The majority of the human genome is transcribed, yielding a rich repository of non-coding transcripts that are involved in a myriad of biological processes including cancer. However, how non-coding transcripts such as Long Non-coding RNAs (lncRNAs) function in prostate cancer is still unclear. In this study, we have identified a novel set of clinically relevant androgen-regulated lncRNAs in prostate cancer. Among this group, we found LINC00844 is a direct androgen regulated target that is actively transcribed in AR-dependent prostate cancer cells. In clinical analysis, the expression of LINC00844 is higher in normal prostate compared to malignant and metastatic prostate cancer samples and patients with low expression demonstrate poor prognosis and significantly increased biochemical recurrence suggesting LINC00844 may function in suppressing tumor progression and metastasis. From in-vitroloss-of-function studies, we showed LINC00844 prevents prostate cancer cell migration and invasion. Moreover, in gene expression studies we demonstrate LINC00844 functions in trans, affecting global androgen-regulated gene transcription. Mechanistically, we provide evidence to show LINC00844 is important in facilitating AR binding to the chromatin. Finally, we showed LINC00844 mediates its phenotypic effects in part by activating the expression of NDRG1, a crucial cancer metastasis suppressor. Collectively, our findings indicate LINC00844 is a novel coregulator of AR that plays an important role in the androgen transcriptional network and the development and progression of prostate cancer.
Novel lncRNA <i>LINC00844</i> Regulates Prostate Cancer Cell Migration and Invasion through AR Signaling.
Cell line, Treatment
View SamplesTime course experiment of the CEC differentiation. Samples collected from differentiation 0, 2, 4, 6, 8 weeks.
No associated publication
Specimen part, Cell line, Time
View SamplesWe applied LY294002 in mesoderm downstream differentiation. LY294002-induced cells enriched in cardiomyocytes as well as WNT inhibitor IWP2.
Endogenous IGF Signaling Directs Heterogeneous Mesoderm Differentiation in Human Embryonic Stem Cells.
Specimen part, Cell line, Treatment
View SamplesConsider the problem of designing a panel of complex biomarkers to predict a patient's health or disease state when one can pair his or her current test sample, called a target sample, with the patient's previously acquired healthy sample, called a reference sample. As contrasted to a population averaged reference, this reference sample is individualized. Automated predictor algorithms that compare and contrast the paired samples to each other could result in a new generation of test panels that compare to a person's healthy reference to enhance predictive accuracy. This study develops such an individualized predictor and illustrates the added value of including the healthy reference for design of predictive gene expression panels. The objective is to predict each subject's state of infection, e.g., neither exposed nor infected, exposed but not infected, pre-acute phase of infection, acute phase of infection, post-acute phase of infection. Using gene microarray data collected in a large-scale serially sampled respiratory virus challenge study, we quantify the diagnostic advantage of pairing a person's baseline reference with his or her target sample.
An individualized predictor of health and disease using paired reference and target samples.
Specimen part, Subject, Time
View SamplesAfrican-American individuals of the GENOA cohort
Genetic Architecture of Gene Expression in European and African Americans: An eQTL Mapping Study in GENOA.
Sex, Age, Specimen part
View SamplesThe NIH Roadmap Epigenomics Mapping Consortium aims to produce a public resource of epigenomic maps for stem cells and primary ex vivo tissues selected to represent the normal counterparts of tissues and organ systems frequently involved in human disease.
The NIH Roadmap Epigenomics Mapping Consortium.
Sex, Specimen part, Disease, Subject
View SamplesThis SuperSeries is composed of the SubSeries listed below.
Innate immune activity is detected prior to seroconversion in children with HLA-conferred type 1 diabetes susceptibility.
Sex, Specimen part
View SamplesA cardinal symptom of Major Depressive Disorder (MDD) is the disruption of circadian patterns. Yet, to date, there is no direct evidence of circadian clock dysregulation in the brains of MDD patients. Circadian rhythmicity of gene expression has been observed in animals and peripheral human tissues, but its presence and variability in the human brain was difficult to characterize. Here we applied time-of-death analysis to gene expression data from high-quality postmortem brains, examining 24-hour cyclic patterns in six cortical and limbic regions of 55 subjects with no history of psychiatric or neurological illnesses ('Controls') and 34 MDD patients. Our dataset covered ~12,000 transcripts in the dorsolateral prefrontal cortex (DLPFC), anterior cingulate cortex (AnCg), hippocampus (HC), amygdala (AMY), nucleus accumbens (NAcc) and cerebellum (CB). Several hundred transcripts in each region showed 24-hour cyclic patterns in Controls, and >100 transcripts exhibited consistent rhythmicity and phase-synchrony across regions. Among the top ranked rhythmic genes were the canonical clock genes BMAL1(ARNTL), PER1-2-3, NR1D1(REV-ERB), DBP, BHLHE40(DEC1), and BHLHE41(DEC2). The phasing of known circadian genes was consistent with data derived from other diurnal mammals. Cyclic patterns were much weaker in MDD brains, due to shifted peak timing and potentially disrupted phase relationships between individual circadian genes. This is the first transcriptome-wide analysis of cyclic patterns in the human brain and demonstrates a rhythmic rise and fall of gene expression in regions outside of the suprachiasmatic nucleus in control subjects. The description of its breakdown in MDD suggest novel molecular targets for treatment of mood disorders.
Circadian patterns of gene expression in the human brain and disruption in major depressive disorder.
Subject
View SamplesWith aging, significant changes in circadian rhythms occur, including a shift in phase toward a morning chronotype and a loss of rhythmicity in circulating hormones. However, the effects of aging on molecular rhythms in the human brain have remained elusive. Here we employed a previously-described time-of-death analyses to identify transcripts throughout the genome that have a significant circadian rhythm in expression in the human prefrontal cortex (Brodmanns areas (BA) 11 and 47). Expression levels were determined by microarray analysis in 146 individuals. Rhythmicity in expression was found in ~10% of detected transcripts (p<0.05). Using a meta-analysis across the two brain areas, we identified a core set of 235 genes (q<0.05) with significant circadian rhythms of expression. These 235 genes showed 92% concordance in the phase of expression between the two areas. In addition to the canonical core circadian genes, a number of other genes were found to exhibit rhythmic expression in the brain. Notably, we identified more than one thousand genes (1186 in BA11; 1591 in BA47) that exhibited age-dependent rhythmicity or alterations in rhythmicity patterns with aging. Interestingly, a set of transcripts gained rhythmicity in older individuals, which may represent a compensatory mechanism due to a loss of canonical clock function. Thus, we confirm that rhythmic gene expression can be reliably measured in human brain and identified for the first time significant changes in molecular rhythms with aging that may contribute to altered cognition, sleep and mood in later life.
Effects of aging on circadian patterns of gene expression in the human prefrontal cortex.
Sex, Age, Specimen part, Race
View SamplesHistologic diagnosis of T cell-mediated rejection in kidney transplant biopsies has limited reproducibility because it is based on non-specific lesions using arbitrary rules that are subject to differing interpretations. We used microarray results from 403 indication biopsies previously given histologic diagnoses to develop a molecular classifier that assigned a molecular T cell-mediated rejection score to each biopsy. Independent assessment of the biopsies by multiple pathologists confirmed considerable disagreement on the presence of TCMR features: 79-88% accuracy and 35-69% sensitivity. The agreement of the molecular T cell-mediated rejection score with the histology diagnosis was similar to agreement among individual pathologists: accuracy 89%, sensitivity 51%. However, the score also predicted the consensus among pathologists, being highest when all agreed. Many discrepancies between the scores and the histologic diagnoses were in situations where histology is unreliable e.g. scarred biopsies. The score correlated with histologic lesions and gene sets associated with T cell-mediated rejection. The transcripts most often selected by the classifier were expressed in effector T cells, dendritic cells, or macrophages or inducible by interferon-gamma. Thus the T cell-mediated rejection score offers an objective assessment of kidney transplant biopsies, predicting the consensus opinion among multiple pathologists, and offering insights into underlying disease mechanisms.
Molecular diagnosis of T cell-mediated rejection in human kidney transplant biopsies.
Disease
View Samples