2 resultados para Multiple play

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


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Torpor is a successful survival strategy displayed by several mammalian species to cope with harsh environmental conditions. A complex interplay of ambient, genetic and circadian stimuli acts centrally to induce a severe suppression of metabolic rate, usually followed by an apparently undefended reduction of body temperature. Some animals, such as marmots, are able to maintain this physiological state for months (hibernation), during which torpor bouts are periodically interrupted by short interbouts of normothermia (arousals). Interestingly, torpor adaptations have been shown to be associated with a large resistance towards stressors, such as radiation: indeed, if irradiated during torpor, hibernators can tolerate higher doses of radiation, showing an increased survival rate. New insights for radiotherapy and long-term space exploration could arise from the induction of torpor in non-hibernators, like humans. The present research project is centered on synthetic torpor (ST), a hypometabolic/hypothermic condition induced in a non-hibernator, the rat, through the pharmacological inhibition of the Raphe Pallidus, a key brainstem area controlling thermogenic effectors. By exploiting this procedure, this thesis aimed at: i) providing a multiorgan description of the functional cellular adaptations to ST; ii) exploring the possibility, and the underpinning molecular mechanisms, of enhanced radioresistance induced by ST. To achieve these aims, transcriptional and histological analysis have been performed in multiple organs of synthetic torpid rats and normothermic rats, either exposed or not exposed to 3 Gy total body of X-rays. The results showed that: i) similarly to natural torpor, ST induction leads to the activation of survival and stress resistance responses, which allow the organs to successfully adapt to the new homeostasis; ii) ST provides tissue protection against radiation damage, probably mainly through the cellular adaptations constitutively induced by ST, even though the triggering of specific responses when the animal is irradiated during hypothermia might play a role.

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Multiple Myeloma (MM) is a hematologic cancer with heterogeneous and complex genomic landscape, where Copy Number Alterations (CNAs) play a key role in the disease's pathogenesis and prognosis. It is of biological and clinical interest to study the temporal occurrence of early alterations, as they play a disease "driver" function by deregulating key tumor pathways. This study presents an innovative bioinformatic tools suite created for harmonizing and tracing the origin of CNAs throughout the evolutionary history of MM. To this aim, large cohorts of newly-diagnosed MM (NDMM, N=1582) and Smoldering-MM (SMM, N=282) were aggregated. The tools developed in this study enable the harmonization of CNAs as obtained from different genomic platforms in such a way that a high statistical power can be obtained. By doing so, the high numerosity of those cohorts was harnessed for the identification of novel genes characterized as "driver" (NFKB2, NOTCH2, MAX, EVI5 and MYC-ME2-enhancer), and the generation of an innovative timing model, implemented with a statistical method to introduce confidence intervals in the CNAs-calls. By applying this model on both NDMM and SMM cohorts, it was possible to identify specific CNAs (1q(CKS1B)amp, 13q(RB1)del, 11q(CCND1)amp and 14q(MAX)del) and categorize them as "early"/ "driver" events. A high level of precision was guaranteed by the narrow confidence intervals in the timing estimates. These CNAs were proposed as critical MM alterations, which play a foundational role in the evolutionary history of both SMM and NDMM. Finally, a multivariate survival model was able to identify the independent genomic alterations with the greatest effect on patients’ survival, including RB1-del, CKS1B-amp, MYC-amp, NOTCH2-amp and TRAF3-del/mut. In conclusion, the alterations that were identified as both "early-drivers” and correlated with patients’ survival were proposed as biomarkers that, if included in wider survival models, could provide a better disease stratification and an improved prognosis definition.