XBP1s levels are implicated in the biology and outcome of myeloma mediating different clinical outcomes to thalidomide-based treatments.

Immunoglobulin production by myeloma plasma cells depends on the unfolded protein response for protein production and folding. Recent studies have highlighted the importance of IRE1alpha and X box binding protein 1 (XBP1), key members of this pathway, in normal B-plasma cell development. We have determined the gene expression levels of IRE1alpha, XBP1, XBP1UNSPLICED (XBP1u), and XBP1SPLICED (XBP1s) in a series of patients with myeloma and correlated findings with clinical outcome. We show that IRE1alpha and XBP1 are highly expressed and that patients with low XBP1s/u ratios have a significantly better overall survival. XBP1s is an independent prognostic marker and can be used with beta2 microglobulin and t(4;14) to identify a group of patients with a poor outcome. Furthermore, we show the beneficial therapeutic effects of thalidomide in patients with low XBP1s/u ratios. This study highlights the importance of XBP1 in myeloma and its significance as an independent prognostic marker and as a predictor of thalidomide response.

Molecular Typing, Virulence Traits and Antimicrobial Resistance of Diabetic Foot Staphylococci

Diabetes mellitus is a major chronic disease that continues to increase significantly. One of the most important and costly complications of diabetes are foot infections that may be colonized by pathogenic and antimicrobial resistant bacteria, harboring several virulence factors, that could impair its successful treatment. Staphylococcus aureus is one of the most prevalent isolate in diabetic foot infections, together with aerobes and anaerobes.

CpxR activates MexAB-OprM efflux pump expression and enhances antibiotic resistance in both laboratory and clinical nalB-type isolates of Pseudomonas aeruginosa

Resistance-Nodulation-Division (RND) efflux pumps are responsible for multidrug resistance in Pseudomonas aeruginosa. In this study, we demonstrate that CpxR, previously identified as a regulator of the cell envelope stress response in Escherichia coli, is directly involved in activation of expression of RND efflux pump MexAB-OprM in P. aeruginosa. A conserved CpxR binding site was identified upstream of the mexA promoter in all genome-sequenced P. aeruginosa strains. CpxR is required to enhance mexAB-oprM expression and drug resistance, in the absence of repressor MexR, in P. aeruginosa strains PA14. As defective mexR is a genetic trait associated with the clinical emergence of nalB-type multidrug resistance in P. aeruginosa during antibiotic treatment, we investigated the involvement of CpxR in regulating multidrug resistance among resistant isolates generated in the laboratory via antibiotic treatment and collected in clinical settings. CpxR is required to activate expression of mexAB-oprM and enhances drug resistance, in the absence or presence of MexR, in ofloxacin-cefsulodin-resistant isolates generated in the laboratory. Furthermore, CpxR was also important in the mexR-defective clinical isolates. The newly identified regulatory linkage between CpxR and the MexAB-OprM efflux pump highlights the presence of a complex regulatory network modulating multidrug resistance in P. aeruginosa.

Bacterial biofilms, antibiotic resistance and healthcare-associated infections: a dangerous connection

In 2012, were estimated 6.7 million cases of healthcare-associated infections (HAI) either in long-term care facilities or acute-care hospitals from which result 37,000 deaths configuring a serious public health problem. The etiological agents are diverse and often resistant to antimicrobial drugs. One of the mechanisms responsible for the emergence of drug resistance is biofilm assembly. Biofilms are defined as thin layers of microorganisms adhering to the surface of a structure, which may be organic or inorganic, together with the polymers that they secrete. They are dynamic structures which experience different stages of organization with the ageing and are linked to an increase in bacterial resistance to host defense mechanisms, antibiotics, sterilization procedures other than autoclaving, persistence in water distribution systems and other surfaces. The understanding of bacteria organization within the biofilm and the identification of differences between planktonic and sessile forms of bacteria will be a step forward to fight HAIs.

DATA DRIVEN APPROACHES TO IDENTIFY DETERMINANTS OF HEART DISEASES AND CANCER RESISTANCE

Cancer and cardio-vascular diseases are the leading causes of death world-wide. Caused by systemic genetic and molecular disruptions in cells, these disorders are the manifestation of profound disturbance of normal cellular homeostasis. People suffering or at high risk for these disorders need early diagnosis and personalized therapeutic intervention. Successful implementation of such clinical measures can significantly improve global health. However, development of effective therapies is hindered by the challenges in identifying genetic and molecular determinants of the onset of diseases; and in cases where therapies already exist, the main challenge is to identify molecular determinants that drive resistance to the therapies. Due to the progress in sequencing technologies, the access to a large genome-wide biological data is now extended far beyond few experimental labs to the global research community. The unprecedented availability of the data has revolutionized the capabilities of computational researchers, enabling them to collaboratively address the long standing problems from many different perspectives. Likewise, this thesis tackles the two main public health related challenges using data driven approaches. Numerous association studies have been proposed to identify genomic variants that determine disease. However, their clinical utility remains limited due to their inability to distinguish causal variants from associated variants. In the presented thesis, we first propose a simple scheme that improves association studies in supervised fashion and has shown its applicability in identifying genomic regulatory variants associated with hypertension. Next, we propose a coupled Bayesian regression approach -- eQTeL, which leverages epigenetic data to estimate regulatory and gene interaction potential, and identifies combinations of regulatory genomic variants that explain the gene expression variance. On human heart data, eQTeL not only explains a significantly greater proportion of expression variance in samples, but also predicts gene expression more accurately than other methods. We demonstrate that eQTeL accurately detects causal regulatory SNPs by simulation, particularly those with small effect sizes. Using various functional data, we show that SNPs detected by eQTeL are enriched for allele-specific protein binding and histone modifications, which potentially disrupt binding of core cardiac transcription factors and are spatially proximal to their target. eQTeL SNPs capture a substantial proportion of genetic determinants of expression variance and we estimate that 58% of these SNPs are putatively causal. The challenge of identifying molecular determinants of cancer resistance so far could only be dealt with labor intensive and costly experimental studies, and in case of experimental drugs such studies are infeasible. Here we take a fundamentally different data driven approach to understand the evolving landscape of emerging resistance. We introduce a novel class of genetic interactions termed synthetic rescues (SR) in cancer, which denotes a functional interaction between two genes where a change in the activity of one vulnerable gene (which may be a target of a cancer drug) is lethal, but subsequently altered activity of its partner rescuer gene restores cell viability. Next we describe a comprehensive computational framework --termed INCISOR-- for identifying SR underlying cancer resistance. Applying INCISOR to mine The Cancer Genome Atlas (TCGA), a large collection of cancer patient data, we identified the first pan-cancer SR networks, composed of interactions common to many cancer types. We experimentally test and validate a subset of these interactions involving the master regulator gene mTOR. We find that rescuer genes become increasingly activated as breast cancer progresses, testifying to pervasive ongoing rescue processes. We show that SRs can be utilized to successfully predict patients' survival and response to the majority of current cancer drugs, and importantly, for predicting the emergence of drug resistance from the initial tumor biopsy. Our analysis suggests a potential new strategy for enhancing the effectiveness of existing cancer therapies by targeting their rescuer genes to counteract resistance. The thesis provides statistical frameworks that can harness ever increasing high throughput genomic data to address challenges in determining the molecular underpinnings of hypertension, cardiovascular disease and cancer resistance. We discover novel molecular mechanistic insights that will advance the progress in early disease prevention and personalized therapeutics. Our analyses sheds light on the fundamental biological understanding of gene regulation and interaction, and opens up exciting avenues of translational applications in risk prediction and therapeutics.

A molecular platform for the diagnosis of multidrug-resistant and pre-extensively drug-resistant tuberculosis based on single nucleotide polymorphism mutations present in Colombian isolates of Mycobacterium tuberculosis

Developing a fast, inexpensive, and specific test that reflects the mutations present in Mycobacterium tuberculosis isolates according to geographic region is the main challenge for drug-resistant tuberculosis (TB) control. The objective of this study was to develop a molecular platform to make a rapid diagnosis of multidrug-resistant (MDR) and extensively drug-resistant TB based on single nucleotide polymorphism (SNP) mutations present in the rpoB, katG, inhA, ahpC, and gyrA genes from Colombian M. tuberculosis isolates. The amplification and sequencing of each target gene was performed. Capture oligonucleotides, which were tested before being used with isolates to assess the performance, were designed for wild type and mutated codons, and the platform was standardised based on the reverse hybridisation principle. This method was tested on DNA samples extracted from clinical isolates from 160 Colombian patients who were previously phenotypically and genotypically characterised as having susceptible or MDR M. tuberculosis. For our method, the kappa index of the sequencing results was 0,966, 0,825, 0,766, 0,740, and 0,625 for rpoB, katG, inhA, ahpC, and gyrA, respectively. Sensitivity and specificity were ranked between 90-100% compared with those of phenotypic drug susceptibility testing. Our assay helps to pave the way for implementation locally and for specifically adapted methods that can simultaneously detect drug resistance mutations to first and second-line drugs within a few hours.

Sub-epidemics explain localized high prevalence of reduced susceptibility to Rilpivirine in treatment-naive HIV-1-infected patients: subtype and geographic compartmentalization of baseline resistance mutations

This Open Access article is distributed under the terms of the Creative Commons Attribution Noncommercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.

Pharmacists’ knowledge and perception of topical antibacterial drug dispensing in community pharmacy setting in Kedah, Malaysia

Purpose: To assess Pharmacists’ Perceptions and Experiences of Topical Antibacterial Drug Dispensing in Community Pharmacy Setting in Kedah State, Malaysia in order to minimize drug resistance issues. Methods: A cross-sectional study involving a pre-validated questionnaire was conducted in community pharmacies within Kedah State, Malaysia. Descriptive statistics and Spearman’s correlation coefficient were used for data analysis. The collected were analysed using statistical package for social sciences (SPSS) version 18.0. Results: The result shows that, 53.4 % of CPs in Kedah State perceived that topical antibacterial is not necessary for every topical bacterial infection. Fusidic acid was the most frequently dispensed topical antibacterial drug while superficial wound was reported to be the most frequently encountered topical bacterial infection. CPs (12.60 %) encountered antibacterial resistance cases but none reported them. The drug that had resistance issue was neomycin. Conclusion: CPs in Kedah State, Malaysia generally have the right perceptions on the dispensing of topical antibacterial drugs. However, their knowledge on the rational use of topical antibacterial drugs and vigilance on antibacterial resistance issue need improvement.

Bioenergetics of cancer cells in anoxia and role of the miRNAs in melanoma resistance to targeted therapies

Tumours are characterized by a metabolic rewiring that helps transformed cells to survive in harsh conditions. The endogenous inhibitor of the ATP-synthase IF1 is overexpressed in several tumours and it has been proposed to drive metabolic adaptation. In ischemic normal-cells, IF1 acts limiting the ATP consumption by the reverse activity of the ATP-synthase, activated by ΔΨm collapse. Conversely, IF1 role in cancer cells is still unclear. It has been proposed that IF1 favours cancer survival by preventing energy dissipation in low oxygen availability, a frequent condition in solid tumours. Our previous data proved that in cancer cells hypoxia does not abolish ΔΨm, avoiding the ATP-synthase reversal and IF1 activation. In this study, we investigated the bioenergetics of cancer cells in conditions mimicking anoxia to evaluate the possible role of IF1. Data obtained indicate that also in cancer cells the ΔΨm collapse induces the ATP-synthase reversal and its inhibition by IF1. Moreover, we demonstrated that upon uncoupling conditions, IF1 favours cancer cells growth preserving ATP levels and energy charge. We also showed that in these conditions IF1 favours the mitochondrial mass renewal, a mechanism we proposed driving apoptosis-resistance. Cancer adaptability is also associated with the onset of therapy resistance, the major challenge for melanoma treatment. Recent studies demonstrated that miRNAs dysregulation drive melanoma progression and drug-resistance by regulating tumour-suppressor and oncogenes. In this context, we attempted to identify and characterize miRNAs driving resistance to vemurafenib in patient-derived metastatic melanoma cells BRAFV600E-mutated. Our results highlighted that several oncogenic pathways are altered in resistant cells, indicating the complexity of both drug-resistance phenomena and miRNAs action. Profiling analysis identified a group of dysregulated miRNAs conserved in vemurafenib-resistance cells from distinct patients, suggesting that they ubiquitously drive drug-resistance. Functional studies performed with a first miRNA confirmed its pivotal role in resistance towards vemurafenib.

TAZ role in lung cancer: resistance to BET inhibitors and functional interaction with lncRNA

Despite extensive research and introduction of innovative therapy, lung cancer prognosis remains poor, with a five years survival of only 17%. The success of pharmacological treatment is often impaired by drug resistance. Thus, the characterization of response mechanisms to anti-cancer compounds and of the molecular mechanisms supporting lung cancer aggressiveness are crucial for patient’s management. In the first part of this thesis, we characterized the molecular mechanism behind resistance of lung cancer cells to the Inhibitors of the Bromodomain and Extraterminal domain containing Proteins (BETi). Through a CRISPR/Cas9 screening we identified three Hippo Pathway members, LATS2, TAOK1 and NF2 as genes implicated in susceptibility to BETi. These genes confer sensitivity to BETi inhibiting TAZ activity. Conversely, TAZ overexpression increases resistance to BETi. We also displayed that BETi downregulate both YAP, TAZ and TEADs expression in several cancer cell lines, implying a novel BETi-dependent cytotoxic mechanism. In the second part of this work, we attempted to characterize the crosstalk between the TAZ gene and its cognate antisense long-non coding RNA (lncRNA) TAZ-AS202 in lung tumorigenesis. As for TAZ downregulation, TAZ-AS202 silencing impairs NSCLC cells proliferation, migration and invasion, suggesting a pro-tumorigenic function for this lncRNA during lung tumorigenesis. TAZ-AS202 regulates TAZ target genes without altering TAZ expression or localization. This finding implies an uncovered functional cooperation between TAZ and TAZ-AS202. Moreover, we found that the EPH-ephrin signaling receptor EPHB2 is a downstream effector affected by both TAZ and TAZ-AS202 silencing. EPHB2 downregulation significantly attenuates cells proliferation, migration and invasion, suggesting that, at least in part, TAZ-AS202 and TAZ pro-oncogenic activity depends on EPH-ephrin signaling final deregulation. Finally, we started to dissect the mechanism underlying the TAZ-AS202 regulatory activity on EPHB2 in lung cancer, which may involve the existence of an intermediate transcription factor and is the object of our ongoing research.

The human gut microbiome in disease: Role in chemotherapy treatments and relationship with clinical outcomes

The gut microbiome (GM) is a plastic entity, capable of adapting in response to intrinsic and extrinsic factors. However, several circumstances can disrupt this homeostatic balance, forcing the GM to shift from a health-associated mutualistic configuration to a disease-associated profile. Nowadays, a new frontier of microbiome research is understanding the GM role in chemo-immunotherapies and clinical outcomes. Here, the role of the genotoxin‐producing pathogen Salmonella in colorectal carcinogenesis was characterized by in-vitro models. A synergistic effect of Salmonella and the CRC-associated mutation (APC gene) promoted a tumorigenic microenvironment by increasing cellular genomic instability. Subsequently, the GM involvement in anti-cancer therapies was investigated via next-generation sequencing in different patient cohorts. The GM trajectory during treatments was characterized for women with epithelial ovarian cancer and pediatric patients undergoing hematopoietic stem cell transplantation (HSCT). The results highlighted the loss of GM homeostasis, with diversity reduction, decrease in health-associated microorganisms and pathobiont bloom. Interestingly, a distinctive GM profile was identified in ovarian cancer patients with a poor response to chemotherapy compared to patients in remission. Moreover, maintenance of GM homeostasis through enteral feeding in pediatric HSCT patients highlighted a better prognosis, with reduced risk of clinical complications. In this context, the gut resistome – the pattern of GM antibiotic-resistance genes (ARGs) – was evaluated longitudinally in HSCT patients. The results showed new acquisitions and consolidation of ARGs already present in patients developing clinical complications. Antibiotic exposure was also evaluated in infants under low-dose antibiotic prophylaxis for vesico-ureteral reflux showing an impairment of the GM configuration with possible long-term health implications. Dramatic GM dysbiosis was finally observed in critically ill patients with COVID-19 (undergoing multiple drug therapies) and correlated with increased risk of bloodstream infection. All these findings pointed out the importance of maintaining GM homeostasis during chemotherapy treatments for improving patients’ clinical outcomes.

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.

Anticancer drug discovery using artificial intelligence: an application in pharmacological activity prediction

Hematological cancers are a heterogeneous family of diseases that can be divided into leukemias, lymphomas, and myelomas, often called “liquid tumors”. Since they cannot be surgically removable, chemotherapy represents the mainstay of their treatment. However, it still faces several challenges like drug resistance and low response rate, and the need for new anticancer agents is compelling. The drug discovery process is long-term, costly, and prone to high failure rates. With the rapid expansion of biological and chemical "big data", some computational techniques such as machine learning tools have been increasingly employed to speed up and economize the whole process. Machine learning algorithms can create complex models with the aim to determine the biological activity of compounds against several targets, based on their chemical properties. These models are defined as multi-target Quantitative Structure-Activity Relationship (mt-QSAR) and can be used to virtually screen small and large chemical libraries for the identification of new molecules with anticancer activity. The aim of my Ph.D. project was to employ machine learning techniques to build an mt-QSAR classification model for the prediction of cytotoxic drugs simultaneously active against 43 hematological cancer cell lines. For this purpose, first, I constructed a large and diversified dataset of molecules extracted from the ChEMBL database. Then, I compared the performance of different ML classification algorithms, until Random Forest was identified as the one returning the best predictions. Finally, I used different approaches to maximize the performance of the model, which achieved an accuracy of 88% by correctly classifying 93% of inactive molecules and 72% of active molecules in a validation set. This model was further applied to the virtual screening of a small dataset of molecules tested in our laboratory, where it showed 100% accuracy in correctly classifying all molecules. This result is confirmed by our previous in vitro experiments.

Tadalafil-induced Improvement In Left Ventricular Diastolic Function In Resistant Hypertension.

Left ventricular hypertrophy and diastolic dysfunction (LVDD) remain highly frequent markers of cardiac damage and risk of progression to symptomatic heart failure, especially in resistant hypertension (RHTN). We have previously demonstrated that administration of sildenafil in hypertensive rats improves LVDD, restoring phosphodiesterase type 5 (PDE-5) inhibition in cardiac myocytes. We hypothesized that the long-acting PDE-5 inhibitor tadalafil may be clinically useful in improving LVDD in RHTN independently of blood pressure (BP) reduction. A single blinded, placebo-controlled, crossover study enrolled 19 patients with both RHTN and LVDD. Firstly, subjects received tadalafil (20 mg) for 14 days and after a 2-week washout period, they received placebo orally for 14 days. Patients were evaluated by office BP and ambulatory BP monitoring (ABPM), endothelial function (FMD), echocardiography, plasma brain natriuretic peptide (BNP-32), cyclic guanosine monophosphate (cGMP) and nitrite levels. No significant differences were detected in BP measurements. Remarkably, at least four echocardiographic parameters related with diastolic function improved accompanied by decrease in BNP-32 in tadalafil use. Although increasing cGMP, tadalafil did not change endothelial function or nitrites. There were no changes in those parameters after placebo. The current findings suggest that tadalafil improves LV relaxation through direct effects PDE-5-mediated in the cardiomyocytes with potential benefit as an adjunct to treat symptomatic subjects with LVDD such as RHTN patients.

Deregulation Of Adipokines Related To Target Organ Damage On Resistant Hypertension.

Resistant hypertension (RHTN) includes patients with controlled blood pressure (BP) (CRHTN) and uncontrolled BP (UCRHTN). In fact, RHTN patients are more likely to have target organ damage (TOD), and resistin, leptin and adiponectin may affect BP control in these subjects. We assessed the relationship between adipokines levels and arterial stiffness, left ventricular hypertrophy (LVH) and microalbuminuria (MA). This cross-sectional study included CRHTN (n=51) and UCRHTN (n=38) patients for evaluating body mass index, ambulatory blood pressure monitoring, plasma adiponectin, leptin and resistin concentrations, pulse wave velocity (PWV), MA and echocardiography. Leptin and resistin levels were higher in UCRHTN, whereas adiponectin levels were lower in this same subgroup. Similarly, arterial stiffness, LVH and MA were higher in UCRHTN subgroup. Adiponectin levels negatively correlated with PWV (r=-0.42, P<0.01), and MA (r=-0.48, P<0.01) only in UCRHTN. Leptin was positively correlated with PWV (r=0.37, P=0.02) in UCRHTN subgroup, whereas resistin was not correlated with TOD in both subgroups. Adiponectin is associated with arterial stiffness and renal injury in UCRHTN patients, whereas leptin is associated with arterial stiffness in the same subgroup. Taken together, our results showed that those adipokines may contribute to vascular and renal damage in UCRHTN patients.