Perfluoroalkylated substances in food matrices: development of mass spectrometry based analytical methods and preliminary monitoring

Perfluoroalkylated substances are a group of chemicals that have been largely employed during the last 60 years in several applications, widely spreading and accumulating in the environment due to their extreme resistance to degradation. As a consequence, they have been found also in various types of food as well as in drinking water, proving that they can easily reach humans through the diet. The available information concerning their adverse effects on health has recently increased the interest towards these contaminants and highlighted the importance of investigating all the potential sources of human exposure, among which diet was proved to be the most relevant. This need has been underlined by the European Union through Recommendation 2010/161/EU: in this document, Member States were called to monitor their presence of in food, producing accurate estimations of human exposure. The purpose of the research presented in this thesis, which is the result of a partnership between an Italian and a French laboratory, was to develop reliable tools for the analysis of these pollutants in food, to be used for generating data on potentially contaminated matrices. An efficient method based on liquid chromatography-mass spectrometry for the detection of 16 different perfluorinated compounds in milk has been validated in accordance with current European regulation guidelines (2002/657/EC) and is currently under evaluation for ISO 17025 accreditation. The proposed technique was applied to cow, powder and human breast milk samples from Italy and France to produce a preliminary monitoring on the presence of these contaminants. In accordance with the above mentioned European Recommendation, this project led also to the development of a promising technique for the quantification of some precursors of these substances in fish. This method showed extremely satisfying performances in terms of linearity and limits of detection, and will be useful for future surveys.

Lesion detection and classification in breast cancer: evaluation of approaches based on morphological features, tracer kinetic modelling and semi-quantitative parameters in MR functional imaging (DCE-MRI)

The diagnosis, grading and classification of tumours has benefited considerably from the development of DCE-MRI which is now essential to the adequate clinical management of many tumour types due to its capability in detecting active angiogenesis. Several strategies have been proposed for DCE-MRI evaluation. Visual inspection of contrast agent concentration curves vs time is a very simple yet operator dependent procedure, therefore more objective approaches have been developed in order to facilitate comparison between studies. In so called model free approaches, descriptive or heuristic information extracted from time series raw data have been used for tissue classification. The main issue concerning these schemes is that they have not a direct interpretation in terms of physiological properties of the tissues. On the other hand, model based investigations typically involve compartmental tracer kinetic modelling and pixel-by-pixel estimation of kinetic parameters via non-linear regression applied on region of interests opportunely selected by the physician. This approach has the advantage to provide parameters directly related to the pathophysiological properties of the tissue such as vessel permeability, local regional blood flow, extraction fraction, concentration gradient between plasma and extravascular-extracellular space. Anyway, nonlinear modelling is computational demanding and the accuracy of the estimates can be affected by the signal-to-noise ratio and by the initial solutions. The principal aim of this thesis is investigate the use of semi-quantitative and quantitative parameters for segmentation and classification of breast lesion. The objectives can be subdivided as follow: describe the principal techniques to evaluate time intensity curve in DCE-MRI with focus on kinetic model proposed in literature; to evaluate the influence in parametrization choice for a classic bi-compartmental kinetic models; to evaluate the performance of a method for simultaneous tracer kinetic modelling and pixel classification; to evaluate performance of machine learning techniques training for segmentation and classification of breast lesion.

Preclinical development of anti-cancer strategies against human HER-2

HER-2 is a 185 kDa transmembrane receptor tyrosine kinase that belongs to the EGFR family. HER-2 is overexpressed in nearly 25% of human breast cancers and women with this subtype of breast cancer have a worse prognosis and frequently develop metastases. The progressive high number of HER-2-positive breast cancer patients with metastatic spread in the brain (up to half of women) has been attributed to the reduction in mortality, the effectiveness of Trastuzumab in killing metastatic cells in other organs and to its incapability to cross the blood-brain barrier. Apart from full-length-HER-2, a splice variant of HER-2 lacking exon 16 (here referred to as D16) was identified in human HER-2-positive breast cancers. Here, the contribution of HER-2 and D16 to mammary carcinogenesis was investigated in a model transgenic for both genes (F1 model). A dominant role of D16, especially in early stages of tumorigenesis, was suggested and the coexistence of heterogeneous levels of HER-2 and D16 in F1 tumors revealed the undeniable value of F1 strain as preclinical model of HER-2-positive breast cancer, closer resembling the human situation in respect to previous models. The therapeutical efficacy of anti-HER-2 agents, targeting HER-2 receptor (Trastuzumab, Lapatinib, R-LM249) or signaling effectors (Dasatinib, UO126, NVP-BKM120), was investigated in models of local or advanced HER-2-positive breast cancer. In contrast with early studies, data herein collected suggested that the presence of D16 can predict a better response to Trastuzumab and other agents targeting HER-2 receptor or Src activity. Using a multiorgan HER-2-positive metastatic model, the efficacy of NVP-BKM120 (PI3K inhibitor) in blocking the growth of brain metastases and the oncolytic ability of R-LM249 (HER-2-retargeted HSV) to reach and destroy metastatic HER-2-positive cancer cells were shown. Finally, exploiting the definition of “oncoantigen” given to HER-2, the immunopreventive activity of two vaccines on HER-2-positive mammary tumorigenesis was demonstrated.

Small molecules exploiting emerging therapeutic opportunities for breast cancer treatment

Among the different types of breast cancer (BC), the estrogen receptor positive (ER+) subtype, which requires estrogens for its growth and proliferation, is the most common, while triple negative BC, characterized by the absence of ER, progesterone receptor and human epidermal growth factor receptor 2, often leads to poor prognosis. First-line therapies for the treatment of ER+ BC act either by suppressing estrogen production, through the inhibition of aromatase (AR) enzyme, or by blocking estrogen prooncogenic activity, via the modulation/degradation of ERs. The serious side effects and the intrinsic or acquired resistance phenomena that arise with prolonged use of these drugs limit their therapeutic application, stimulating the search for new strategies to face this disease. In this context, the development of dual acting aromatase inhibitors, able to target both the orthosteric and the recently identified allosteric pockets of AR could be an opportunity to fight ER+ BC. Another promising strategy could be the development of multitarget compounds, targeting both AR and ERs. In this scenario, here we designed and synthesized two series of new xanthones or more flexible benzophenones as potential dual acting aromatase inhibitors. Moreover, inspired from tamoxifen metabolites and a literature compound endowed with activity on both AR and ER, different structurally related series of potential multitarget compounds were developed. The biological results showed that some of the new molecules were promising candidates for further development. It was recently observed that the lately discovered histamine H4 receptor is expressed in human breast tissue, displaying a key role in biological processes mediated by histamine such as cell proliferation, senescence, and apoptosis in malignant cells, representing a potential target in triple negative BC. Thus, a broad series of methyl quinazoline sulfonamides, carrying different functional groups on the sulfonamide moiety, were designed and synthesized as potential H4 receptor ligands.