New approaches to open problems in gene expression microarray data

In the past decade, the advent of efficient genome sequencing tools and high-throughput experimental biotechnology has lead to enormous progress in the life science. Among the most important innovations is the microarray tecnology. It allows to quantify the expression for thousands of genes simultaneously by measurin the hybridization from a tissue of interest to probes on a small glass or plastic slide. The characteristics of these data include a fair amount of random noise, a predictor dimension in the thousand, and a sample noise in the dozens. One of the most exciting areas to which microarray technology has been applied is the challenge of deciphering complex disease such as cancer. In these studies, samples are taken from two or more groups of individuals with heterogeneous phenotypes, pathologies, or clinical outcomes. these samples are hybridized to microarrays in an effort to find a small number of genes which are strongly correlated with the group of individuals. Eventhough today methods to analyse the data are welle developed and close to reach a standard organization (through the effort of preposed International project like Microarray Gene Expression Data -MGED- Society [1]) it is not unfrequant to stumble in a clinician's question that do not have a compelling statistical method that could permit to answer it.The contribution of this dissertation in deciphering disease regards the development of new approaches aiming at handle open problems posed by clinicians in handle specific experimental designs. In Chapter 1 starting from a biological necessary introduction, we revise the microarray tecnologies and all the important steps that involve an experiment from the production of the array, to the quality controls ending with preprocessing steps that will be used into the data analysis in the rest of the dissertation. While in Chapter 2 a critical review of standard analysis methods are provided stressing most of problems that In Chapter 3 is introduced a method to adress the issue of unbalanced design of miacroarray experiments. In microarray experiments, experimental design is a crucial starting-point for obtaining reasonable results. In a two-class problem, an equal or similar number of samples it should be collected between the two classes. However in some cases, e.g. rare pathologies, the approach to be taken is less evident. We propose to address this issue by applying a modified version of SAM [2]. MultiSAM consists in a reiterated application of a SAM analysis, comparing the less populated class (LPC) with 1,000 random samplings of the same size from the more populated class (MPC) A list of the differentially expressed genes is generated for each SAM application. After 1,000 reiterations, each single probe given a "score" ranging from 0 to 1,000 based on its recurrence in the 1,000 lists as differentially expressed. The performance of MultiSAM was compared to the performance of SAM and LIMMA [3] over two simulated data sets via beta and exponential distribution. The results of all three algorithms over low- noise data sets seems acceptable However, on a real unbalanced two-channel data set reagardin Chronic Lymphocitic Leukemia, LIMMA finds no significant probe, SAM finds 23 significantly changed probes but cannot separate the two classes, while MultiSAM finds 122 probes with score >300 and separates the data into two clusters by hierarchical clustering. We also report extra-assay validation in terms of differentially expressed genes Although standard algorithms perform well over low-noise simulated data sets, multi-SAM seems to be the only one able to reveal subtle differences in gene expression profiles on real unbalanced data. In Chapter 4 a method to adress similarities evaluation in a three-class prblem by means of Relevance Vector Machine [4] is described. In fact, looking at microarray data in a prognostic and diagnostic clinical framework, not only differences could have a crucial role. In some cases similarities can give useful and, sometimes even more, important information. The goal, given three classes, could be to establish, with a certain level of confidence, if the third one is similar to the first or the second one. In this work we show that Relevance Vector Machine (RVM) [2] could be a possible solutions to the limitation of standard supervised classification. In fact, RVM offers many advantages compared, for example, with his well-known precursor (Support Vector Machine - SVM [3]). Among these advantages, the estimate of posterior probability of class membership represents a key feature to address the similarity issue. This is a highly important, but often overlooked, option of any practical pattern recognition system. We focused on Tumor-Grade-three-class problem, so we have 67 samples of grade I (G1), 54 samples of grade 3 (G3) and 100 samples of grade 2 (G2). The goal is to find a model able to separate G1 from G3, then evaluate the third class G2 as test-set to obtain the probability for samples of G2 to be member of class G1 or class G3. The analysis showed that breast cancer samples of grade II have a molecular profile more similar to breast cancer samples of grade I. Looking at the literature this result have been guessed, but no measure of significance was gived before.

Trasduzione del segnale inositide-dipendente nel carcinoma della mammella

Breast carcinoma, one of the most frequent malignancies in women, is a complex disease in which a number of different factors combine to drive pathogenesis. The biopathological characterization of these tumors is essential to determine their aggressiveness and to find the most appropriate therapy. As in others neoplasms, the deregulation of signal transduction pathways is frequently responsible for conferring selective biological advantages to the tumor. Phosphoinositides play an essential role in diverse cellular functions, their metabolism is highly active, and is tightly controlled. Among the enzymes implicated in this pathway, phospholipase C beta 1 (PLCβ1) is one of the key regulators, both at the cytoplasmic and the nuclear level. The PLCβ1 gene maps onto the short arm of chromosome 20, a region that has been shown to be altered in several solid tumors, including breast cancer. In the present study a FISH approach was used to investigate the genetic alterations of the PLCβ1 gene in various classes of breast cancer which differ in their invasiveness and proliferation status, according to their mitotic index. The overall aim was to find out whether this enzyme could be a suitable prognostic marker for this neoplasm. Our results show that 83% of cases had aneusomies at the 20p12 level, and the most frequent alteration is a gain in this specific locus. Indeed, we found that this amplification is not related to the invasion status since there were no differences in amplified tumor frequencies between in situ and invasive breast cancer. On the contrary, the gain of PLCβ1 was significantly related to the mitotic index (p = 0.001). To verify if the change in genetic dosage influences the expression of PLCβ1 we performed Real Time PCR and Immunohystochemical analysis. Our results confirmed that amplified tumors have higher levels of PLCβ1 mRNA, which is the sum of the two splicing isoforms 1a and 1b. On the other hand, even if protein levels were higher in the majority of cases compared to the nontumoral specimens, there were no significant associations between gain and overexpression. Finally, the significant association between the amplification of PLCβ1 and others important clinicopathological parameters, such as grading and hormonal receptors status, confirmed a correlation of this enzyme with the aggressiveness of breast cancer. This suggests that PLCβ1 has the potential to be a prognostic marker in these tumors. However, further work needs to be carried out to validate these preliminary findings.

Genetic and environmental factors associated with the risk of cognitive decline and dementia

AD is the most common age related neurodegenerative disease in the industrialized world. Clinically AD is defined as a progressing decline of cognitive functions. Neuropathologically, AD is characterized by the aggregation of b-amyloid (Ab) peptide in the form of extracellular senile plaques, and hyperphosphorlylated tau protein in the form of intracellular neurofibrillary tangles. These neuropathological hallmarks are often accompanied by abundant microvascular damage and pronounced inflammation of the affected brain regions. In this thesis we investigated several aspects of AD focusing on the genetic aspect. We confirmed that Alpha 1 antichymotrypsin (ACT), an acute phase protein, was associated to AD subjects, being plasma levels higher in AD cases than controls. In addition, in a GWA study we demonstrated that two different gene, Clusterin and CR1 were strongly associated to AD. A single gene association not explain such a complex disease like AD. The goal should be to created a network of genetic, phenotypic and clinical data associated to AD. We used a new algorithm, the ANNs, aimed to map variables and search for connectivity among variables. We found specific variables associated to AD like cholesterol levels, the presence of variation in HMGCR enzyme and the age. Other factors such as the BMI, the amount of HDL and blood folate levels were also associated with AD. Pathogen infections, above all viral infections, have been previously associated to AD. The hypothesis suggests that virus and in particular herpes virus could enter the brain when an individual becomes older, perhaps because of a decline in the immune system. Our new hypothesis is that the presence of SNPs in our GWA gene study results in a genetic signature that might affect individual brain susceptibility to infection by herpes virus family during aging.

New Synthetic Polyamines as Multi-Target-Directed Ligands for the Treatment of Alzheimer's Disease and Cancer: Design, Synthesis and Biological Evaluation

Alzheimer's disease (AD) and cancer represent two of the main causes of death worldwide. They are complex multifactorial diseases and several biochemical targets have been recognized to play a fundamental role in their development. Basing on their complex nature, a promising therapeutical approach could be represented by the so-called "Multi-Target-Directed Ligand" approach. This new strategy is based on the assumption that a single molecule could hit several targets responsible for the onset and/or progression of the pathology. In particular in AD, most currently prescribed drugs aim to increase the level of acetylcholine in the brain by inhibiting the enzyme acetylcholinesterase (AChE). However, clinical experience shows that AChE inhibition is a palliative treatment, and the simple modulation of a single target does not address AD aetiology. Research into newer and more potent anti-AD agents is thus focused on compounds whose properties go beyond AChE inhibition (such as inhibition of the enzyme β-secretase and inhibition of the aggregation of beta-amyloid). Therefore, the MTDL strategy seems a more appropriate approach for addressing the complexity of AD and may provide new drugs for tackling its multifactorial nature. In this thesis, it is described the design of new MTDLs able to tackle the multifactorial nature of AD. Such new MTDLs designed are less flexible analogues of Caproctamine, one of the first MTDL owing biological properties useful for the AD treatment. These new compounds are able to inhibit the enzymes AChE, beta-secretase and to inhibit both AChE-induced and self-induced beta-amyloid aggregation. In particular, the most potent compound of the series is able to inhibit AChE in subnanomolar range, to inhibit β-secretase in micromolar concentration and to inhibit both AChE-induced and self-induced beta-amyloid aggregation in micromolar concentration. Cancer, as AD, is a very complex pathology and many different therapeutical approaches are currently use for the treatment of such pathology. However, due to its multifactorial nature the MTDL approach could be, in principle, apply also to this pathology. Aim of this thesis has been the development of new molecules owing different structural motifs able to simultaneously interact with some of the multitude of targets responsible for the pathology. The designed compounds displayed cytotoxic activity in different cancer cell lines. In particular, the most potent compounds of the series have been further evaluated and they were able to bind DNA resulting 100-fold more potent than the reference compound Mitonafide. Furthermore, these compounds were able to trigger apoptosis through caspases activation and to inhibit PIN1 (preliminary result). This last protein is a very promising target because it is overexpressed in many human cancers, it functions as critical catalyst for multiple oncogenic pathways and in several cancer cell lines depletion of PIN1 determines arrest of mitosis followed by apoptosis induction. In conclusion, this study may represent a promising starting pint for the development of new MTDLs hopefully useful for cancer and AD treatment.

Human herpes virus and Alzheimer’s disease

Alzheimer’s disease (AD) is a chronic and progressive neurodegenerative disorder and according to the WHO it is estimated that 36 millions of people worldwide currently suffer from AD. Genetic and environmental factors interact in a complex interplay that might affect pathogenic mechanisms leading to age-related neurodegeneration. The hypothesis is that the presence of allelic polymorphisms in selected genes affecting individual brain susceptibility to infection by the herpes virus family during aging, may contribute to neuronal loss, inflammation and amyloid deposition. Herpes virus family show features relevant to AD, since they infect a large proportion of human population, develop a latent form persisting for several years, are difficult to eliminate by immune responses especially when latency has been established and are able to infect neurons. The association between AD and herpes viruses infection has been investigated. In particular the investigation focused on CMV, EBV and HHV-6 in DNA samples from peripheral blood of a large cohort of patients with clinical diagnosis of AD and age matched CTR, from a longitudinal population study, and DNA samples from brain tissue of patients with neuropathological diagnosis of definitive AD. An association between the presence of EBV and HHV-6 DNA from PBL positivity with the cognitive deterioration and progression to AD has been focused. Moreover, IgG plasma levels in CTR and AD to these viruses were tested. CMV and EBV IgG plasma levels were higher in elderly subjects that developed clinical AD at the end of the five year follow up. Our findings support the notion that persistent cycles of latency and reactivation of herpes viruses may contribute to impair systemic immune response and induce altered inflammatory process that in turn affect cognitive decline during aging.

The search for Multiple Myeloma Stem cells: molecular characterization and self-renewal mechanisms involved in the disease persistence

The existence of Multiple Myeloma Stem cells (MMSCs)is supposed to be one of the major causes of MM drug-resistance. However, very little is known about the molecular characteristics of MMSCs, even if some studies suggested that these cells resembles the memory B cells. In order to molecularly characterize MMSCs, we isolated the 138+138- population. For each cell fraction we performed a VDJ rearrangement analysis. The complete set of aberrations were performed by SNP Array 6.0 and HG-U133 Plus 2.0 microarray analyses (Affymetrix). The VDJ rearrangement analyses confirmed the clonal relationship between the 138+ clone and the immature clone. Both BM and PBL 138+ clones showed exactly the same genomic macroalterations. In the BM and PBL 138-19+27+ cell fractions several micro-alterations (range: 1-350 Kb) unique of the memory B cells clone were highlighted. Any micro-alterations detected were located out of any genomic variants region and are presumably associated to the MM pathogenesis, as confirmed by the presence of KRAS, WWOX and XIAP genes among the amplified regions. To get insight into the biology of the clonotypic B cell population, we compared the gene expression profile of 8 MM B cells samples 5 donor B cells vs, thus showing a differential expression of 11480 probes (p-value: <0,05). Among the self-renewal mechanisms, we observed the down-regulation of Hedgehog pathway and the iperactivation of Notch and Wnt signaling. Moreover, these immature cells showed a particular phenotype correlated to resistance to proteasome inhibitors (IRE1α-XBP1: -18.0; -19.96. P<0,05). Data suggested that the MM 138+ clone might resume the end of the complex process of myelomagenesis, whereas the memory B cells have some intriguing micro-alterations and a specific transcriptional program, supporting the idea that these post germinal center cells might be involved in the transforming event that originate and sustain the neoplastic clone.