This SuperSeries is composed of the SubSeries listed below.
Histone demethylase KDM2B regulates lineage commitment in normal and malignant hematopoiesis.
Specimen part, Cell line
View SamplesDevelopment of the hematopoietic system is dynamically controlled by the interplay of transcriptional and epigenetic networks to determine cellular identity. Those networks are critical for homeostasis and frequently dysregulated in leukemias. We identified histone demethylase Kdm2b as a critical regulator of definitive hematopoiesis and lineage specification of hematopoietic stem and progenitor cells (HSPCs). RNA sequencing in murine HSPCs and genome-wide chromatin immunoprecipitation studies in human leukemias revealed that Kdm2b regulates differentiation, lineage choice, cytokine signaling, and quiescence.
Histone demethylase KDM2B regulates lineage commitment in normal and malignant hematopoiesis.
Specimen part
View SamplesDevelopment of the hematopoietic system is dynamically controlled by the interplay of transcriptional and epigenetic networks to determine cellular identity. Those networks are critical for homeostasis and frequently dysregulated in leukemias. We identified histone demethylase Kdm2b as a critical regulator of definitive hematopoiesis and lineage specification of hematopoietic stem and progenitor cells (HSPCs). RNA sequencing in murine HSPCs and genome-wide chromatin immunoprecipitation studies in human leukemias revealed that Kdm2b regulates differentiation, lineage choice, cytokine signaling, and quiescence. Overall design: Comparison of gene expression in wild-type and knockout HSPCs
Histone demethylase KDM2B regulates lineage commitment in normal and malignant hematopoiesis.
No sample metadata fields
View SamplesBackground: Local recurrence is the major manifestation of treatment failure in patients with operable laryngeal carcinoma. Established clinicopathological factors cannot sufficiently predict patients that are likely to recur after treatment. Additional tools are therefore required to accurately identify patients at high risk for recurrence. Methods: Using Affymetrix U133A Genechips, we profiled fresh-frozen tumor tissues from 59 patients with operable laryngeal cancer. All patients were treated locally with surgery, with or without radiation therapy. We performed Cox regression proportional hazards modeling to identify multigene predictors of recurrence. The end-point of our analysis was disease-free survival (DFS). Gene models were directly validated in a separate, similarly treated cohort of 50 patients using Affymetrix chips. In an attempt to further validate our results, we profiled 12 selected genes of our model in formalin-fixed tumor tissues from an independent cohort of 75 patients, using quantitative real time-polymerase chain reaction (qRT-PCR). Results: We focused on genes univariately associated with DFS (p<0.05) in the training set. Among several gene models comprising different numbers of genes, a 30-gene model demonstrated optimal performance (log-rank, p<0.001). We directly applied these gene models to the validation set, after adjusting for non-biological experimental variability, and observed similar results. Specifically, median DFS, as predicted by the 30-gene model, was 34 and 80 months for high- and low-risk patients, respectively (p=0.01). Hazard Ratio (HR) for recurrence for the high-risk group was 3.87 (95% CI 1.28-11.73, p=0.017). Furthermore, unsupervised hierarchical clustering of the 75 patients, based on the qRT-PCR 12-gene profile, yielded two groups, which differed significantly in DFS (log-rank, p=0.027). HR= for recurrence was 2.26, (95% CI 1.08-4.76, p=0.031). Conclusion: We have established and validated gene models that can successfully stratify patients with laryngeal cancer, based on their risk for recurrence. Thus, patients with unfavorable prognosis, when accurately identified, could be ideal candidates for the application of more aggressive treatment modalities.
Identification and validation of a multigene predictor of recurrence in primary laryngeal cancer.
Age, Specimen part, Disease stage
View SamplesWe aimed to predict obesity risk with genetic data, specifically, obesity-associated gene expression profiles. Genetic risk score was computed. The genetic risk score was significantly correlated with BMI when an optimization algorithm was used. Linear regression and built support vector machine models predicted obesity risk using gene expression profiles and the genetic risk score with a new mathematical method.
A computational framework for predicting obesity risk based on optimizing and integrating genetic risk score and gene expression profiles.
Specimen part
View SamplesInfection with non-cytopathic bovine viral diarrhea virus (ncpBVDV) is associated with uterine disease and infertility. This study investigated the influence of ncpBVDV on immune functions of the bovine endometrium by testing the response to bacterial lipopolysaccharide (LPS) at the level of whole-transcriptomic gene expression. Analysis showed that approximately 30% of the 1,006 genes altered by LPS are involved in immune response. Many innate immune genes that typically respond to LPS were inhibited by ncpBVDV including those involved in pathogen recognition, inflammation, interferon response, chemokines, tissue remodeling, cell migration and cell death/survival. Infection with ncpBVDV can thus compromise immune function and pregnancy recognition thereby potentially predisposing infected cows to postpartum bacterial endometritis and reduced fertility.
Global transcriptomic profiling of bovine endometrial immune response in vitro. I. Effect of lipopolysaccharide on innate immunity.
Sex, Treatment
View SamplesTCF7L2 regulates multiple metabolic pathways in hepatocytes through a transcriptional network involving HNF4a Overall design: For the identification of Tcf7l2 target genes using a RNA-seq timecourse, and for identifying the binding sites of Tcf7l2 and Hnf4a, Tcf7l2 was silenced in rat H4IIE hepatocytes using siRNA for Tcf7l2 with a scrambled siRNA as control. Treatment times for RNA-seq samples were 3, 6, 9, 12, 15, 18, 48, and 96 hours, and for ChIP-seq samples 15 h. RNA-seq timecourse was performed in duplicate or triplicate, and the ChIP-seq in duplicate for Tcf7l2 and in singlicate for Hnf4a. The H4IIE-specific transcriptome was defined from an independent set of pooled 24 h siRNA treated samples (N=3 for siRNA for Tcf7l2 and N=3 for scrambled siRNA).
The mechanisms of genome-wide target gene regulation by TCF7L2 in liver cells.
No sample metadata fields
View SamplesWe explored gene expression profile of human aortic valves in patients with or without aortic stenosis. The dataset that we generated constitutes a large-scale quantitative measurements of gene expression in normal and stenotic human valves. The goal was to compare gene expression levels between the two groups and identified a list of genes that are up- or down-regulated in aortic stenosis.
Refining molecular pathways leading to calcific aortic valve stenosis by studying gene expression profile of normal and calcified stenotic human aortic valves.
Sex, Age
View SamplesThe human steroid receptor RNA activator (SRA) gene encodes both non-coding RNAs (ncRNAs) and protein-generating isoforms. However, the breadth of endogenous target genes that might be regulated by SRA RNAs remains largely unknown. To address this, we depleted SRA RNA in two human cancer cell lines (HeLa and MCF-7) with small interfering RNAs, then assayed for changes in gene expression by microarray analyses using Affymetrix HGU133+2 arrays. We also tested if SRA depletion affects estradiol-regulated genes in MCF-7 breast cancer cells.
Research resource: expression profiling reveals unexpected targets and functions of the human steroid receptor RNA activator (SRA) gene.
Cell line
View Samples4 chorionic villus sampling specimens in pregnancies destined for preeclampsia and 8 matched controls were analyzed
Altered global gene expression in first trimester placentas of women destined to develop preeclampsia.
No sample metadata fields
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