Project description:Pancreatic neuroendocrine tumor (PanNET) is relatively infrequent but is nevertheless metastatic. Seeking to extend a new paradigm of personalized medicine, we performed an integrative analysis of transcriptomic (mRNA and microRNA) and mutational profiles and defined three clinically relevant human PanNET subtypes. Importantly, cross-species analysis revealed two of these three subtypes in a well-characterized, genetically engineered mouse model (RIP1-Tag2) of PanNET and its cell lines. Each subtype share similarities to distinct cell types in pancreatic neuroendocrine development, features are reflected in their metabolic profiles. Subtype-specific molecular signatures metabolites are proposed to identify these subtypes. RNA was extracted from fresh frozen archival patient PanNET samples and hybridized on Affymetrix GeneChip human Gene 1.0 ST arrays. The CEL files were processed using R based bioconductor and normalized values were obtained using RMA.
Project description:Pancreatic neuroendocrine tumor (PanNET) is relatively infrequent but is nevertheless metastatic. Seeking to extend a new paradigm of personalized medicine, we performed an integrative analysis of transcriptomic (mRNA and microRNA) and mutational profiles and defined three clinically relevant human PanNET subtypes. Importantly, cross-species analysis revealed two of these three subtypes in a well-characterized, genetically engineered mouse model (RIP1-Tag2) of PanNET and its cell lines. Each subtype share similarities to distinct cell types in pancreatic neuroendocrine development, features are reflected in their metabolic profiles. Subtype-specific molecular signatures metabolites are proposed to identify these subtypes.
Project description:Pancreatic neuroendocrine tumor (PanNET) is relatively infrequent but is nevertheless metastatic. Seeking to extend a new paradigm of personalized medicine, we performed an integrative analysis of transcriptomic (mRNA and microRNA) and mutational profiles and defined three clinically relevant human PanNET subtypes. Importantly, cross-species analysis revealed two of these three subtypes in a well-characterized, genetically engineered mouse model (RIP1-Tag2) of PanNET and its cell lines. Each subtype share similarities to distinct cell types in pancreatic neuroendocrine development, features are reflected in their metabolic profiles. Subtype-specific molecular signatures metabolites are proposed to identify these subtypes.
Project description:Pancreatic neuroendocrine tumor (PanNET) is relatively infrequent but is nevertheless metastatic. Seeking to extend a new paradigm of personalized medicine, we performed an integrative analysis of transcriptomic (mRNA and microRNA) and mutational profiles and defined three clinically relevant human PanNET subtypes. Importantly, cross-species analysis revealed two of these three subtypes in a well-characterized, genetically engineered mouse model (RIP1-Tag2) of PanNET and its cell lines. Each subtype share similarities to distinct cell types in pancreatic neuroendocrine development, features are reflected in their metabolic profiles. Subtype-specific molecular signatures metabolites are proposed to identify these subtypes. Gene expression data from different stages of RIP1-TAG2 genetically engineered PanNET mouse model RT2 mouse PanNET tumors, liver metastases, normal, hyperplastic, and angiogenic islets were dissected out or isolated. RNA was extracted and hybridized on Affymetrix GeneChip Mouse Gene 1.0 ST arrays. The CEL files were processed using aroma.affymetrix.
Project description:Pancreatic neuroendocrine tumor (PanNET) is relatively infrequent but is nevertheless metastatic. Seeking to extend a new paradigm of personalized medicine, we performed an integrative analysis of transcriptomic (mRNA and microRNA) and mutational profiles and defined three clinically relevant human PanNET subtypes. Importantly, cross-species analysis revealed two of these three subtypes in a well-characterized, genetically engineered mouse model (RIP1-Tag2) of PanNET and its cell lines. Each subtype share similarities to distinct cell types in pancreatic neuroendocrine development, features are reflected in their metabolic profiles. Subtype-specific molecular signatures metabolites are proposed to identify these subtypes. Gene expression data from different stages of RIP1-TAG2 genetically engineered PanNET mouse model
Project description:The largest of the tuna species, Atlantic bluefin tuna, Thunnus thynnus (Linnaeus, 1758), inhabits the North Atlantic Ocean and the Mediterranean Sea and is considered to be an endangered species, largely through overfishing. Thus, the development of aquaculture practices independent of wild resources can provide an important contribution towards ensuring security and sustainability of this species in the longer-term. In order to provide a resource for ongoing studies, we have used 454 pyrosequencing technology to sequence a mixed-tissue normalized cDNA library, derived from adult individuals. Transcript sequences were used to develop a novel 15K Agilent oligo microarray for T. thynnus and comparative tissue gene expression profiles were inferred for gill, heart, liver, ovaries and testes.
Project description:Pancreatic neuroendocrine tumor (PanNET) is relatively infrequent but is nevertheless metastatic. Seeking to extend a new paradigm of personalized medicine, we performed an integrative analysis of transcriptomic (mRNA and microRNA) and mutational profiles and defined three clinically relevant human PanNET subtypes. Importantly, cross-species analysis revealed two of these three subtypes in a well-characterized, genetically engineered mouse model (RIP1-Tag2) of PanNET and its cell lines. Each subtype share similarities to distinct cell types in pancreatic neuroendocrine development, features are reflected in their metabolic profiles. Subtype-specific molecular signatures metabolites are proposed to identify these subtypes. Total RNA was extracted from fresh frozen archival patient PanNET samples and hybridized on Agilent microRNA arrays. All normalization methods were performed on the Total Gene Signal from Agilent "GeneView" data files in R, an open source statistical scripting language (http://www.r-project.org). Except for VSN, data were log2 transformed after adding a small constant such that the smallest value of the data set was 1 before taking the log. Scaling normalization was performed by dividing each array by its mean signal intensity and then by rescaling to the global mean intensity of all arrays. Quantile normalization was performed using the "normalize.quantiles" function from R package "affy" from the Bioconductor project (http://www.bioconductor.org).
Project description:Sargassum is one of the most diverse brown algal genus with more than 150 known species, mostly benthic and few pelagic species. They contribute significantly to global primary production and serve as important habitat for wide range of marine organisms. Sargassum vulgare is one of the dominant habitat forming species along Mediterranean coast. Despite their huge ecological importance, it is relatively unknown how they will respond under future global climate change scenario. This work used de novo transcriptome sequencing approach to understand the molecular response of S. vulgare to chronic acidification at the shallow underwater volcanic CO2 vents off Ischia Island, Italy. Keywords: brown algae, Sargassum, de novo transcriptome, ocean acidification, CO2 vents.