Project description:Terminal differentiation in parotid acini relies on sustained changes in gene expression during the first few postnatal weeks. Little is known about what drives these changes. Expression measurements along with knowledgebased network analysis was used to develop a prospective gene regulatory network that drives differentiation. We used expression measurements along with knowledgebased network analysis was used to develop a prospective gene regulatory network that drives differentiation. laser capture microdissection was used to isolate acinar cells from the parotid at nine timepoints in triplicate (E18, E20, P0, P2, P5, P9, P15, P20, and P25). RNA was isolated, and applied to the affymetrix rat genome array 230.
Project description:Hyper-activation of the PI 3-Kinase/ AKT pathway is a driving force of many cancers. Here we identify the AKT-inactivating phosphatase PHLPP1 as a prostate tumor suppressor. We show that Phlpp1-loss causes neoplasia and, upon partial Pten-loss, carcinoma in mouse prostate. This genetic setting initially triggers a growth suppressive response via p53 and the Phlpp2 ortholog, and reveals spontaneous Trp53 inactivation as a condition for full-blown disease. Surprisingly, the co-deletion of PTEN and PHLPP1 in patient samples is highly restricted to metastatic disease and tightly correlated to deletion of TP53 and PHLPP2. These data establish a conceptual framework for progression of PTEN-mutant prostate cancer to life-threatening disease. To better assess the role of Phlpp in prostate we performed micorarray analysis of gene expression in the WT and Pten+/-; Phlpp1-/- mice.
Project description:Analysis of purified immune and breast tumor cells from three major compartments where cancer and immune cells interact: primary tumor, tumor draining lymph nodes (tumor invaded or tumor free), and peripheral blood. The results suggests that node-positive patients’ immune regulation and functionality is down-regulated compared to node-negative patients. CD45+ Immune and ESA+ tumor cells were purified from breast cancer patients' primary tumor, tumor-draining lymph node, and peripheral blood (ficoll) and placed onto Agilent microarrays using the dye-swap method. A universal human reference was used as a reference for the patient samples.
Project description:ChIP-Sequencing of 4 diffuse large B-cell lymphoma cell lines expressing different amounts of FOXP1 was performed in order to identify target genes bound by the transcription factor FOXP1.
Project description:Terminal differentiation in parotid acini relies on sustained changes in gene expression during the first few postnatal weeks. Little is known about what drives these changes. Expression measurements along with knowledgebased network analysis was used to develop a prospective gene regulatory network that drives differentiation. We used both microRNA and mRNA expression measurements along with knowledgebased network analysis was used to develop a prospective gene regulatory network that drives differentiation. laser capture microdissection was used to isolate acinar cells from the parotid at four timepoints in triplicate (E20, P5, P15, and P25). RNA was isolated, and used to measure microRNA expression.
Project description:Terminal differentiation in parotid acini relies on sustained changes in gene expression during the first few postnatal weeks. Little is known about what drives these changes. Expression measurements along with knowledgebased network analysis was used to develop a prospective gene regulatory network that drives differentiation. We used expression measurements along with knowledgebased network analysis was used to develop a prospective gene regulatory network that drives differentiation.
Project description:Terminal differentiation in parotid acini relies on sustained changes in gene expression during the first few postnatal weeks. Little is known about what drives these changes. Expression measurements along with knowledgebased network analysis was used to develop a prospective gene regulatory network that drives differentiation. We used both microRNA and mRNA expression measurements along with knowledgebased network analysis was used to develop a prospective gene regulatory network that drives differentiation.