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SRP075767
Mus musculus
4 Downloadable Samples
Illumina HiSeq 2500
Description
Introduction: HGFL-Ron signaling is augmented in human breast cancer and is associated with poor overall prognosis. Here, we investigate the role of HGFL-Ron signaling in murine breast cancer stem cells (BCSC) through characterization of BCSC transcriptomes through RNA-sequencing, focusing on the impact of Ron knockdown through a short hairpin construct. Methods:R7 breas cancer cell lines were drived from mammary tumors in transgenic MMTV_Ron mice. They were sorted based on expression of cell surface markers indicative of lineage negative, CD29hi and CD24+ cells. Bulk R7, sorted cells, and sorted cells treated with shRon were submitted for transcriptomic characterization on the Illumina HiSeq 2500. High quality reads were aligned to the mm9 genome and quantified to generate RPKM. Results: Approximately 30 million reads were aligned to the mouse genome in each sample which corresponded to over 36000 transcripts. Of these, ~16000 were included in analysis. Conclusions: Differential expression analysis indicated that depletion of Ron markely reduces mammosphere formation and self-renewal, and highlighted by the decrease in B-catenin and NFKB pathways. Overall design: Transcriptome profiles of bulk and sorted R7 BCSCs with Ron knockdown through RNA-sequencing.
Publication Title
HGFL-mediated RON signaling supports breast cancer stem cell phenotypes via activation of non-canonical β-catenin signaling.
Sample Metadata Fields
Specimen part, Cell line, Treatment, Subject
View Samples- Homo sapiens
- 42 Downloadable Samples
Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
RNA 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.
Publication Title
Molecular profiling predicts the existence of two functionally distinct classes of ovarian cancer stroma.
Sample Metadata Fields
Age, Specimen part, Disease stage, Subject
View Samples- Homo sapiens
- 18 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
Transcriptional override: a regulatory network model of indirect responses to modulations in microRNA expression.
Sample Metadata Fields
Specimen part
View Samples- Homo sapiens
- 18 Downloadable Samples
Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
MicroRNAs 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.
Publication Title
Transcriptional override: a regulatory network model of indirect responses to modulations in microRNA expression.
Sample Metadata Fields
Specimen part
View Samples- Homo sapiens
- 27 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Samples of primary tumors collected from 23 ovarian cancer patients
Publication Title
Machine learning predicts individual cancer patient responses to therapeutic drugs with high accuracy.
Sample Metadata Fields
Sex, Specimen part, Disease
View Samples- Homo sapiens
- 28 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
MicroRNAs (miRNAs) are short (~22 nucleotides) regulatory RNAs that can modulate gene expression and are aberrantly expressed in many diseases including cancer. Previous studies have shown that miRNAs inhibit the translation and facilitate the degradation of their targeted mRNAs making them attractive candidates for use in cancer therapy. However, the potential clinical utility of miRNAs in cancer therapy rests heavily upon our ability to understand and accurately predict the consequences of fluctuations in levels of miRNAs within the context of complex tumor cells. To evaluate the predictive power of current models, levels of miRNAs and their targeted messenger RNAs (mRNAs) were measured in laser captured micro-dissected (LCM) ovarian cancer epithelial cells (CEPI) and compared with levels present in ovarian surface epithelial cells (OSE). We found that the predicted inverse correlation between changes in levels of miRNAs and levels of their mRNA targets held for only ~6-11% of predicted target mRNAs. Our results underscore the complexities of miRNA-mediated regulation in vivo and caution against the widespread clinical application of miRNAs and miRNA inhibitors until the basis of these complexities is more fully understood.
Publication Title
Evidence for the complexity of microRNA-mediated regulation in ovarian cancer: a systems approach.
Sample Metadata Fields
Cell line
View Samples- Homo sapiens
- 23 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
In contrast to epithelial derived carcinomas that arise in most human organs, ovarian surface epithelial cells become more rather than less differentiated as the malignancy progresses. To test the hypothesis that ovarian surface epithelial cells retain properties of relatively uncommitted pluripotent cells until undergoing neoplastic transformation, we conducted gene expression profiling analysis (Affymetrix, U133 Plus 2.0) of 12 ovarian surface epithelial cells and 12 laser capture microdissected serous papillary ovarian cances. We find that over 2000 genes are significantly differentially expressed between the surface epithelial and cancer samples. Network analysis implicates key signaling pathways and pathway interactions in ovarian cancer development. Genes previously associated with adult stem cell maintenance are expressed in ovarian surface epithelial cells and significantly down-regulated in ovarian cancer cells. Our results indicate that the surface of the ovary is an adult stem cell niche and that deregulation of genes involved in maintaining the quiescence of ovarian surface epithelial cells is instrumental in the initiation and development of ovarian cancer.
Publication Title
Gene expression profiling supports the hypothesis that human ovarian surface epithelia are multipotent and capable of serving as ovarian cancer initiating cells.
Sample Metadata Fields
Disease, Disease stage
View Samples- Homo sapiens
- 8 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
MicroRNAs (miRNAs) are short (~22 nucleotides) regulatory RNAs that can modulate gene expression and are aberrantly expressed in many diseases including cancer. We report the results of a systems analysis of miRNA regulation in ovarian cancer. We found that 33 miRNAs are up-regulated and 9 down-regulated in CEPI relative to OSE (p<0.01, 2 fold change). Of these, 12 were previously annotated miRNAs (Sanger miRBase) of which 9 are up-regulated and 3 are down-regulated in CEPI relative to OSE. Current models predict that changes in levels of miRNAs will be inversely correlated with changes in the levels of targeted mRNAs due to miRNA regulation. This predicted inverse correlation held for only ~9% of predicted target mRNAs. Computational analyses indicate the unexpected low inverse correlation may be at least partially explained by variation in the number of miRNA binding sites within the 3 UTRs of targeted mRNAs and by miRNA-mediated changes in levels of transcription factors that can exert overriding trans-regulatory controls on target loci.
Publication Title
Evidence for the complexity of microRNA-mediated regulation in ovarian cancer: a systems approach.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 43 Downloadable Samples
- Affymetrix Human Genome U95 Version 2 Array (hgu95av2)
Description
Gene expression profiles of malignant carcinomas surgically removed from ovarian cancer patients pre-treated with chemotherapy (neo-adjuvant) prior to surgery group into two distinct clusters. One group clusters with carcinomas from patients not pre-treated with chemotherapy prior to surgery (C-L) while the other clusters with non-malignant adenomas (A-L).
Publication Title
Evidence that p53-mediated cell-cycle-arrest inhibits chemotherapeutic treatment of ovarian carcinomas.
Sample Metadata Fields
No sample metadata fields
View Samples- Mus musculus
- 33 Downloadable Samples
- Affymetrix Mouse Gene 1.1 ST Array (mogene11st)
Description
This study was designed to address key questions concerning the use of alternative protein sources for animal feeds and addresses aspects such as their nutrient composition and impact on gut function, the immune system and systemic physiology. We used casein (CAS), partially delactosed whey powder (DWP), spray dried porcine plasma (SDPP), soybean meal (SBM), wheat gluten meal (WGM) and yellow meal worm (YMW) as protein sources.
Publication Title
Multi-Level Integration of Environmentally Perturbed Internal Phenotypes Reveals Key Points of Connectivity between Them.
Sample Metadata Fields
Sex, Specimen part
View Samples