Project description:This SuperSeries is composed of the following subset Series:; GSE9890: Expression profile of 5 ovarian tumour samples (two different cell types from each sample profiles); GSE9891: Expression profile of 285 ovarian tumour samples Experiment Overall Design: Refer to individual Series
Project description:single cell RNA-seq was performed on tumour and stromal cells from a single patient with ovarian cancer to establish gene expression profile differences between the two cell types and also heterogeneity within the tumour population.
Project description:Ascites or solid tumour from patients with ovarian cancer was collected and grown in culture as ex vivo models. Each sample has a tumour component and some samples have matched stromal cells, which were separated into individual cultures. RNA-seq was performed on these models to establish gene expression profiles, which allow the assessment of the separation protocol and identification of genes that are differentially expressed. The histological subtype from which the models were collected includes majorly high-grade serous, but also low-grade serous, clear cell and mucinous ovarian cancer. The sample subtypes have been assessed using a machine-learning based transcriptional classifier. These samples are processed in the same manner as a previous study, “E-MTAB-7223 - RNA-seq of human ex vivo ovarian cancer models with matched stromal cells”
Project description:Transcriptomic profiling was done on 81 primary tumours, 1 relapse tumour, 5 autopsy tumours (whole tissue sections or macrodissected to enrich for tumour), 29 ascites and 7 normal fallopian tube samples. 1 of the primary tumours is a low grade serous ovarian cancer sample.
Project description:We validated fifteen models from “living biobank” to provide models that support interrogation of Chromosome Instability and to evaluate novel therapeutics. Single cell RNA-seq was performed on tumour and stromal cells from 4 patients with ovarian cancer to establish gene expression profile differences between the two cell types and also heterogeneity within the tumour population. The samples used were AS38b, AS59, AS74-1, AS79, they are grown in OCMI media supplemented with 5% hyclone serum (AS38, AS59) or 5% FBS (AS74, AS79) in 5% CO2 and 5% O2. At 37C
Project description:We used microarrays to profile the expression levels of 5 tumour samples Keywords: expression difference of cell types in tumour samples
Project description:Metastatic ovarian tissues represent a complex tumour microenviroment. We analysed the tumour matrisome and immune cell environment in 39 metastatic ovarian tissues. We developed a disease score system, which positively correlated with the tumour matrisome. A distinct matrisome signature was identfied with increasing disease. Immune abundance and phenotype positively correaletd with tumour matrisome components. We developed a decellularised tissue model using metastatic ovarian omental tissues that maintained ECM protein content and architecture and cultured human blood-derived macrophages derived from four different donors. Monocytes cultured on high diseased tissues differerntiated into a distinct macrophage population, different from uninvovled (low disease) samples. Tumour ECM cultured macrophages had pro-tumorgenic phenotype and function.
Project description:We used microarrays to profile the expression levels of 285 ovarian samples in order to identify molecular subtypes of the tumour Keywords: disease state analysis
