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.
Project description:Recent studies indicate that cancer-associated fibroblasts (CAFs) are phenotypically and functionally heterogeneous. However, little is known about CAF subtypes and the roles they play in cancer progression. Here we identify and characterize two CAF subtypes that coexist within high grade serous ovarian cancers: Fibroblast activation protein (FAP)-high (FH) CAFs resemble the classical myofibroblast-type CAF, whereas FAP-low (FL) CAFs possesses a preadipocyte-like molecular signature.
Project description:Recent studies indicate that cancer-associated fibroblasts (CAFs) are phenotypically and functionally heterogeneous. However, little is known about CAF subtypes and the roles they play in cancer progression. Here we identify and characterize two CAF subtypes that coexist within high grade serous ovarian cancers: Fibroblast activation protein (FAP)-high (FH) CAFs resemble the classical myofibroblast-type CAF, whereas FAP-low (FL) CAFs possesses a preadipocyte-like molecular signature.
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.
Project description:The Japanese Serous Ovarian Cancer Study Group Advanced-stage ovarian cancer is one of the most lethal gynecologic malignancies. To improve prognosis of patients with ovarian cancers, a predictive biomarkers leading to personalized treatments are required. In this large-scale cross-platform study of six microarray datasets consisting of 1054 ovarian cancer patients, we developed a novel risk classification system based on a 126-gene expression signature for predicting overall survival by applying elastic net7 and 10-fold cross validation to a Japanese dataset A (n = 260). We further validated its predictive ability with the five other datasets using multivariate analysis. Also, through gene ontology and pathway analyses of 1109 high-risk ovarian cancer specific transcripts, we identified a significant reduction of expression of immune-response related genes, especially on the antigen presentation pathway. Furthermore, an immunohistochemical analysis demonstrated that the number of CD8 T lymphocytes infiltrating into tumor tissue was significantly decreased in high-risk ovarian cancers. These predictive biomarkers based on the 126-gene expression signature will identify high-risk ovarian cancer patients who need novel immune-activating therapeutic approaches, leading to improved outcomes for such patients. Two hundred sixty patients who were diagnosed as advanced-stage high-grade serous ovarian cancer were analyzed in this study. Microaray data from 10 patients who were diagnosed as advanced-stage high-grade serous ovarian cancer were analyzed to investigate coefficient of correlation in each probes between Agilent Whole Human Genome Oligo Microarray and Affymetrix HG-U133Plus2.0.
Project description:To demonstrate the use of a whole-genome oligonucleotide array to perform expression profiling on a series of microdissected late-stage, high-grade papillary serous ovarian adenocarcinomas to establish a prognostic gene signature correlating with survival and to identify novel survival factors in ovarian cancer. Advanced stage papillary serous tumors of the ovary are responsible for the majority of ovarian cancer deaths, yet the molecular determinants modulating patient survival are poorly characterized. We identify and validate a prognostic gene expression signature correlating with survival in a series of microdissected serous ovarian tumors. Experiment Overall Design: We identified 53 advanced stage, high-grade primary tumor specimens and 10 normal ovarian surface epithelium (OSE) brushings.
Project description:Ovarian cancer is the fifth most common form of cancer in women in the United States. Among different types of ovarian cancer, epithelial ovarian cancer is the most common and is highly lethal, however, prognostic and predictive markers, which can be used to predict chemoresponse and patient survival, have not been thoroughly explored. One critically important yet often overlooked component to the tumor progression process is the tumor microenvironment. Primarily composed of fibroblasts and extracellular matrix proteins (ECM) as well as endothelial cells and lymphocytic infiltrate, the tumor microenvironment has been shown to directly affect cell growth, migration, and differentiation through secreted proteins, cell-cell interactions and matrix remodeling (Tlsty and Coussens, 2006). The tumor microenvironment has the potential to promote tumor initiation of normal epithelial cells and facilitate progression of malignant cells, thereby, presenting a unique approach to diagnosing, understanding and treating cancer. Using a whole-genome oligonucleotide array platform to perform transcriptome profiling on the fibroblastic stromal component microdissected from a series of advanced stage high-grade serous ovarian adenocarcinomas, we identified a transcriptome signature for the ovarian cancer associated fibroblast (CAF). We further functionally characterized one of the identified genes, MFAP5, and we showed that stromal MFAP5 is a prognostic marker associated with poor patient survival. In addition to that, to investigate the signaling machanism and the effect of MFAP5 treatment on ovarian cancer cells, transcriptome profiling of MFAP5 treated OVCA432 high-grade serous ovarian cancer cells was performed. Further functional studies showed that stromal MFAP5 modulated ovarian cancer cell motility and invasion potential. High grade serous ovarian cancer cell line OVCA432 was used. Total RNA was isolated from control samples and MFAP5 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.
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.
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.