Citations

Abstract Context: Recent studies showed that transcription of the MYC gene is driven by the interaction of bromodomain and extraterminal domain (BET) proteins with acetylated histones on chromatin. JQ1, a potent inhibitor that effectively disrupts the interaction of BET proteins with acetylated histones, preferentially suppresses transcription of the MYC gene. We recently reported that JQ1 decreased thyroid tumor growth and improved survival in a mouse model of anaplastic thyroid cancer (ATC) by targeting MYC transcription. The role of MYC in human ATC and whether JQ1 can effectively target MYC as a treatment modality have not been elucidated. Objective: To understand the underlying molecular mechanisms of JQ1, we evaluated its efficacy in human ATC cell lines and xenograft models. Design: We determined the effects of JQ1 on proliferation and invasion in cell lines and xenograft tumors. We identified key regulators critical for JQ1-affected proliferation and invasion of tumor cells. Results: JQ1 markedly inhibited proliferation of four ATC cell lines by suppression of MYC and elevation of p21and p27 to decrease phosphorylated Rb and delay cell cycle progression from the G0/G1 phase to the S phase. JQ1 blocked cell invasion by attenuating epithelial-mesenchymal transition signals. These cell-based studies were further confirmed in xenograft studies in which the size and rate of tumor growth were inhibited by JQ1 via inhibition of p21-cyclin/cyclin-dependent kinase-Rb-E2F signaling. Conclusions: These results suggest targeting of the MYC protein could be a potential treatment modality for human ATC for which effective treatment options are limited.

Abstract Downstream regulatory element antagonist modulator (DREAM) is an EF-hand Ca2+-binding protein that also binds to a specific DNA sequence, downstream regulatory elements (DRE), and thereby regulates transcription in a calcium-dependent fashion. DREAM binds to DRE in the absence of Ca2+ but detaches from DRE under Ca2+ stimulation, allowing gene expression. The Ca2+ binding properties of DREAM and the consequences of the binding on protein structure are key to understanding the function of DREAM. Here we describe the application of hydrogen–deuterium exchange mass spectrometry (HDX-MS) and site-directed mutagenesis to investigate the Ca2+ binding properties and the subsequent conformational changes of full-length DREAM. We demonstrate that all EF-hands undergo large conformation changes upon calcium binding even though the EF-1 hand is not capable of binding to Ca2+. Moreover, EF-2 is a lower-affinity site compared to EF-3 and -4 hands. Comparison of HDX profiles between wild-type DREAM and two EF-1 mutated constructs illustrates that the conformational changes in the EF-1 hand are induced by long-range structural interactions. HDX analyses also reveal a conformational change in an N-terminal leucine-charged residue-rich domain (LCD) remote from Ca2+-binding EF-hands. This LCD domain is responsible for the direct interaction between DREAM and cAMP response element-binding protein (CREB) and regulates the recruitment of the co-activator, CREB-binding protein. These long-range interactions strongly suggest how conformational changes transmit the Ca2+ signal to CREB-mediated gene transcription.

Objectives Recent studies have indicated that excessive fat may confound assessment of diffusion in organs with high fat content, such as the liver and breast. However, the extent of this effect in the kidney, which is not considered a major fat deposition site, remains unclear. This study tested the hypothesis that renal fat may impact diffusion-weighted imaging (DWI) parameters, and proposes a 3-compartment model (TCM) to circumvent this effect. Methods Using computer simulations, we investigated the effect of fat on assessment of apparent diffusion coefficient (ADC), intravoxel incoherent motion (IVIM), and TCM-derived pure-diffusivity. We also investigated the influence of magnetic resonance repetition (TR) and echo time (TE) on DWI parameters as a result of variation in the relative contribution of the fat signal. Apparent diffusion coefficient, IVIM and TCM DWI parameters were calculated in domestic pigs fed a high-cholesterol (obese group) or normal diet (lean group), and correlated to renal histology. Intravoxel incoherent motion–derived pure-diffusivity was also compared among 15 essential hypertension patients classified by body mass index (BMI) (high vs normal). Finally, pure-diffusivity was calculated and compared in 8 patients with atherosclerotic renal artery stenosis (ARAS) and 5 healthy subjects using IVIM and TCM. Results Simulations showed that unaccounted fat results in the underestimation of IVIM-derived pure diffusivity. The underestimation increases as the fat fraction increases, with higher pace at lower fat contents. The underestimation was larger for shorter TR and longer TE values due to the enhancement of the relative contribution of the fat signal. Moreover, TCM, which incorporates highly diffusion-weighted images (b > 2500 s/mm2), could correct for fat-dependent underestimation. Animal studies in the lean and obese groups confirmed lower ADC and IVIM pure-diffusivity in obese versus lean pigs with otherwise healthy kidneys, whereas pure-diffusivity calculated using TCM were not different between the 2 groups. Similarly, essential hypertension patients with high BMI had lower ADC (1.9 vs 2.1 × 10−3 mm2/s) and pure-diffusivity (1.7 vs 1.9 × 10−3 mm2/s) than those with normal BMI. Pure-diffusivity calculated using IVIM was not different between the ARAS and healthy subjects, but TCM revealed significantly lower diffusivity in ARAS. Conclusions Excessive renal fat may cause underestimation of renal ADC and IVIM-derived pure-diffusivity, which may hinder detection of renal pathology. Models accounting for fat contribution may help reduce the variability of diffusivity calculated using DWI.

AbstractMotivationNext generation sequencing technologies have enabled the study of the human microbiome through direct sequencing of microbial DNA, resulting in an enormous amount of microbiome sequencing data. One unique characteristic of microbiome data is the phylogenetic tree that relates all the bacterial species. Closely related bacterial species have a tendency to exhibit a similar relationship with the environment or disease. Thus, incorporating the phylogenetic tree information can potentially improve the detection power for microbiome-wide association studies, where hundreds or thousands of tests are conducted simultaneously to identify bacterial species associated with a phenotype of interest. Despite much progress in multiple testing procedures such as false discovery rate (FDR) control, methods that take into account the phylogenetic tree are largely limited.ResultsWe propose a new FDR control procedure that incorporates the prior structure information and apply it to microbiome data. The proposed procedure is based on a hierarchical model, where a structure-based prior distribution is designed to utilize the phylogenetic tree. By borrowing information from neighboring bacterial species, we are able to improve the statistical power of detecting associated bacterial species while controlling the FDR at desired levels. When the phylogenetic tree is mis-specified or non-informative, our procedure achieves a similar power as traditional procedures that do not take into account the tree structure. We demonstrate the performance of our method through extensive simulations and real microbiome datasets. We identified far more alcohol-drinking associated bacterial species than traditional methods.Availability and implementationR package StructFDR is available from CRAN.Supplementary informationSupplementary data are available at Bioinformatics online.

Abstract Endometrial cancer studies have led to a number of well-defined but mechanistically unconnected genetic and environmental risk factors. One of the emerging modulators between environmental triggers and genetic expression is the microbiome. Because of the inflammatory display in endometrial cancer, we set out to inquire about the composition of the uterine microbiome and its putative role in endometrial cancer. We undertook a pilot study of the microbiome in 238 samples taken from different locations along the entire female reproductive tract in hysterectomy patients with endometrial cancer (n=17), patients with endometrial hyperplasia (n=4) and patients afflicted with a benign uterine condition (n=10). Samples were collected aseptically both in the operating room and the pathology laboratory. Following DNA extraction, the 16S rDNA (V3-V5 region) microbial gene was amplified and sequenced to identify the microbiota present. The microbiome sequencing revealed a structural microbiome shift in the cancer and hyperplasia cases, distinguishable from the benign cases (p=0.01). Several taxa were found to be significantly enriched in samples belonging to the endometrial cancer cohort: Firmicutes (Anaerostipes, ph2, Dialister, Peptoniphilus, 1-68, Ruminococcus, and Anaerotruncus), Spirochaetes (Treponema), Actinobacteria (Atopobium), Bacteroidetes (Bacteroides and Porphyromonas), and Proteobacteria (Arthrospira). Of particular relevance, the simultaneous presence of Atopobium vaginae and an uncultured representative of the Porphyromonas sp. (99% match to P.somerae) were found to be predictive of the disease status (sensitivity 73-93%; specificity 67-90%, AUC 0.918). Sensitivity is increased to 100% if combined with a high vaginal pH (>4.5), although specificity is decreased to 60%. Although our numbers are low, the microbiome signature of hyperplasia was even more distinct from benign disease than endometrial cancer itself. This is suggestive of an early microbiome role in the disease. Given the pathogenic profile of the identified microorganisms these findings raise the possibility of a microbiome role in the etiology or progression of endometrial cancer that should be further investigated. Citation Format: Marina Walther-Antonio, Jun Chen, Francesco Multinu, Alexis Hokenstad, Tammy Distad, Heidi Cheek, Gary Keeney, Douglas Creedon, Heidi Nelson, Andrea Mariani, Nicholas Chia. Endometrial cancer microbiome signature and its implications for carcinogenesis. [abstract]. In: Proceedings of the AACR Precision Medicine Series: Targeting the Vulnerabilities of Cancer; May 16-19, 2016; Miami, FL. Philadelphia (PA): AACR; Clin Cancer Res 2017;23(1_Suppl):Abstract nr B45.

ABSTRACT Whole-genome sequencing (WGS) can provide excellent resolution in global and local epidemiological investigations of Staphylococcus aureus outbreaks. A variety of sequencing approaches and analytical tools have been used; it is not clear which is ideal. We compared two WGS strategies and two analytical approaches to the standard method of SmaI restriction digestion pulsed-field gel electrophoresis (PFGE) for typing S. aureus . Forty-two S. aureus isolates from three outbreaks and 12 reference isolates were studied. Near-complete genomes, assembled de novo with paired-end and long-mate-pair (8 kb) libraries were first assembled and analyzed utilizing an in-house assembly and analytical informatics pipeline. In addition, paired-end data were assembled and analyzed using a commercial software package. Single nucleotide variant (SNP) analysis was performed using the in-house pipeline. Two assembly strategies were used to generate core genome multilocus sequence typing (cgMLST) data. First, the near-complete genome data generated with the in-house pipeline were imported into the commercial software and used to perform cgMLST analysis. Second, the commercial software was used to assemble paired-end data, and resolved assemblies were used to perform cgMLST. Similar isolate clustering was observed using SNP calling and cgMLST, regardless of data assembly strategy. All methods provided more discrimination between outbreaks than did PFGE. Overall, all of the evaluated WGS strategies yielded statistically similar results for S. aureus typing.