U1 small nuclear (sn)RNA, required for splicing of pre-mRNA, is encoded by genes on chromosome 1p36. Imperfect copies of these true (t)U1 snRNA genes, located on chromosome 1q12-21, were thought to be pseudogenes. However, many of these variant (v)U1 snRNA genes produce fully-processed transcripts that are packaged into potentially functional particles. Using antisense oligonucleotides, we have achieved functional knockdown of a specific vU1 snRNA in HeLa cells and identified over 400 transcriptome changes following interrogation of the Affymetrix Human Exon ST 1.0 array.
Differentially expressed, variant U1 snRNAs regulate gene expression in human cells.
Cell line
View SamplesGene expression levels of pancreatic cell lines Overall design: RNA was extracted from cell lines and subjected to 50bp paired-end RNA sequencing
Integrated Patient-Derived Models Delineate Individualized Therapeutic Vulnerabilities of Pancreatic Cancer.
Specimen part, Subject
View SamplesThis SuperSeries is composed of the SubSeries listed below.
Master regulators of FGFR2 signalling and breast cancer risk.
Specimen part, Cell line
View SamplesGenome-wide association studies for breast cancer have identified over 80 different risk regions in the genome, with the FGFR2 locus consistently identified as the most strongly associated locus. However, we know little about the mechanisms by which the FGFR2 locus mediates risk or the pathways in which multiple risk loci may combine to cause disease. Here we use a systems biology approach to elucidate the regulatory networks operating in breast cancer and examine the role of FGFR2 in mediating risk. Using model systems we identify FGFR2-regulated genes and, combining variant set enrichment and eQTL analysis, show that these are preferentially linked to breast cancer risk loci. Our results support the concept that cancer-risk associated genes cluster in pathways
Master regulators of FGFR2 signalling and breast cancer risk.
Cell line
View SamplesGenome-wide association studies for breast cancer have identified over 80 different risk regions in the genome, with the FGFR2 locus consistently identified as the most strongly associated locus. However, we know little about the mechanisms by which the FGFR2 locus mediates risk or the pathways in which multiple risk loci may combine to cause disease. Here we use a systems biology approach to elucidate the regulatory networks operating in breast cancer and examine the role of FGFR2 in mediating risk. Using model systems we identify FGFR2-regulated genes and, combining variant set enrichment and eQTL analysis, show that these are preferentially linked to breast cancer risk loci. Our results support the concept that cancer-risk associated genes cluster in pathways
Master regulators of FGFR2 signalling and breast cancer risk.
Cell line
View SamplesGenome-wide association studies for breast cancer have identified over 80 different risk regions in the genome, with the FGFR2 locus consistently identified as the most strongly associated locus. However, we know little about the mechanisms by which the FGFR2 locus mediates risk or the pathways in which multiple risk loci may combine to cause disease. Here we use a systems biology approach to elucidate the regulatory networks operating in breast cancer and examine the role of FGFR2 in mediating risk. Using model systems we identify FGFR2-regulated genes and, combining variant set enrichment and eQTL analysis, show that these are preferentially linked to breast cancer risk loci. Our results support the concept that cancer-risk associated genes cluster in pathways
Master regulators of FGFR2 signalling and breast cancer risk.
Cell line
View SamplesGenome-wide association studies for breast cancer have identified over 80 different risk regions in the genome, with the FGFR2 locus consistently identified as the most strongly associated locus. However, we know little about the mechanisms by which the FGFR2 locus mediates risk or the pathways in which multiple risk loci may combine to cause disease. Here we use a systems biology approach to elucidate the regulatory networks operating in breast cancer and examine the role of FGFR2 in mediating risk. Using model systems we identify FGFR2-regulated genes and, combining variant set enrichment and eQTL analysis, show that these are preferentially linked to breast cancer risk loci. Our results support the concept that cancer-risk associated genes cluster in pathways
Master regulators of FGFR2 signalling and breast cancer risk.
Specimen part
View SamplesMice with a congenital Snord116 deletion model aspects of the Prader-Willi Syndrome. In this study, we examine the gene expression changes in four hypothalamic nuclei across 24-hour food deprived versus ad libitum fed mice. Overall design: Using mice with paternal deletion of the Snord116 cluster, we laser-captured microdissected four hypothalamic nuclei for RNA sequencing: the ventromedial hypothalamus (VMH), arcuate nucleus (ARC), dorsomedial hypothalamus (DMH) and paraventricular nucleus (PVN). Samples were taken from male mice in either the fed or 24-hour fasted state.
Hypothalamic loss of Snord116 recapitulates the hyperphagia of Prader-Willi syndrome.
Cell line, Subject
View SamplesMutations in TRP53, prevalent in human cancers, reportedly drive tumorigenesis through dominant-negative-effects (DNE) over wt TRP53 and neomorphic gain-of-function (GOF) effects. We show that five TRP53 mutants do not accelerate lymphomagenesis on a TRP53-deficient background but strongly synergize with c-MYC over-expression. RNA-seq analysis revealed that mutant TRP53 does not globally repress wt TRP53 function but exerts a DNE with disproportionate impact on subsets of wt TRP53 target genes, particularly those involved in DNA repair, proliferation and metabolism. This reveals that the mutant TRP53 DNE drives tumorigenesis by modulating wt TRP53 function in a manner that is advantageous for neoplastic transformation. Overall design: Each of 5 mutant human TRP53 proteins, and a negative control, was expressed in 3 mouse lymphoma cell lines, both before and after activation of WT TRP53 with nutlin-3a.
Mutant TRP53 exerts a target gene-selective dominant-negative effect to drive tumor development.
Cell line, Subject
View SamplesObesity-associated insulin resistance is characterized by a state of chronic, low-grade inflammation that is associated with the accumulation of M1 proinflammatory macrophages in adipose tissue. Although different evidence explains the mechanisms linking the expansion of adipose tissue and adipose tissue macrophage (ATM) polarization, in the current study we investigated the concept of lipid-induced toxicity as the pathogenic link that could explain the trigger of this response. We addressed this question using isolated ATMs and adipocytes from genetic and diet-induced murine models of obesity. Through transcriptomic and lipidomic analysis, we created a model integrating transcript and lipid species networks simultaneously occurring in adipocytes and ATMs and their reversibility by thiazolidinedione treatment. We show that polarization of ATMs is associated with lipid accumulation and the consequent formation of foam celllike cells in adipose tissue. Our study reveals that early stages of adipose tissue expansion are characterized by M2-polarized ATMs and that progressive lipid accumulation within ATMs heralds the M1 polarization, a macrophage phenotype associated with severe obesity and insulin resistance. Furthermore, rosiglitazone treatment, which promotes redistribution of lipids toward adipocytes and extends the M2 ATM polarization state, prevents the lipid alterations associated with M1 ATM polarization. Our data indicate that the M1 ATM polarization in obesity might be a macrophage-specific manifestation of a more general lipotoxic pathogenic mechanism. This indicates that strategies to optimize fat deposition and repartitioning toward adipocytes might improve insulin sensitivity by preventing ATM lipotoxicity and M1 polarization.
Differential lipid partitioning between adipocytes and tissue macrophages modulates macrophage lipotoxicity and M2/M1 polarization in obese mice.
Specimen part
View Samples