02951nas a2200445   4500008004100000022001400041245009500055210006900150260001600219300001400235490000700249520156700256653002101823653002101844653002401865653003001889653004301919653002901962653001101991653002602002653001502028653001302043653001402056653001402070653001402084653001402098653002702112653002702139653001802166653002202184100001802206700002202224700001902246700002202265700002102287700002002308700003102328700002002359856012602379       2018                        eng d  a1538-744500aGene Expression Integration into Pathway Modules Reveals a Pan-Cancer Metabolic Landscape.0 aGene Expression Integration into Pathway Modules Reveals a PanCa  c2018 Nov 01  a6059-60720 v783 a<p>Metabolic reprogramming plays an important role in cancer development and progression and is a well-established hallmark of cancer. Despite its inherent complexity, cellular metabolism can be decomposed into functional modules that represent fundamental metabolic processes. Here, we performed a pan-cancer study involving 9,428 samples from 25 cancer types to reveal metabolic modules whose individual or coordinated activity predict cancer type and outcome, in turn highlighting novel therapeutic opportunities. Integration of gene expression levels into metabolic modules suggests that the activity of specific modules differs between cancers and the corresponding tissues of origin. Some modules may cooperate, as indicated by the positive correlation of their activity across a range of tumors. The activity of many metabolic modules was significantly associated with prognosis at a stronger magnitude than any of their constituent genes. Thus, modules may be classified as tumor suppressors and oncomodules according to their potential impact on cancer progression. Using this modeling framework, we also propose novel potential therapeutic targets that constitute alternative ways of treating cancer by inhibiting their reprogrammed metabolism. Collectively, this study provides an extensive resource of predicted cancer metabolic profiles and dependencies. Combining gene expression with metabolic modules identifies molecular mechanisms of cancer undetected on an individual gene level and allows discovery of new potential therapeutic targets. .</p>10aCell Line, Tumor10aCluster Analysis10aDisease Progression10aGene Expression Profiling10aGene Expression Regulation, Neoplastic10aGene Regulatory Networks10aHumans10aKaplan-Meier Estimate10aMetabolome10amutation10aNeoplasms10aOncogenes10aPhenotype10aPrognosis10aRNA, Small Interfering10aSequence Analysis, RNA10aTranscriptome10aTreatment Outcome1 aCubuk, Cankut1 aHidalgo, Marta, R1 aAmadoz, Alicia1 aPujana, Miguel, A1 aMateo, Francesca1 aHerranz, Carmen1 aCarbonell-Caballero, José1 aDopazo, Joaquin  uhttps://www.clinbioinfosspa.es/content/gene-expression-integration-pathway-modules-reveals-pan-cancer-metabolic-landscape02568nas a2200445   4500008004100000022001400041245010000055210006900155260001300224300001200237490000700249520111500256653001201371653002201383653003901405653002601444653002201470653004401492653001701536653003201553653000901585653002701594653005201621653002101673653002701694653001801721653003201739100002201771700001901793700001501812700002001827700002201847700001901869700002001888700002001908700002201928700002101950700002201971856012901993       2012                        eng d  a1530-686000aThe protease MT1-MMP drives a combinatorial proteolytic program in activated endothelial cells.0 aprotease MT1MMP drives a combinatorial proteolytic program in ac  c2012 Nov  a4481-940 v263 a<p>The mechanism by which proteolytic events translate into biological responses is not well understood. To explore the link of pericellular proteolysis to events relevant to capillary sprouting within the inflammatory context, we aimed at the identification of the collection of substrates of the protease MT1-MMP in endothelial tip cells induced by inflammatory stimuli. We applied quantitative proteomics to endothelial cells (ECs) derived from wild-type and MT1-MMP-null mice to identify the substrate repertoire of this protease in TNF-α-activated ECs. Bioinformatics analysis revealed a combinatorial MT1-MMP proteolytic program, in which combined rather than single substrate processing would determine biological decisions by activated ECs, including chemotaxis, cell motility and adhesion, and vasculature development. MT1-MMP-deficient ECs inefficiently processed several of these substrates (TSP1, CYR61, NID1, and SEM3C), validating the model. This novel concept of MT1-MMP-driven combinatorial proteolysis in angiogenesis might be extendable to proteolytic actions in other cellular contexts.</p>10aAnimals10aBlotting, Western10aCombinatorial Chemistry Techniques10aComputational Biology10aEndothelial Cells10aGene Expression Regulation, Enzymologic10aInflammation10aMatrix Metalloproteinase 1410aMice10aProtein Array Analysis10aReverse Transcriptase Polymerase Chain Reaction10aRNA Interference10aRNA, Small Interfering10aTranscriptome10aTumor Necrosis Factor-alpha1 aKoziol, Agnieszka1 aGonzalo, Pilar1 aMota, Alba1 aPollán, Angela1 aLorenzo, Cristina1 aColomé, Nuria1 aMontaner, David1 aDopazo, Joaquin1 aArribas, Joaquín1 aCanals, Francesc1 aArroyo, Alicia, G  uhttps://www.clinbioinfosspa.es/content/protease-mt1-mmp-drives-combinatorial-proteolytic-program-activated-endothelial-cells