Increased entropy of signal transduction in the cancer metastasis phenotype

Studies into the statistical properties of biological networks have led to important biological insights, such as the presence of hubs and hierarchical modularity. There is also a growing interest in studying the statistical properties of networks in the context of cancer genomics. However, relatively little is known as to what network features differ between the cancer and normal cell physiologies, or between different cancer cell phenotypes. Based on the observation that frequent genomic alterations underlie a more aggressive cancer phenotype, we asked if such an effect could be detectable as an increase in the randomness of local gene expression patterns. Using a breast cancer gene expression data set and a model network of protein interactions we derive constrained weighted networks defined by a stochastic information flux matrix reflecting expression correlations between interacting proteins. Based on this stochastic matrix we propose and compute an entropy measure that quantifies the degree of randomness in the local pattern of information flux around single genes. By comparing the local entropies in the non-metastatic versus metastatic breast cancer networks, we here show that breast cancers that metastasize are characterised by a small yet significant increase in the degree of randomness of local expression patterns. We validate this result in three additional breast cancer expression data sets and demonstrate that local entropy better characterises the metastatic phenotype than other non-entropy based measures. We show that increases in entropy can be used to identify genes and signalling pathways implicated in breast cancer metastasis. Further exploration of such integrated cancer expression and protein interaction networks will therefore be a fruitful endeavour.Comment: 5 figures, 2 Supplementary Figures and Table

Basic and clinical significance of IGF-I-induced signatures in cancer

The insulin-like growth factor (IGF) system mediates growth, differentiation and developmental processes; it is also involved in various metabolic activities. Deregulation of IGF system expression and action is linked to diverse pathologies, ranging from growth deficits to cancer development. Targeting of the IGF axis emerged in recent years as a promising therapeutic approach in cancer and other medical conditions. Rational use of IGF-I-induced gene signatures may help to identify patients who might benefit from IGF axis-directed therapeutic modalities. In the accompanying research article in BMC Medicine, Rajski et al. show that IGF-I-induced gene expression in primary breast and lung fibroblasts accurately predict outcomes in breast and lung cancer patients

Vascular histopathology and connective tissue ultrastructure in spontaneous coronary artery dissection: pathophysiological and clinical implications.

AIMS: Spontaneous coronary artery dissection (SCAD) is a cause of acute coronary syndromes and in rare cases sudden cardiac death (SCD). Connective tissue abnormalities, coronary inflammation, increased coronary vasa vasorum density and coronary fibromuscular dysplasia have all been implicated in the pathophysiology of SCAD but have not previously been systematically assessed. We designed a study to investigate the coronary histological and dermal collagen ultrastructural findings in SCAD. METHODS AND RESULTS: 36 autopsy SCAD cases were compared with 359 SCAD survivors. Coronary and myocardial histology and immunohistochemistry were undertaken. Transmission electron microscopy (TEM) of dermal extracellular matrix components (ECM) of n = 31 SCAD survivors and n = 16 healthy volunteers were compared. Autopsy cases were more likely male (19% versus 5%; p = 0.0004) with greater proximal left coronary involvement (56% versus 18%; p < 0.0001) compared to SCAD survivors. N = 24 (66%) of cases showed no myocardial infarction on macro- or microscopic examination consistent with arrhythmogenic death. There was significantly (p < 0.001) higher inflammation in cases with delayed-onset death vs sudden death and significantly more inflammation surrounding the dissected vs. non-dissected vessel segments. N = 17 (47%) cases showed limited intimal fibro-elastic thickening but no features of fibromuscular dysplasia and no endothelial or internal elastic lamina abnormalities. There were no differences in vasa vasorum density between SCAD and control cases. TEM revealed no general ultrastructural differences in ECM components or markers of fibroblast metabolic activity. CONCLUSIONS: Assessment of SCD requires careful exclusion of SCAD, particularly in cases without myocardial necrosis. Peri-coronary inflammation in SCAD is distinct from vasculitides and likely a reaction to, rather than a cause for SCAD. Coronary fibromuscular dysplasia or increased vasa vasorum density do not appear pathophysiologically important. Dermal connective tissue changes are not common in SCAD survivors. TRANSLATIONAL PERSPECTIVE: SCAD, especially of distal coronary territories should be carefully assessed at post mortem in SCD cases, even where there are no signs of myocardial infarction. The immediate cause of SCAD is likely to be the development of a spontaneous intramural haematoma rather than an intimal disruption or 'tear'. This does not seem to be directly related to increased vasa vasorum density, coronary fibromuscular dysplasia or local inflammation (except as a response to injury). Although SCAD is rarely associated with hereditary connective tissue disorders, there does not seem to be a more generalizable global connective tissue ultrastructural abnormality in most cases

Using matrix assisted laser desorption ionisation mass spectrometry (MALDI-MS) profiling in order to predict clinical outcomes of patients with heart failure

Background Current risk prediction models in heart failure (HF) including clinical characteristics and biomarkers only have moderate predictive value. The aim of this study was to use matrix assisted laser desorption ionisation mass spectrometry (MALDI-MS) profiling to determine if a combination of peptides identified with MALDI-MS will better predict clinical outcomes of patients with HF. Methods A cohort of 100 patients with HF were recruited in the biomarker discovery phase (50 patients who died or had a HF hospital admission vs. 50 patients who did not have an event). The peptide extraction from plasma samples was performed using reversed phase C18. Then samples were analysed using MALDI-MS. A multiple peptide biomarker model was discovered that was able to predict clinical outcomes for patients with HF. Finally, this model was validated in an independent cohort with 100 patients with HF. Results After normalisation and alignment of all the processed spectra, a total of 11,389 peptides (m/z) were detected using MALDI-MS. A multiple biomarker model was developed from 14 plasma peptides that was able to predict clinical outcomes in HF patients with an area under the receiver operating characteristic curve (AUC) of 1.000 (p = 0.0005). This model was validated in an independent cohort with 100 HF patients that yielded an AUC of 0.817 (p = 0.0005) in the biomarker validation phase. Addition of this model to the BIOSTAT risk prediction model increased the predictive probability for clinical outcomes of HF from an AUC value of 0.643 to an AUC of 0.823 (p = 0.0021). Moreover, using the prediction model of fourteen peptides and the composite model of the multiple biomarker of fourteen peptides with the BIOSTAT risk prediction model achieved a better predictive probability of time-to-event in prediction of clinical events in patients with HF (p = 0.0005). Conclusions The results obtained in this study suggest that a cluster of plasma peptides using MALDI-MS can reliably predict clinical outcomes in HF that may help enable precision medicine in HF

Replication of the association of chromosomal region 9p21.3 with generalized aggressive periodontitis (gAgP) using an independent case-control cohort

Background: The human chromosomal region 9p21.3 has been shown to be strongly associated with Coronary Heart Disease (CHD) in several Genome-wide Association Studies (GWAS). Recently, this region has also been shown to be associated with Aggressive Periodontitis (AgP), strengthening the hypothesis that the established epidemiological association between periodontitis and CHD is caused by a shared genetic background, in addition to common environmental and behavioural risk factors. However, the size of the analyzed cohorts in this primary analysis was small compared to other association studies on complex diseases. Using our own AgP cohort, we attempted to confirm the described associations for the chromosomal region 9p21.3. Methods: We analyzed our cohort consisting of patients suffering from the most severe form of AgP, generalized AgP (gAgP) (n = 130) and appropriate periodontally healthy control individuals (n = 339) by genotyping four tagging SNPs (rs2891168, rs1333042, rs1333048 and rs496892), located in the chromosomal region 9p21.3, that have been associated with AgP. Results: The results confirmed significant associations between three of the four SNPs and gAgP. The combination of our results with those from the study which described this association for the first time in a meta-analysis of the four tagging SNPs produced clearly lower p-values compared with the results of each individual study. According to these results, the most plausible genetic model for the association of all four tested SNPs with gAgP seems to be the multiplicative one. Conclusion: We positively replicated the finding of an association between the chromosomal region 9p21.3 and gAgP. This result strengthens support for the hypothesis that shared susceptibility genes within this chromosomal locus might be involved in the pathogenesis of both CHD and gAgP

Small Interfering RNA Targeted to IGF-IR Delays Tumor Growth and Induces Proinflammatory Cytokines in a Mouse Breast Cancer Model

Insulin-like growth factor I (IGF-I) and its type I receptor (IGF-IR) play significant roles in tumorigenesis and in immune response. Here, we wanted to know whether an RNA interference approach targeted to IGF-IR could be used for specific antitumor immunostimulation in a breast cancer model. For that, we evaluated short interfering RNA (siRNAs) for inhibition of in vivo tumor growth and immunological stimulation in immunocompetent mice. We designed 2′-O-methyl-modified siRNAs to inhibit expression of IGF-IR in two murine breast cancer cell lines (EMT6, C4HD). Cell transfection of IGF-IR siRNAs decreased proliferation, diminished phosphorylation of downstream signaling pathway proteins, AKT and ERK, and caused a G0/G1 cell cycle block. The IGF-IR silencing also induced secretion of two proinflammatory cytokines, TNF- α and IFN-γ. When we transfected C4HD cells with siRNAs targeting IGF-IR, mammary tumor growth was strongly delayed in syngenic mice. Histology of developing tumors in mice grafted with IGF-IR siRNA treated C4HD cells revealed a low mitotic index, and infiltration of lymphocytes and polymorphonuclear neutrophils, suggesting activation of an antitumor immune response. When we used C4HD cells treated with siRNA as an immunogen, we observed an increase in delayed-type hypersensitivity and the presence of cytotoxic splenocytes against wild-type C4HD cells, indicative of evolving immune response. Our findings show that silencing IGF-IR using synthetic siRNA bearing 2′-O-methyl nucleotides may offer a new clinical approach for treatment of mammary tumors expressing IGF-IR. Interestingly, our work also suggests that crosstalk between IGF-I axis and antitumor immune response can mobilize proinflammatory cytokines

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

Recent methods for polygenic analysis of genome-wide data implicate an important effect of common variants on cardiovascular disease risk

<p>Abstract</p> <p>Background</p> <p>Traditional genome-wide association studies are generally limited in their ability explain a large portion of genetic risk for most common diseases. We sought to use both traditional GWAS methods, as well as more recently developed polygenic genome-wide analysis techniques to identify subsets of single-nucleotide polymorphisms (SNPs) that may be involved in risk of cardiovascular disease, as well as estimate the heritability explained by common SNPs.</p> <p>Methods</p> <p>Using data from the Framingham SNP Health Association Resource (SHARe), three complimentary methods were applied to examine the genetic factors associated with the Framingham Risk Score, a widely accepted indicator of underlying cardiovascular disease risk. The first method adopted a traditional GWAS approach - independently testing each SNP for association with the Framingham Risk Score. The second two approaches involved polygenic methods with the intention of providing estimates of aggregate genetic risk and heritability.</p> <p>Results</p> <p>While no SNPs were independently associated with the Framingham Risk Score based on the results of the traditional GWAS analysis, we were able to identify cardiovascular disease-related SNPs as reported by previous studies. A predictive polygenic analysis was only able to explain approximately 1% of the genetic variance when predicting the 10-year risk of general cardiovascular disease. However, 20% to 30% of the variation in the Framingham Risk Score was explained using a recently developed method that considers the joint effect of all SNPs simultaneously.</p> <p>Conclusion</p> <p>The results of this study imply that common SNPs explain a large amount of the variation in the Framingham Risk Score and suggest that future, better-powered genome-wide association studies, possibly informed by knowledge of gene-pathways, will uncover more risk variants that will help to elucidate the genetic architecture of cardiovascular disease.</p

Genome-wide association meta-analysis of spontaneous coronary artery dissection identifies risk variants and genes related to artery integrity and tissue-mediated coagulation

Spontaneous coronary artery dissection (SCAD) is an understudied cause of myocardial infarction primarily affecting women. It is not known to what extent SCAD is genetically distinct from other cardiovascular diseases, including atherosclerotic coronary artery disease (CAD). Here we present a genome-wide association meta-analysis (1,917 cases and 9,292 controls) identifying 16 risk loci for SCAD. Integrative functional annotations prioritized genes that are likely to be regulated in vascular smooth muscle cells and artery fibroblasts and implicated in extracellular matrix biology. One locus containing the tissue factor gene F3, which is involved in blood coagulation cascade initiation, appears to be specific for SCAD risk. Several associated variants have diametrically opposite associations with CAD, suggesting that shared biological processes contribute to both diseases, but through different mechanisms. We also infer a causal role for high blood pressure in SCAD. Our findings provide novel pathophysiological insights involving arterial integrity and tissue-mediated coagulation in SCAD and set the stage for future specific therapeutics and preventions