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The CMRF-56+ blood dendritic cell preparation as a vehicle for multiple myeloma immunotherapy /Turtle, Cameron J. January 2004 (has links) (PDF)
Thesis (Ph.D.) - University of Queensland, 2005. / Includes bibliography.
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Epigenetic regulation of the myeloid cell lineagePliuskys, Laurynas January 2014 (has links)
The myeloid cell lineage is a fundamental element of the immune system and it can give rise to a diverse set of terminally differentiated cells, such as macrophages or osteoclasts among many others. Mutations or misregulation of gene expression may lead to severe clinical conditions, such as arthritis, osteoporosis or cancers. Epigenetics, the regulation of gene expression and chromatin remodelling, is implicated in cell differentiation, function and disease, and hence it is a promising new area to explore in order to explain underlying cellular mechanisms. Firstly, human macrophage subtypes were studied. Chemokine (C-C motif) ligand (CCL) 1 and mannose receptor were validated to be granulocyte macrophage (GM) colony stimulating factor (CSF) induced macrophage markers, while CCL<sub>2</sub> was specifically expressed in macrophage CSF (MCSF) macrophage population. By utilising publicly available high-throughput sequencing data, new biomarkers dehydrogenase/reductase (SDR family) member 2 and CCL<sub>26</sub> were discovered to be MCSF-macrophage specific while guanylate binding protein 5 and apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like 3A were highly up-regulated in GMCSF cells. Secondly, a range of gene knock-down techniques for the myeloid cell lineage were optimised and established. Lentiviral short-hairpin RNA (shRNA) delivery methods were shown to induce an undesirable pro-inflammatory response in macrophages. Furthermore, the frequently utilised cytomegalovirus promoter for gene expression was shown to be completely silenced in macrophage populations. Locked nucleic acids were selected as a suitable alternative to shRNA knock-down and by employing this new tool it was shown that a histone demethylase lysine (K)-specific demethylase (KDM) 6B is fundamental for macrophage differentiation. Finally, a small molecule GSK-J<sub>4</sub>, a potent inhibitor of histone demethylases KDM6A, KDM6B and KDM<sub>5</sub>B specific for H<sub>3</sub>K<sub>27me3</sub> and H<sub>3</sub>K<sub>4me3</sub>, respectively, was used to dissect epigenetic signalling in osteoclasts and multiple myeloma. In osteoclasts it was shown to act mainly by inhibiting transcriptional changes required for osteoclastogenesis when MCSF-macrophages are stimulated with Receptor Activator Of Nuclear Factor Kappa-B Ligand (RANKL), as indicated by the differential increase in H<sub>3</sub>K<sub>27me3</sub> marks, leading to inhibition of c-Jun and potentially abolition of transcription factor AP-1, required for the transcriptional initiation of nuclear factor of activated T-cells 1 (NFATc1). In multiple myeloma cells, GSK-J<sub>4</sub> causes a dramatic increase in expression, further supported by the build-up of global H<sub>3</sub>K<sub>4me3</sub> marks, which results in the upregulation of the unfolded protein response pathway. In both cell systems, there is an early upregulation of metallothionein genes, which in multiple myeloma was shown to increase potentially due to rapid influx of zinc ions within the first 30 minutes, and as such may cause induction of apoptosis in multiple myeloma and may inhibit differentiation of osteoclasts.
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Withanolide D Exhibits Similar Cytostatic Effect in Drug-Resistant and Drug-Sensitive Multiple Myeloma CellsIssa, Mark E., Wijeratne, E. M. K., Gunatilaka, A. A. L., Cuendet, Muriel 08 September 2017 (has links)
In spite of recent therapeutic advances, multiple myeloma (MM) remains a malignancy with very low curability. This has been partly attributed to the existence of a drug-resistant subpopulation known as cancer stem cells (CSCs). MM-CSCs are equipped with the necessary tools that render them highly resistant to virtually all conventional therapies. In this study, the growth inhibitory effects of withanolide D (WND), a steroidal lactone isolated from Withania somnifera, on drug-sensitive tumoral plasma cells and drug-resistant MM cells have been investigated. In MTT/XTT assays, WND exhibited similar cytostatic effects between drug-resistant and drug-sensitive cell lines in the nM range. WND also induced cell death and apoptosis in MM-CSCs and RPMI 8226 cells, as examined by the calcein/ethidium homodimer and annexin V/propidium iodide stainings, respectively. To determine whether P-glycoprotein (P-gp) efflux affected the cytostatic activity of WND, P-gp was inhibited with verapamil and results indicated that the WND cytostatic effect in MM-CSCs was independent of P-gp efflux. Furthermore, WND did not increase the accumulation of the fluorescent P-gp substrate rhodamine 123 in MM-CSCs, suggesting that WND may not inhibit P-gp at the tested relevant doses. Therefore, the WND-induced cytostatic effect may be independent of P-gp efflux. These findings warrant further investigation of WND in MM-CSC animal models.
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Les modèles de régression dynamique et leurs applications en analyse de survie et fiabilité / Dynamic regression models and their applications in survival and reliability analysisTran, Xuan Quang 26 September 2014 (has links)
Cette thèse a été conçu pour explorer les modèles dynamiques de régression, d’évaluer les inférences statistiques pour l’analyse des données de survie et de fiabilité. Ces modèles de régression dynamiques que nous avons considérés, y compris le modèle des hasards proportionnels paramétriques et celui de la vie accélérée avec les variables qui peut-être dépendent du temps. Nous avons discuté des problèmes suivants dans cette thèse.Nous avons présenté tout d’abord une statistique de test du chi-deux généraliséeY2nquiest adaptative pour les données de survie et fiabilité en présence de trois cas, complètes,censurées à droite et censurées à droite avec les covariables. Nous avons présenté en détailla forme pratique deY2nstatistique en analyse des données de survie. Ensuite, nous avons considéré deux modèles paramétriques très flexibles, d’évaluer les significations statistiques pour ces modèles proposées en utilisantY2nstatistique. Ces modèles incluent du modèle de vie accélérés (AFT) et celui de hasards proportionnels (PH) basés sur la distribution de Hypertabastic. Ces deux modèles sont proposés pour étudier la distribution de l’analyse de la duré de survie en comparaison avec d’autre modèles paramétriques. Nous avons validé ces modèles paramétriques en utilisantY2n. Les études de simulation ont été conçus.Dans le dernier chapitre, nous avons proposé les applications de ces modèles paramétriques à trois données de bio-médicale. Le premier a été fait les données étendues des temps de rémission des patients de leucémie aiguë qui ont été proposées par Freireich et al. sur la comparaison de deux groupes de traitement avec des informations supplémentaires sur les log du blanc du nombre de globules. Elle a montré que le modèle Hypertabastic AFT est un modèle précis pour ces données. Le second a été fait sur l’étude de tumeur cérébrale avec les patients de gliome malin, ont été proposées par Sauerbrei & Schumacher. Elle a montré que le meilleur modèle est Hypertabastic PH à l’ajout de cinq variables de signification. La troisième demande a été faite sur les données de Semenova & Bitukov, à concernant les patients de myélome multiple. Nous n’avons pas proposé un modèle exactement pour ces données. En raison de cela était les intersections de temps de survie.Par conséquent, nous vous conseillons d’utiliser un autre modèle dynamique que le modèle de la Simple Cross-Effect à installer ces données. / This thesis was designed to explore the dynamic regression models, assessing the sta-tistical inference for the survival and reliability data analysis. These dynamic regressionmodels that we have been considered including the parametric proportional hazards andaccelerated failure time models contain the possibly time-dependent covariates. We dis-cussed the following problems in this thesis.At first, we presented a generalized chi-squared test statisticsY2nthat is a convenient tofit the survival and reliability data analysis in presence of three cases: complete, censoredand censored with covariates. We described in detail the theory and the mechanism to usedofY2ntest statistic in the survival and reliability data analysis. Next, we considered theflexible parametric models, evaluating the statistical significance of them by usingY2nandlog-likelihood test statistics. These parametric models include the accelerated failure time(AFT) and a proportional hazards (PH) models based on the Hypertabastic distribution.These two models are proposed to investigate the distribution of the survival and reliabilitydata in comparison with some other parametric models. The simulation studies were de-signed, to demonstrate the asymptotically normally distributed of the maximum likelihood estimators of Hypertabastic’s parameter, to validate of the asymptotically property of Y2n test statistic for Hypertabastic distribution when the right censoring probability equal 0% and 20%.n the last chapter, we applied those two parametric models above to three scenes ofthe real-life data. The first one was done the data set given by Freireich et al. on thecomparison of two treatment groups with additional information about log white blood cellcount, to test the ability of a therapy to prolong the remission times of the acute leukemiapatients. It showed that Hypertabastic AFT model is an accurate model for this dataset.The second one was done on the brain tumour study with malignant glioma patients, givenby Sauerbrei & Schumacher. It showed that the best model is Hypertabastic PH onadding five significance covariates. The third application was done on the data set given by Semenova & Bitukov on the survival times of the multiple myeloma patients. We did not propose an exactly model for this dataset. Because of that was an existing oneintersection of survival times. We, therefore, suggest fitting other dynamic model as SimpleCross-Effect model for this dataset.
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