Le myélome multiple (MM) est le second cancer hématologique le plus répandu après les lymphomes. Malgré une amélioration de sa prise en charge au cours des 20 dernières années, les traitements actuels ne permettent pas d’éviter les rechutes répétitives associées au développement de mécanismes de résistance. Les résistances aux traitements sont notamment expliquées par la forte hétérogénéité de la maladie qui rend nécessaire le développement de prises en charges adaptées aux profils moléculaires des patients. L’avènement des technologies de séquençage haut-débit permet d’accéder à des niveaux de plus en plus détaillés de l’hétérogénéité moléculaire tumorale, ce qui permettra de proposer des solutions plus performantes dans l’optique de développer une médecine personnalisée. Dans cet objectif, nous avons analysé l’exome, le transcriptome et l’épigénome de cellules primaires de patients et de lignées cellulaires de MM. Sur la base de ces analyses, nous avons non seulement mis en évidence de nouveaux mécanismes impliqués dans la physiopathologie du MM mais également de nouvelles cibles thérapeutiques potentielles, des biomarqueurs pronostiques ainsi que des signatures d’orientation thérapeutiques. Les données et résultats de nos études constituent une ressource d’intérêt pour la communauté scientifique et permettront d’améliorer la prise en charge thérapeutique des patients atteints de MM. / Multiple myeloma (MM) is the second most common hematological malignancy after lymphoma. Recent advances in treatment have led to an overall survival of intensively-treated patients of 6-7 years. However, patients invariably relapse after multiple lines of treatment, with shortened intervals between relapses, and finally become resistant to all treatments, resulting in loss of clinical control over the disease in association with drug resistance. Treatment improvements will come from a better comprehension of tumorigenesis and detailed molecular analyses to develop individualized therapies taking into account the molecular heterogeneity and subclonal evolution. In this purpose, we analyzed the exome, transcriptome and epigenome of primary MM cells from patients and human MM cell lines. Our results have highlighted new mechanisms involved in the pathophysiology of MM as well as potential new therapeutic targets, prognostic signatures and theranostic biomarkers. The data and results of our studies represent an important resource to understand the mechanisms of tumor progression and drug resistance and develop new ways to diagnose and treat patients.

Topic models for focused analysis aim to capture topics within the limiting scope of a targeted aspect (which could be thought of as some inner topic within a certain domain). To serve their analytic purposes, topics are expected to be semantically-coherent and closely aligned with human intuition – this in itself poses a major challenge for the more common topic modeling algorithms which, in a broader sense, perform a full analysis that covers all aspects and themes within a collection of texts. The paper attempts to construct a viable focused-analysis topic model which learns topics from Twitter data written in a closely related group of non-standardized varieties of Arabic widely spoken in the Levant region (i.e Levantine Arabic). Results are compared to a baseline model as well as another targeted topic model designed precisely to serve the purpose of focused analysis. The model is capable of adequately capturing topics containing terms which fall within the scope of the targeted aspect when judged overall. Nevertheless, it fails to produce human-friendly and semantically-coherent topics as several topics contained a number of intruding terms while others contained terms, while still relevant to the targeted aspect, thrown together seemingly at random.

Glioblastoma (GBM) is a deadly, malignant brain tumor with a poor long-term prognosis. The current median survival is approximately fifteen to seventeen months with the standard of care therapy which includes surgery, radiation, and chemotherapy. An important factor contributing to recurrence of GBM is high resistance of GBM cancer stem cells (CSCs), for which a systematically delivered single drug approach will be unlikely to produce a viable cure. Therefore, multi-drug therapies are needed. Currently, only temozolomide (TMZ), which is a DNA alkylator, affects overall survival in GBM patients. CSCs regenerate rapidly and over-express a methyl transferase which overrides the DNA-alkylating mechanism of TMZ, leading to drug resistance. Idasanutlin (RG7388, R05503781) is a potent, selective MDM2 antagonist that additively kills GBM CSCs when combined with diagnostics in a truly theranostic manner for enhancing personalized medicine against GBM. The goal of this thesis was to develop a multi-drug therapy using mutli-functional nanoparticles (NPs) that preferentially target the GBM CSC subpopulation and provide in vivo preclinical imaging capability. Polymer-micellar NPs composed of poly(styrene-<i>b</i>-ethylene oxide) (PS-<i>b</i>-PEO) and poly(lactic-<i>co</i>-glycolic) acid (PLGA) were developed investigating both single and double emulsion fabrication techniques as well as combinatinos of TMZ and RG7388. The NPs were covalently bound to a 15 base-pair CD133 aptamer in order to target a specific epitope on the CD133 antigen expressed on the surface of GBM CSC subpopulation. For theranostic functionality, the NPs were also labelled with a positron emission tomography (PET) radiotracer, zirconium-89 (⁸⁹Zr). The NPs maintained a small size of less than 100 nm, a relatively neutral charge and exhibited the ability to produce a cytotoxic effect on CSCs. There was a slight increase in killing with the aptamer-bound NPs compared to those without a targeting agent. This work has provided a potentially therapeutic option for GBM specific for CSC targeting and future in vivo biodistribution

<p>Triple Negative Breast Cancer (TNBC) is the most aggressive type of breast cancer. TNBC patients are resistant to virtually all target therapies and suffer a higher post-chemotherapy relapse with a worse overall survival compared with other types of breast cancers. Therefore, the development of an effective therapy is urgently needed. PKM2 plays a prominent role in mediating<b> </b>tumor glycolysis and PKM2 is often overexpressed in human cancers. However, whether PKM2 mediated glycolysis is necessary for cancer cell growth is questionable. Here, I have found that inhibition of PKM2 does not affect TNBC cell growth due to a metabolic switch from glycolysis to fatty acid oxidation (FAO). We show that PKM2 directly interacts with EZH2 to coordinately mediate epigenetic silencing of SLC16A9, transporter of a key player in FAO, Carnitine. Inhibition of either PKM2 or EZH2 increases levels of SLC16A9 and intracellular Carnitine to promote FAO and thereby sustains cancer cell growth. Direct inhibition of EZH2 using a clinically tested EZH2 inhibitor, GSK126, is able to elicit a previously unidentified vulnerability to a clinically tested FAO inhibitor, Etomoxir. As a result, combined GSK126-Etomoxir treatment synergistically abolishes TNBC xenograft tumor growth in vivo. Together, this study uncovers PKM2-EZH2 mediated metabolic reprogramming that leads to a new drug combination therapy by dual targeting of EZH2 and FAO for effective treatment of TNBC.<b> </b></p> <p> </p> <p>Furthermore, Dendritic Cell (DC) vaccination has shown promise in treating cancer patients. However, the <i>in vitro</i> generation of a fully functional DC remains a big challenge in this field. EZH2 inhibition has shown to be able to create an immunologically ‘hot’ tumors. Nonetheless, the role of EZH2 in regulation of DC function is still unclear. I found that the expression levels of EZH2 and its functional maker, H3K27Me3, are enhanced following maturation from immature DC (iDC) into two functional DCs, α-type 1-polarized-DC (αDC) and gold standard DC (sDC). Moreover, inhibition of EZH2 by GSK126 treatment elicits a dependency of sDC on FAO. These results suggest that EZH2 plays a role in maturation of DC through metabolic reprogramming, which may also provide new DC based immunotherapy of TNBC. </p>

Autophagy is a critical cellular maintenance machinery in cells, and prevents the accumulation of toxic protein aggregates, organelles or lipid droplets through degradation via the lysosome. In macro-autophagy, autophagosome first engulfs around aggregates or cellular debris and subsequently fuses with a lysosome that is sufficiently acidic (pH 4.5–5.5), where the contents are then degraded via lysosomal enzymes. Autophagy inhibition as a result of lysosomal acidification dysfunction (pH > 5.5) have been reported to play a major role in various diseases pathogenesis. Hence, there is a pressing need to target lysosomal pH to rescue autophagy. Nanoparticles are attractive materials which has been shown to be efficiently uptaken into cellular organelles and can serve as an agent to specifically localize into lysosomes and modulate its pH. Lipotoxicity, induced by chronic exposure to free fatty acids, and exposure to neurotoxins (e.g. MPP+), elevates lysosomal pH in pancreatic beta cells (Type II Diabetes, T2D) and hepatocytes (Non-alcoholic fatty liver disease, NAFLD), and PC-12 cells (Parkinson’s Disease), respectively. We first tested the lysosome acidification capability of photo-activable nanoparticles (paNPs) and poly (lactic-co-glycolic) acid nanoparticles (PLGA NPs) in a T2D model. Both NPs lowered lysosomal pH in pancreatic beta cells under lipotoxicity and improved insulin secretion function. However, paNPs only release acids upon UV trigger, limiting its applicability in vivo, while PLGA NPs degrade upon lysosome localization. We further showed that PLGA NPs are able to rescue MPP+ induced cell death in a PD model, though it has a slow degradation rate. To attain the most efficacious nanoparticle with a fast degradation and acidification rate, we synthesized acidic nanoparticles (acNPs) based on tetrafluorosuccinic and succinic acids to form optimized nanoparticles. The acNPs showed faster rescue of cellular function compared to PLGA NPs in the PD model. Finally, we tested the acNPs in NAFLD model, and where lysosomal pH reduction by acNPs restored autophagy, reduced lipid accumulation, and improved mitochondria function in high-fat diet mice. In sum, nanoparticles are of potential therapeutic interest for pathologies associated with lysosomal acidity impairment. Future studies include testing the acNPs in NASH disease model and clinical studies. / 2022-05-18T00:00:00Z

Prostate cancer (PCa) bone metastases have been reported in ~90% of patients with advanced disease. Bone metastases disrupt tissue homeostasis and weaken the skeleton, resulting in an increased risk of bone fractures and morbidity. Specifically, PCa cells disrupt the crosstalk between critical cells within the tumor/bone microenvironment (osteoblasts, osteoclasts, and immune cells), and utilize this effector-rich environment for cancer survival and growth. Therefore, a key therapeutic objective in malignant skeletal disease management is to eliminate tumors while restoring bone homeostasis. Current treatments include palliative radiotherapy, chemotherapy, or anti-RANK treatments, all of which have considerable side effects such as osteonecrosis of the jaw or enhanced tumor invasion. There remains a critical gap in therapies than can reduce tumor burden and simultaneously restore bone homeostasis. To address this gap, our work explores emerging gene therapy approaches for treating skeletal malignancies by utilizing multifunctional cytokine-based agents that can simultaneously combat tumor growth and promote bone regeneration.<div><br></div><div>We hypothesize that rationally designed cytokine-based gene therapies that can be secreted from skeletal muscle and targeted to the bone/tumor microenvironment, could effectively reduce tumor growth and restore bone cell homeostasis. To test this hypothesis, we adopted two strategies: 1) a second-generation targeted IL-27 cytokine, and 2) a de novodesign of a cytokine-like therapeutic agent (Propeptide) that includes anti-tumorigenic and pro-osteogenic domains. Both strategies share modules with overlapping therapeutic functions, rendering them complementary in their therapeutic application. In this work, we examined the proof of principle for propeptide gene therapy in muscle cells (in vitro models) and assessed the therapeutic efficacy of our cytokine-based biologics in reducing prostate tumor growth and rebalancing bone cell proliferation and differentiation. Our studies resulted in a propeptide construct representative of a cytokine structure comprised of a bundle of helices that we were able to express in cells. Additionally, our work demonstrated the targeting and anti-tumor efficacy of our therapeutic cytokines in cancer and bone cell models. Ultimately, this will provide the framework for innovative peptide and cytokine-based therapeutics that target and treat both the tumor metastases and bone. This approach will facilitate improvement of morbidity and quality of life of prostate cancer patients with bone metastases and could be applicable to other diseases with bone/tumor pathologies. <br><div><br></div></div>

By means of return-based style analysis (RBSA), heterogeneous style sub-categories were identified within the TARR category of the South African unit trust market to create a framework for sub-categorisation. The study dealt with TARR funds and their place within the investment universe. The literature review emphasised the importance of asset allocation, which supports the use of RBSA to identify asset allocation. The literature review further provided a motivation for the semi-strong form of RBSA applied to the sample data. In the study, RBSA was applied to two groups within the sample data, namely funds that have data points for the full measurement period (Group 1) and funds that have less than 75 data points (Group 2). A four-phase process was applied to the sample data. The findings suggest the following:<ul><li> in general, return-based style analysis applied to each fund identifies the asset allocation for the fund and is valid; but it is emphasised that for specific periods, the explanatory power of the regression model may become questionable; </li><li> the collective results of return-based style analysis applied to the funds can be used to create a framework for sub-categorisation. The framework proposed was the result of nine out of a potential 54 funds. The explanatory power of the regression results was less questionable. The proposed framework was applied to the remaining 45 funds (Group 2), but there were indeed inconsistencies in the application; </li><li> the framework created did not raise any concerns as a result of the Group 1 analysis. However, it was questionable when applied to the Group 2 funds in its entirety; </li><li> sub-categorisation based on only the allocation to the domestic short-term asset class was definitely a criterion that was true irrelevant of which sample group it was applied to. </li></ul> / Dissertation (MCom)--University of Pretoria, 2011. / Financial Management / unrestricted

The main aim of this study is to synthesize theranostic nanoparticles (NPs) that will drastically increase the diagnostics and therapeutic efficacy for cancer. In this research, we had prepared the NPs which constitute carbon dots (CDs), the imaging agent, Folic acid, the targeting agent, and Doxorubicin (DOX) or Gemcitabine (GEM) as the chemotherapy agents. The prepared NPs include noncovalent FA-CDs-DOX, covalent CDs-FA-DOX, and covalent FA-CDs-GEM. The spectroscopy, ultraviolet-visible spectroscopy (UV-vis), fluorescence spectroscopy, and Fourier transform-infrared spectroscopy (FT-IR), were used to confirm the successful fabrication of these complexes. Through UV-vis analysis, the drug loading capacity (DLC) and drug loading efficiency (DLE) of the complexes were determined. The noncovalent series had a higher DLE of about 83% while the covalent series showed higher DLC, 70% on average indicating high drug content. The in-vitro pH-dependent drug release shows that the noncovalent FA-CDs-DOX and the covalent FA-CDs-GEM series release more drugs into the cancer cells (pH of 5.0) than into healthy normal (pH of 7.4). The sizes of NPs were measure around 2-5 nm with Dynamic light Scattering (DLS). The toxicity of CDs, CDs-drug, and FA-CDs-drug on MDA-MB468 breast cancer cell was tested through the methylthiazolytetrazolium (MTT) assay and found that the FA bonded NPs exhibited strong therapeutic efficacy. More pharmaceutical data towards the cancer cells are investigated by our research collaborators – the pharmaceutical department at ETSU and Xavier University at Louisiana.

No description available.

The maintenance of infrastructure is critical to the well-being of society. This work focuses on a novel method for inspecting the exterior of dams using unmanned aerial vehicles (UAVs) in an automated fashion. The UAVs are equipped with optical sensors capturing still images. The resulting images are used to generate three-dimensional (3D) models using Structure from Motion (SfM) computer software. The SfM models are then used to inspect the exterior of the dam. As typical dam inspections entail completing a checklist of inspection items with varied degrees of precision (e.g. a concrete spillway may be finely inspected for cracking or joint deterioration while the general stability and water-tightness of a large embankment may be observed from a distance), a targeted inspection is also needed for the UAV method. In conjunction with the work presented in this thesis, a novel algorithm was developed which uses camera view planning across multiple proximity levels to generate a set of camera poses (positions and orientations) which can be collected in an autonomous UAV flight that facilitates generation of SfM models having tiered model quality for targeted inspection of infrastructure features. In this thesis, this novel algorithm and accompanying mobile application (referred to together as the novel advanced autonomous method) were field validated at Tibble Fork Dam, UT. The advanced autonomous method was compared to two other common image acquisition methods—basic autonomous and manual piloted—based on the SfM models produced from the collected image sets. The advanced autonomous method was found to produce models having tiered quality needed for efficient targeted inspection (25% and 50% higher resolution in medium and high priority target areas). The advanced autonomous method was found to produce models having on average 38% higher precise point accuracy (1.3cm) and 53% tighter surface reproducibility (for repeat inspections) (1.9cm) than basic autonomous and manual piloted image acquisition methods. The advanced autonomous method required on average 167% longer flight time and 38% fewer images than the other two methods, resulting in increased field time but decreased processing load. Additionally, viability of the advanced autonomous method for practical dam inspection was assessed through a case study inspection of Tibble Fork Dam using the collected SfM model and corresponding still images. The SfM model and corresponding images were found fully adequate for performing 94% of the inspection tasks and partially adequate for the remaining tasks. In consideration of this and other practical implementation factors such as time and safety, the method appears highly viable as an alternate to or supplement with traditional on-foot visual exterior inspection of dams such as Tibble Fork Dam. Suggestions for future work include adjustments to the optimization framework to improve field efficiency, development of a framework for cooperative inspection using UAV swarms, and development of a more automated workflow that would allow fully-remote dam inspections.