Preclinical studies of the combined effect of anti-MYCN PNA and Retinoic Acid as potential approach to treat Neuroblastoma

Neuroblastoma (NB) is the deadliest cancer in early childhood. Around 25% of patients pre- sent MYCN-amplification (MNA) which is linked to poor prognosis, metastasis, and therapy- resistance. While retinoic acid (RA) is beneficial only for some NB patients, the cause of its resistance is still unknown. Thus, there remains a need for new therapies to treat NB. I show that MYCN-specific inhibition by the antigene oligonucleotide BGA002 in combination with 13-cis RA (BGA002-RA) overcome resistance in MNA-NB cell lines, leading to potent MYCN mRNA expression and protein decrease. Moreover, BGA002-RA reactivated neuron differentiation or led to apoptosis in MNA-NB cell lines, and inhibited invasiveness capacity. Since NB and PI3K/mTOR pathway are strictly related MYCN down-regulation by BGA002 led to mTOR pathway inhibition in MNA-NB, that was strengthened by BGA002-RA. I further analyzed if MYCN silencing may induce autophagy reactivation, and indeed BGA002-RA caused a massive increase in lysosomes and macrovacuoles in MNA-NB cells. In addition, while MYCN is known to induce angiogenesis, BGA002-RA in vivo treatment elim- inated the tumor vascularization in a MNA-NB mice model, and significantly increased the survival. Overall, these results indicate that MYCN modulation mediates the therapeutic efficacy of RA and the development of RA resistance in MNA-NB. Furthermore, by targeting MYCN, we show a cancer-specific way of mTOR pathway inhibition only in MNA-NB, avoiding side effects of targeting mTOR in normal cells. These findings warrant clinical testing of BGA002-RA as a potential strategy to overcome RA resistance in MNA-NB.

Development of new chemical entities to target neuroinflammatory pathways.

Neuroinflammatory pathways are main culprits of neurodegenerative diseases' onset and progression, including Alzheimer’s disease (AD). On this basis, several anti-inflammatory drugs were repurposed in clinical trials. However, they have failed, probably because neuroinflammation is a complex network, still not fully understood. From these evidences, this thesis focused on the design and synthesis of new chemical entities as potential neuroinflammatory drugs or chemical probes. Projects 1 and 2 aimed to multi-target-directed ligand (MTDL) development to target neuroinflammation in AD. Polypharmacology by MTDLs is considered one of the most promising strategies to face the multifactorial nature of neurodegenerative diseases. Particularly, Project 1 took inspiration from a cromolyn-ibuprofen drug combination polypharmacological approach, which was recently investigated in AD clinical trials. Based on that, two cromolyn-(S)-ibuprofen codrug series were designed and synthesized. Parent drugs were combined via linking or fusing strategies in 1:2 or 1:1 ratio, by means of hydrolyzable bonds. Project 2 started from a still ongoing AD clinical trial on investigational drug neflamapimod. It is a selective inhibitor of p38α-MAPK, a kinase strictly involved in neuroinflammatory pathways. On the other side, rasagiline, an anti-Parkinson drug, was also repurposed as AD treatment. Indeed, rasagiline’s propargylamine fragment demonstrated to be responsible not only for the MAO-B selective inhibition, but also for the neuroprotective activity. Thus, to synergistically combine these two effects into single-molecules, a small set of neflamapimod-rasagiline hybrids was developed. In the end BMX, a poorly investigated kinase, which seems to be involved in pro-inflammatory mediator production, was explored for the development of new chemical probes. High-quality chemical probes are a powerful tool in target validation and starting points for the development of new drug candidates. Thus, Project 3 focused on the design and synthesis of two series of optimized BMX covalent inhibitors as selective chemical probes.

Comprehensive characterization of SDH-deficient GIST using NGS data and iPSC models

Gastrointestinal stromal tumors (GIST) are the most common di tumors of the gastrointestinal tract, arising from the interstitial cells of Cajal (ICCs) or their precursors. The vast majority of GISTs (75–85% of GIST) harbor KIT or PDGFRA mutations. A small percentage of GIST (about 10‐15%) do not harbor any of these driver mutations and have historically been called wild-type (WT). Among them, from 20% to 40% show loss of function of the succinate dehydrogenase complex (SDH), also defined as SDH‐deficient GIST. SDH-deficient GISTs display distinctive clinical and pathological features, and can be sporadic or associated with Carney triad or Carney-Stratakis syndrome. These tumors arise most frequently in the stomach with predilection to distal stomach and antrum, have a multi-nodular growth, display a histological epithelioid phenotype, and present frequent lympho-vascular invasion. Occurrence of lymph node metastases and indolent course are representative features of SDH-deficient GISTs. This subset of GIST is known for the immunohistochemical loss of succinate dehydrogenase subunit B (SDHB), which signals the loss of function of the entire SDH-complex. The overall aim of my PhD project consists of the comprehensive characterization of SDH deficient GIST. Throughout the project, clinical, molecular and cellular characterizations were performed using next-generation sequencing technologies (NGS), that has the potential to allow the identification of molecular patterns useful for the diagnosis and development of novel treatments. Moreover, while there are many different cell lines and preclinical models of KIT/PDGFRA mutant GIST, no reliable cell model of SDH-deficient GIST has currently been developed, which could be used for studies on tumor evolution and in vitro assessments of drug response. Therefore, another aim of this project was to develop a pre-clinical model of SDH deficient GIST using the novel technology of induced pluripotent stem cells (iPSC).

Advanced cell culture platforms: methods for drug testing with microfluidics and microstructured devices

Advanced cell cultures are developing rapidly in biomedical research. Nowadays, various approaches and technologies are being used, however, these culturing systems present limitations from increasing complexity, requiring high costs, and not easily customization. We present two versatile and cost-effective methods for developing culturing systems that integrate 3D cell culture and microfluidic platforms. Firstly, for drug screening applications, many high-quality cell spheres of homogeneous size and shape are required. Conventional approaches usually have a dearth of control over the size and geometry of cell spheres and require sample collection and manipulation. To overcome this difficulty, in this study, hundreds of spheroids of several cell lines were generated using multi-well plates that housed our microdevices. Tumor spheroids grow at a uniform rate (in scaffolded or scaffold-free environments) and can be harvested at will. Microscopy imaging are done in real time during or after the culture. After in situ immunostaining, fluorescence imaging can be conducted while keeping the spatial distribution of spheroids in the microwells. Drug effects were successfully observed through viability, growth, and morphologic investigations. Also, we fabricated a microfluidic device suitable for directed and selective cell culture treatments. The microfluidic device was used to reproduce and confirm in vitro investigations carried out using normal culture methods, using a microglia cell line. The device layout and the syringe pump system, entirely designed in our lab, successfully allowed culture growth and medium flow regulation. Solution flows can be finely controlled, allowing treatments and immunofluorescence in one single chamber selectively. To conclude, we propose the development of two culturing platforms (microstructured well devices and in-flow microfluidic chip), which are the result of separate scientific investigations but have the primary goal of performing treatments in a reproducible manner. Our devices shall improve future studies on drug exposure testing, representing adjustable and versatile cell culture systems.

Preclinical evaluation of a MYCN-specific inhibitor for the treatment of small cell lung cancer

Small cell lung cancer (SCLC) is the most aggressive form of lung cancer, characterized by rapid growth, early metastasis and acquired drug resistance. SCLC is usually sensitive to initial treatment, however, most patients relapse within few months; thus more effective therapies are urgently needed. Key genetic alterations very frequently observed in SCLC include loss of TP53 and RB1 and mutations in the MYC family genes (MYC, MYCL or MYCN). One of them is amplified and overexpressed in a mutually exclusive manner and represents the most prominent activating oncogene alteration in this malignancy. In particular, MYCN amplification is associated with tumor progression, treatment failure and poor prognosis. Given the role of MYCN in SCLC and its restricted expression profile, MYCN represents a promising therapeutic target; although it is considered undruggable by traditional approaches. An innovative approach to target the oncogene concerns specific MYCN expression inhibition, acting directly at the level of DNA, through an antigene peptide nucleic acid (agPNA) oligonucleotide, called BGA002. This thesis focused on the study of BGA002, as a possible targeted therapeutic strategy for the treatment of MYCN-related SCLC. In this context, BGA002 proved to be a specific and highly effective inhibitor. Furthermore, MYCN silencing induced alterations in many downstream pathways and led to apoptosis, in concomitance with autophagy reactivation. Moreover, systemic administration of BGA002 was effective in vivo as well, significantly increasing survival in MNA mouse models, even in the scenario of multidrug-resistance. In addition, BGA002 treatment successfully reduced N-Myc protein expression and, more importantly, caused a massive diminishment in tumor vascularization in the multidrug-resistant model. Overall, these results proved that MYCN inhibition by BGA002 may represent a new promising precision medicine approach, to treat MYCN-related SCLC.

Development of effect-based bio-chemiluminescent cell bioassays for nutraceutical and biomedical applications

The final goal of the bioassay developed during the first two years of my Ph.D. was its application for the screening of antioxidant activity of nutraceuticals and for monitoring the intracellular H2O2 production in peripheral blood mononuclear cells (PBMCs) from hypercholesterolemic subjects before and after two months treatment with Evolocumab, a new generation LDL-cholesterol lowering drug. Moreover, a recombinant bioluminescent protein was developed during the last year using the Baculovirus expression system in insect cells. In particular, the protein combines the extracellular domain (ECD) of the Notch high affinity mutated form of one of the selective Notch ligands defined as Jagged 1 (Jag1) with a red emitting firefly luciferase since a pivotal role of “aberrant” Notch signaling activation in colorectal cancer (CRC) was reported. The probe was validated and characterized in terms of analytical performance and through imaging experiments, in order to understand if Jagged1-FLuc binding correlates with a Notch signaling overexpression and activation in CRC progression.

New chemical modalities for leishmaniasis drug discovery

Leishmaniasis is one of the major parasitic diseases among neglected tropical diseases with a high rate of morbidity and mortality. Human migration and climate change have spread the disease from limited endemic areas all over the world, also reaching regions in Southern Europe, and causing significant health and economic burden. The currently available treatments are far from ideal due to host toxicity, elevated cost, and increasing rates of drug resistance. Safer and more effective drugs are thus urgently required. Nevertheless, the identification of new chemical entities for leishmaniasis has proven to be incredibly hard and exacerbated by the scarcity of well-validated targets. Trypanothione reductase (TR) represents one robustly validated target in Leishmania that fulfils most of the requirements for a good drug target. However, due to the large and featureless active site, TR is considered extremely challenging and almost undruggable by small molecules. This scenario advocates the development of new chemical entities by unlocking new modalities for leishmaniasis drug discovery. The classical toolbox for drug discovery has enormously expanded in the last decade, and medicinal chemists can now strategize across a variety of new chemical modalities and a vast chemical space, to efficiently modulate challenging targets and provide effective treatments. Beyond others, Targeted p Protein Degradation (TPD) is an emerging strategy that uses small molecules to hijack endogenous proteolysis systems to degrade disease-relevant proteins and thus reduce their abundance in the cell. Based on these considerations, this thesis aimed to develop new strategies for leishmaniasis drug discovery while embracing novel chemical modalities and navigating the chemical space by chasing unprecedented chemotypes. This has been achieved by four complementary projects. We believe that these next-generation chemical modalities for leishmaniasis will play an important role in what was previously thought to be a drug discovery landscape dominated by small molecules.

Development of unsupervised learning methods with applications to life sciences data

Machine Learning makes computers capable of performing tasks typically requiring human intelligence. A domain where it is having a considerable impact is the life sciences, allowing to devise new biological analysis protocols, develop patients’ treatments efficiently and faster, and reduce healthcare costs. This Thesis work presents new Machine Learning methods and pipelines for the life sciences focusing on the unsupervised field. At a methodological level, two methods are presented. The first is an “Ab Initio Local Principal Path” and it is a revised and improved version of a pre-existing algorithm in the manifold learning realm. The second contribution is an improvement over the Import Vector Domain Description (one-class learning) through the Kullback-Leibler divergence. It hybridizes kernel methods to Deep Learning obtaining a scalable solution, an improved probabilistic model, and state-of-the-art performances. Both methods are tested through several experiments, with a central focus on their relevance in life sciences. Results show that they improve the performances achieved by their previous versions. At the applicative level, two pipelines are presented. The first one is for the analysis of RNA-Seq datasets, both transcriptomic and single-cell data, and is aimed at identifying genes that may be involved in biological processes (e.g., the transition of tissues from normal to cancer). In this project, an R package is released on CRAN to make the pipeline accessible to the bioinformatic Community through high-level APIs. The second pipeline is in the drug discovery domain and is useful for identifying druggable pockets, namely regions of a protein with a high probability of accepting a small molecule (a drug). Both these pipelines achieve remarkable results. Lastly, a detour application is developed to identify the strengths/limitations of the “Principal Path” algorithm by analyzing Convolutional Neural Networks induced vector spaces. This application is conducted in the music and visual arts domains.

Network analysis and machine learning assist drug repurposing and safety assessment in neurological diseases

In recent decades, two prominent trends have influenced the data modeling field, namely network analysis and machine learning. This thesis explores the practical applications of these techniques within the domain of drug research, unveiling their multifaceted potential for advancing our comprehension of complex biological systems. The research undertaken during this PhD program is situated at the intersection of network theory, computational methods, and drug research. Across six projects presented herein, there is a gradual increase in model complexity. These projects traverse a diverse range of topics, with a specific emphasis on drug repurposing and safety in the context of neurological diseases. The aim of these projects is to leverage existing biomedical knowledge to develop innovative approaches that bolster drug research. The investigations have produced practical solutions, not only providing insights into the intricacies of biological systems, but also allowing the creation of valuable tools for their analysis. In short, the achievements are: • A novel computational algorithm to identify adverse events specific to fixed-dose drug combinations. • A web application that tracks the clinical drug research response to SARS-CoV-2. • A Python package for differential gene expression analysis and the identification of key regulatory "switch genes". • The identification of pivotal events causing drug-induced impulse control disorders linked to specific medications. • An automated pipeline for discovering potential drug repurposing opportunities. • The creation of a comprehensive knowledge graph and development of a graph machine learning model for predictions. Collectively, these projects illustrate diverse applications of data science and network-based methodologies, highlighting the profound impact they can have in supporting drug research activities.

In Vitro And In Vivo Anti-angiogenic Effects Of Hydroxyurea.

Hydroxyurea (HU), or hydroxycarbamide, is used for the treatment of some myeloproliferative and neoplastic diseases, and is currently the only drug approved by the FDA for use in sickle cell disease (SCD). Despite the relative success of HU therapy for SCD, a genetic disorder of the hemoglobin β chain that results in red-cell sickling, hemolysis, vascular inflammation and recurrent vasoocclusion, the exact mechanisms by which HU actuates remain unclear. We hypothesized that HU may modulate endothelial angiogenic processes, with important consequences for vascular inflammation. The effects of HU (50-200 μM; 17-24 h) on endothelial cell functions associated with key steps of angiogenesis were evaluated using human umbilical vein endothelial cell (HUVEC) cultures. Expression profiles of the HIF1A gene and the miRNAs 221 and 222, involved in endothelial function, were also determined in HUVECs following HU administration and the direct in vivo antiangiogenic effects of HU were assessed using a mouse Matrigel-plug neovascularization assay. Following incubation with HU, HUVECs exhibited high cell viability, but displayed a significant 75% inhibition in the rate of capillary-like-structure formation, and significant decreases in proliferative and invasive capacities. Furthermore, HU significantly decreased HIF1A expression, and induced the expression of miRNA 221, while downregulating miRNA 222. In vivo, HU reduced vascular endothelial growth factor (VEGF)-induced vascular development in Matrigel implants over 7 days. Findings indicate that HU is able to inhibit vessel assembly, a crucial angiogenic process, both in vitro and in vivo, and suggest that some of HU's therapeutic effects may occur through novel vascular mechanisms.

[the Use Of Fish On Buccal Smear To Investigate Mosaicism With A 45,x Cell Line: Study On Healthy Men And Patients With Disorders Of Sex Development].

To verify whether fluorescence in situ hybridization (FISH) of cells from the buccal epithelium could be employed to detect cryptomosaicism with a 45,X lineage in 46,XY patients. Samples of nineteen 46,XY healthy young men and five patients with disorders of sex development (DSD), four 45,X/46,XY and one 46,XY were used. FISH analysis with X and Y specific probes on interphase nuclei from blood lymphocytes and buccal epithelium were analyzed to investigate the proportion of nuclei containing only the signal of the X chromosome. The frequency of nuclei containing only the X signal in the two tissues of healthy men did not differ (p = 0.69). In all patients with DSD this frequency was significantly higher, and there was no difference between the two tissues (p = 0.38), either. Investigation of mosaicism with a 45,X cell line in patients with 46,XY DSD or sterility can be done by FISH directly using cells from the buccal epithelium.

The Influence Of The Environment On The Development Of Thyroid Tumors: A New Appraisal.

Most epidemiological studies concerning differentiated thyroid cancers (DTC) indicate an increasing incidence over the last two decades. This increase might be partially explained by the better access to health services worldwide, but clinicopathological analyses do not fully support this hypothesis, indicating that there are carcinogenetic factors behind this noticeable increasing incidence. Although we have undoubtedly understood the biology and molecular pathways underlying thyroid carcinogenesis in a better way, we have made very little progresses in identifying a risk profile for DTC, and our knowledge of risk factors is very similar to what we knew 30-40 years ago. In addition to ionizing radiation exposure, the most documented and established risk factor for DTC, we also investigated the role of other factors, including eating habits, tobacco smoking, living in a volcanic area, xenobiotics, and viruses, which could be involved in thyroid carcinogenesis, thus, contributing to the increase in DTC incidence rates observed.

Iis--integrated Interactome System: A Web-based Platform For The Annotation, Analysis And Visualization Of Protein-metabolite-gene-drug Interactions By Integrating A Variety Of Data Sources And Tools.

High-throughput screening of physical, genetic and chemical-genetic interactions brings important perspectives in the Systems Biology field, as the analysis of these interactions provides new insights into protein/gene function, cellular metabolic variations and the validation of therapeutic targets and drug design. However, such analysis depends on a pipeline connecting different tools that can automatically integrate data from diverse sources and result in a more comprehensive dataset that can be properly interpreted. We describe here the Integrated Interactome System (IIS), an integrative platform with a web-based interface for the annotation, analysis and visualization of the interaction profiles of proteins/genes, metabolites and drugs of interest. IIS works in four connected modules: (i) Submission module, which receives raw data derived from Sanger sequencing (e.g. two-hybrid system); (ii) Search module, which enables the user to search for the processed reads to be assembled into contigs/singlets, or for lists of proteins/genes, metabolites and drugs of interest, and add them to the project; (iii) Annotation module, which assigns annotations from several databases for the contigs/singlets or lists of proteins/genes, generating tables with automatic annotation that can be manually curated; and (iv) Interactome module, which maps the contigs/singlets or the uploaded lists to entries in our integrated database, building networks that gather novel identified interactions, protein and metabolite expression/concentration levels, subcellular localization and computed topological metrics, GO biological processes and KEGG pathways enrichment. This module generates a XGMML file that can be imported into Cytoscape or be visualized directly on the web. We have developed IIS by the integration of diverse databases following the need of appropriate tools for a systematic analysis of physical, genetic and chemical-genetic interactions. IIS was validated with yeast two-hybrid, proteomics and metabolomics datasets, but it is also extendable to other datasets. IIS is freely available online at: http://www.lge.ibi.unicamp.br/lnbio/IIS/.

Study Of The Homogeneity Of Drug Loaded In Polymeric Films Using Near-infrared Chemical Imaging And Split-plot Design.

Split-plot design (SPD) and near-infrared chemical imaging were used to study the homogeneity of the drug paracetamol loaded in films and prepared from mixtures of the biocompatible polymers hydroxypropyl methylcellulose, polyvinylpyrrolidone, and polyethyleneglycol. The study was split into two parts: a partial least-squares (PLS) model was developed for a pixel-to-pixel quantification of the drug loaded into films. Afterwards, a SPD was developed to study the influence of the polymeric composition of films and the two process conditions related to their preparation (percentage of the drug in the formulations and curing temperature) on the homogeneity of the drug dispersed in the polymeric matrix. Chemical images of each formulation of the SPD were obtained by pixel-to-pixel predictions of the drug using the PLS model of the first part, and macropixel analyses were performed for each image to obtain the y-responses (homogeneity parameter). The design was modeled using PLS regression, allowing only the most relevant factors to remain in the final model. The interpretation of the SPD was enhanced by utilizing the orthogonal PLS algorithm, where the y-orthogonal variations in the design were separated from the y-correlated variation.

Development And Shelf-life Determination Of Pasteurized, Microfiltered, Lactose Hydrolyzed Skim Milk.

The segment of the world population showing permanent or temporary lactose intolerance is quite significant. Because milk is a widely consumed food with an high nutritional value, technological alternatives have been sought to overcome this dilemma. Microfiltration combined with pasteurization can not only extend the shelf life of milk but can also maintain the sensory, functional, and nutritional properties of the product. This studied developed a pasteurized, microfiltered, lactose hydrolyzed (delactosed) skim milk (PMLHSM). Hydrolysis was performed using β-galactosidase at a concentration of 0.4mL/L and incubation for approximately 21h at 10±1°C. During these procedures, the degree of hydrolysis obtained (>90%) was accompanied by evaluation of freezing point depression, and the remaining quantity of lactose was confirmed by HPLC. Milk was processed using a microfiltration pilot unit equipped with uniform transmembrane pressure (UTP) ceramic membranes with a mean pore size of 1.4 μm and UTP of 60 kPa. The product was submitted to physicochemical, microbiological, and sensory evaluations, and its shelf life was estimated. Microfiltration reduced the aerobic mesophilic count by more than 4 log cycles. We were able to produce high-quality PMLHSM with a shelf life of 21 to 27d when stored at 5±1°C in terms of sensory analysis and proteolysis index and a shelf life of 50d in regard to total aerobic mesophile count and titratable acidity.