Systematic Identification of Epithelial–Stromal Crosstalk Signaling Networks in Ovarian Cancer
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE115635 | GEO | 2018/10/22
REPOSITORIES: GEO
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Project description:Ovarian cancer is the most lethal malignancy in the United States. In the year 2012, there will be an estimated 22,280 new cases and 15,500 deaths from ovarian cancer in the country (Siegel et al., 2012). While studies on ovarian cancer pathogenesis were mainly focused on the epithelial component of the tumor, understanding in the role of cancer associated fibroblasts (CAFs) in ovarian cancer progression is limited. We hypothesized that comparing the gene expression profiles of different components from laser capture microdissected ovarian tissue will allow us to identify an ovarian CAFs specific gene signature which accounts for the supportive role of CAFs in ovarian cancer progression. In this study, gene expression profiling was completed for 31 cancer stroma samples and 32 samples of epithelial component from high grade serous ovarian cancer patients. 8 microdissected normal ovarian stroma and 6 normal human ovarian surface epithelium (HOSE) samples were also included in the study. By comparing the expression data from cancer stroma against that from normal stroma, cancer cells and HOSE, we identified a set of differential expressed genes in ovarian CAFs which showed correlation with cancer patient survival. Further study on these genes can reveal their roles in ovarian cancer progression and pathogenesis. Ultimately, ovarian CAFs specified genes identified in this study may aid in the classification and enhancement of patient outcome. Transcriptome profiling analyses were performed on 31 laser microdissected cancer associated stroma samples, 32 epithelial tumor samples from high grade serous ovarian cancer patients, 8 microdissected normal ovarian stroma samples and 6 ovarian surface epthelium (HOSE) samples using the Affymetrix human genome U133 Plus 2.0 microarray.
2014-09-11 | E-GEOD-40595 | biostudies-arrayexpress
Project description:Ovarian cancer is the most lethal malignancy in the United States. In the year 2012, there will be an estimated 22,280 new cases and 15,500 deaths from ovarian cancer in the country (Siegel et al., 2012). While studies on ovarian cancer pathogenesis were mainly focused on the epithelial component of the tumor, understanding in the role of cancer associated fibroblasts (CAFs) in ovarian cancer progression is limited. We hypothesized that comparing the gene expression profiles of different components from laser capture microdissected ovarian tissue will allow us to identify an ovarian CAFs specific gene signature which accounts for the supportive role of CAFs in ovarian cancer progression. In this study, gene expression profiling was completed for 31 cancer stroma samples and 32 samples of epithelial component from high grade serous ovarian cancer patients. 8 microdissected normal ovarian stroma and 6 normal human ovarian surface epithelium (HOSE) samples were also included in the study. By comparing the expression data from cancer stroma against that from normal stroma, cancer cells and HOSE, we identified a set of differential expressed genes in ovarian CAFs which showed correlation with cancer patient survival. Further study on these genes can reveal their roles in ovarian cancer progression and pathogenesis. Ultimately, ovarian CAFs specified genes identified in this study may aid in the classification and enhancement of patient outcome.
2014-09-11 | GSE40595 | GEO
Project description:High-grade serous carcinoma has a poor prognosis, owing primarily to its early dissemination throughout the abdominal cavity. Genomic and proteomic approaches have provided snapshots of the proteogenomics of ovarian cancer, but a systematic examination of both the tumour and stromal compartments is critical in understanding ovarian cancer metastasis. We developed a label- free proteomic workflow to analyse as few as 5,000 formalin-fixed, paraffin-embedded cells microdissected from each compartment. The tumour proteome was stable during progression from in situ lesions to metastatic disease; however, the metastasis-associated stroma was characterized by a highly conserved proteomic signature, prominently including the methyltransferase nicotinamide N-methyltransferase (NNMT) and several of the proteins that it regulates. Stromal NNMT expression was necessary and sufficient for functional aspects of the cancer-associated fibroblast (CAF) phenotype, including the expression of CAF markers and the secretion of cytokines and oncogenic extracellular matrix. Stromal NNMT expression supported ovarian cancer migration, proliferation and in vivo growth and metastasis. Expression of NNMT in CAFs led to depletion of S-adenosyl methionine and reduction in histone methylation associated with widespread gene- expression changes in the tumour stroma. This work supports the use of ultra-low-input proteomics to identify candidate drivers of disease phenotypes. NNMT is a central, metabolic regulator of CAF differentiation and cancer progression in the stroma that may be therapeutically targeted.
2019-04-18 | PXD006396 | Pride
Project description:Advanced ovarian cancer is the most lethal gynecologic malignancy in the United States. Ovarian cancer cells are known to have diminished response to TGF-beta, but it remains unclear whether TGF-beta can modulate ovarian cancer cell growth in an indirect manner through cancer-associated fibroblasts (CAFs). Using transcriptome profiling analyses on TGF-beta-treated ovarian fibroblasts, we identified a TGF-beta-responsive gene signature in ovarian fibroblasts. Identifying TGF-beta-regulated genes in the ovarian microenvironment helps in understanding the role of TGF-beta in ovarian cancer progression.
2013-12-31 | GSE40266 | GEO
Project description:Advanced ovarian cancer is the most lethal gynecologic malignancy in the United States. Currently patients are treated by surgical cytoreductive surgery with the aim of reducing tumor burden to microscopic disease followed by adjuvant combined treatment with a platinum and taxane containing chemotherapy, which affords 80% of patients an initial complete response. However, Abdominal and pelvic recurrence rates are high and response to further chemotherapy is limited. Attempts at introducing biologic therapeutic agents to improve outcome in this disease are ongoing, while prognostic or predictive biomarkers that can stratify patients for treatment are still lacking. Using transcriptome profiling of microdissected tissue samples from high-grade serous ovarian cancer patients, we identified a cancer associated fibroblast (CAF) specific gene signature. Versican, which encodes a extracellular matrix protein, was one of the identified genes which demonstrated up-regulation in cancer stroma. To investigate the function roles, signaling machanism and the effect of versican treatment on ovarian cancer cells, transcriptome profiling of versican treated OVCA433 high-grade serous ovarian cancer cells was performed.
2013-12-31 | GSE40241 | GEO
Project description:Advanced ovarian cancer is the most lethal gynecologic malignancy in the United States. Ovarian cancer cells are known to have diminished response to TGF-beta, but it remains unclear whether TGF-beta can modulate ovarian cancer cell growth in an indirect manner through cancer-associated fibroblasts (CAFs). Using transcriptome profiling analyses on TGF-beta-treated ovarian fibroblasts, we identified a TGF-beta-responsive gene signature in ovarian fibroblasts. Identifying TGF-beta-regulated genes in the ovarian microenvironment helps in understanding the role of TGF-beta in ovarian cancer progression. The human telomerase-immortalized ovarian fibroblast line NOF151 was treated with 5ng/mL of either TGF-beta-1 or TGF-beta-2. Total RNA was isolated from control samples and TGF-beta-treated fibroblasts samples at 48 hours post-treatment, followed by cDNA synthesis, IVT and biotin labeling. Samples were then hybridized onto Affymetrix Human Genome U133 Plus 2.0 microarrays. For each treatment group, three independent samples were prepared for the microarray experiment.
2013-12-31 | E-GEOD-40266 | biostudies-arrayexpress
Project description:Advanced ovarian cancer is the most lethal gynecologic malignancy in the United States. Currently patients are treated by surgical cytoreductive surgery with the aim of reducing tumor burden to microscopic disease followed by adjuvant combined treatment with a platinum and taxane containing chemotherapy, which affords 80% of patients an initial complete response. However, Abdominal and pelvic recurrence rates are high and response to further chemotherapy is limited. Attempts at introducing biologic therapeutic agents to improve outcome in this disease are ongoing, while prognostic or predictive biomarkers that can stratify patients for treatment are still lacking. Using transcriptome profiling of microdissected tissue samples from high-grade serous ovarian cancer patients, we identified a cancer associated fibroblast (CAF) specific gene signature. Versican, which encodes a extracellular matrix protein, was one of the identified genes which demonstrated up-regulation in cancer stroma. To investigate the function roles, signaling machanism and the effect of versican treatment on ovarian cancer cells, transcriptome profiling of versican treated OVCA433 high-grade serous ovarian cancer cells was performed. High grade serous ovarian cancer cell line OVCA433 was used. Total RNA was isolated from control samples and versican treated cancer cell samples at 48 hours post-treatment followed by cDNA synthesis, IVT and biotin labeling. Samples were then hybridized onto Affymetrix Human genome U133 plus 2.0 microarrays. For each treatment group, three independent samples were prepared for the microarray experiment.
2013-12-31 | E-GEOD-40241 | biostudies-arrayexpress
Project description:A data set of normal epithelium, serous ovarian surface epithelial-stromal tumors (benign and type II malignancies), stroma distal to tumor, and stroma adjacent to tumor (50 samples total). Additional cel files are included which represent replicate sampling from patients, and cel files that failed quality control but may be bioinformatically interesting. Additional replicate or failed cel files were not included in the final analysis (and so these samples were not included in the matrix). Background: Ovarian cancer is the most lethal gynecologic cancer in the United States. If caught in early stages, patient survival rate can reach 94%, when diagnosed at late stages survival rates drop to 28%. Correct diagnosis depends on the presence of definite symptoms: while ~90% of diagnosed ovarian cancers have symptoms, they tend to be unfocused and subacute. A definitive and early molecular signature of disease is thus desired. To further progress towards this goal, we present an Affymetrix™ human exon array data set measuring ovarian tumor expression, assembled using best practices. Method: Samples were collected from patients with benign and malignant (type II) serous ovarian surface epithelial-stromal tumors. Normal epithelium, tumor, stroma adjacent to tumor, and distal stroma were selected based on histopathology, and isolated using laser capture microdissection. Nugen products were used to perform random-primed mRNA amplification procedures (for full transcript capture) before hybridization to Affymetrix exon chips. Tumor expression and paracrine signaling was assessed using GC-RMA and a two-way Model I ANOVA. Single enrichment ontological analysis and gene network construction were performed to guide inferences about biological context. Results: In total, across 50 microarrays, ~270 million measurements were obtained. Based on comparisons to known ovarian cancer properties as established in molecular genetics literature, the initial analysis presented emphasizes data quality. Major trends between sample classes included: apical surface and tight junction activity, mitotic activity, benign tumor suppression, epithelial-mesenchymal transitioning, tumor oncogene activity, and paracrine signaling. A list of differentially expressed transcripts has been produced to enable rapid comparisons with published biomarker lists, but it is expected that detailed alternative transcript analysis will refine these predictions. Conclusions: A data set of 50 arrays, from carefully dissected serous ovarian surface epithelial-stromal tumors, has been produced, from which high quality measurements were obtained. While relatively small in number, this represents an important addition to the community pool of ovarian tumor samples, and the chosen platform enables bridging between 3' expression and exome sequencing data sets. This represents a significant contribution to the ovarian cancer genetics community. A total of 50 human ovary samples were used in analysis: 23 tissue samples laser capture microdissected from an ovary with a benign serous tumor (specifically 4 normal epithelium samples, 5 tumor samples, 6 stroma samples adjacent to the tumor, and 8 stroma samples distal of the tumor), and 27 tissue samples laser capture microdissected from an ovary with a malignant serous tumor (specifically 5 normal epithelium samples, 8 tumor samples, 7 stroma samples adjacent to the tumor, and 7 stroma samples distal of the tumor). Additional cel files were provided which, although were used in the quality control of the data set, were not used in the final experimental analysis. 8 replicates are included as cel files (1 from each cohort previously listed). 14 cel files were also included which failed quality control. Although the replicate and failed cel files were not used in the final analysis, they may still be interesting in other research.
2011-05-11 | E-GEOD-29156 | biostudies-arrayexpress
Project description:Cancer-associated fibroblasts (CAFs) are an important component of the desmoplastic stroma in rectal cancer. Preoperative chemoradiotherapy plays a pivotal role in the management of locally advanced rectal cancer. Patient-derived CAFs were used to evaluate the response to radiotherapy and its consequent impact on colorectal cancer cells (COLO320DM). COLO320DM cells were seeded and 24 hours later 1.8Gy irradiated. Subsequently, 24h later COLO320DM cells were treated with the secretome of 10x 1.8Gy irradiated CAFs or sham treated CAFs in 0.5% of serum. RNA was isolated 6 hours or 48 hours later.
2017-11-01 | E-MTAB-5364 | biostudies-arrayexpress
Project description:Pancreatic ductal adenocarcinoma (PDAC) has a characteristically dense stroma comprised predominantly of cancer associated fibroblasts (CAFs). CAFs promote tumor growth, metastasis and treatment resistance. We aimed to investigate the molecular changes and functional consequences associated with chemotherapy treatment of PDAC CAFs. Chemoresistant immortalized CAFs (R-CAFs) were generated by continuous incubation in 100nM gemcitabine. Gene expression differences between treatment naïve CAFs (N-CAFs) and R-CAFs were compared by array analysis. Immortalized human pancreatic CAFs were grown for 30 days in either control media or media containing 100nM gemcitabine. RNA was then isolated and hybidized on U133 Plus 2.0 Affymetrix arrays.
2016-03-09 | E-GEOD-78982 | biostudies-arrayexpress