Epigenetic modifications such as histone methylation play an important role in human cancer metastasis. Enhancer of zeste homolog 2 (EZH2), which encodes the histone methyltransferase component of the polycomb repressive complex 2 (PRC2), is overexpressed widely in breast and prostate cancers and epigenetically silences tumor suppressor genes. Expression levels of the novel tumor and metastasis suppressor Raf-1 kinase inhibitor protein (RKIP) have been shown to correlate negatively with those of EZH2 in breast and prostate cell lines as well as in clinical cancer tissues. Here, we show that the RKIP/EZH2 ratio significantly decreases with the severity of disease and is negatively associated with relapse-free survival in breast cancer. Using a combination of loss-and gain-of-function approaches, we found that EZH2 negatively regulated RKIP transcription through repressionassociated histone modifications. Direct recruitment of EZH2 and suppressor of zeste 12 (Suz12) to the proximal E-boxes of the RKIP promoter was accompanied by H3-K27-me3 and H3-K9-me3 modifications. The repressing activity of EZH2 on RKIP expression was dependent on histone deacetylase promoter recruitment and was negatively regulated upstream by miR-101. Together, our findings indicate that EZH2 accelerates cancer cell invasion, in part, via RKIP inhibition. These data also implicate EZH2 in the regulation of RKIP transcription, suggesting a potential mechanism by which EZH2 promotes tumor progression and metastasis.

Aims While most patients with myocardial infarction (MI) have underlying coronary atherosclerosis, not all patients with coronary artery disease (CAD) develop MI. We sought to address the hypothesis that some of the genetic factors which establish atherosclerosis may be distinct from those that predispose to vulnerable plaques and thrombus formation. Methods and results We carried out a genome-wide association study for MI in the UK Biobank (n∼472 000), followed by a meta-analysis with summary statistics from the CARDIoGRAMplusC4D Consortium (n∼167 000). Multiple independent replication analyses and functional approaches were used to prioritize loci and evaluate positional candidate genes. Eight novel regions were identified for MI at the genome wide significance level, of which effect sizes at six loci were more robust for MI than for CAD without the presence of MI. Confirmatory evidence for association of a locus on chromosome 1p21.3 harbouring choline-like transporter 3 (SLC44A3) with MI in the context of CAD, but not with coronary atherosclerosis itself, was obtained in Biobank Japan (n∼165 000) and 16 independent angiography-based cohorts (n∼27 000). Follow-up analyses did not reveal association of the SLC44A3 locus with CAD risk factors, biomarkers of coagulation, other thrombotic diseases, or plasma levels of a broad array of metabolites, including choline, trimethylamine N-oxide, and betaine. However, aortic expression of SLC44A3 was increased in carriers of the MI risk allele at chromosome 1p21.3, increased in ischaemic (vs. non-diseased) coronary arteries, up-regulated in human aortic endothelial cells treated with interleukin-1β (vs. vehicle), and associated with smooth muscle cell migration in vitro. Conclusions A large-scale analysis comprising ∼831 000 subjects revealed novel genetic determinants of MI and implicated SLC44A3 in the pathophysiology of vulnerable plaques.

Among thousands of non-protein-coding RNAs which have been found in humans, a significant group represents snoRNA molecules that guide other types of RNAs to specific chemical modifications, cleavages, or proper folding. Yet, hundreds of mammalian snoRNAs have unknown function and are referred to as "orphan" molecules. In 2006, for the first time, it was shown that a particular orphan snoRNA (HBII-52) plays an important role in the regulation of alternative splicing of the serotonin receptor gene in humans and other mammals. In order to facilitate the investigation of possible involvement of snoRNAs in the regulation of pre-mRNA processing, we developed a new computational web resource, snoTARGET, which searches for possible guiding sites for snoRNAs among the entire set of human and rodent exonic and intronic sequences. Application of snoTARGET for finding possible guiding sites for a number of human and rodent orphan C/D-box snoRNAs showed that another subgroup of these molecules (HBII-85) have statistically elevated guiding preferences toward exons compared to introns. Moreover, these energetically favorable putative targets of HBII-85 snoRNAs are non-randomly associated with genes producing alternatively spliced mRNA isoforms. The snoTARGET resource is freely available at: (http://hsc.utoledo.edu/depts/bioinfo/snotarget.html).

Asthma resistance to glucocorticoid treatment is a major health problem with unclear etiology. Glucocorticoids inhibit adrenal androgen production. However, androgens have potential benefits in asthma. HSD3B1 encodes for 3β-hydroxysteroid dehydrogenase-1 (3β-HSD1), which catalyzes peripheral conversion from adrenal dehydroepiandrosterone (DHEA) to potent androgens and has a germline missense-encoding polymorphism. The adrenal restrictive HSD3B1(1245A) allele limits conversion, whereas the adrenal permissive HSD3B1(1245C) allele increases DHEA metabolism to potent androgens. In the Severe Asthma Research Program (SARP) III cohort, we determined the association between DHEA-sulfate and percentage predicted forced expiratory volume in 1 s (FEV1PP). HSD3B1(1245) genotypes were assessed, and association between adrenal restrictive and adrenal permissive alleles and FEV1PP in patients with (GC) and without (noGC) daily oral glucocorticoid treatment was determined (n = 318). Validation was performed in a second cohort (SARP I&II; n = 184). DHEA-sulfate is associated with FEV1PP and is suppressed with GC treatment. GC patients homozygous for the adrenal restrictive genotype have lower FEV1PP compared with noGC patients (54.3% vs. 75.1%; P < 0.001). In patients with the homozygous adrenal permissive genotype, there was no FEV1PP difference in GC vs. noGC patients (73.4% vs. 78.9%; P = 0.39). Results were independently confirmed: FEV1PP for homozygous adrenal restrictive genotype in GC vs. noGC is 49.8 vs. 63.4 (P < 0.001), and for homozygous adrenal permissive genotype, it is 66.7 vs. 67.7 (P = 0.92). The adrenal restrictive HSD3B1(1245) genotype is associated with GC resistance. This effect appears to be driven by GC suppression of 3β-HSD1 substrate. Our results suggest opportunities for prediction of GC resistance and pharmacologic intervention.

Epithelial ovarian cancer (EOC) is the leading cause of gynecologic cancer death. Despite initial responses to intervention, up to 80% of patient tumors recur and require additional treatment. Retrospective clinical analysis of OC patients indicates antibiotic use during chemotherapy treatment is associated with poor overall survival. Here, we assessed whether antibiotic (ABX) treatment would impact growth of EOC and sensitivity to cisplatin. Immunocompetent or immunocompromised mice were given untreated control or ABX-containing (metronidazole, ampicillin, vancomycin, and neomycin) water prior to intraperitoneal injection with EOC cells, and cisplatin therapy was administered biweekly until endpoint. Tumor-bearing ABX-treated mice exhibited accelerated tumor growth and resistance to cisplatin therapy compared with control treatment. ABX treatment led to reduced apoptosis, increased DNA damage repair, and enhanced angiogenesis in cisplatin-treated tumors, and tumors from ABX-treated mice contained a higher frequency of cisplatin-augmented cancer stem cells than control mice. Stool analysis indicated non-resistant gut microbial species were disrupted by ABX treatment. Cecal transplants of microbiota derived from control-treated mice was sufficient to ameliorate chemoresistance and prolong survival of ABX-treated mice, indicative of a gut-derived tumor suppressor. Metabolomics analyses identified circulating gut-derived metabolites that were altered by ABX treatment and restored by recolonization, providing candidate metabolites that mediate the crosstalk between the gut microbiome and ovarian cancer. Collectively, these findings indicate that an intact microbiome functions as a tumor suppressor in EOC, and perturbation of the gut microbiota with ABX treatment promotes tumor growth and suppresses cisplatin sensitivity.

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Background Trimethylamine‐ N ‐oxide (TMAO) is a small molecule derived from the metabolism of dietary nutrients by gut microbes and contributes to cardiovascular disease. Plasma TMAO increases following consumption of red meat. This metabolic change is thought to be partly because of the expansion of gut microbes able to use nutrients abundant in red meat. Methods and Results We used data from a randomized crossover study to estimate the degree to which TMAO can be estimated from fecal microbial composition. Healthy participants received a series of 3 diets that differed in protein source (red meat, white meat, and non‐meat), and fecal, plasma, and urine samples were collected following 4 weeks of exposure to each diet. TMAO was quantitated in plasma and urine, while shotgun metagenomic sequencing was performed on fecal DNA. While the cai gene cluster was weakly correlated with plasma TMAO (rho=0.17, P =0.0007), elastic net models of TMAO were not improved by abundances of bacterial genes known to contribute to TMAO synthesis. A global analysis of all taxonomic groups, genes, and gene families found no meaningful predictors of TMAO. We postulated that abundances of known genes related to TMAO production do not predict bacterial metabolism, and we measured choline‐ and carnitine‐trimethylamine lyase activity during fecal culture. Trimethylamine lyase genes were only weakly correlated with the activity of the enzymes they encode. Conclusions Fecal microbiome composition does not predict systemic TMAO because, in this case, gene copy number does not predict bacterial metabolic activity. Registration URL: https://www.clinicaltrials.gov ; Unique identifier: NCT01427855.

Cytochrome P450 2D6 (CYP2D6) is used to develop an approach for predicting affinity and relevant binding conformation(s) for highly flexible binding sites. The approach combines the use of docking scores and compound properties as attributes in building a neural network (NN) model. It begins by identifying segments of CYP2D6 that are important for binding specificity, based on structural variability among diverse CYP enzymes. A family of distinct, low-energy conformations of CYP2D6 are generated using simulated annealing (SA) and a collection of 82 compounds with known CYP2D6 affinities are docked. Interestingly, docking poses are observed on the backside of the heme as well as in the known actiVe site. Docking scores for the actiVe site binders, along with compound-specific attributes, are used to train a neural network model to properly bin compounds as strong binders, moderate binders, or nonbinders. Attribute selection is used to preselect the most important scores and compound-specific attributes for the model. A prediction accuracy of 85 ( 6% is achieved. Dominant attributes include docking scores for three of the 20 conformations in the ensemble as well as the compound's formal charge, number of aromatic rings, and AlogP. Although compound properties were highly predictive attributes (12% improvement over baseline) in the NN-based prediction of CYP2D6 binders, their combined use with docking score attributes is synergistic (net increase of 23% above baseline). Beyond prediction of affinity, attribute selection provides a way to identify the most relevant protein conformation(s), in terms of binding competence. In the case of CYP2D6, three out of the ensemble of 20 SA-generated structures are found to be the most predictive for binding.