Cancer somatic mutations cluster in a subset of regulatory sites predicted from the ENCODE data

Background: Transcriptional regulation of gene expression is essential for cellular differentiation and function, and defects in the process are associated with cancer. The ENCODE project has mapped potential regulatory sites across the complete genome in many cell types, and these regions have been shown to harbour many of the somatic mutations that occur in cancer cells, suggesting that their effects may drive cancer initiation and development. The ENCODE data suggests a very large number of regulatory sites, and methods are needed to identify those that are most relevant and to connect them to the genes that they control. Methods: Predictive models of gene expression were developed by integrating the ENCODE data for regulation, including transcription factor binding and DNase1 hypersensitivity, with RNA-seq data for gene expression. A penalized regression method was used to identify the most predictive potential regulatory sites for each transcript. Known cancer somatic mutations from the COSMIC database were mapped to potential regulatory sites, and we examined differences in the mapping frequencies associated with sites chosen in regulatory models and other (rejected) sites. The effects of potential confounders, for example replication timing, were considered. Results: Cancer somatic mutations preferentially occupy those regulatory regions chosen in our models as most predictive of gene expression. Conclusion: Our methods have identified a significantly reduced set of regulatory sites that are enriched in cancer somatic mutations and are more predictive of gene expression. This has significance for the mechanistic interpretation of cancer mutations, and the understanding of genetic regulation

Identifying a High Fraction of the Human Genome to be under Selective Constraint Using GERP++

Computational efforts to identify functional elements within genomes leverage comparative sequence information by looking for regions that exhibit evidence of selective constraint. One way of detecting constrained elements is to follow a bottom-up approach by computing constraint scores for individual positions of a multiple alignment and then defining constrained elements as segments of contiguous, highly scoring nucleotide positions. Here we present GERP++, a new tool that uses maximum likelihood evolutionary rate estimation for position-specific scoring and, in contrast to previous bottom-up methods, a novel dynamic programming approach to subsequently define constrained elements. GERP++ evaluates a richer set of candidate element breakpoints and ranks them based on statistical significance, eliminating the need for biased heuristic extension techniques. Using GERP++ we identify over 1.3 million constrained elements spanning over 7% of the human genome. We predict a higher fraction than earlier estimates largely due to the annotation of longer constrained elements, which improves one to one correspondence between predicted elements with known functional sequences. GERP++ is an efficient and effective tool to provide both nucleotide- and element-level constraint scores within deep multiple sequence alignments

The quest for the solar g modes

Solar gravity modes (or g modes) -- oscillations of the solar interior for which buoyancy acts as the restoring force -- have the potential to provide unprecedented inference on the structure and dynamics of the solar core, inference that is not possible with the well observed acoustic modes (or p modes). The high amplitude of the g-mode eigenfunctions in the core and the evanesence of the modes in the convection zone make the modes particularly sensitive to the physical and dynamical conditions in the core. Owing to the existence of the convection zone, the g modes have very low amplitudes at photospheric levels, which makes the modes extremely hard to detect. In this paper, we review the current state of play regarding attempts to detect g modes. We review the theory of g modes, including theoretical estimation of the g-mode frequencies, amplitudes and damping rates. Then we go on to discuss the techniques that have been used to try to detect g modes. We review results in the literature, and finish by looking to the future, and the potential advances that can be made -- from both data and data-analysis perspectives -- to give unambiguous detections of individual g modes. The review ends by concluding that, at the time of writing, there is indeed a consensus amongst the authors that there is currently no undisputed detection of solar g modes.Comment: 71 pages, 18 figures, accepted by Astronomy and Astrophysics Revie

Associations between XPD Asp312Asn Polymorphism and Risk of Head and Neck Cancer: A Meta-Analysis Based on 7,122 Subjects

Background: To investigate the association between XPD Asp312Asn polymorphism and head and neck cancer risk through this meta-analysis. Methods: We performed a meta-analysis of 9 published case-control studies including 2,670 patients with head and neck cancer and 4,452 controls. An odds ratio (OR) with a 95 % confidence interval (CI) was applied to assess the association between XPD Asp312Asn polymorphism and head and neck cancer risk. Results: Overall, no significant association between XPD Asp312Asn polymorphism and head and neck cancer risk was found in this meta-analysis (Asn/Asn vs. Asp/Asp: OR = 0.95, 95%CI = 0.80–1.13, P = 0.550, Pheterogeneity = 0.126; Asp/Asn vs. Asp/Asp: OR = 1.11, 95%CI = 0.99–1.24, P = 0.065, P heterogeneity = 0.663; Asn/Asn+Asp/Asn vs. Asp/Asp: OR = 1.07, 95%CI = 0.97–1.19, P = 0.189, P heterogeneity = 0.627; Asn/Asn vs. Asp/Asp+Asp/Asn: OR = 0.87, 95%CI = 0.68–1.10, P = 0.243, Pheterogeneity = 0.089). In the subgroup analysis by HWE, ethnicity, and study design, there was still no significant association detected in all genetic models. Conclusions: This meta-analysis demonstrates that XPD Asp312Asn polymorphism may not be a risk factor for developing head and neck cancer

Results from the dissemination of an evidence-based telephone-delivered intervention for healthy lifestyle and weight loss: the Optimal Health Program

Despite proven efficacy, there are few published evaluations of telephone-delivered interventions targeting physical activity, healthy eating, and weight loss in community dissemination contexts. This study aims to evaluate participant and program outcomes from the Optimal Health Program, a telephone-delivered healthy lifestyle and weight loss program provided by a primary health care organization. Dissemination study used a single-group, repeated measures design; outcomes were assessed at 6-month (mid-program; n = 166) and 12-month (end of program; n = 88) using paired analyses. The program reached a representative sample of at-risk, primary care patients, with 56 % withdrawing before program completion. Among completers, a statistically significant improvement between baseline and end of program was observed for weight [mean change (SE) −5.4 (7.0) kg] and waist circumference [−4.8 (9.7) cm], underpinned by significant physical activity and dietary change. Findings suggest that telephone-delivered weight loss and healthy lifestyle programs can provide an effective model for use in primary care settings, but participant retention remains a challenge

Association between DNA Damage Response and Repair Genes and Risk of Invasive Serous Ovarian Cancer

BACKGROUND: We analyzed the association between 53 genes related to DNA repair and p53-mediated damage response and serous ovarian cancer risk using case-control data from the North Carolina Ovarian Cancer Study (NCOCS), a population-based, case-control study. METHODS/PRINCIPAL FINDINGS: The analysis was restricted to 364 invasive serous ovarian cancer cases and 761 controls of white, non-Hispanic race. Statistical analysis was two staged: a screen using marginal Bayes factors (BFs) for 484 SNPs and a modeling stage in which we calculated multivariate adjusted posterior probabilities of association for 77 SNPs that passed the screen. These probabilities were conditional on subject age at diagnosis/interview, batch, a DNA quality metric and genotypes of other SNPs and allowed for uncertainty in the genetic parameterizations of the SNPs and number of associated SNPs. Six SNPs had Bayes factors greater than 10 in favor of an association with invasive serous ovarian cancer. These included rs5762746 (median OR(odds ratio)(per allele) = 0.66; 95% credible interval (CI) = 0.44-1.00) and rs6005835 (median OR(per allele) = 0.69; 95% CI = 0.53-0.91) in CHEK2, rs2078486 (median OR(per allele) = 1.65; 95% CI = 1.21-2.25) and rs12951053 (median OR(per allele) = 1.65; 95% CI = 1.20-2.26) in TP53, rs411697 (median OR (rare homozygote) = 0.53; 95% CI = 0.35 - 0.79) in BACH1 and rs10131 (median OR( rare homozygote) = not estimable) in LIG4. The six most highly associated SNPs are either predicted to be functionally significant or are in LD with such a variant. The variants in TP53 were confirmed to be associated in a large follow-up study. CONCLUSIONS/SIGNIFICANCE: Based on our findings, further follow-up of the DNA repair and response pathways in a larger dataset is warranted to confirm these results