Ovarian carcinoma has the highest mortality rate among gynecological malignancies. In this project, we investigated the hypothesis that molecular markers are able to predict outcome of ovarian cancer independently of classical clinical predictors, and that these molecular markers can be validated using independent data sets. We applied a semi-supervised method for prediction of patient survival. Microarrays from a cohort of 80 ovarian carcinomas (TOC cohort) were used for the development of a predictive model, which was then evaluated in an entirely independent cohort of 118 carcinomas (Duke cohort). A 300 gene ovarian prognostic index (OPI) was generated and validated in a leave-one-out approach in the TOC cohort (Kaplan-Meier analysis, p=0.0087). In a second validation step the prognostic power of the OPI was confirmed in an independent data set (Duke cohort, p=0.0063). In multivariate analysis, the OPI was independent of the postoperative residual tumour, the main clinico-pathological prognostic parameter with an adjusted hazard ratio of 6.4 (TOC cohort, CI 1.8 23.5, p=0.0049) and 1.9 (Duke cohort, CI 1.2 3.0, p=0.0068). We constructed a combined score of molecular data (OPI) and clinical parameters (residual tumour), which was able to define patient groups with highly significant differences in survival. The integrated analysis of gene expression data as well as residual tumour can be used for optimised assessment of prognosis. As traditional treatment options are limited, this analysis may be able to optimise clinical management and to identify those patients that would be candidates for new therapeutic strategies.
A prognostic gene expression index in ovarian cancer - validation across different independent data sets.
Specimen part, Disease stage
View SamplesCircadian profiling of total RNA collected from wildtype and NPY KO murine liver. Liver RNA collected every 4 hours in a 12hr light:12hr dark cycle.
Neural clocks and Neuropeptide F/Y regulate circadian gene expression in a peripheral metabolic tissue.
No sample metadata fields
View SamplesThe spliceosome is a dynamic RNA-protein complex that executes pre-mRNA splicing and is composed of five core small nuclear ribonucleoprotein particles (U1, U2, U4/5/6 snRNP) and >150 additional proteins specific for each snRNP. We report a circadian role for Pre-mRNA Processing factor 4 (PRP4), a conserved component of the spliceosomal U4/U6.U5 triple small nuclear ribonucleoprotein (tri-snRNP) complex. We broadly hypothesized that downregulation of prp4 led to the aberrant splicing of one or many of the core clock transcripts. To identify these splicing events in an unbiased way, we performed RNA-Sequencing (RNA-Seq) analysis. We reasoned that we could have a more targeted approach if we could zoom in on the overlapping splicing changes that would be driven by the knockdown of at least two different tri-snRNP components. Because the pan-neuronal knockdown of all tri-snRNP components tested in our study led to lethality, we decided to utilize an alternative broad driver. For that purpose, we selected a strong eye-specific Glass Multiple Promoter driver (GMR-Gal4). Because most of the signal from head lysates comes directly from the eye tissue and because the core splicing factors are ubiquitously expressed, GMR-specific downregulation of prp4 and prp8 promised to be a viable alternative to the pan-neuronal knockdown. We examined changes in both the total transcript levels and splicing events upon prp4 knockdown in the eye. The overall gene expression seemed to be dramatically influenced by prp4 downregulation (433 DOWN, 310 UP at FDR < 0.05). Despite the fact that PRP4 is a component of the core spliceosome that is required for constitutive exon splicing, we did not detect dramatic effects on global splicing. Only 45 genes exhibited differential alternate splicing upon prp4 downregulation at FDR < 0.05). Overall design: 3 samples with 5 replicates each were analyzed using Illumina Next-Generation Sequencing (NextSeq 500).
Spliceosome factors target timeless (<i>tim</i>) mRNA to control clock protein accumulation and circadian behavior in Drosophila.
Specimen part, Subject
View SamplesIn skeletal muscle differentiation, muscle-specific genes are regulated by two groups of transcription factors, the MyoD and MEF2 families, which work together to drive the differentiation process. Here we show that ERK5 regulates muscle cell fusion through Klf transcription factors. The inhibition of ERK5 activity suppresses muscle cell fusion with minimal effects on the expression of MyoD, MEF2, and their target genes. Promoter analysis coupled to microarray assay reveals that Klf-binding motifs are highly enriched in the promoter regions of ERK5-dependent upregulated genes. Remarkably, Klf2 and Klf4 expression are also upregulated during differentiation in an ERK5-dependent manner, and knockdown of Klf2 or Klf4 specifically suppresses muscle cell fusion. Moreover, we show that the Sp1 transcription factor links ERK5 to Klf2/4, and that nephronectin, a Klf transcriptional target, is involved in muscle cell fusion. Therefore, an ERK5/Sp1/Klf module plays a key role in the fusion process during skeletal muscle differentiation.
ERK5 regulates muscle cell fusion through Klf transcription factors.
Cell line, Time
View SamplesNote: non-normalized values and associated raw data cannot be located by the submitter
Maternal nutrition induces pervasive gene expression changes but no detectable DNA methylation differences in the liver of adult offspring.
Sex, Specimen part
View SamplesThe aim of this study is to characterize transcriptional changes induced by maternal diet in several adult tissues and to test whether differences in DNA methylation or microRNA expression could explain these changes.
Maternal nutrition induces pervasive gene expression changes but no detectable DNA methylation differences in the liver of adult offspring.
Sex, Specimen part
View SamplesThe aim of this study is to characterize transcriptional changes induced by maternal diet in several adult tissues and to test whether differences in DNA methylation or microRNA expression could explain these changes.
Maternal nutrition induces pervasive gene expression changes but no detectable DNA methylation differences in the liver of adult offspring.
Sex, Specimen part
View SamplesThe aim of this study is to characterize transcriptional changes induced by maternal diet in several adult tissues and to test whether differences in DNA methylation or microRNA expression could explain these changes.
Maternal nutrition induces pervasive gene expression changes but no detectable DNA methylation differences in the liver of adult offspring.
Sex, Specimen part
View SamplesThe aim of this study is to characterize transcriptional changes induced by maternal diet in several adult tissues and to test whether differences in DNA methylation or microRNA expression could explain these changes.
Maternal nutrition induces pervasive gene expression changes but no detectable DNA methylation differences in the liver of adult offspring.
Sex, Specimen part
View SamplesThe aim of this study is to characterize transcriptional changes induced by maternal diet in several adult tissues and to test whether differences in DNA methylation or microRNA expression could explain these changes.
Maternal nutrition induces pervasive gene expression changes but no detectable DNA methylation differences in the liver of adult offspring.
Sex, Specimen part
View Samples