Super-Enhancer-Associated LncRNA UCA1 Interacts Directly with AMOT to Activate YAP Target Genes in Epithelial Ovarian Cancer

Long noncoding RNAs (lncRNAs) have emerged as critical regulators of tumorigenesis, and yet their mechanistic roles remain challenging to characterize. Here, we integrate functional proteomics with lncRNA-interactome profiling to characterize Urothelial Cancer Associated 1 (UCA1), a candidate driver of ovarian cancer development. Reverse phase protein array (RPPA) analysis indicates that UCA1 activates transcription coactivator YAP and its target genes. In vivo RNA antisense purification (iRAP) of UCA1 interacting proteins identified angiomotin (AMOT), a known YAP regulator, as a direct binding partner. Loss-of-function experiments show that AMOT mediates YAP activation by UCA1, as UCA1 enhances the AMOT-YAP interaction to promote YAP dephosphorylation and nuclear translocation. Together, we characterize UCA1 as a lncRNA regulator of Hippo-YAP signaling and highlight the UCA1-AMOT-YAP signaling axis in ovarian cancer development

Clinical Characteristics of a Nationwide Hospital-based Registry of Mild-to-Moderate Alzheimer's Disease Patients in Korea: A CREDOS (Clinical Research Center for Dementia of South Korea) Study

With rapid population aging, the socioeconomic burden caused by dementia care is snowballing. Although a few community-based studies of Alzheimer's disease (AD) have been performed in Korea, there has never been a nationwide hospital-based study thereof. We aimed to identify the demographics and clinical characteristics of mild-to-moderate AD patients from the Clinical Research Center for Dementia of Korea (CREDOS) registry. A total of 1,786 patients were consecutively included from September 2005 to June 2010. Each patient underwent comprehensive neurological examination, interview for caregivers, laboratory investigations, neuropsychological tests, and brain MRI. The mean age was 74.0 yr and the female percentage 67.0%. The mean period of education was 7.1 yr and the frequency of early-onset AD (< 65 yr old) was 18.8%. Among the vascular risk factors, hypertension (48.9%) and diabetes mellitus (22.3%) were the most frequent. The mean score of the Korean version of Mini-Mental State Examination (K-MMSE) was 19.2 and the mean sum of box scores of Clinical Dementia Rating (CDR-SB) 5.1. Based on the well-structured, nationwide, and hospital-based registry, this study provides the unique clinical characteristics of AD and emphasizes the importance of vascular factors in AD in Korea

Sublingual Immunization with M2-Based Vaccine Induces Broad Protective Immunity against Influenza

The ectodomain of matrix protein 2 (M2e) of influenza A virus is a rationale target antigen candidate for the development of a universal vaccine against influenza as M2e undergoes little sequence variation amongst human influenza A strains. Vaccine-induced M2e-specific antibodies (Abs) have been shown to display significant cross-protective activity in animal models. M2e-based vaccine constructs have been shown to be more protective when administered by the intranasal (i.n.) route than after parenteral injection. However, i.n. administration of vaccines poses rare but serious safety issues associated with retrograde passage of inhaled antigens and adjuvants through the olfactory epithelium. In this study, we examined whether the sublingual (s.l.) route could serve as a safe and effective alternative mucosal delivery route for administering a prototype M2e-based vaccine. The mechanism whereby s.l. immunization with M2e vaccine candidate induces broad protection against infection with different influenza virus subtypes was explored.A recombinant M2 protein with three tandem copies of the M2e (3M2eC) was expressed in Escherichia coli. Parenteral immunizations of mice with 3M2eC induced high levels of M2e-specific serum Abs but failed to provide complete protection against lethal challenge with influenza virus. In contrast, s.l. immunization with 3M2eC was superior for inducing protection in mice. In the latter animals, protection was associated with specific Ab responses in the lungs.The results demonstrate that s.l. immunization with 3M2eC vaccine induced airway mucosal immune responses along with broad cross-protective immunity to influenza. These findings may contribute to the understanding of the M2-based vaccine approach to control epidemic and pandemic influenza infections

Prediction of cognitive impairment via deep learning trained with multi-center neuropsychological test data

Background Neuropsychological tests (NPTs) are important tools for informing diagnoses of cognitive impairment (CI). However, interpreting NPTs requires specialists and is thus time-consuming. To streamline the application of NPTs in clinical settings, we developed and evaluated the accuracy of a machine learning algorithm using multi-center NPT data. Methods Multi-center data were obtained from 14,926 formal neuropsychological assessments (Seoul Neuropsychological Screening Battery), which were classified into normal cognition (NC), mild cognitive impairment (MCI) and Alzheimers disease dementia (ADD). We trained a machine learning model with artificial neural network algorithm using TensorFlow (https://www.tensorflow.org) to distinguish cognitive state with the 46-variable data and measured prediction accuracies from 10 randomly selected datasets. The features of the NPT were listed in order of their contribution to the outcome using Recursive Feature Elimination. Results The ten times mean accuracies of identifying CI (MCI and ADD) achieved by 96.66 ± 0.52% of the balanced dataset and 97.23 ± 0.32% of the clinic-based dataset, and the accuracies for predicting cognitive states (NC, MCI or ADD) were 95.49 ± 0.53 and 96.34 ± 1.03%. The sensitivity to the detection CI and MCI in the balanced dataset were 96.0 and 96.0%, and the specificity were 96.8 and 97.4%, respectively. The time orientation and 3-word recall score of MMSE were highly ranked features in predicting CI and cognitive state. The twelve features reduced from 46 variable of NPTs with age and education had contributed to more than 90% accuracy in predicting cognitive impairment. Conclusions The machine learning algorithm for NPTs has suggested potential use as a reference in differentiating cognitive impairment in the clinical setting.The publication costs, design of the study, data management and writing the manuscript for this article were supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2017S1A6A3A01078538), Korea Ministry of Health & Welfare, and from the Original Technology Research Program for Brain Science through the National Research Foundation of Korea funded by the Korean Government (MSIP; No. 2014M3C7A1064752)

Cis-eQTL analysis and functional validation of candidate susceptibility genes for high-grade serous ovarian cancer

Genome-wide association studies have reported 11 regions conferring risk of high-grade serous epithelial ovarian cancer (HGSOC). Expression quantitative trait locus (eQTL) analyses can identify candidate susceptibility genes at risk loci. Here we evaluate cis-eQTL associations at 47 regions associated with HGSOC risk (PPeer reviewe

Cis-eQTL analysis and functional validation of candidate susceptibility genes for high-grade serous ovarian cancer

Genome-wide association studies have reported 11 regions conferring risk of high-grade serous epithelial ovarian cancer (HGSOC). Expression quantitative trait locus (eQTL) analyses can identify candidate susceptibility genes at risk loci. Here we evaluate cis-eQTL associations at 47 regions associated with HGSOC risk (P≤10−5). For three cis-eQTL associations (P<1.4 × 10−3, FDR<0.05) at 1p36 (CDC42), 1p34 (CDCA8) and 2q31 (HOXD9), we evaluate the functional role of each candidate by perturbing expression of each gene in HGSOC precursor cells. Overexpression of HOXD9 increases anchorage-independent growth, shortens population-doubling time and reduces contact inhibition. Chromosome conformation capture identifies an interaction between rs2857532 and the HOXD9 promoter, suggesting this SNP is a leading causal variant. Transcriptomic profiling after HOXD9 overexpression reveals enrichment of HGSOC risk variants within HOXD9 target genes (P=6 × 10−10 for risk variants (P<10−4) within 10 kb of a HOXD9 target gene in ovarian cells), suggesting a broader role for this network in genetic susceptibility to HGSOC

A multi-level investigation of the genetic relationship between endometriosis and ovarian cancer histotypes.

Endometriosis is associated with increased risk of epithelial ovarian cancers (EOCs). Using data from large endometriosis and EOC genome-wide association meta-analyses, we estimate the genetic correlation and evaluate the causal relationship between genetic liability to endometriosis and EOC histotypes, and identify shared susceptibility loci. We estimate a significant genetic correlation (rg) between endometriosis and clear cell (rg = 0.71), endometrioid (rg = 0.48), and high-grade serous (rg = 0.19) ovarian cancer, associations supported by Mendelian randomization analyses. Bivariate meta-analysis identified 28 loci associated with both endometriosis and EOC, including 19 with evidence for a shared underlying association signal. Differences in the shared risk suggest different underlying pathways may contribute to the relationship between endometriosis and the different histotypes. Functional annotation using transcriptomic and epigenomic profiles of relevant tissues/cells highlights several target genes. This comprehensive analysis reveals profound genetic overlap between endometriosis and EOC histotypes with valuable genomic targets for understanding the biological mechanisms linking the diseases

A multi-level investigation of the genetic relationship between endometriosis and ovarian cancer histotypes

Endometriosis is associated with increased risk of epithelial ovarian cancers (EOCs). Using data from large endometriosis and EOC genome-wide association meta-analyses, we estimate the genetic correlation and evaluate the causal relationship between genetic liability to endometriosis and EOC histotypes, and identify shared susceptibility loci. We estimate a significant genetic correlation (rg) between endometriosis and clear cell (rg&nbsp;= 0.71), endometrioid (rg&nbsp;= 0.48), and high-grade serous (rg&nbsp;= 0.19) ovarian cancer, associations supported by Mendelian randomization analyses. Bivariate meta-analysis identified 28 loci associated with both endometriosis and EOC, including 19 with evidence for a shared underlying association signal. Differences in the shared risk suggest different underlying pathways may contribute to the relationship between endometriosis and the different histotypes. Functional annotation using transcriptomic and epigenomic profiles of relevant tissues/cells highlights several target genes. This comprehensive analysis reveals profound genetic overlap between endometriosis and EOC histotypes with valuable genomic targets for understanding the biological mechanisms linking the diseases