Don't forget asking the others! - The added value of significant other's reports on patient interpersonal style for the prediction of therapy process and outcome

Theory: Interpersonal factors play a major role in causing and maintaining depression. It is unclear, however, to what degree significant others of the patient need to be involved for characterizing the patient's interpersonal style. Therefore, our study sought to investigate how impact messages as perceived by the patients' significant others add to the prediction of psychotherapy process and outcome above and beyond routine assessments, and therapist factors. Method: 143 outpatients with major depressive disorder were treated by 24 therapists with CBT or Exposure-Based Cognitive Therapy. Interpersonal style was measured pre and post therapy with the informant‐based Impact Message Inventory (IMI), in addition to the self‐report Inventory of Interpersonal Problems (IIP‐32). Indicators for the patients' dominance and affiliation as well as interpersonal distress were calculated from these measures. Depressive and general symptomatology was assessed at pre, post, and at three months follow‐up, and by process measures after every session. Results: Whereas significant other's reports did not add significantly to the prediction of the early therapeutic alliance, central mechanisms of change, or post‐therapy outcome including therapist factors, the best predictor of outcome 3 months post therapy was an increase in dominance as perceived by significant others. Conclusions: The patients' significant others seem to provide important additional information about the patients' interpersonal style and therefore should be included in the diagnostic process. Moreover, practitioners should specifically target interpersonal change as a potential mechanism of change in psychotherapy for depression.

MicroRNA Regulation of Prostate Cancer Stem/Progenitor Cells and Prostate Cancer Development

Most human tumors contain a population of cells with stem cell properties, called cancer stem cells (CSCs), which are believed to be responsible for tumor establishment, metastasis, and resistance to clinical therapy. It’s crucial to understand the regulatory mechanisms unique to CSCs, so that we may design CSC-specific therapeutics. Recent discoveries of microRNA (miRNA) have provided a new avenue in understanding the regulatory mechanisms of cancer. However, how miRNAs may regulate CSCs is still poorly understood. Here, we present miRNA expression profiling in six populations of prostate cancer (PCa) stem/progenitor cells that possess distinct tumorigenic properties. Six miRNAs were identified to be commonly and differentially expressed, namely, four miRNAs (miR-34a, let-7b, miR-106a and miR-141) were under-expressed, and two miRNAs (miR-301 and miR-452) were over-expressed in the tumorigenic subsets compared to the corresponding marker-negative subpopulations. Among them, the expression patterns of miR-34, let-7b, miR-141 and miR-301 were further confirmed in the CD44+ human primary prostate cancer (HPCa) samples. We then showed that miR-34a functioned as a critical negative regulator in prostate CSCs and PCa development and metastasis. Over-expression of miR-34a in either bulk or CD44+ PCa cells significantly suppressed clonal expansion, tumor development and metastasis. Systemic delivery of miR-34a in tumor-bearing mice demonstrated a potent therapeutic effect again tumor progression and metastasis, leading to extended animal survival. Of great interest, we identified CD44 itself as a direct and relevant downstream target of miR-34a in mediating its tumor-inhibitory effects. Like miR-34a, let-7 manifests similar tumor suppressive effects in PCa cells. In addition, we observed differential mechanisms between let-7 and miR-34a on cell cycle, with miR-34a mainly inducing G1 cell-cycle arrest followed by cell senescence and let-7 inducing G2/M arrest. MiR-301, on the other hand, exerted a cell type dependent effect in regulating prostate CSC properties and PCa development. In summary, our work reveals that the prostate CSC populations display unique miRNA expression signatures and different miRNAs distinctively and coordinately regulate various aspects of CSC properties. Altogether, our results lay a scientific foundation for developing miRNA-based anti-cancer therapy.

Yield prediction and inbreeding of maize synthetics generated with lines and single crosses : classic probability

reduce costs and labor associated with predicting the genotypic mean (GM) of a synthetic variety (SV) of maize (Zea mays L.), breeders can develop SVs from L lines and s single crosses (SynL,SC) instead of L+2s lines (SynL). The objective of this work was to derive and study formulae for the inbreeding coefficient (IC) and GM of SynL,SC, SynL, and the SV derived from (L+2s)/2 single crosses (SynSC). All SVs were derived from the same L+2s unrelated lines whose IC is FL, and each parent of a SV was represented by m plants. An a priori probability equation for the IC was used. Important results were: 1) the largest and smallest GMs correspond to SynL and SynL,SC, respectively; 2) the GM predictors with the largest and intermediate precision are those for SynL and SynL,SC, respectively; 3) only when FL=1, or m is large, SynL and SynSC are the same population, but only with SynSC prediction costs and labor undergo the maximum decrease, although its prediction precision is the lowest. To determine the SV to be developed, breeders should also consider the availability of lines, single crosses, manpower and land area; besides budget, target farmers, target environments, etc.

Cooperative off-policy prediction of markov decision processes in adaptive networks

We apply diffusion strategies to propose a cooperative reinforcement learning algorithm, in which agents in a network communicate with their neighbors to improve predictions about their environment. The algorithm is suitable to learn off-policy even in large state spaces. We provide a mean-square-error performance analysis under constant step-sizes. The gain of cooperation in the form of more stability and less bias and variance in the prediction error, is illustrated in the context of a classical model. We show that the improvement in performance is especially significant when the behavior policy of the agents is different from the target policy under evaluation.

Recent improvements in prediction of protein structure by global optimization of a potential energy function

Recent improvements of a hierarchical ab initio or de novo approach for predicting both α and β structures of proteins are described. The united-residue energy function used in this procedure includes multibody interactions from a cumulant expansion of the free energy of polypeptide chains, with their relative weights determined by Z-score optimization. The critical initial stage of the hierarchical procedure involves a search of conformational space by the conformational space annealing (CSA) method, followed by optimization of an all-atom model. The procedure was assessed in a recent blind test of protein structure prediction (CASP4). The resulting lowest-energy structures of the target proteins (ranging in size from 70 to 244 residues) agreed with the experimental structures in many respects. The entire experimental structure of a cyclic α-helical protein of 70 residues was predicted to within 4.3 Å α-carbon (Cα) rms deviation (rmsd) whereas, for other α-helical proteins, fragments of roughly 60 residues were predicted to within 6.0 Å Cα rmsd. Whereas β structures can now be predicted with the new procedure, the success rate for α/β- and β-proteins is lower than that for α-proteins at present. For the β portions of α/β structures, the Cα rmsd's are less than 6.0 Å for contiguous fragments of 30–40 residues; for one target, three fragments (of length 10, 23, and 28 residues, respectively) formed a compact part of the tertiary structure with a Cα rmsd less than 6.0 Å. Overall, these results constitute an important step toward the ab initio prediction of protein structure solely from the amino acid sequence.

MicroRNAs in pathology and as therapeutic target in gene therapy?

Dissertação para obtenção do grau de Mestre no Instituto Superior de Ciências da Saúde Egas Moniz

MicroRNA-155 promotes resolution of hypoxia-inducible factor 1α activity during prolonged hypoxia

The hypoxia-inducible factor (HIF) is a key regulator of the transcriptional response to hypoxia. While the mechanism underpinning HIF activation is well understood, little is known about its resolution. Both the protein and the mRNA levels of HIF-1a (but not HIF-2a) were decreased in intestinal epithelial cells exposed to prolonged hypoxia. Coincident with this, microRNA (miRNA) array analysis revealed multiple hypoxiainducible miRNAs. Among these was miRNA-155 (miR-155), which is predicted to target HIF-1a mRNA. We confirmed the hypoxic upregulation of miR-155 in cultured cells and intestinal tissue from mice exposed to hypoxia. Furthermore, a role for HIF-1a in the induction of miR-155 in hypoxia was suggested by the identification of hypoxia response elements in the miR-155 promoter and confirmed experimentally. Application of miR-155 decreased the HIF-1a mRNA, protein, and transcriptional activity in hypoxia, and neutralization of endogenous miR-155 reversed the resolution of HIF-1a stabilization and activity. Based on these data and a mathematical model of HIF-1a suppression by miR-155, we propose that miR-155 induction contributes to an isoform-specific negative-feedback loop for the resolution of HIF-1a activity in cells exposed to prolonged hypoxia, leading to oscillatory behavior of HIF-1a-dependent transcription. © 2011, American Society for Microbiology.

Molecular docking and geographical information systems as tools to assess the potential impact of veterinary medicines on non-target organisms and the environment

Veterinary medicines (VMs) from agricultural industry can enter the environment in a number of ways. This includes direct exposure through aquaculture, accidental spillage and disposal, and indirect entry by leaching from manure or runoff after treatment. Many compounds used in animal treatments have ecotoxic properties that may have chronic or sometimes lethal effects when they come into contact with non-target organisms. VMs enter the environment in mixtures, potentially having additive effects. Traditional ecotoxicology tests are used to determine the lethal and sometimes reproductive effects on freshwater and terrestrial organisms. However, organisms used in ecotoxicology tests can be unrepresentative of the populations that are likely to be exposed to the compound in the environment. Most often the tests are on single compound toxicity but mixture effects may be significant and should be included in ecotoxicology testing. This work investigates the use, measured environmental concentrations (MECs) and potential impact of sea lice treatments on salmon farms in Scotland. Alternative methods for ecotoxicology testing including mixture toxicity, and the use of in silico techniques to predict the chronic impact of VMs on different species of aquatic organisms were also investigated. The Scottish Environmental Protection Agency (SEPA) provided information on the use of five sea lice treatments from 2008-2011 on Scottish salmon farms. This information was combined with the recently available data on sediment MECs for the years 2009-2012 provided by SEPA using ArcGIS 10.1. In depth analysis of this data showed that from a total of 55 sites, 30 sites had a MEC higher than the maximum allowable concentration (MAC) as set out by SEPA for emamectin benzoate and 7 sites had a higher MEC than MAC for teflubenzuron. A number of sites that were up to 16 km away from the nearest salmon farm reported as using either emamectin benzoate or teflubenzuron measured positive for the two treatments. There was no relationship between current direction and the distribution of the sea lice treatments, nor was there any evidence for alternative sources of the compounds e.g. land treatments. The sites that had MECs higher than the MAC could pose a risk to non-target organisms and disrupt the species dynamics of the area. There was evidence that some marine protected sites might be at risk of exposure to these compounds. To complement this work, effects on acute mixture toxicity of the 5 sea lice treatments, plus one major metabolite 3-phenoxybenzoic acid (3PBA), were measured using an assay using the bioluminescent bacteria Aliivibrio fischeri. When exposed to the 5 sea lice treatments and 3PBA A. fischeri showed a response to 3PBA, emamectin benzoate and azamethiphos as well as combinations of the three. In order to establish any additive effect of the sea lice treatments, the efficacy of two mixture prediction equations, concentration addition (CA) and independent action ii(IA) were tested using the results from single compound dose response curves. In this instance IA was the more effective prediction method with a linear regression confidence interval of 82.6% compared with 22.6% of CA. In silico molecular docking was carried out to predict the chronic effects of 15 VMs (including the five used as sea lice control). Molecular docking has been proposed as an alternative screening method for the chronic effects of large animal treatments on non-target organisms. Oestrogen receptor alpha (ERα) of 7 non-target bony fish and the African clawed frog Xenopus laevis were modelled using SwissModel. These models were then ‘docked’ to oestradiol, the synthetic oestrogen ethinylestradiol, two known xenoestrogens dichlorodiphenyltrichloroethane (DDT) and bisphenol A (BPA), the antioestrogen breast cancer treatment tamoxifen and 15 VMs using Auto Dock 4. Based on the results of this work, four VMs were identified as being possible xenoestrogens or anti-oestrogens; these were cypermethrin, deltamethrin, fenbendazole and teflubenzuron. Further investigation, using in vitro assays, into these four VMs has been suggested as future work. A modified recombinant yeast oestrogen screen (YES) was attempted using the cDNA of the ERα of the zebrafish Danio rerio and the rainbow trout Oncorhynchus mykiss. Due to time and difficulties in cloning protocols this work was unable to be completed. Use of such in vitro assays would allow for further investigation of the highlighted VMs into their oestrogenic potential. In conclusion, VMs used as sea lice treatments, such as teflubenzuron and emamectin benzoate may be more persistent and have a wider range in the environment than previously thought. Mixtures of sea lice treatments have been found to persist together in the environment, and effects of these mixtures on the bacteria A. fischeri can be predicted using the IA equation. Finally, molecular docking may be a suitable tool to predict chronic endocrine disrupting effects and identify varying degrees of impact on the ERα of nine species of aquatic organisms.

The role of microRNA 21 in the development of in-stent restenosis

Coronary heart disease is a major cause of morbidity and mortality worldwide. Percutaneous coronary intervention (PCI) has become the most widely used method of coronary artery revascularisation. The use of stents to hold open atherosclerosis induced arterial narrowing has significantly reduced elastic recoil and acute vessel occlusion following balloon angioplasty. However, bare metal stents have been associated with in-stent restenosis attributed to vascular smooth muscle cell (VSMC) hyperplasia and excessive neointimal formation. The resultant luminal renarrowing may manifest clinically with the return of symptoms such as chest pain or shortness of breath. The development of drug eluting stents has significantly reduced the incidence of in-stent restenosis (ISR). Unfortunately the antiproliferative medications used not only inhibit VSMC proliferation but also re-endothelialisation of the stented vessel. In addition, the drug impregnated polymer coating has been associated with a chronic inflammatory response within the vessel wall predisposing patients to stent thrombosis. Thus the identification of novel therapies which promote vessel healing without excessive proliferative or inflammatory response may improve long term outcome and reduce the need for repeated revascularisation. MicroRNAs (miRs) are short (18-25 nucleotide) non-coding RNAs acting to regulate gene expression. By binding to the 3’untranslated region of mRNA they act to fine tune gene expression either by mRNA degradation or translational repression. Originally identified in coordinating tissue development microRNAs have also been shown to play important roles coordinating the inflammatory response and in numerous cardiovascular diseases. MiR-21 has been identified in human atherosclerotic plaques, arteriosclerosis obliterans and abdominal aortic aneurysms. In addition, its up regulation has been documented in preclinical models of vascular injury. This study sought to identify the role of miR-21 in the development of ISR. Utilising a small animal model of stenting and in vitro techniques, we sought to investigate its influence upon VSMC and immune cell response following stenting. 19 The refinement of a murine stenting model within the Baker laboratory and the electrochemical dissolution of the metal stent from within harvested vascular tissues significantly improved the ability to perform detailed histological analysis. In addition, identification of miRNAs using in situ hybridisation was achieved for the first time within stented tissue. Neointimal formation and ISR was significantly reduced in mice in which miR-21 had been genetically deleted. In addition, neointimal composition was found to be altered in miR-21 KO mice with reductions in VSMC and elastin content demonstrated. Importantly, no difference in re-endothelialisation was observed. In vitro analysis demonstrated that VSMCs from miR-21 KO mice had both reduced proliferative and migratory capacity following platelet derived growth factor stimulation. Molecular analysis revealed that these differences may, at least in part, be due to de-repression of programmed cell death 4 (PDCD4). PDCD4 is a known miR-21 target within VSMCs implicated in the suppression of proliferation and promotion of apoptosis. Unfortunately, initial attempts at antimiR mediated knockdown of miR-21 in vivo, failed to produce a similar change in the suppression of ISR. Furthermore, a significant alteration in macrophage polarisation state within the neointima of miR-21 WT and KO mice was noted. Immunohistochemical staining revealed a preponderance of anti-inflammatory M2 macrophages in KO mice. Analysis of bone marrow derived macrophages from miR-21 KO mice demonstrated an increased level of the peroxisome proliferation activating receptor-γ (PPARγ) which facilitates M2 polarisation. Importantly, significant alterations in numerous pro-inflammatory cytokines, which also have mitogenic effects, were also found following genetic deletion of miR-21. In Summary, this is the first study to look at miRs in the development of ISR. MiR-21 plays an important role in the development of ISR by influencing the proliferative response of VSMCs and modulating the immune response following stent deployment. Further attempts to modulate miR-21 expression following PCI may reduce ISR and the need for repeat revascularisation while also reducing the risk of stent thrombosis.

PAMP-triggered immunity against Pseudomonas syringae involves microRNA-mediated regulation of several uncharacterized R genes

Two main types of noncoding small RNA molecules have been found in plants: microRNAs (miRNAs) and small interfering RNAs (siRNAs). They differ in their biogenesis and mode of action, but share similar sizes (20-24 nt). Their precursors are processed by Dicer-Like RNase III (dcl) proteins present in Arabidopsis thaliana, and in their mature form can act as negative regulators of gene expression, being involved in a vast array of plant processes, including plant development, genomic integrity or response to stress. Small-RNA mediated regulation can occurs at transcriptional level (TGS) or at post-transcriptional level (PTGS). In recent years, the role of gene silencing in the regulation of expression of genes related to plant defence responses against bacterial pathogens is becoming clearer. Comparisons carried out in our lab between the expression profiles of different mutants affected in gene silencing, and plants challenged with Pseudomonas syringae pathovar tomato DC3000, led us to identify a set of uncharacterized R genes, belonging to the TIR-NBS-LRR gene family, differentially expressed in these conditions. Through the use of bioinformatics tools, we found a miRNA* of 22 nt putatively responsible for down-regulating expression of these R genes through the generation of siRNAs. We have also found that the corresponding pri-miRNA is down-regulated after PAMP-perception in a SA-dependent manner. We also demonstrate that plants with altered levels of miRNA* (knockdown lines or overexpression lines) exhibit altered PTI-associated phenotypes, suggesting a role for this miRNA* in this defence response against bacteria. In addition we identify one of the target genes as a negative regulator of defence response against Pseudomonas syringae.

Kinetic modelling of in vitro data of PI3K, mTOR1, PTEN enzymes and on-target inhibitors Rapamycin, BEZ235, and LY294002

The phosphatidylinositide 3-kinases (PI3K) and mammalian target of rapamycin-1 (mTOR1) are two key targets for anti-cancer therapy. Predicting the response of the PI3K/AKT/mTOR1 signalling pathway to targeted therapy is made difficult because of network complexities. Systems biology models can help explore those complexities but the value of such models is dependent on accurate parameterisation. Motivated by a need to increase accuracy in kinetic parameter estimation, and therefore the predictive power of the model, we present a framework to integrate kinetic data from enzyme assays into a unified enzyme kinetic model. We present exemplar kinetic models of PI3K and mTOR1, calibrated on in vitro enzyme data and founded on Michaelis-Menten (MM) approximation. We describe the effects of an allosteric mTOR1 inhibitor (Rapamycin) and ATP-competitive inhibitors (BEZ2235 and LY294002) that show dual inhibition of mTOR1 and PI3K. We also model the kinetics of phosphatase and tensin homolog (PTEN), which modulates sensitivity of the PI3K/AKT/mTOR1 pathway to these drugs. Model validation with independent data sets allows investigation of enzyme function and drug dose dependencies in a wide range of experimental conditions. Modelling of the mTOR1 kinetics showed that Rapamycin has an IC50 independent of ATP concentration and that it is a selective inhibitor of mTOR1 substrates S6K1 and 4EBP1: it retains 40% of mTOR1 activity relative to 4EBP1 phosphorylation and inhibits completely S6K1 activity. For the dual ATP-competitive inhibitors of mTOR1 and PI3K, LY294002 and BEZ235, we derived the dependence of the IC50 on ATP concentration that allows prediction of the IC50 at different ATP concentrations in enzyme and cellular assays. Comparison of the drug effectiveness in enzyme and cellular assays showed that some features of these drugs arise from signalling modulation beyond the on-target action and MM approximation and require a systems-level consideration of the whole PI3K/PTEN/AKT/mTOR1 network in order to understand mechanisms of drug sensitivity and resistance in different cancer cell lines. We suggest that using these models in systems biology investigation of the PI3K/AKT/mTOR1 signalling in cancer cells can bridge the gap between direct drug target action and the therapeutic response to these drugs and their combinations.

Prediction of a low-risk concentration of diflubenzuron to aquatic organisms and evaluation of clay and gravel in reducing the toxicity.

Resumo: Predição da concentração de baixo risco de diflubenzuron para organismos aquáticos e avaliação da argila e brita na redução da toxicidade. O diflubenzuron é um inseticida que além de ser usado agricultura, tem sido amplamente empregado na piscicultura, apesar do seu uso ser proibido nesta atividade. Este composto não consta na lista da legislação brasileira que estabelece limites máximos permissíveis em corpos de água para a proteção das comunidades aquáticas. No presente trabalho, a partir da toxicidade do diflubenzuron em organismos não-alvo, foi calculada a concentração de risco para somente 5% das espécies (HC5). O valor deste parâmetro foi estimado em aproximadamente 7 x 10-6 mg L-1 . Este baixo valor é devido à extremamente alta toxicidade do diflubenzuron para dafnídeos e à grande variação de sensibilidade entre as espécies testadas. Dois matérias de relativamente baixo custo se mostraram eficientes na remoção da toxicidade do diflubenzuron de soluções contendo este composto. Dentre esses materiais, a argila expandida promoveu a redução em aproximadamente 50% da toxicidade de uma solução contendo diflubenzuron. Os resultados podem contribuir para políticas públicas no Brasil relacionadas ao estabelecimento de limites máximos permissíveis de xenobióticos no compartimento aquático. Também, para a pesquisa de matérias inertes e de baixo custo com potencial de remoção de xenobióticos presentes em efluentes da aquicultura ou da agricultura. Abstract: Diflubenzuron is an insecticide that, besides being used in the agriculture, has been widely used in fish farming. However, its use is prohibited in this activity. Diflubenzuron is not in the list of Brazilian legislation establishing maximum permissible limits in water bodies for the protection of aquatic communities. In this paper, according toxicity data of diflubenzuron in non-target organisms, it was calculated an hazardous concentration for only 5% of the species (HC5) of the aquatic community. This parameter value was estimated to be about 7 x 10 -6 mg L -1 . The low value is due to the extreme high toxicity of diflubenzuron to daphnids and to the large variation in sensitivity among the species tested. Two relatively low cost and inert materials were efficient in removing the diflubenzuron from solutions containing this compound. Among these materials, expanded clay shown to promote reduction of approximately 50% of the toxicity of a solution containing diflubenzuron. The results may contribute to the establishment of public policies in Brazil associated to the definition of maximum permissible limits of xenobiotics in the aquatic compartment. This study is also relevant to the search of low cost and inert materials for xenobiotics removal from aquaculture or agricultural effluents.

Identificazione di un nuovo meccanismo microRNA-dipendente di resistenza all'inibizione della via di segnale PI3K/AKT nel carcinoma della prostata

Benché le alterazioni della via PI3K/AKT siano molto sudiate a causa del loro ruolo nella tumorigenesi, e rappresentino pertanto un importante bersaglio terapeutico, i risultati di numerosi studi clinici con inibitori di PI3K o AKT sono finora deludenti, in parte a causa dell’insorgenza di resistenza provocata dall'interruzione dei circuiti di feedback negativo. In questo studio, abbiamo scoperto che l’inattivazione farmacologica di AKT in cellule di carcinoma prostatico PC3 porta alla down-regolazione di un microRNA con funzione di oncosoppressore, il miR-145-5p, e ad un drammatico aumento di espressione di uno dei suoi geni target, cioè N/KRas. E’ interessante sottolineare che questo microRNA è considerato un marker di progressione metastatica nel carcinoma prostatico, il cui livello di espressione aiuta a discriminare tra pazienti con iperplasia prostatica benigna e cancro alla prostata. Inoltre, la bassa espressione di miR-145 aumenta il rischio di progressione della malattia da localizzata a metastatica. La conferma che l’aumento di Ras, osservato sia in termini di mRNA che di proteina, è dipendente dalla caduta del miR-145-5p, è stata poi ottenuta tramite un modello di PC3 ingegnerizzate per ottenere il silenziamento inducibile del miR-145-5p. Tramite un array di fosfoproteine siamo poi stati in grado di verificare che l’aumento di Ras provoca la riattivazione della cascata di PI3K/AKT e di ERK. Dal punto di vista meccanicistico, quindi, lo studio ha portato all’identificazione di un nuovo meccanismo di resistenza adattativa, in cui l’inattivazione di AKT provoca una caduta del miR-145-5p che, a sua volta, aumenta l’espressione di Ras e riattiva il signaling di PI3K, rendendo inefficace il trattamento farmacologico. Questi risultati sono particolarmente rilevanti alla luce di recenti studi (NCT04493853; NCT03072238; NCT02525068) e di trial clinici in corso (NCT04737109; NCT03673787), basati sulla somministrazione combinata di inibitori della sintesi degli androgeni con gli inibitori di AKT capitasertib o ipatasertib.

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.

Identification Of Target Genes Using Gene Expression Profile Of Granulocytes From Patients With Chronic Myeloid Leukemia Treated With Tyrosine Kinase Inhibitors.

Differential gene expression analysis by suppression subtractive hybridization with correlation to the metabolic pathways involved in chronic myeloid leukemia (CML) may provide a new insight into the pathogenesis of CML. Among the overexpressed genes found in CML at diagnosis are SEPT5, RUNX1, MIER1, KPNA6 and FLT3, while PAN3, TOB1 and ITCH were decreased when compared to healthy volunteers. Some genes were identified and involved in CML for the first time, including TOB1, which showed a low expression in patients with CML during tyrosine kinase inhibitor treatment with no complete cytogenetic response. In agreement, reduced expression of TOB1 was also observed in resistant patients with CML compared to responsive patients. This might be related to the deregulation of apoptosis and the signaling pathway leading to resistance. Most of the identified genes were related to the regulation of nuclear factor κB (NF-κB), AKT, interferon and interleukin-4 (IL-4) in healthy cells. The results of this study combined with literature data show specific gene pathways that might be explored as markers to assess the evolution and prognosis of CML as well as identify new therapeutic targets.