Project description:Ascites or solid tumour samples from patients with ovarian cancer were collected and grown in culture as ex vivo models of purified tumour cells. RNA-seq was performed on these models to establish gene expression profiles, which allow identification of genes that are differentially expressed between patients with differing tumour intrinsic properties. These samples have been interrogated for the presence of a gene expression signature indicative of sensitivity to an inhibitor of poly(ADP-ribose) glycohydrolase (PARG). These samples are processed in the same manner as previous studies: “E-MTAB-7223 - RNA-seq of human ex vivo ovarian cancer models with matched stromal cells” and “E-MTAB-10801 - RNA-seq of human ex vivo ovarian cancer models with matched stromal cells - part II” with no stromal counterparts included in this current sequencing batch.
Project description:Analyses of circulating tumor cells (CTC) cultured from blood of patients with cancer may allow individualized testing for susceptibility to therapeutic regimens. We established ex vivo cultures of CTCs from six patients with metastatic estrogen receptor-positive breast cancer and performed RNA-Seq on those cultures. One sample each from six metastatic estrogen receptor positive breast cancer patients
Project description:RNA-seq analysis was performed to compare differentially expressed genes in freshly isolated and ex-vivo cultured human cord blood CD34+ cells. Mitochondrion related genes are upregulated in CD34+ hematopoietic stem and progenitor cells upon ex vivo culture. In vivo transplantation experiments demonstrate that stemness of CD34+ cells is significantly decreased due to oxidative stress induced by ex vivo culture.
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”