The role of epithelial cell-derived tumour necrosis Factor Alpha in pancreatic carcinogenesis

PhDActivating mutations of the kras proto-oncogene are found in more than 90 % of human pancreatic ductal adenocarcinoma (PDAC) and can result in increased activity of the NF-κB pathway, leading to constitutive production of proinflammatory cytokines such as TNF-α. Pancreatic cancer progression occurs through a series of pre-invasive lesions, pancreatic intraepithelial neoplasias (PanIN lesions), which progress into invasive carcinoma. The aim of this thesis is to understand the autocrine role of TNF-α produced by premalignant epithelial cells in pancreatic tumour progression. This cytokine has already been shown to be involved in the progression of cancer. The major hypothesis therefore tested was that TNF-α secreted by pre-malignant epithelial cells promotes the early stages of pancreatic carcinogenesis by sustaining an inflamed microenvironment. In the spontaneous kras+/LSL-G12D; pdx1-cre mouse model of pancreatic cancer, concomitant genetic deletion of the TNF-α/IKK2 pathway substantially delayed pancreatic cancer progression and resulted in downregulation of the classical Notch target genes hes1 and hey1. Cell lines from the different PanIN bearing mice were established and used to dissect the cooperation between TNF-α/IKK2 and Notch signalling during PanIN progression. Optimal expression of Notch target genes was induced upon TNF-α stimulation of the canonical NF-κB signalling pathway, in cooperation with basal Notch signals. Mechanistically, TNF-α stimulation resulted in phosphorylation of histone H3 at the hes1 promoter and this signal was lost upon ikk2 genetic deletion. HES1 suppressed the expression of pparg, which encodes for the anti-inflammatory nuclear receptor PPAR-γ. Thus, crosstalk between TNF-α/IKK2 and Notch sustained an intrinsic inflammatory profile of the transformed cells. The treatment of PanIN bearing mice with rosiglitazone, a PPAR-γ agonist, also delayed PanIN progression. A malignant cell-autonomous, low-grade inflammatory process was shown to operate from the very early stages of kras-driven pancreatic carcinogenesis, which may cooperate with the Notch signalling pathway to promote pancreatic cancer progression.Medical Research Counci

Controlling Microgrids Without External Data: A Benchmark of Stochastic Programming Methods

Microgrids are local energy systems that integrate energy production, demand, and storage units. They are generally connected to the regional grid to import electricity when local production and storage do not meet the demand. In this context, Energy Management Systems (EMS) are used to ensure the balance between supply and demand, while minimizing the electricity bill, or an environmental criterion. The main implementation challenges for an EMS come from the uncertainties in the consumption, the local renewable energy production, and in the price and the carbon intensity of electricity. Model Predictive Control (MPC) is widely used to implement EMS but is particularly sensitive to the forecast quality, and often requires a subscription to expensive third-party forecast services. We introduce four Multistage Stochastic Control Algorithms relying only on historical data obtained from on-site measurements. We formulate them under the shared framework of Multistage Stochastic Programming and benchmark them against two baselines in 61 different microgrid setups using the EMSx dataset. Our most effective algorithm produces notable cost reductions compared to an MPC that utilizes the same uncertainty model to generate predictions, and it demonstrates similar performance levels to an ideal MPC that relies on perfect forecasts

Controlling Microgrids Without External Data: A Benchmark of Stochastic Programming Methods

Microgrids are local energy systems that integrate energy production, demand, and storage units. They are generally connected to the regional grid to import electricity when local production and storage do not meet the demand. In this context, Energy Management Systems (EMS) are used to ensure the balance between supply and demand, while minimizing the electricity bill, or an environmental criterion. The main implementation challenges for an EMS come from the uncertainties in the consumption, the local renewable energy production, and in the price and the carbon intensity of electricity. Model Predictive Control (MPC) is widely used to implement EMS but is particularly sensitive to the forecast quality, and often requires a subscription to expensive third-party forecast services. We introduce four Multistage Stochastic Control Algorithms relying only on historical data obtained from on-site measurements. We formulate them under the shared framework of Multistage Stochastic Programming and benchmark them against two baselines in 61 different microgrid setups using the EMSx dataset. Our most effective algorithm produces notable cost reductions compared to an MPC that utilizes the same uncertainty model to generate predictions, and it demonstrates similar performance levels to an ideal MPC that relies on perfect forecasts

Controlling Microgrids Without External Data: A Benchmark of Stochastic Programming Methods

Microgrids are local energy systems that integrate energy production, demand, and storage units. They are generally connected to the regional grid to import electricity when local production and storage do not meet the demand. In this context, Energy Management Systems (EMS) are used to ensure the balance between supply and demand, while minimizing the electricity bill, or an environmental criterion. The main implementation challenges for an EMS come from the uncertainties in the consumption, the local renewable energy production, and in the price and the carbon intensity of electricity. Model Predictive Control (MPC) is widely used to implement EMS but is particularly sensitive to the forecast quality, and often requires a subscription to expensive third-party forecast services. We introduce four Multistage Stochastic Control Algorithms relying only on historical data obtained from on-site measurements. We formulate them under the shared framework of Multistage Stochastic Programming and benchmark them against two baselines in 61 different microgrid setups using the EMSx dataset. Our most effective algorithm produces notable cost reductions compared to an MPC that utilizes the same uncertainty model to generate predictions, and it demonstrates similar performance levels to an ideal MPC that relies on perfect forecasts

Crosstalk between the canonical NF-κB and Notch signaling pathways inhibits Pparγ expression and promotes pancreatic cancer progression in mice

The majority of human pancreatic cancers have activating mutations in the KRAS proto-oncogene. These mutations result in increased activity of the NF-κB pathway and the subsequent constitutive production of proinflammatory cytokines. Here, we show that inhibitor of κB kinase 2 (Ikk2), a component of the canonical NF-κB signaling pathway, synergizes with basal Notch signaling to upregulate transcription of primary Notch target genes, resulting in suppression of antiinflammatory protein expression and promotion of pancreatic carcinogenesis in mice. We found that in the KrasG12DPdx1-cre mouse model of pancreatic cancer, genetic deletion of Ikk2 in initiated pre-malignant epithelial cells substantially delayed pancreatic oncogenesis and resulted in downregulation of the classical Notch target genes Hes1 and Hey1. Tnf-α stimulated canonical NF-κB signaling and, in collaboration with basal Notch signals, induced optimal expression of Notch targets. Mechanistically, Tnf-α stimulation resulted in phosphorylation of histone H3 at the Hes1 promoter, and this signal was lost with Ikk2 deletion. Hes1 suppresses expression of Pparg, which encodes the antiinflammatory nuclear receptor Pparγ. Thus, crosstalk between Tnf-α/Ikk2 and Notch sustains the intrinsic inflammatory profile of transformed cells. These findings reveal what we believe to be a novel interaction between oncogenic inflammation and a major cell fate pathway and show how these pathways can cooperate to promote cancer progression

USP9X deubiquitinase couples the pluripotency network and cell metabolism to regulate ESC differentiation potential

International audienceABSTRACT Embryonic stem cells (ESC) have the unique ability to differentiate into all three germ cell layers. ESC transition through different states of pluripotency in response to growth factor signals and environmental cues before becoming terminally differentiated. Here, we demonstrated, by a multi-omic strategy, that the deubiquitinase USP9X regulates the developmental potential of ESC, and their transition from a naive to a more developmentally advance, or primed, state of pluripotency. We show that USP9X facilitates developmental gene expression and induces modifications of the mitochondrial bioenergetics, including decreased routing of pyruvate towards its oxidation and reduced respiration. In addition, USP9X binds to the pluripotency factor ESRRB, regulates its abundance and the transcriptional levels of a subset of its target genes. Finally, under permissive culture conditions, depletion of Usp9X accelerates cell differentiation in all cell lineages. We thus identified a new regulator of naive pluripotency and show that USP9X couples ESRRB pluripotency transcriptional network and cellular metabolism, both of which are important for ESC fate and pluripotency

Lkb1 suppresses amino acid-driven gluconeogenesis in the liver

International audienceExcessive glucose production by the liver is a key factor in the hyperglycemia observed in type 2 diabetes mellitus (T2DM). Here, we highlight a novel role of liver kinase B1 (Lkb1) in this regulation. We show that mice with a hepatocyte-specific deletion of Lkb1 have higher levels of hepatic amino acid catabolism, driving gluconeogenesis. This effect is observed during both fasting and the postprandial period, identifying Lkb1 as a critical suppressor of postprandial hepatic gluconeogenesis. Hepatic Lkb1 deletion is associated with major changes in whole-body metabolism, leading to a lower lean body mass and, in the longer term, sarcopenia and cachexia, as a consequence of the diversion of amino acids to liver metabolism at the expense of muscle. Using genetic, proteomic and pharmacological approaches, we identify the aminotransferases and specifically Agxt as effectors of the suppressor function of Lkb1 in amino acid-driven gluconeogenesis

Lkb1 suppresses amino acid-driven gluconeogenesis in the liver. Correction

International audienc

ADAM8 as a drug target in pancreatic cancer

Schlomann U, Koller G, Conrad C, et al. ADAM8 as a drug target in pancreatic cancer. NATURE COMMUNICATIONS. 2015;6(1): 6175.Pancreatic ductal adenocarcinoma (PDAC) has a grim prognosis with <5% survivors after 5 years. High expression levels of ADAM8, a metalloprotease disintegrin, are correlated with poor clinical outcome. We show that ADAM8 expression is associated with increased migration and invasiveness of PDAC cells caused by activation of ERK1/2 and higher MMP activities. For biological function, ADAM8 requires multimerization and associates with beta 1 integrin on the cell surface. A peptidomimetic ADAM8 inhibitor, BK-1361, designed by structural modelling of the disintegrin domain, prevents ADAM8 multimerization. In PDAC cells, BK-1361 affects ADAM8 function leading to reduced invasiveness, and less ERK1/2 and MMP activation. BK-1361 application in mice decreased tumour burden and metastasis of implanted pancreatic tumour cells and provides improved metrics of clinical symptoms and survival in a Kras(G12D)-driven mouse model of PDAC. Thus, our data integrate ADAM8 in pancreatic cancer signalling and validate ADAM8 as a target for PDAC therapy