? Recent advances in the study of BRCA1 and BRCA2, discussed herein, have provided new opportunities to address this question

An investigation of breast cancer risk factors in Cyprus: a case control study

Background: Breast cancer is the most common form of malignancy affecting women worldwide. It is also the leading cancer in females in Cyprus, with approximately 400 new cases diagnosed annually. It is well recognized that genetic variation as well as environmental factors modulate breast cancer risk. The main aim of this study was to assess the strength of associations between recognized risk factors and breast cancer among Cypriot women. This is the first epidemiological investigation on risk factors of breast cancer among the Cypriot female population.Methods: We carried out a case-control study, involving 1,109 breast cancer patients and a group of 1,177 controls who were recruited while participating in the National screening programme for breast cancer. Information on demographic characteristics and potential risk factors were collected from both groups during a standardized interview. Logistic regression analysis was used to assess the strength of the association between each risk factor and breast cancer risk, before and after adjusting for the possible confounding effect of other factors.Results: In multivariable models, family history of breast cancer (OR 1.64, 95% CI 1.23, 2.19) was the strongest predictor of breast cancer risk in the Cypriot population. Late menarche (OR 0.64, 95% CI 0.45, 0.92 among women reaching menarche after the age of 15 vs. before the age of 12) and breastfeeding (OR 0.74, 95% CI 0.59, 0.92) exhibited a strong protective effect. In the case of breastfeeding, the observed effect appeared stronger than the effect of pregnancy alone. Surprisingly, we also observed an inverse association between hormone replacement therapy (HRT) although this may be a product of the retrospective nature of this study.Conclusion: Overall the findings of our study corroborate with the results of previous investigations on descriptive epidemiology of risk factors for breast cancer. This investigation provides important background information for designing detailed studies that aim to improve our understanding of the epidemiology of breast cancer in the Cypriot population, including the study of gene-environment interactions. Furthermore, our study provides the first scientific evidence for formulating targeted campaigns for prevention and early diagnosis of breast cancer in Cyprus

Model-Derived Dispersal Pathways from Multiple Source Populations Explain Variability of Invertebrate Larval Supply

Background: Predicting the spatial and temporal patterns of marine larval dispersal and supply is a challenging task due to the small size of the larvae and the variability of oceanographic processes. Addressing this problem requires the use of novel approaches capable of capturing the inherent variability in the mechanisms involved. Methodology/Principal Findings: In this study we test whether dispersal and connectivity patterns generated from a biophysical model of larval dispersal of the crab Carcinus maenas, along the west coast of the Iberian Peninsula, can predict the highly variable daily pattern of wind-driven larval supply to an estuary observed during the peak reproductive season (March–June) in 2006 and 2007. Cross-correlations between observed and predicted supply were significant (p,0.05) and strong, ranging from 0.34 to 0.81 at time lags of 26 to+5 d. Importantly, the model correctly predicted observed cross-shelf distributions (Pearson r = 0.82, p,0.001, and r = 0.79, p,0.01, in 2006 and 2007) and indicated that all supply events were comprised of larvae that had been retained within the inner shelf; larvae transported to the outer shelf and beyond never recruited. Estimated average dispersal distances ranged from 57 to 198 km and were only marginally affected by mortality. Conclusions/Significance: The high degree of predicted demographic connectivity over relatively large geographic scales is consistent with the lack of genetic structuring in C. maenas along the Iberian Peninsula. These findings indicate that the dynamic nature of larval dispersal can be captured by mechanistic biophysical models, which can be used to provid

Deep sequencing of gastric carcinoma reveals somatic mutations relevant to personalized medicine

<p>Abstract</p> <p>Background</p> <p>Globally, gastric cancer is the second most common cause of cancer-related death, with the majority of the health burden borne by economically less-developed countries.</p> <p>Methods</p> <p>Here, we report a genetic characterization of 50 gastric adenocarcinoma samples, using affymetrix SNP arrays and Illumina mRNA expression arrays as well as Illumina sequencing of the coding regions of 384 genes belonging to various pathways known to be altered in other cancers.</p> <p>Results</p> <p>Genetic alterations were observed in the WNT, Hedgehog, cell cycle, DNA damage and epithelial-to-mesenchymal-transition pathways.</p> <p>Conclusions</p> <p>The data suggests targeted therapies approved or in clinical development for gastric carcinoma would be of benefit to ~22% of the patients studied. In addition, the novel mutations detected here, are likely to influence clinical response and suggest new targets for drug discovery.</p

Minimising oil droplet size using ultrasonic emulsification

The efficient production of nanoemulsions, with oil droplet sizes of less than 100nm would facilitate the inclusion of oil soluble bio-active agents into a range of water based foods. Small droplet sizes lead to transparent emulsions so that product appearance is not altered by the addition of an oil phase. In this paper, we demonstrate that it is possible to create remarkably small transparent O/W nanoemulsions with average diameters as low as 40nm from sunflower oil. This is achieved using ultrasound or high shear homogenization and a surfactant/co-surfactant/oil system that is well optimised. The minimum droplet size of 40nm, was only obtained when both droplet deformability (surfactant design) and the applied shear (equipment geometry) were optimal. The time required to achieve the minimum droplet size was also clearly affected by the equipment configuration. Results at atmospheric pressure fitted an expected exponential relationship with the total energy density. However, we found that this relationship changes when an overpressure of up to 400kPa is applied to the sonication vessel, leading to more efficient emulsion production. Oil stability is unaffected by the sonication process