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SRP158109
Homo sapiens
36 Downloadable Samples
Illumina HiSeq 2000
Description
Carcinoma-associated mesenchymal stem cells (CA-MSCs) are critical stromal progenitor cells within the tumor microenvironment. We previously demonstrated that CA-MSCs differentially express BMP genes, promote tumor cell growth, increase cancer 'stemness' and chemotherapy resistance. Here we use RNA sequencing of normal omental MSCs and ovarian CA-MSCs to demonstrate CA-MSCs have global changes in gene expression. Using these expression profiles we create a unique predictive algorithm to classify CA-MSCs. Our classifier, accurately distinguishes normal omental, ovary and bone marrow MSCs from ovarian cancer CA-MSCs. Suggesting broad applicability, the model correctly classifies pancreatic and endometrial cancer CA-MSCs and distinguishes cancer associated fibroblasts (CAFs) from CA-MSCs. Using this classifier, we definitively demonstrate ovarian CA-MSCs arise from tumor mediated reprograming of local tissue MSCs. While cancer cells alone cannot induce a CA-MSC phenotype, the in vivo ovarian tumor micoenvironment (TME) can reprogram omental or ovary MSCs to protumorigenic CA-MSC (classifier score of >0.96). In vitro studies suggest that both tumor secreted factors and hypoxia are critical to induce the CA-MSC phenotype. Interestingly, while the breast cancer TME can reprogram BM MSCs into CA-MSCs, the ovarian TME cannot, demonstrating for the first time that tumor mediated CA-MSC conversion is tissue and cancer type dependent. Together these findings (1) provide a critical tool to define CA-MSCs and (2) highlight cancer cell influence on distinct normal tissues providing powerful insights into the mechanisms underlying cancer specific metastatic niche formation. Carcinoma-associated mesenchymal stem cells (CA-MSCs) are critical stromal progenitor cells within the tumor microenvironment. We previously demonstrated that CA-MSCs differentially express BMP genes, promote tumor cell growth, increase cancer 'stemness' and chemotherapy resistance. Here we use RNA sequencing of normal omental MSCs and ovarian CA-MSCs to demonstrate CA-MSCs have global changes in gene expression. Using these expression profiles we create a unique predictive algorithm to classify CA-MSCs. Our classifier, accurately distinguishes normal omental, ovary and bone marrow MSCs from ovarian cancer CA-MSCs. Suggesting broad applicability, the model correctly classifies pancreatic and endometrial cancer CA-MSCs and distinguishes cancer associated fibroblasts (CAFs) from CA-MSCs. Using this classifier, we definitively demonstrate ovarian CA-MSCs arise from tumor mediated reprograming of local tissue MSCs. While cancer cells alone cannot induce a CA-MSC phenotype, the in vivo ovarian tumor micoenvironment (TME) can reprogram omental or ovary MSCs to protumorigenic CA-MSC (classifier score of >0.96). In vitro studies suggest that both tumor secreted factors and hypoxia are critical to induce the CA-MSC phenotype. Interestingly, while the breast cancer TME can reprogram BM MSCs into CA-MSCs, the ovarian TME cannot, demonstrating for the first time that tumor mediated CA-MSC conversion is tissue and cancer type dependent. Together these findings (1) provide a critical tool to define CA-MSCs and (2) highlight cancer cell influence on distinct normal tissues providing powerful insights into the mechanisms underlying cancer specific metastatic niche formation. Overall design: mRNA profiles of 4 normal omental MSCs and 10 ovarian CA-MSCs using Illumina TruSeq RNA Sample Preparation kit and Illumina HiSeq 100bp PE sequencing.
Publication Title
Ovarian Carcinoma-Associated Mesenchymal Stem Cells Arise from Tissue-Specific Normal Stroma.
Sample Metadata Fields
Specimen part, Subject
View Samples- Mus musculus
- 12 Downloadable Samples
Illumina MouseRef-8 v2.0 expression beadchip
Description
Chronic, low-grade adipose tissue inflammation associated with adipocyte hypertrophy is an important link in the relationship between obesity and insulin resistance. Although ubiquitin ligases are essential regulators of inflammatory processes, the role of these enzymes in metabolically driven adipose tissue inflammation is relatively unexplored. In this study, we found that the ubiquitin ligase Siah2 is a central factor in obesity-related adipose tissue inflammation. When challenged with chronic excess energy intake, Siah2-null mice become obese with enlarged adipocytes, but do not develop obesity-induced insulin resistance. Proinflammatory gene expression is substantially reduced in the Siah2-null epididymal adipose tissue of the obese Siah2KO mice.
Publication Title
The ubiquitin ligase Siah2 regulates obesity-induced adipose tissue inflammation.
Sample Metadata Fields
Sex, Age, Specimen part
View Samples- Homo sapiens
- 8 Downloadable Samples
- Affymetrix Human Gene 1.0 ST Array (hugene10st)
Description
We used unsupervised hierarchical clustering to analyse expression in primary ovarian tumors and associated abdominal deposits. GeneGo pathway analysis of differentially expressed genes between primary tumors and deposits revealed 4 of the top 10 pathways related to cytoskeleton remodeling and cell adhesion.
Publication Title
LRP1B deletion in high-grade serous ovarian cancers is associated with acquired chemotherapy resistance to liposomal doxorubicin.
Sample Metadata Fields
Sex, Specimen part, Subject
View Samples- Homo sapiens
- 83 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Expression profile of 30 LMP tumours and 60 Serous tumours were compared to identify the biolgical pathways specific to these groups. Genotyping was done to identify the mutations potentially causing these phenotypes
Publication Title
Mutation of ERBB2 provides a novel alternative mechanism for the ubiquitous activation of RAS-MAPK in ovarian serous low malignant potential tumors.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 98 Downloadable Samples
- Affymetrix Human Gene 1.0 ST Array (hugene10st)
Description
We used microarrays to assess gene expression in proliferating ovarian cancer cell lines
Publication Title
Synergistic inhibition of ovarian cancer cell growth by combining selective PI3K/mTOR and RAS/ERK pathway inhibitors.
Sample Metadata Fields
Specimen part, Cell line
View Samples- Homo sapiens
- 20 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
To identify the gene signature accounting for the distinct clinical outcomes in ovarian clear cell cancer patients
Publication Title
Identification of novel therapeutic targets in microdissected clear cell ovarian cancers.
Sample Metadata Fields
Specimen part
View Samples- Homo sapiens
- 10 Downloadable Samples
- Affymetrix Human Gene 1.0 ST Array (hugene10st)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
Resistance to CDK2 inhibitors is associated with selection of polyploid cells in CCNE1-amplified ovarian cancer.
Sample Metadata Fields
Specimen part
View Samples- Homo sapiens
- 10 Downloadable Samples
Affymetrix Human Gene 1.0 ST Array (hugene10st)
Description
Cyclin E1 (CCNE1) is amplified in various tumor types including high-grade serous ovarian cancer where it is associated with poor clinical outcome. We have demonstrate that suppression of the Cyclin E1 partner kinase, CDK2, induces apoptosis in a CCNE1 amplicon-dependent manner. Little is known of mechanisms of resistance to CDK inhibitors. We therefore generated OVCAR-3 sublines with reduced sensitivity to CDK2 inhibitors and profiled by gene expression microarrays.
Publication Title
Resistance to CDK2 inhibitors is associated with selection of polyploid cells in CCNE1-amplified ovarian cancer.
Sample Metadata Fields
Specimen part
View Samples- Homo sapiens
- 12 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
In the past three years the role of inflammatory cytokines and chemokines in tumour promotion and progression has been intensively studied. The chemokine receptor CXCR4 and its ligand CXCL12 are commonly expressed in malignant cells from primary tumours, metastases and also in malignant cell lines. To investigate the biological significance of this receptor/ligand pair, we knocked-down CXCR4 expression in ovarian cancer cell line IGROV-1 using shRNA, and established stable cell lines.
Publication Title
A dynamic inflammatory cytokine network in the human ovarian cancer microenvironment.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 9 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
We present evidence for an autocrine cytokine network in human ovarian cancer that has paracrine actions on the tumour microenvironment. In experiments using bioinformatics analysis of large gene expression array datasets and ovarian cancer biopsies, we found that the inflammatory cytokines TNF- and IL-6, the chemokine receptor CXCR4 and its ligand CXCL12, are co-regulated in malignant cells. We named this co-regulation the TNF network.
Publication Title
A dynamic inflammatory cytokine network in the human ovarian cancer microenvironment.
Sample Metadata Fields
Specimen part
View Samples