Genetic variation in genes interacting with BRCA1/2 and risk of breast cancer in Cypriot population.

Inability to correctly repair DNA damage is known to play a role in the development of breast cancer. Single nucleotide polymorphisms (SNPs) of DNA repair genes have been identified, which modify the DNA repair capacity, which in turn may affect the risk of developing breast cancer. To assess whether alterations in DNA repair genes contribute to breast cancer, we genotyped 62 SNPs in 29 genes in 1,109 Cypriot women with breast cancer and 1,177 age-matched healthy controls. Five SNPs were associated with breast cancer. SNPs rs13312840 and rs769416 in the NBS1 gene were associated with a decrease in breast cancer risk (OR TT vs. TC/CC = 0.58; 95% CI, 0.37-0.92; P = 0.019 and OR GG vs. GT/TT = 0.23, 95% CI 0.06-0.85, P = 0.017, respectively). The variant allele of MRE11A rs556477 was also associated with a reduced risk of developing the disease (OR AA vs. AG/GG = 0.76; 95% CI, 0.64-0.91; P = 0.0022). MUS81 rs545500 and PBOV1 rs6927706 SNPs were associated with an increased risk of developing breast cancer (OR GG vs. GC/CC = 1.21, 95% CI, 1.02-1.45; P = 0.031; OR AA vs. AG/GG = 1.53, 95% CI, 1.07-2.18; P = 0.019, respectively). Finally, haplotype-based tests identified significant associations between specific haplotypes in MRE11A and NBS1 genes and breast cancer risk. Further large-scale studies are needed to confirm these results

Arsenic concentrations in seagrass around the Mediterranean coast and seasonal variations

Arsenic’s occurrence in the environment could be due to human activities as well as to natural sources. In this study, Posidonia oceanica and Cymodocea nodosa are collected in 84 sites around the Mediterranean basin. In addition, both seagrass are collected monthly, in two sites (Calvi in Corsica and Salammbô in Tunisia). Arsenic concentrations in C. nodosa present seasonal variations in relation with spring phytoplankton blooms. For both species arsenic concentration is higher in the vicinity of geological sources (mining), lagoon outlets and industrial activities. Moreover, Mediterranean islands (Balearic, Sardinia, Corsica, Malta, Crete and Cyprus) and the Southern basin coastline exhibit lower concentrations in Arsenic than the rest of the Mediterranean basin. The wide spread distribution of these two species would encourage their use in a global monitoring network devoted to Arsenic contamination.peer-reviewe

Online chemical modeling environment (OCHEM): web platform for data storage, model development and publishing of chemical information

The Online Chemical Modeling Environment is a web-based platform that aims to automate and simplify the typical steps required for QSAR modeling. The platform consists of two major subsystems: the database of experimental measurements and the modeling framework. A user-contributed database contains a set of tools for easy input, search and modification of thousands of records. The OCHEM database is based on the wiki principle and focuses primarily on the quality and verifiability of the data. The database is tightly integrated with the modeling framework, which supports all the steps required to create a predictive model: data search, calculation and selection of a vast variety of molecular descriptors, application of machine learning methods, validation, analysis of the model and assessment of the applicability domain. As compared to other similar systems, OCHEM is not intended to re-implement the existing tools or models but rather to invite the original authors to contribute their results, make them publicly available, share them with other users and to become members of the growing research community. Our intention is to make OCHEM a widely used platform to perform the QSPR/QSAR studies online and share it with other users on the Web. The ultimate goal of OCHEM is collecting all possible chemoinformatics tools within one simple, reliable and user-friendly resource. The OCHEM is free for web users and it is available online at http://www.ochem.eu

Improving virtual screening of G protein-coupled receptors via ligand-directed modeling

G protein-coupled receptors (GPCRs) play crucial roles in cell physiology and pathophysiology. There is increasing interest in using structural information for virtual screening (VS) of libraries and for structure-based drug design to identify novel agonist or antagonist leads. However, the sparse availability of experimentally determined GPCR/ligand complex structures with diverse ligands impedes the application of structure-based drug design (SBDD) programs directed to identifying new molecules with a select pharmacology. In this study, we apply ligand-directed modeling (LDM) to available GPCR X-ray structures to improve VS performance and selectivity towards molecules of specific pharmacological profile. The described method refines a GPCR binding pocket conformation using a single known ligand for that GPCR. The LDM method is a computationally efficient, iterative workflow consisting of protein sampling and ligand docking. We developed an extensive benchmark comparing LDM-refined binding pockets to GPCR X-ray crystal structures across seven different GPCRs bound to a range of ligands of different chemotypes and pharmacological profiles. LDM-refined models showed improvement in VS performance over origin X-ray crystal structures in 21 out of 24 cases. In all cases, the LDM-refined models had superior performance in enriching for the chemotype of the refinement ligand. This likely contributes to the LDM success in all cases of inhibitor-bound to agonist-bound binding pocket refinement, a key task for GPCR SBDD programs. Indeed, agonist ligands are required for a plethora of GPCRs for therapeutic intervention, however GPCR X-ray structures are mostly restricted to their inactive inhibitor-bound state

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

Low HDL Cholesterol, Smoking and IL-13 R130Q Polymorphism are Associated with Myocardial Infarction in Greek Cypriot Males. A Pilot Study

This study was carried out in Greek Cypriot males to identify risk factors that predispose to myocardial infarction (MI). Genetic and lipid risk factors were investigated for the first time in a Greek Cypriot male case-control study.Contrary to other studies, mean low density lipoprotein cholesterol did not differ between cases and controls. High density lipoprotein cholesterol on the other hand, although within normal range in cases and controls, was significantly higher in the control population. In agreement with many other studies, smoking was significantly more prevalent in cases compared with controls. In pooled cases and controls, smokers had a significantly lower HDL-C level compared with non-smokers. The frequency of the IL-13 R130Q homozygotes for the mutation (QQ), as well as the mutant allele were significantly higher in cases compared with controls. The IL-13 R130Q variant, or another locus, linked to it, may increase the risk of MI

Structure-Based Virtual Screening for Drug Discovery: a Problem-Centric Review

Structure-based virtual screening (SBVS) has been widely applied in early-stage drug discovery. From a problem-centric perspective, we reviewed the recent advances and applications in SBVS with a special focus on docking-based virtual screening. We emphasized the researchers’ practical efforts in real projects by understanding the ligand-target binding interactions as a premise. We also highlighted the recent progress in developing target-biased scoring functions by optimizing current generic scoring functions toward certain target classes, as well as in developing novel ones by means of machine learning techniques