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Triple negative breast cancer (TNBC) is the deadliest form of breast cancer because it is more aggressive, diagnosed at later stage and more likely to develop local and systemic recurrence. Many patients do not experience adequate tumor control after current clinical treatments involving surgical removal, chemotherapy and/or radiotherapy, leading to disease progression and significantly decreased quality of life. Here we report a new combinatory therapy strategy involving cannabinoid-based medicine and photodynamic therapy (PDT) for the treatment of TNBC. This combinatory therapy targets two proteins upregulated in TNBC: the cannabinoid CB2 receptor (CBR, a G-protein coupled receptor) and translocator protein (TSPO, a mitochondria membrane receptor). We found that the combined CBR agonist and TSPO-PDT treatment resulted in synergistic inhibition in TNBC cell and tumor growth. This combinatory therapy approach provides new opportunities to treat TNBC with high efficacy. In addition, this study provides new evidence on the therapeutic potential of CBR agonists for cancer.
Copyright © 2018 Elsevier B.V. All rights reserved.
Esophageal adenocarcinoma (EAC) is a highly aggressive malignancy that is characterized by resistance to chemotherapy and a poor clinical outcome. The overexpression of the receptor tyrosine kinase AXL is frequently associated with unfavorable prognosis in EAC. Although it is well documented that AXL mediates cancer cell invasion as a downstream effector of epithelial-to-mesenchymal transition, the precise molecular mechanism underlying this process is not completely understood. Herein, we demonstrate for the first time that AXL mediates cell invasion through the regulation of lysosomes peripheral distribution and cathepsin B secretion in EAC cell lines. Furthermore, we show that AXL-dependent peripheral distribution of lysosomes and cell invasion are mediated by extracellular acidification, which is potentiated by AXL-induced secretion of lactate through AKT-NF-κB-dependent MCT-1 regulation. Our novel mechanistic findings support future clinical studies to evaluate the therapeutic potential of the AXL inhibitor R428 (BGB324) in highly invasive EAC.
Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.
Proteomics, metabolomics, and transcriptomics generate comprehensive data sets, and current biocomputational capabilities allow their efficient integration for systems biology analysis. Published multiomics studies cover methodological advances as well as applications to biological questions. However, few studies have focused on the development of a high-throughput, unified sample preparation approach to complement high-throughput omic analytics. This report details the automation, benchmarking, and application of a strategy for transcriptomic, proteomic, and metabolomic analyses from a common sample. The approach, sample preparation for multi-omics technologies (SPOT), provides equivalent performance to typical individual omic preparation methods but greatly enhances throughput and minimizes the resources required for multiomic experiments. SPOT was applied to a multiomics time course experiment for zinc-treated HL-60 cells. The data reveal Zn effects on NRF2 antioxidant and NFkappaB signaling. High-throughput approaches such as these are critical for the acquisition of temporally resolved, multicondition, large multiomic data sets such as those necessary to assess complex clinical and biological concerns. Ultimately, this type of approach will provide an expanded understanding of challenging scientific questions across many fields.
Differential gene expression defines individual neuron types and determines how each contributes to circuit physiology and responds to injury and disease. The C. elegans Neuronal Gene Expression Map & Network (CeNGEN) will establish a comprehensive gene expression atlas of an entire nervous system at single-neuron resolution.
Copyright © 2018. Published by Elsevier Inc.
Systemic lupus erythematosus (SLE) is an autoimmune disease characterized by a wide spectrum of clinical manifestations and degrees of severity. Few genomic biomarkers for SLE have been validated and employed to inform clinical classifications and decisions. To discover and assess the gene-expression based SLE predictors in published studies, we performed a meta-analysis using our established signature database and a data similarity-driven strategy. From 13 training data sets on SLE gene-expression studies, we identified a SLE meta-signature (SLEmetaSig100) containing 100 concordant genes that are involved in DNA sensors and the IFN signaling pathway. We rigorously examined SLEmetaSig100 with both retrospective and prospective validation in two independent data sets. Using unsupervised clustering, we retrospectively elucidated that SLEmetaSig100 could classify clinical samples into two groups that correlated with SLE disease status and disease activities. More importantly, SLEmetaSig100 enabled personalized stratification demonstrating its ability to prospectively predict SLE disease at the individual patient level. To evaluate the performance of SLEmetaSig100 in predicting SLE, we predicted 1,171 testing samples to be either non-SLE or SLE with positive predictive value (97-99%), specificity (85%-84%), and sensitivity (60-84%). Our study suggests that SLEmetaSig100 has enhanced predictive value to facilitate current SLE clinical classification and provides personalized disease activity monitoring.
We apply integrative approaches to expression quantitative loci (eQTLs) from 44 tissues from the Genotype-Tissue Expression project and genome-wide association study data. About 60% of known trait-associated loci are in linkage disequilibrium with a cis-eQTL, over half of which were not found in previous large-scale whole blood studies. Applying polygenic analyses to metabolic, cardiovascular, anthropometric, autoimmune, and neurodegenerative traits, we find that eQTLs are significantly enriched for trait associations in relevant pathogenic tissues and explain a substantial proportion of the heritability (40-80%). For most traits, tissue-shared eQTLs underlie a greater proportion of trait associations, although tissue-specific eQTLs have a greater contribution to some traits, such as blood pressure. By integrating information from biological pathways with eQTL target genes and applying a gene-based approach, we validate previously implicated causal genes and pathways, and propose new variant and gene associations for several complex traits, which we replicate in the UK BioBank and BioVU.
DA closure is crucial for the transition from fetal to neonatal life. This closure is supported by changes to the DA's signaling and structural properties that distinguish it from neighboring vessels. Examining transcriptional differences between these vessels is key to identifying genes or pathways responsible for DA closure. Several microarray studies have explored the DA transcriptome in animal models but varied experimental designs have led to conflicting results. Thorough transcriptomic analysis of the human DA has yet to be performed. A clear picture of the DA transcriptome is key to guiding future research endeavors, both to allow more targeted treatments in the clinical setting, and to understand the basic biology of DA function. In this review, we use a cross-species cross-platform analysis to consider all available published rodent microarray data and novel human RNAseq data in order to provide high priority candidate genes for consideration in future DA studies.
Copyright © 2018 Elsevier Inc. All rights reserved.
Metastasis is the most lethal aspect of cancer, yet current therapeutic strategies do not target its key rate-limiting steps. We have previously shown that the entry of cancer cells into the blood stream, or intravasation, is highly dependent upon in vivo cancer cell motility, making it an attractive therapeutic target. To systemically identify genes required for tumor cell motility in an in vivo tumor microenvironment, we established a novel quantitative in vivo screening platform based on intravital imaging of human cancer metastasis in ex ovo avian embryos. Utilizing this platform to screen a genome-wide shRNA library, we identified a panel of novel genes whose function is required for productive cancer cell motility in vivo, and whose expression is closely associated with metastatic risk in human cancers. The RNAi-mediated inhibition of these gene targets resulted in a nearly total (>99.5%) block of spontaneous cancer metastasis in vivo.
Pulmonary arterial hypertension (PAH) is a deadly disease with no cure. Alternate conversion of angiotensin II (AngII) to angiotensin-(1-7) (Ang-(1-7)) by angiotensin-converting enzyme 2 (ACE2) resulting in Mas receptor (Mas1) activation improves rodent models of PAH. Effects of recombinant human (rh) ACE2 in human PAH are unknown. Our objective was to determine the effects of rhACE2 in PAH.We defined the molecular effects of Mas1 activation using porcine pulmonary arteries, measured AngII/Ang-(1-7) levels in human PAH and conducted a phase IIa, open-label pilot study of a single infusion of rhACE2 (GSK2586881, 0.2 or 0.4 mg·kg intravenously).Superoxide dismutase 2 (SOD2) and inflammatory gene expression were identified as markers of Mas1 activation. After confirming reduced plasma ACE2 activity in human PAH, five patients were enrolled in the trial. GSK2586881 was well tolerated with significant improvement in cardiac output and pulmonary vascular resistance. GSK2586881 infusion was associated with reduced plasma markers of inflammation within 2-4 h and increased SOD2 plasma protein at 2 weeks.PAH is characterised by reduced ACE2 activity. Augmentation of ACE2 in a pilot study was well tolerated, associated with improved pulmonary haemodynamics and reduced markers of oxidant and inflammatory mediators. Targeting this pathway may be beneficial in human PAH.
Copyright ©ERS 2018.
PURPOSE - The identification of biomarkers related to the prognosis of triple-negative breast cancer (TNBC) is critically important for improved understanding of the biology that drives TNBC progression.
METHODS - We evaluated gene expression in total RNA isolated from formalin-fixed paraffin-embedded tumor samples using the NanoString nCounter assay for 469 TNBC cases from the Shanghai Breast Cancer Survival Study. We used Cox regression to quantify Hazard Ratios (HR) and corresponding confidence intervals (CI) for overall survival (OS) and disease-free survival (DFS) in models that included adjustment for breast cancer intrinsic subtype. Of 302 genes in our discovery analysis, 22 were further evaluated in relation to OS among 134 TNBC cases from the Nashville Breast Health Study and the Southern Community Cohort Study; 16 genes were further evaluated in relation to DFS in 335 TNBC cases from four gene expression omnibus datasets. Fixed-effect meta-analysis was used to combine results across data sources.
RESULTS - Twofold higher expression of EOMES (HR 0.90, 95% CI 0.83-0.97), RASGRP1 (HR 0.89, 95% CI 0.82-0.97), and SOD2 (HR 0.80, 95% CI 0.66-0.96) was associated with better OS. Twofold higher expression of EOMES (HR 0.89, 95% CI 0.81-0.97) and RASGRP1 (HR 0.87, 95% CI 0.81-0.95) was also associated with better DFS. On the contrary, a doubling of FA2H (HR 1.14, 95% CI 1.06-1.22) and GSPT1 (HR 1.33, 95% CI 1.14-1.55) expression was associated with shorter DFS.
CONCLUSIONS - We identified five genes (EOMES, FA2H, GSPT1, RASGRP1, and SOD2) that may serve as potential prognostic biomarkers and/or therapeutic targets for TNBC.