Il cane come modello animale spontaneo di patologie neoplastiche dell'uomo: ene Ataxia-Telangiectasia Mutated (ATM) Nnella predisposizione al cancro ed importanza dei riarrangimanti genici dei geni Ig/TCR per la diagnosi e prognosi delle malattie linfoproliferative

“Naturally occurring cancers in pet dogs and humans share many features, including histological appearance, tumour genetics, molecular targets, biological behaviour and response to conventional therapies. Studying dogs with cancer is likely to provide a valuable perspective that is distinct from that generated by the study of human or rodent cancers alone. The value of this opportunity has been increasingly recognized in the field of cancer research for the identification of cancer-associated genes, the study of environmental risk factors, understanding tumour biology and progression, and, perhaps most importantly, the evaluation and development of novel cancer therapeutics”.(Paoloni and Khanna, 2008) In last years, the author has investigated some molecular features of cancer in dogs. The Thesis is articulated in two main sections. In section 1, the preliminary results of a research project aimed at investigating the role of somatic mutations of Ataxia-Telangiectasia mutated (ATM) gene in predisposing to cancer in boxer dogs, are presented. The canine boxer breed may be considered an unique opportunity to disclose the role of ATM somatic mutation since boxer dogs are known to be dramatically susceptible to cancer and since they may be considered a closed gene pool. Furthermore, dogs share with human the some environment. Overall, the abovementioned features could be considered extremely useful for our purposes. In the section 2, the results of our studies aimed at setting up accurate and sensitive molecular assays for diagnosing and assessing minimal residual disease in lymphoproliferative disorders of dogs, are presented. The results of those molecular assay may be directly translated in the field of Veterinary practice as well as the may be used to improve our objective evaluation of new investigational drugs effectiveness in canine cancer trials.

Investigating the role of single point mutations in the human proteome: a computational study

In the post genomic era with the massive production of biological data the understanding of factors affecting protein stability is one of the most important and challenging tasks for highlighting the role of mutations in relation to human maladies. The problem is at the basis of what is referred to as molecular medicine with the underlying idea that pathologies can be detailed at a molecular level. To this purpose scientific efforts focus on characterising mutations that hamper protein functions and by these affect biological processes at the basis of cell physiology. New techniques have been developed with the aim of detailing single nucleotide polymorphisms (SNPs) at large in all the human chromosomes and by this information in specific databases are exponentially increasing. Eventually mutations that can be found at the DNA level, when occurring in transcribed regions may then lead to mutated proteins and this can be a serious medical problem, largely affecting the phenotype. Bioinformatics tools are urgently needed to cope with the flood of genomic data stored in database and in order to analyse the role of SNPs at the protein level. In principle several experimental and theoretical observations are suggesting that protein stability in the solvent-protein space is responsible of the correct protein functioning. Then mutations that are found disease related during DNA analysis are often assumed to perturb protein stability as well. However so far no extensive analysis at the proteome level has investigated whether this is the case. Also computationally methods have been developed to infer whether a mutation is disease related and independently whether it affects protein stability. Therefore whether the perturbation of protein stability is related to what it is routinely referred to as a disease is still a big question mark. In this work we have tried for the first time to explore the relation among mutations at the protein level and their relevance to diseases with a large-scale computational study of the data from different databases. To this aim in the first part of the thesis for each mutation type we have derived two probabilistic indices (for 141 out of 150 possible SNPs): the perturbing index (Pp), which indicates the probability that a given mutation effects protein stability considering all the “in vitro” thermodynamic data available and the disease index (Pd), which indicates the probability of a mutation to be disease related, given all the mutations that have been clinically associated so far. We find with a robust statistics that the two indexes correlate with the exception of all the mutations that are somatic cancer related. By this each mutation of the 150 can be coded by two values that allow a direct comparison with data base information. Furthermore we also implement computational methods that starting from the protein structure is suited to predict the effect of a mutation on protein stability and find that overpasses a set of other predictors performing the same task. The predictor is based on support vector machines and takes as input protein tertiary structures. We show that the predicted data well correlate with the data from the databases. All our efforts therefore add to the SNP annotation process and more importantly found the relationship among protein stability perturbation and the human variome leading to the diseasome.

Mechanisms Contributing to Tyrosin Kinase Inhibitor Resistance in GISTs: Toward a Personalized Therapy

Gastrointestinal stromal tumors (GISTs) are the most common mesenchymal tumors in the gastrointestinal tract. This work considers the pharmacological response in GIST patients treated with imatinib by two different angles: the genetic and somatic point of view. We analyzed polymorphisms influence on treatment outcome, keeping in consideration SNPs in genes involved in drug transport and folate pathway. Naturally, all these intriguing results cannot be considered as the only main mechanism in imatinib response. GIST mainly depends by oncogenic gain of function mutations in tyrosin kinase receptor genes, KIT or PDGFRA, and the mutational status of these two genes or acquisition of secondary mutation is considered the main player in GIST development and progression. To this purpose we analyzed the secondary mutations to better understand how these are involved in imatinib resistance. In our analysis we considered both imatinib and the second line treatment, sunitinib, in a subset of progressive patients. KIT/PDGFRA mutation analysis is an important tool for physicians, as specific mutations may guide therapeutic choices. Currently, the only adaptations in treatment strategy include imatinib starting dose of 800 mg/daily in KIT exon-9-mutated GISTs. In the attempt to individualize treatment, genetic polymorphisms represent a novelty in the definition of biomarkers of imatinib response in addition to the use of tumor genotype. Accumulating data indicate a contributing role of pharmacokinetics in imatinib efficacy, as well as initial response, time to progression and acquired resistance. At the same time it is becoming evident that genetic host factors may contribute to the observed pharmacokinetic inter-patient variability. Genetic polymorphisms in transporters and metabolism may affect the activity or stability of the encoded enzymes. Thus, integrating pharmacogenetic data of imatinib transporters and metabolizing genes, whose interplay has yet to be fully unraveled, has the potential to provide further insight into imatinib response/resistance mechanisms.