This SuperSeries is composed of the SubSeries listed below.
Functional and evolutionary significance of human microRNA seed region mutations.
Cell line
View SamplesMicroRNAs (miRNAs) are small non-coding RNAs that play a central role in the regulation of gene expression at the post transcriptional and/or translational level thus impacting various biological processes. Dysregulation of miRNAs could affect processes associated with progression of a variety of diseases including cancer. Majority of miRNA targeting in animals involves a 7-nt seed region mapping to positions 2-8 at the molecules 5' end. The importance of this 7 nt sequence to miRNA function is evidenced by the fact that the seed region sequence of many miRNAs is highly conserved within and between species. In this study, we computationally and experimentally explore the functional significance of sequence variation within the seed region of human miRNAs. Our results indicate that change of a single nt within the 7-nt seed region changes the spectrum of targeted mRNAs significantly meanwhile further nt changes have little to no additional effect. This high functional cost of even a single nucleotide change within the seed region of miRNAs explains why the seed sequence is highly conserved among many miRNA families both within and between species and could help clarify the likely mechanisms underlying the evolution of miRNA regulatory control.
Functional and evolutionary significance of human microRNA seed region mutations.
Cell line
View SamplesMicroRNAs (miRNAs) are small non-coding RNAs that play a central role in the regulation of gene expression at the post transcriptional and/or translational level thus impacting various biological processes. Dysregulation of miRNAs could affect processes associated with progression of a variety of diseases including cancer. Majority of miRNA targeting in animals involves a 7-nt seed region mapping to positions 2-8 at the molecules 5' end. The importance of this 7 nt sequence to miRNA function is evidenced by the fact that the seed region sequence of many miRNAs is highly conserved within and between species. In this study, we computationally and experimentally explore the functional significance of sequence variation within the seed region of human miRNAs. Our results indicate that change of a single nt within the 7-nt seed region changes the spectrum of targeted mRNAs significantly meanwhile further nt changes have little to no additional effect. This high functional cost of even a single nucleotide change within the seed region of miRNAs explains why the seed sequence is highly conserved among many miRNA families both within and between species and could help clarify the likely mechanisms underlying the evolution of miRNA regulatory control.
Functional and evolutionary significance of human microRNA seed region mutations.
Cell line
View SamplesMicroRNAs (miRNAs) are small non-coding RNAs that play a central role in the regulation of gene expression at the post transcriptional and/or translational level thus impacting various biological processes. Dysregulation of miRNAs could affect processes associated with progression of a variety of diseases including cancer. Majority of miRNA targeting in animals involves a 7-nt seed region mapping to positions 2-8 at the molecules 5' end. The importance of this 7 nt sequence to miRNA function is evidenced by the fact that the seed region sequence of many miRNAs is highly conserved within and between species. In this study, we computationally and experimentally explore the functional significance of sequence variation within the seed region of human miRNAs. Our results indicate that change of a single nt within the 7-nt seed region changes the spectrum of targeted mRNAs significantly meanwhile further nt changes have little to no additional effect. This high functional cost of even a single nucleotide change within the seed region of miRNAs explains why the seed sequence is highly conserved among many miRNA families both within and between species and could help clarify the likely mechanisms underlying the evolution of miRNA regulatory control.
Functional and evolutionary significance of human microRNA seed region mutations.
Cell line
View SamplesMicroRNAs (miRNAs) are small non-coding RNAs that play a central role in the regulation of gene expression at the post transcriptional and/or translational level thus impacting various biological processes. Dysregulation of miRNAs could affect processes associated with progression of a variety of diseases including cancer. Majority of miRNA targeting in animals involves a 7-nt seed region mapping to positions 2-8 at the molecules 5' end. The importance of this 7 nt sequence to miRNA function is evidenced by the fact that the seed region sequence of many miRNAs is highly conserved within and between species. In this study, we computationally and experimentally explore the functional significance of sequence variation within the seed region of human miRNAs. Our results indicate that change of a single nt within the 7-nt seed region changes the spectrum of targeted mRNAs significantly meanwhile further nt changes have little to no additional effect. This high functional cost of even a single nucleotide change within the seed region of miRNAs explains why the seed sequence is highly conserved among many miRNA families both within and between species and could help clarify the likely mechanisms underlying the evolution of miRNA regulatory control.
Functional and evolutionary significance of human microRNA seed region mutations.
Cell line
View SamplesRNA microarray profiling of 45 tissue samples was carried out using the Affymetrix (U133) gene expression platform. Laser capture microdissection (LCM) was employed to isolate cancer cells from the tumors of 18 serous ovarian cancer patients (Cepi). For 7 of these patients, a matched set of surrounding cancer stroma (CS) was also collected. For controls, surface ovarian epithelial cells (OSE) were isolated from the normal (non-cancerous) ovaries of 12 individuals including matched sets of samples of OSE and normal stroma (NS) from 8 of these patients. Unsupervised hierarchical clustering of the microarray data resulted in the expected separation between the OSE and Cepi samples. Consistent with models of stromal activation, we also observed significant separation between the NS and CS samples. Unexpectedly, the CS samples sub-divided into two distinct groups. Analysis of expression patterns of genes encoding signaling molecules and compatible receptors in the CS and Cepi samples are consistent with the hypothesis that the two CS sub-groups differ significantly in their relative propensities to support tumor growth.The results indicate the existence of distinct categories of ovarian cancer stroma and suggest that functionally significant variability exists among ovarian cancer patients in the ability of the microenvironment to modulate cancer development.
Molecular profiling predicts the existence of two functionally distinct classes of ovarian cancer stroma.
Age, Specimen part, Disease stage, Subject
View SamplesThis SuperSeries is composed of the SubSeries listed below.
Transcriptional override: a regulatory network model of indirect responses to modulations in microRNA expression.
Specimen part
View SamplesMicroRNAs are small non-coding molecules that have been shown to repress the translation of thousands of genes. Changes in microRNA expression in a variety of diseases, including cancer, are leading to the development of microRNAs as early indicators of disease, and to their potential use as therapeutic agents. A significant hurdle to the use of microRNAs as therapeutics is our inability to predict the molecular and cellular consequences of perturbations in the levels of specific microRNAs on targeted cells. While the direct gene (mRNA) targets of individual microRNAs can be computationally predicted and are often experimentally validated, assessing the indirect effects of microRNA variation remains a major challenge in molecular systems biology. We present experimental evidence for a computational model that quantifies the extent to which down-regulated transcriptional repressors contribute to the unanticipated upregulation of putative microRNA targets. An appreciation of the effects of these repressors may provide a more complete understanding of the indirect effects of microRNA dysregulation in diseases such as cancer, and to their successful clinical application.
Transcriptional override: a regulatory network model of indirect responses to modulations in microRNA expression.
Specimen part
View SamplesIncreasing evidence supports the existence of a subpopulation of cancer cells capable of self-renewal and differentiation into diverse cell lineages. These cancer stem-like or cancer-initiating cells (CICs) also demonstrate resistance to chemo- and radiotherapy and may function as a primary source of cancer recurrence. We report here on the isolation and in vitro propagation of multicellular ovarian cancer spheroids from a well-established ovarian cancer cell line (OVCAR-3). The spheroid-derived cells (SDCs) display self-renewal potential, the ability to produce differentiated progeny, and increased expression of genes previously associated with CICs. SDCs also demonstrate higher invasiveness, migration potential, and enhanced resistance to standard anticancer agents relative to parental OVCAR-3 cells. Furthermore, SDCs display up-regulation of genes associated with epithelial-to-mesenchymal transition (EMT), anticancer drug resistance and/or decreased susceptibility to apoptosis, as well as, down-regulation of genes typically associated with the epithelial cell phenotype and pro-apoptotic genes. Pathway and biological process enrichment analyses indicate significant differences between the SDCs and precursor OVCAR-3 cells in TGF-beta-dependent induction of EMT, regulation of lipid metabolism, NOTCH and Hedgehog signaling. Collectively, our results indicate that these SDCs will be a useful model for the study of ovarian CICs and for the development of novel CIC-targeted therapies.
Isolation and characterization of stem-like cells from a human ovarian cancer cell line.
Cell line
View SamplesSamples of primary tumors collected from 23 ovarian cancer patients
Machine learning predicts individual cancer patient responses to therapeutic drugs with high accuracy.
Sex, Specimen part, Disease
View Samples