Digital health behaviour change interventions targeting physical activity and diet in cancer survivors: a systematic review and meta-analysis

Purpose: The number of cancer survivors has risen substantially due to improvements in early diagnosis and treatment. Health behaviours such as physical activity (PA) and diet can reduce recurrence and mortality, and alleviate negative consequences of cancer and treatments. Digital behaviour change interventions (DBCIs) have the potential to reach large numbers of cancer survivors. Methods: We conducted a systematic review and meta-analyses of relevant studies identified by a search of Medline, EMBASE, PubMed and CINAHL. Studies which assessed a DBCI with measures of PA, diet and/or sedentary behaviour were included. Results: 15 studies were identified. Random effects meta-analyses showed significant improvements in moderate-vigorous PA (7 studies; mean difference (MD) = 41 minutes per week; 95% CI: 12, 71) and body mass index (BMI)/weight (standardised mean difference (SMD) = -0.23; 95% CI: -0.41, -0.05). There was a trend toward significance for reduced fatigue and no significant change in cancer-specific quality of life (QoL). Narrative synthesis revealed mixed evidence for effects on diet, generic QoL and self-efficacy and no evidence of an effect on mental health. Two studies suggested improved sleep quality. Conclusions: DBCIs may improve PA and BMI among cancer survivors and there is mixed evidence for diet. The number of included studies is small and risk of bias and heterogeneity was high. Future research should address these limitations with large, high-quality RCTs, with objective measures of PA and sedentary time. Implications for cancer survivors: Digital technologies offer a promising approach to encourage health behaviour change among cancer survivors

Network-Based Integration of GWAS and Gene Expression Identifies a HOX-Centric Network Associated with Serous Ovarian Cancer Risk

BACKGROUND: Genome-wide association studies (GWAS) have so far reported 12 loci associated with serous epithelial ovarian cancer (EOC) risk. We hypothesized that some of these loci function through nearby transcription factor (TF) genes and that putative target genes of these TFs as identified by coexpression may also be enriched for additional EOC risk associations. METHODS: We selected TF genes within 1 Mb of the top signal at the 12 genome-wide significant risk loci. Mutual information, a form of correlation, was used to build networks of genes strongly coexpressed with each selected TF gene in the unified microarray dataset of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this dataset were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls). RESULTS: Gene set enrichment analysis identified six networks centered on TF genes (HOXB2, HOXB5, HOXB6, HOXB7 at 17q21.32 and HOXD1, HOXD3 at 2q31) that were significantly enriched for genes from the risk-associated end of the ranked list (P < 0.05 and FDR < 0.05). These results were replicated (P < 0.05) using an independent association study (7,035 cases/21,693 controls). Genes underlying enrichment in the six networks were pooled into a combined network. CONCLUSION: We identified a HOX-centric network associated with serous EOC risk containing several genes with known or emerging roles in serous EOC development. IMPACT: Network analysis integrating large, context-specific datasets has the potential to offer mechanistic insights into cancer susceptibility and prioritize genes for experimental characterization

Identification of gene specific cis-regulatory elements during differentiation of mouse embryonic stem cells: An integrative approach using high-throughput datasets.

Gene expression governs cell fate, and is regulated via a complex interplay of transcription factors and molecules that change chromatin structure. Advances in sequencing-based assays have enabled investigation of these processes genome-wide, leading to large datasets that combine information on the dynamics of gene expression, transcription factor binding and chromatin structure as cells differentiate. While numerous studies focus on the effects of these features on broader gene regulation, less work has been done on the mechanisms of gene-specific transcriptional control. In this study, we have focussed on the latter by integrating gene expression data for the in vitro differentiation of murine ES cells to macrophages and cardiomyocytes, with dynamic data on chromatin structure, epigenetics and transcription factor binding. Combining a novel strategy to identify communities of related control elements with a penalized regression approach, we developed individual models to identify the potential control elements predictive of the expression of each gene. Our models were compared to an existing method and evaluated using the existing literature and new experimental data from embryonic stem cell differentiation reporter assays. Our method is able to identify transcriptional control elements in a gene specific manner that reflect known regulatory relationships and to generate useful hypotheses for further testing.Wellcome Trust, BBSRC, CRU

Common variants in the ATM, BRCA1, BRCA2, CHEK2 and TP53 cancer susceptibility genes are unlikely to increase breast cancer risk

RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are.Abstract Introduction Certain rare, familial mutations in the ATM, BRCA1, BRCA2, CHEK2 or TP53 genes increase susceptibility to breast cancer but it has not, until now, been clear whether common polymorphic variants in the same genes also increase risk. Methods We have attempted a comprehensive, single nucleotide polymorphism (SNP)- and haplotype-tagging association study on each of these five genes in up to 4,474 breast cancer cases from the British, East Anglian SEARCH study and 4,560 controls from the EPIC-Norfolk study, using a two-stage study design. Nine tag SNPs were genotyped in ATM, together with five in BRCA1, sixteen in BRCA2, ten in CHEK2 and five in TP53, with the aim of tagging all other known, common variants. SNPs generating the common amino acid substitutions were specifically forced into the tagging set for each gene. Results No significant breast cancer associations were detected with any individual or combination of tag SNPs. Conclusion It is unlikely that there are any other common variants in these genes conferring measurably increased risks of breast cancer in our study population

No association between a candidate TCF7L2 variant and risk of breast or ovarian cancer

<p>Abstract</p> <p>Background</p> <p>TCF7L2 is a transcription factor involved in Wnt/β-catenin signaling which has a variant known to be associated with risk of Type 2 diabetes and, in some studies, with risk of certain cancers, including familial breast cancer. No studies of ovarian cancer have been reported to date.</p> <p>Methods</p> <p>Two clinic-based case-control studies at the Mayo Clinic were assessed including 798 breast cancer cases, 843 breast cancer controls, 391 ovarian cancer cases, and 458 ovarian cancer controls. Genotyping at <it>TCF7L2 </it>rs12255372 used a 5' endonuclease assay, and statistical analysis used logistic regression among participants as a whole and among <it>a priori</it>-defined subsets.</p> <p>Results</p> <p>No associations with risk of breast or ovarian cancer were observed (ordinal model, p = 0.62 and p = 0.75, respectively). In addition, no associations were observed among sub-groups defined by age, BMI, family history, stage, grade, histology, or tumor behavior.</p> <p>Conclusion</p> <p>Although the biology of the Wnt/β-catenin signaling pathway and prior association between rs12255372 and numerous phenotypes warranted examination of this <it>TCF7L2 </it>SNP, no compelling evidence for association with breast or ovarian cancer was observed.</p

Genetic Variants in TGF-β Pathway Are Associated with Ovarian Cancer Risk

The transforming growth factor-β (TGF-β) signaling pathway is involved in a diverse array of cellular processes responsible for tumorigenesis. In this case-control study, we applied a pathway-based approach to evaluate single-nucleotide polymorphisms (SNPs) in the TGF-β signaling pathway as predictors of ovarian cancer risk. We systematically genotyped 218 SNPs from 21 genes in the TGF-β signaling pathway in 417 ovarian cancer cases and 417 matched control subjects. We analyzed the associations of these SNPs with ovarian cancer risk, performed haplotype analysis and identified potential cumulative effects of genetic variants. We also performed analysis to identify higher-order gene-gene interactions influencing ovarian cancer risk. Individual SNP analysis showed that the most significant SNP was SMAD6: rs4147407, with an adjusted odds ratio (OR) of 1.60 (95% confidence interval [CI], 1.14–2.24, P = 0.0066). Cumulative genotype analysis of 13 SNPs with significant main effects exhibited a clear dose-response trend of escalating risk with increasing number of unfavorable genotypes. In gene-based analysis, SMAD6 was identified as the most significant gene associated with ovarian cancer risk. Haplotype analysis further revealed that two haplotype blocks within SMAD6 were significantly associated with decreased ovarian cancer risk, as compared to the most common haplotype. Gene-gene interaction analysis further categorized the study population into subgroups with different ovarian cancer risk. Our findings suggest that genetic variants in the TGF-β signaling pathway are associated with ovarian cancer risk and may facilitate the identification of high-risk subgroups in the general population

Concerted Action of Two Formins in Gliding Motility and Host Cell Invasion by Toxoplasma gondii

The invasive forms of apicomplexan parasites share a conserved form of gliding motility that powers parasite migration across biological barriers, host cell invasion and egress from infected cells. Previous studies have established that the duration and direction of gliding motility are determined by actin polymerization; however, regulators of actin dynamics in apicomplexans remain poorly characterized. In the absence of a complete ARP2/3 complex, the formin homology 2 domain containing proteins and the accessory protein profilin are presumed to orchestrate actin polymerization during host cell invasion. Here, we have undertaken the biochemical and functional characterization of two Toxoplasma gondii formins and established that they act in concert as actin nucleators during invasion. The importance of TgFRM1 for parasite motility has been assessed by conditional gene disruption. The contribution of each formin individually and jointly was revealed by an approach based upon the expression of dominant mutants with modified FH2 domains impaired in actin binding but still able to dimerize with their respective endogenous formin. These mutated FH2 domains were fused to the ligand-controlled destabilization domain (DD-FKBP) to achieve conditional expression. This strategy proved unique in identifying the non-redundant and critical roles of both formins in invasion. These findings provide new insights into how controlled actin polymerization drives the directional movement required for productive penetration of parasites into host cells

Dissecting the Transcriptional Regulatory Properties of Human Chromosome 16 Highly Conserved Non-Coding Regions

Non-coding DNA conservation across species has been often used as a predictor for transcriptional enhancer activity. However, only a few systematic analyses of the function of these highly conserved non-coding regions (HCNRs) have been performed. Here we use zebrafish transgenic assays to perform a systematic study of 113 HCNRs from human chromosome 16. By comparing transient and stable transgenesis, we show that the first method is highly inefficient, leading to 40% of false positives and 20% of false negatives. When analyzed in stable transgenic lines, a great majority of HCNRs were active in the central nervous system, although some of them drove expression in other organs such as the eye and the excretory system. Finally, by testing a fraction of the HCNRs lacking enhancer activity for in vivo insulator activity, we find that 20% of them may contain enhancer-blocking function. Altogether our data indicate that HCNRs may contain different types of cis-regulatory activity, including enhancer, insulators as well as other not yet discovered functions