Citations

ABSTRACT The last decade has seen a sharp increase in the number of scientific publications describing physiological and pathological functions of extracellular vesicles (EVs), a collective term covering various subtypes of cell‐released, membranous structures, called exosomes, microvesicles, microparticles, ectosomes, oncosomes, apoptotic bodies, and many other names. However, specific issues arise when working with these entities, whose size and amount often make them difficult to obtain as relatively pure preparations, and to characterize properly. The International Society for Extracellular Vesicles (ISEV) proposed Minimal Information for Studies of Extracellular Vesicles (“MISEV”) guidelines for the field in 2014. We now update these “MISEV2014” guidelines based on evolution of the collective knowledge in the last four years. An important point to consider is that ascribing a specific function to EVs in general, or to subtypes of EVs, requires reporting of specific information beyond mere description of function in a crude, potentially contaminated, and heterogeneous preparation. For example, claims that exosomes are endowed with exquisite and specific activities remain difficult to support experimentally, given our still limited knowledge of their specific molecular machineries of biogenesis and release, as compared with other biophysically similar EVs. The MISEV2018 guidelines include tables and outlines of suggested protocols and steps to follow to document specific EV‐associated functional activities. Finally, a checklist is provided with summaries of key points.

Middle cluneal nerve entrapment neuropathy/neuralgia (MCN-EN) is a rare and potentially underdiagnosed etiology for chronic low back pain. Symptoms include pain in the buttock and posterior superior iliac spine area that is increased by activity and direct pressure over the area, and is “neuropathic” in nature. Previous case reports describe successful treatment of MCN-EN with nerve block and/or surgical decompression of the MCN. We present a case report detailing the first successful use of radiofrequency nerve ablation in treating MCN-EN.

Abstract Background: Whether associations between circulating metabolites and prostate cancer are causal is unknown. We report on the largest study of metabolites and prostate cancer (2,291 cases and 2,661 controls) and appraise causality for a subset of the prostate cancer–metabolite associations using two-sample Mendelian randomization (MR). Methods: The case–control portion of the study was conducted in nine UK centers with men ages 50–69 years who underwent prostate-specific antigen screening for prostate cancer within the Prostate Testing for Cancer and Treatment (ProtecT) trial. Two data sources were used to appraise causality: a genome-wide association study (GWAS) of metabolites in 24,925 participants and a GWAS of prostate cancer in 44,825 cases and 27,904 controls within the Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium. Results: Thirty-five metabolites were strongly associated with prostate cancer (P < 0.0014, multiple-testing threshold). These fell into four classes: (i) lipids and lipoprotein subclass characteristics (total cholesterol and ratios, cholesterol esters and ratios, free cholesterol and ratios, phospholipids and ratios, and triglyceride ratios); (ii) fatty acids and ratios; (iii) amino acids; (iv) and fluid balance. Fourteen top metabolites were proxied by genetic variables, but MR indicated these were not causal. Conclusions: We identified 35 circulating metabolites associated with prostate cancer presence, but found no evidence of causality for those 14 testable with MR. Thus, the 14 MR-tested metabolites are unlikely to be mechanistically important in prostate cancer risk. Impact: The metabolome provides a promising set of biomarkers that may aid prostate cancer classification.

Background: The human Monoamine Transporters (hMATs), primarily including hSERT, hNET and hDAT, are important targets for the treatment of depression and other behavioral disorders with more than the availability of 30 approved drugs. Objective: This paper is to review the recent progress in the binding mode and inhibitory mechanism of hMATs inhibitors with the central or allosteric binding sites, for the benefit of future hMATs inhibitor design and discovery. The Structure-Activity Relationship (SAR) and the selectivity for hit/lead compounds to hMATs that are evaluated by in vitro and in vivo experiments will be highlighted. Methods: PubMed and Web of Science databases were searched for protein-ligand interaction, novel inhibitors design and synthesis studies related to hMATs. Results: Literature data indicate that since the first crystal structure determinations of the homologous bacterial Leucine Transporter (LeuT) complexed with clomipramine, a sizable database of over 100 experimental structures or computational models has been accumulated that now defines a substantial degree of structural variability hMATs-ligands recognition. In the meanwhile, a number of novel hMATs inhibitors have been discovered by medicinal chemistry with significant help from computational models. Conclusion: The reported new compounds act on hMATs as well as the structures of the transporters complexed with diverse ligands by either experiment or computational modeling have shed light on the poly-pharmacology, multimodal and allosteric regulation of the drugs to transporters. All of the studies will greatly promote the Structure-Based Drug Design (SBDD) of structurally novel scaffolds with high activity and selectivity for hMATs.

AbstractRecent research has highlighted the importance of the human microbiome in many human disease and health conditions. Most current microbiome association analyses focus on unrelated samples; such methods are not appropriate for analysis of data collected from more advanced study designs such as longitudinal and pedigree studies, where outcomes can be correlated. Ignoring such correlations can sometimes lead to suboptimal results or even possibly biased conclusions. Thus, new methods to handle correlated outcome data in microbiome association studies are needed. In this paper, we propose the correlated sequence kernel association test (CSKAT) to address such correlations using the linear mixed model. Specifically, random effects are used to account for the outcome correlations and a variance component test is used to examine the microbiome effect. Compared to existing genetic association tests for longitudinal and family samples, we implement a correction procedure to better calibrate the null distribution of the score test statistic to accommodate the small sample size nature of data collected from a typical microbiome study. Comprehensive simulation studies are conducted to demonstrate the validity and efficiency of our method, and we show that CSKAT achieves a higher power than existing methods while correctly controlling the Type I error rate. We also apply our method to a microbiome data set collected from a UK twin study to illustrate its potential usefulness. A free implementation of our method in R software is available at https://github.com/jchen1981/SSKAT.

T cell responses to subunit vaccination require both IL-27 and IL-15 to support an aerobic glycolysis–independent metabolic program.

Abstract Hepatocellular carcinoma (HCC) is the second most common cause of cancer deaths worldwide. Hepatitis C virus (HCV) infection is a major risk factor for HCC in the US. HCV infection may cause cancer by suppressing host defense that controls the propagation of repetitive element (RE) sequences, including LINE-1 and Alu, the most representative REs in the human genome. DNA methylation of RE helps stabilize the genome, while reduced RE methylation, also referred as global hypomethylation, leads to genomic instability and is known as a hallmark of cancer. However, current available high-throughput technology for DNA methylation profiling only enables genomewide RE methylation study on a global scale. The role of individual RE methylation in cancer is largely understudied. In this study, using our recently developed and published machine learning algorithm to enhance the RE coverage of the Illumina methylation array platform, we examined the role of individual RE methylation in HCV-induced HCC across the entire genome. We conducted an epigenome-wide association study on 22 HCC, 20 cirrhotic, and 44 normal liver tissues. We included equal numbers of HCV-induced and alcohol-induced HCC/cirrhosis cases. The Illumina 450k array profiled 1939 REs and we computationally predicted 33184 REs; correlations between the overlapping 1541 profiled and predicted RE methylation were > 0.91. Sex, tumor differentiation, and tumor stage were similarly distributed across the HCV and alcohol groups. We adjusted for batch effects and used Benjamini-Hochberg adjusted false discovery rate (FDR) to account for multiple testing. Relative to normal liver tissue, we observed over twice as many differentially methylated (FDR < 0.05) REs in HCV-HCC compared to alcohol-HCC tissue (2911 vs 1304, 749 in common). We validated our results in The Cancer Genome Atlas (TCGA) (325 vs 129, 74 in common) with high correlation (r = 0.90). We also observed that 169 REs were significantly altered in HCV-cirrhosis tissue (compared to none in alcohol-cirrhosis tissue), of which, 17 REs in 13 genes, including PIK3CD, LY9, GCK, NLRC3, and PRKCZ, were consistently hypomethylated in both HCC and cirrhotic liver tissue induced by HCV (r = 0.87). Using TCGA RNA sequencing data, we found that these REs were located in gene body and their hypomethylation was associated with lower expression of their host genes (r > 0.3, p < 0.05). Gene Ontology Enrichment analysis showed that these genes were enriched in T-cell activation & differentiation and cytokine production (FDR < 0.05). Our findings indicate that HCV infection has a more extensive impact on the DNA methylation landscape in RE than alcohol consumption, and that HCV infection may also induce similar hypomethylation in cirrhotic liver. Hypomethylated RE may alter local chromatin environment and disrupt expression of genes involved in immune and inflammatory responses, both of which may promote HCC development. RE hypomethylation in specific genomic locus may serve as early detection biomarker of HCC in patients with HCV-induced cirrhosis. Citation Format: Yinan Zheng, Jimmy Ren, Ryan A. Hlady, Keith D. Robertson, Robert L. Murphy, Lewis R. Roberts, Lifang Hou. DNA methylation of individual repetitive elements in HCV infection-induced HCC [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr LB-235.

Abstract Biodistribution detection methods currently hold a central role in evaluating clinical potential of new drugs and nanomedicine in vivo, either through therapeutic efficacy or toxicity assays. However, the explorative nature of these methods makes it practically difficult to validate them for clinical studies to comply with regulations as determined by the Food and Drug Administration. This work proposes a new systematic comparison of biodistribution methods to facilitate clinical validation and employment in pre-clinical and early stage clinical studies. Several optical methods (detection through IVIS, confocal microscopy, fluorescence emission), direct detection methods (detection through ICP-OES), and radiation-based methods (detection through gamma counter) are systematically tested and validated on cGMP grade microparticles. The classification here proposed quantitatively highlights the advantages and disadvantages of each method, expressing them in terms of: limit of detection, recovery rate, reproducibility, and sensitivity. As a result, this quantitative evaluation of several preclinical biodistribution detection methods leads to a new rational and objective classification of biodistribution methods based on quantitative characteristics, which is essential to facilitate clinical translation of pre-clinical data collection. Their different characteristics and application-specific advantages are also discussed based in light of the results presented. Overall, this work proposes a new and rational quantitative comparison of biodistribution detection methods with the goal to provide a guide to facilitate clinical translation of on-going and future pre-clinical and early-stage clinical studies. Citation Format: Sara Nizzero, Feng Li, Alessandro Venuta, Guodong Zhang, Carlotta Borsoi, Joy Wolfram, Junhua Mai, Haifa Shen, Zheng Li, Elvin Blanco, Mauro Ferrari. Empowering preclinical studies: A systematic and quantitative analysis of biodistribution methods to facilitate clinical translation of new drugs [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr LB-019.