Averaged Differential Expression for the Discovery of Biomarkers in the Blood of Patients with Prostate Cancer

<div><h3>Background</h3><p>The identification of a blood-based diagnostic marker is a goal in many areas of medicine, including the early diagnosis of prostate cancer. We describe the use of averaged differential display as an efficient mechanism for biomarker discovery in whole blood RNA. The process of averaging reduces the problem of clinical heterogeneity while simultaneously minimizing sample handling.</p> <h3>Methodology/Principal Findings</h3><p>RNA was isolated from the blood of prostate cancer patients and healthy controls. Samples were pooled and subjected to the averaged differential display process. Transcripts present at different levels between patients and controls were purified and sequenced for identification. Transcript levels in the blood of prostate cancer patients and controls were verified by quantitative RT-PCR. Means were compared using a t-test and a receiver-operating curve was generated. The Ring finger protein 19A (RNF19A) transcript was identified as having higher levels in prostate cancer patients compared to healthy men through the averaged differential display process. Quantitative RT-PCR analysis confirmed a more than 2-fold higher level of RNF19A mRNA levels in the blood of patients with prostate cancer than in healthy controls (p = 0.0066). The accuracy of distinguishing cancer patients from healthy men using RNF19A mRNA levels in blood as determined by the area under the receiving operator curve was 0.727.</p> <h3>Conclusions/Significance</h3><p>Averaged differential display offers a simplified approach for the comprehensive screening of body fluids, such as blood, to identify biomarkers in patients with prostate cancer. Furthermore, this proof-of-concept study warrants further analysis of RNF19A as a clinically relevant biomarker for prostate cancer detection.</p> </div

Ethnic Speech and Ethnic Action as Ethnic Behavior: Part 1. Construction of the Brunel Ethnic Behavior Inventory

© 2016 Taylor & Francis.This article reports the construction of a new survey—specifically, the Brunel Ethnic Behavior Inventory (BEBI)—designed to measure ethnic speech and ethnic action as separate, yet related, aspects of individuals’ ethnic behavior. Using Tajfel’s social identity theory as a conceptual frame of reference, this study sought an answer to the research question of how many factors actually are measured by the BEBI, and tested the hypothesis that a two-factor model (i.e., Ethnic Speech and Ethnic Action as two correlated factors) would provide significantly better goodness of fit to the correlational data than would a one-factor model (i.e., Ethnic Behavior as one undifferentiated factor). Across one pilot sample (n = 101) and two main samples (n = 120 for Sample 1, n = 148 for Sample 2), the study found that not only did the BEBI measure two factors at most (i.e., Ethnic Speech and Ethnic Action) but, consistent with the hypothesis, the two-factor model yielded better goodness of fit than did the one-factor model. Implications for the conceptualization and measurement of Verkuyten’s “ways of ethnicity” are discussed

Promoter methylation of RASSF1A and DAPK and mutations of K-ras, p53, and EGFR in lung tumors from smokers and never-smokers

<p>Abstract</p> <p>Background</p> <p>Epidemiological studies indicate that some characteristics of lung cancer among never-smokers significantly differ from those of smokers. Aberrant promoter methylation and mutations in some oncogenes and tumor suppressor genes are frequent in lung tumors from smokers but rare in those from never-smokers. In this study, we analyzed promoter methylation in the <it>ras-association domain isoform A (RASSF1A) </it>and the <it>death-associated protein kinase (DAPK) </it>genes in lung tumors from patients with primarily non-small cell lung cancer (NSCLC) from the Western Pennsylvania region. We compare the results with the smoking status of the patients and the mutation status of the K-<it>ras</it>, <it>p53</it>, and <it>EGFR </it>genes determined previously on these same lung tumors.</p> <p>Methods</p> <p>Promoter methylation of the <it>RASSF1A </it>and <it>DAPK </it>genes was analyzed by using a modified two-stage methylation-specific PCR. Data on mutations of K-<it>ras</it>, <it>p53</it>, and <it>EGFR </it>were obtained from our previous studies.</p> <p>Results</p> <p>The <it>RASSF1A </it>gene promoter methylation was found in tumors from 46.7% (57/122) of the patients and was not significantly different between smokers and never-smokers, but was associated significantly in multiple variable analysis with tumor histology (p = 0.031) and marginally with tumor stage (p = 0.063). The <it>DAPK </it>gene promoter methylation frequency in these tumors was 32.8% (40/122) and did not differ according to the patients' smoking status, tumor histology, or tumor stage. Multivariate analysis adjusted for age, gender, smoking status, tumor histology and stage showed that the frequency of promoter methylation of the <it>RASSF1A </it>or <it>DAPK </it>genes did not correlate with the frequency of mutations of the K<it>-ras, p53</it>, and <it>EGFR </it>gene.</p> <p>Conclusion</p> <p>Our results showed that <it>RASSF1A </it>and <it>DAPK </it>genes' promoter methylation occurred frequently in lung tumors, although the prevalence of this alteration in these genes was not associated with the smoking status of the patients or the occurrence of mutations in the K-<it>ras</it>, <it>p53 </it>and <it>EGFR </it>genes, suggesting each of these events may represent independent event in non-small lung tumorigenesis.</p

The Future of the Correlated Electron Problem

The understanding of material systems with strong electron-electron interactions is the central problem in modern condensed matter physics. Despite this, the essential physics of many of these materials is still not understood and we have no overall perspective on their properties. Moreover, we have very little ability to make predictions in this class of systems. In this manuscript we share our personal views of what the major open problems are in correlated electron systems and we discuss some possible routes to make progress in this rich and fascinating field. This manuscript is the result of the vigorous discussions and deliberations that took place at Johns Hopkins University during a three-day workshop January 27, 28, and 29, 2020 that brought together six senior scientists and 46 more junior scientists. Our hope, is that the topics we have presented will provide inspiration for others working in this field and motivation for the idea that significant progress can be made on very hard problems if we focus our collective energies.Comment: 55 pages, 19 figure

Network-Based Elucidation of Human Disease Similarities Reveals Common Functional Modules Enriched for Pluripotent Drug Targets

Current work in elucidating relationships between diseases has largely been based on pre-existing knowledge of disease genes. Consequently, these studies are limited in their discovery of new and unknown disease relationships. We present the first quantitative framework to compare and contrast diseases by an integrated analysis of disease-related mRNA expression data and the human protein interaction network. We identified 4,620 functional modules in the human protein network and provided a quantitative metric to record their responses in 54 diseases leading to 138 significant similarities between diseases. Fourteen of the significant disease correlations also shared common drugs, supporting the hypothesis that similar diseases can be treated by the same drugs, allowing us to make predictions for new uses of existing drugs. Finally, we also identified 59 modules that were dysregulated in at least half of the diseases, representing a common disease-state “signature”. These modules were significantly enriched for genes that are known to be drug targets. Interestingly, drugs known to target these genes/proteins are already known to treat significantly more diseases than drugs targeting other genes/proteins, highlighting the importance of these core modules as prime therapeutic opportunities

Mapping of HNF4α target genes in intestinal epithelial cells

© 2009 Boyd et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

A framework for secondary cognitive and motor tasks in dual-task gait testing in people with mild cognitive impairment

Background: Cognition is a key factor in the regulation of normal walking and dual-task gait assessment is an accepted method to evaluate the relationship. The objective of this study was to create a framework for task complexity of concurrent motor and cognitive tasks with gait in people with mild cognitive impairment (MCI). Methods: Community-dwelling people with MCI (n = 41, mean age = 76.20 ± 7.65 years) and cognitively normal controls (n = 41, mean age = 72.10 ± 3.80 years) participated in this study. Gait velocity was collected using an instrumented walkway under one single task and six combined tasks of motor and cognitive activities. The cognitive cost was the difference between the single gait task and each of the concurrent motor and cognitive challenges. A repeated two-way measure ANOVA assessed the effect of cognitive group and walking test condition for each gait task test. Results: Gait velocity was significantly slower in the MCI group under all tasks. For both groups, the concurrent motor task of carrying a glass of water conferred a challenge not different from the cognitive task of counting backwards by ones. Performance of the complex cognitive task of serial seven subtractions reduced gait velocity in both groups, but produced a greater change in the MCI group (31.8%). Conclusions: Not all concurrent tasks challenge cognition-motor interaction equivalently. This study has created a framework of task difficulty which allows for the translation of dual-task test conditions to future research and clinical practice to ensure the accuracy of assessing patient deficits and risk