2 resultados para Competition model

em AMS Tesi di Dottorato - Alm@DL - Università di Bologna


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Neoplastic overgrowth depends on the cooperation of several mutations ultimately leading to major rearrangements in cellular behaviour. The molecular crosstalk occurring between precancerous and normal cells strongly influences the early steps of the tumourigenic process as well as later stages of the disease. Precancerous cells are often removed by cell death from normal tissues but the mechanisms responsible for such fundamental safeguard processes remain in part elusive. To gain insight into these phenomena I took advantage of the clonal analysis methods available in Drosophila for studying the phenotypes due to loss of function of the neoplastic tumour suppressor lethal giant larvae (lgl). I found that lgl mutant cells growing in wild-type imaginal wing discs are subject to the phenomenon of cell competition and are eliminated by JNK-dependent cell death because they express very low levels of dMyc oncoprotein compared to those in the surrounding tissue. Indeed, in non-competitive backgrounds lgl mutant clones are able to overgrow and upregulate dMyc, overwhelming the neighbouring tissue and forming tumourous masses that display several cancer hallmarks. These phenotypes are completely abolished by reducing dMyc abundance within mutant cells while increasing it in lgl clones growing in a competitive context re-establishes their tumourigenic potential. Similarly, the neoplastic growth observed upon the oncogenic cooperation between lgl mutation and activated Ras/Raf/MAPK signalling was found to be characterised by and dependent on the ability of cancerous cells to upregulate dMyc with respect to the adjacent normal tissue, through both transcriptional and post-transcriptional mechanisms, thereby confirming its key role in lgl-induced tumourigenesis. These results provide first evidence that the dMyc oncoprotein is required in lgl mutant tissue to promote invasive overgrowth in developing and adult epithelial tissues and that dMyc abundance inside versus outside lgl mutant clones plays a key role in driving neoplastic overgrowth.

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In digital markets personal information is pervasively collected by firms. In the first chapter I study data ownership and product customization when there is exclusive access to non rival but excludable data about consumer preferences. I show that an incumbent firm does not have an incentive to sell an exclusively held dataset with a rival firm, but instead it has an incentive to trade a customizing technology with the other firm. In the second chapter I investigate the effects of consumer information on the intensity of competition. In a two dimensional model of product differentiation, firms use information on preferences to practice price discrimination. I contrast a full privacy and a no privacy benchmark with a regime in which firms are able to target consumers only partially. When data is partially informative, firms are always better-off with price discrimination and an exclusive access to user data is not necessarily a competition policy concern. From a consumer protection perspective, the policy recommendation is that the regulator should promote either no privacy or full privacy. In the third chapter I introduce a data broker that observes either only one or both dimensions of consumer information and sells this data to competing firms for price discrimination purposes. When the seller exogenously holds a partially informative dataset, an exclusive allocation arises. Instead, when the dataset held is fully informative, the data broker trades information non exclusively but each competitor acquires consumer data on a different dimension. When data collection is made endogenous, non exclusivity is robust if collection costs are not too high. The competition policy suggestion is that exclusivity should not be banned per se, but it is data differentiation in equilibrium that rises market power in competitive markets. Upstream competition is sufficient to ensure that both firms get access to consumer information.