Wong, Ling Yee. / Thesis submitted in: August 2007. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2008. / Includes bibliographical references (leaves 110-127). / Abstracts in English and Chinese. / Thesis Abstract --- p.i / 論文摘要 --- p.iv / Acknowledgements --- p.vi / Abbreviations --- p.vii / Thesis Content --- p.xii / List of Figures --- p.xv / List of Tables --- p.xvii / Chapter Chapter 1 --- Introduction --- p.1 / Chapter Chapter 2 --- Literature Review --- p.3 / Chapter 2.1. --- Multiple Myeloma (MM) --- p.3 / Chapter 2.1.1 --- Epidemiology --- p.4 / Chapter 2.1.2 --- Cause and Risk Factors --- p.5 / Chapter 2.1.3 --- Pathophysiology --- p.5 / Chapter 2.1.4 --- Diagnosis and Clinical Presentation --- p.6 / Chapter 2.1.5 --- Classification of Plasma Cell Disorders --- p.6 / Chapter 2.1.5.1 --- Monoclonal Gammopathy of Undetermined Significance (MGUS) --- p.6 / Chapter 2.1.5.2 --- Asymptomatic (Smouldering) MM --- p.7 / Chapter 2.1.5.3 --- Indolent MM --- p.7 / Chapter 2.1.5.4 --- Symptomatic MM --- p.8 / Chapter 2.1.6 --- Staging --- p.9 / Chapter 2.1.7 --- Treatment --- p.11 / Chapter 2.1.8 --- Molecular Abnormality --- p.12 / Chapter 2.2 --- DNA Microarray Analysis in MM --- p.13 / Chapter 2.2.1 --- MM Pathogenesis --- p.15 / Chapter 2.2.2 --- Molecular Classification of MM --- p.18 / Chapter 2.2.3 --- Anti-MM Drug Studies --- p.22 / Chapter 2.3 --- Cancer Treatment Response Prediction --- p.24 / Chapter 2.3.1 --- MP Treatment --- p.24 / Chapter 2.3.1.1 --- Melphalan --- p.25 / Chapter 2.3.1.2 --- Prednisone --- p.27 / Chapter 2.3.1.3 --- MP Treatment Response Prediction in MM --- p.29 / Chapter 2.3.2 --- Cancer Prognosis using DNA Microarray --- p.31 / Chapter Chapter 3 --- Materials and Methods --- p.36 / Chapter 3.1. --- Patient Specimens for Gene Expression Profiling and Quantitative Real-time PCR --- p.36 / Chapter 3.2. --- Magnetic Cell Sorting of CD138-positive Plasma Cells --- p.37 / Chapter 3.2.1 --- Density Gradient Centrifugation --- p.37 / Chapter 3.2.2 --- Positive Selection of CD138-positive Cells --- p.37 / Chapter 3.3 --- Generation of Gene Expression Profiles --- p.39 / Chapter 3.3.1 --- RNA Extraction --- p.39 / Chapter 3.3.2 --- RNA Assessment --- p.40 / Chapter 3.3.3 --- Synthesis and Purification of Double-strand cDNA --- p.40 / Chapter 3.3.4 --- In vitro Transcription (IVT) and Recovery of Biotin-labeled cRNA --- p.41 / Chapter 3.3.5 --- cRNA Fragmentation and Hybridization Reaction Mixture Preparation --- p.41 / Chapter 3.3.6 --- Hybridization --- p.42 / Chapter 3.3.7 --- Post-hybridization Wash --- p.42 / Chapter 3.3.8 --- Detection with Streptavidin-dye Conjugate --- p.43 / Chapter 3.3.9 --- Bioarray Scanning and Spot Signal Quantitation --- p.43 / Chapter 3.4 --- Microarray Data Analysis --- p.45 / Chapter 3.4.1 --- Normalization and Filtering --- p.45 / Chapter 3.4.2 --- Unsupervised Clustering Analysis --- p.45 / Chapter 3.4.3 --- Supervised Class Comparison Analysis --- p.46 / Chapter 3.5 --- Microarray Verification and Candidate Gene Validation --- p.47 / Chapter 3.5.1 --- RNA Extraction --- p.47 / Chapter 3.5.2 --- Reverse Transcription PCR --- p.47 / Chapter 3.5.3 --- Quantitative Real-time PCR --- p.48 / Chapter 3.6 --- Predictive Value Calculation --- p.49 / Chapter 3.7 --- Experimental Flow --- p.49 / Chapter Chapter 4 --- Results --- p.53 / Chapter 4.1 --- Gene Expression Profiling of Chinese MM --- p.53 / Chapter 4.1.1 --- Unsupervised Clustering Analysis --- p.53 / Chapter 4.1.1.1 --- Hierarchical Clustering --- p.53 / Chapter 4.1.1.2 --- Principal Component Analysis (PCA) --- p.54 / Chapter 4.1.2 --- Identification of Statistically Differentially Expressed Genes --- p.58 / Chapter 4.1.2.1 --- Two-Sample t-statistics --- p.58 / Chapter 4.1.2.2 --- Significance Analysis of Microarrays (SAM) --- p.58 / Chapter 4.1.2.3 --- Microarray Verification --- p.66 / Chapter 4.2 --- Development of MP Treatment Response Biomarker in MM --- p.70 / Chapter 4.2.1 --- Unsupervised Clustering Analysis --- p.70 / Chapter 4.2.1.1 --- Hierarchical Clustering --- p.70 / Chapter 4.2.1.2 --- PCA --- p.70 / Chapter 4.2.2 --- Identification of Statistically Differentially Expressed Genes --- p.74 / Chapter 4.2.2.1 --- Two sample t-statistics --- p.74 / Chapter 4.2.2.2 --- SAM --- p.74 / Chapter 4.2.3 --- Verification of Candidate Gene CYB5D1 --- p.76 / Chapter Chapter 5 --- Discussion --- p.79 / Chapter 5.1 --- Global Gene Expression Profiling: DNA Microarray --- p.79 / Chapter 5.2 --- Microarray Data Normalization and Gene Filtering --- p.81 / Chapter 5.3 --- Microarray Data Analysis --- p.83 / Chapter 5.3.1 --- Unsupervised Clustering Analysis --- p.83 / Chapter 5.3.1.1 --- Hierarchical Clustering --- p.83 / Chapter 5.3.1.2 --- PCA --- p.85 / Chapter 5.3.2 --- Identification of Statistically Differentially Expressed Genes --- p.86 / Chapter 5.4 --- Verification of Candidate Genes by Quantitative Real-time PCR --- p.89 / Chapter 5.5 --- Gene Expression Profiling of Chinese MM --- p.90 / Chapter 5.5.1 --- Comparison of Gene Expression Patterns of MM and Normal Plasma Cells --- p.90 / Chapter 5.5.2 --- Differentially Expressed Genes between MM and Normal Plasma Cells..… --- p.91 / Chapter 5.5.2.1 --- Common Differentially Expressed Genes with Previous Studies --- p.94 / Chapter 5.5.2.2 --- Potential Tumor Suppressor Genes in Differentially Expressed Genes..… --- p.96 / Chapter 5.5.2.3 --- Verified Differentially Expressed Genes --- p.98 / Chapter 5.5.3 --- Future Studies --- p.101 / Chapter 5.6 --- Development of MP Treatment Response Biomarker in MM --- p.103 / Chapter 5.6.1 --- Comparison of Gene Expression Patterns of MP Good Responders (GR) and Poor Responders (PR) --- p.103 / Chapter 5.6.2 --- Differentially Expressed Gene between MP GR and PR: CYB5D1 --- p.104 / Chapter 5.6.3 --- Possible Role of CYB5D1 in MP Resistance in MM Cells --- p.104 / Chapter 5.6.4 --- Potential Clinical Application of CYB5D1 in MP Treatment Response Prediction in MM --- p.106 / Chapter 5.6.5 --- Future Studies --- p.106 / Chapter Chapter 6 --- Conclusion --- p.108 / Chapter 6.1 --- Gene Expression Profiling of Chinese MM --- p.108 / Chapter 6.2 --- Development of MP Treatment Response Biomarker in MM --- p.108 / References --- p.110 / Appendix --- p.128

The ability of Candida albicans to change morphology plays several roles in its virulence and as a human commensal. The yeast-to-hyphae transition is tightly regulated by several sets of activating and repressing pathways. The DNA-binding proteins Rfg1p, Nrg1p and the global repressor Tup1p are part of the repressors found to regulate this morphogenesis. Knowledge of these repressors is based on extrapolations from homology to S. cerevisiae and from expression studies of mutants in inducing conditions, all of which are indirect means of determining a protein's function. We proposed a genome-wide location study of the Nrg1 and Rfg1 transcription factors to obtain direct data to identify their in vivo targets. Our results suggest different avenues for Nrg1p function and a regulation behaviour diverging from the previously suggested model: Nrg1p acts not only as a repressor but also as a transcription activator. Furthermore it regulates its target genes through binding in their coding regions instead binding to the expected regulatory elements on promoters.

Diss. (sammanfattning) Uppsala : Uppsala universitet, 2007. / Härtill 5 uppsatser.

Thesis (Ph. D.)--University of Washington, 2007. / Vita. Includes bibliographical references (p. 121-126).

Thesis (Ph. D.) -- University of Texas Southwestern Medical Center at Dallas, 2004. / Vita. Bibliography: References located at the end of each chapter.

Thesis (Ph.D. in Human Medical Genetics) -- University of Colorado at Denver and Health Sciences Center, 2005. / Typescript. Includes bibliographical references (leaves 104-138). Free to UCDHSC affiliates. Online version available via ProQuest Digital Dissertations;

Baixos níveis séricos de 25(OH)D3 e 1,25(OH)2D3 (calcitriol) podem estar associados à incidência e prognóstico do câncer de mama. Além disso, vários estudos indicam que a vitamina D tenha um efeito antiproliferativo em linhagens celulares de câncer de mama expostas a concentrações supra-fisiológicas de calcitriol (1,25(OH)2D3, 100nM). A suplementação com vitamina D é indicada a mulheres pós-menopausadas para prevenção de osteoporose e observamos previamente que a suplementação de calcitirol a pacientes pós-menopausadas com câncer de mama causa redução do índice proliferativo tumoral. Entretanto, não há estudos até o momento que avaliam o efeito da vitamina D na expressão gênica global in vivo. Incluímos 31 pacientes pós-menopausadas com câncer de mama. Estas pacientes realizaram suplementação com calcitriol (0,5g/dia, dose indicada para prevenção de osteoporose) por um curto período de tempo (mediana de 32 dias). A amostra tumoral foi coletada por ocasião da biópsia (présuplementação) e da ressecção tumoral (pós-suplementação). Os perfis de expressão gênica de 16 pacientes foram analisados a partir de 100ng de RNA total no gene chip U133 Plus 2.0 Affymetrix. Observamos redução na expressão de Ki-67 após a suplementação. Dentre os genes diferencialmente expressos encontram-se EGR1, FOS, DUSP1, MMP12 e RGS1, os quais foram mais expressos em amostras pós-suplementadas. Genes modulados pela vitamina D estão associados à resposta inflamatória e à membrana. Nossos resultados indicam que a suplementação com vitamina D reduz o índice de proliferação tumoral, sendo a mesma envolvida em vias importantes na regulação da resposta inflamatória / Low 25(OH)2D3 or 1,25(OH)2D3 serum levels may be associated with breast cancer incidence and prognosis. Additionally, the antiproliferative effects of vitamin D are observed in breast cancer cell lines exposed to phamacological doses of calcitriol (1,25(OH)2D3, 100nM). Vitamin D supplementation is indicated for post-menopausal women to prevent osteoporosis and a previous study from our group observed a reduced tumor proliferative index after calcitriol supplementation on post menopausal breast cancer patients. However, there is no study that verifies the effect of vitamin D on gene expression profile in vivo so far. Thirty one post menopausal breast cancer patients were included on our analysis. They were supplemented with calcitriol after tumor biopsy (0.50g/day, indicated dose for osteoporosis prevention) for a short period of time (median 32 days). Tumor samples were collected during biopsy (before supplementation) and breast surgery (after supplementation). Gene expression profile of 16 patients was analyzed using the U133 Plus 2.0 Affymetrix Gene Chips from 100ng of total RNA. After supplementation, a reduced expression of Ki-67 was observed. Among the differentially expressed genes, EGR1, FOS, DUSP1, MMP12 and RGS1 were upregulated after calcitriol supplementation. Differentially expressed genes were involved in inflammatory response or were associated with the membrane. Our results indicate that calcitriol supplementation diminish tumor proliferation index regulating inflammatory pathways .

No description available.

Aplicando tecnologia de microarray, objetivamos traçar o perfil do programa de maturação das Mo-DC pulsadas com HIV autólogo inativado por AT-2, a fim de identificar marcadores específicos de ativação funcional e sugerir um perfil de expressão de genes úteis na identificação de respostas ao modelo in vitro das Mo-vacina DC. Essas informações podem ajudar a estabelecer assinaturas moleculares das funções celulares mais relevante para a melhoria das vacinas terapêuticas. O perfil transcricional foi analisado com base das vias celulares moduladas das Mo-DCs no estado imaturo, transitório e maduro. O HIV-1 inativado por AT-2 induz ativação de genes associados à apresentação de antígenos. Os conjuntos de genes do citoesqueleto podem influenciar a mudança de comportamento migratório das Mo-DCs ativadas. O aumento na expressão dos receptores celulares contribuem para o recrutamento de monócitos, DCs e macrófagos para o local da infecção. Além disso, modulam a resposta imune inata e adaptativa, incluindo a polarização das células Th e sub-regulação da resposta inflamatória, que pode interferir significativamente com a resposta imune. Coletivamente, o perfil transcricional das Mo-DCs induzido pelo HIV-1 inativado com AT-2 reflete uma significativa reprogramação imunológica e celular das células envolvidas na resposta imune do hospedeiro. Os resultados deste estudo focaram na interpretação de genes específicos dos perfis de transcrição das Mo-DCs como modelo terapêutico utilizado na vacina anti-HIV. As análises de assinaturas gene associado e sua correlação as respostas funcionais simplificam a identificação de indivíduos susceptíveis a vacina e a compreensão de eventuais falhas em ensaios clínicos. Microarray permitiu a análise quantitativa e simultânea da expressão de um elevado número de genes. Os estudos do perfil de expressão foram extremamente úteis para identificar os eventos moleculares e vias envolvidas nas funções de celular induzida por estímulos específicos. Em particular, os resultados sobre o padrão global da expressão dos genes subjacentes as modificações induzidas pelo HIV-1 inativado por AT-2, na fase inicial da administração do antígeno, pôde ser extremamente útil para a identificarmos marcadores de ativação e avaliar os efeitos biológicos que poderiam estar envolvidos para modificação e otimização de estratégias vacinação com Mo-DC / Applying microarray technology, we intend to profile the program to mature Mo-DC pulsed with autologous inactivated HIV by AT-2, in order to identify specific markers of functional activation and suggest a profile of expression of specific genes, useful identification of responders to in vitro model of Mo-DC vaccine. Such information may help to establish detailed molecular signatures of cellular functions most relevant to improving the therapeutic vaccines. The transcriptional profile was analyzed on the basis of the cellular pathways modulated in immature MoDC, transitional MoDC and mature MoDC. The AT-2-inactivated HIV-1 induction of MoDC results in the activation of genes associated with antigen presentation functions. A set of cytoskeletal genes that may potentially mediate shape change and migratory behavior of activated MoDC is also observed. The increase in the expression of immune receptors contribute to the recruitment of monocytes, DCs, and macrophages to the site of infection. Moreover, they modulate both innate and adaptive immune response, including the polarization of Th cells, and the down-regulation of the inflammatory response, which may significantly interfere with the immune response. Collectively, the transcriptional profile induced by AT-2-inactivated HIV-1 in MoDc reflects a significant cellular and immunological reprogramming of cells directly involved in the host immune response. The results of this study focused on the interpretation of specific genes of transcription profile of MoDC used in therapeutic HIV vaccine model. Supplementing the analyses with examination of associated gene signatures and their correlation to functional responses will simplify the identification of responsive vaccine individuals and the understanding of eventual failures in individuals enrolled in clinical trials. Microarray approach allows quantitative and simultaneous analysis of gene expression of a large amount of genes and the systematic studies of expression patterns are extremely useful for identify molecular events and key pathways involved in cellular functions induced by specific stimuli. In particular, data on the global pattern of gene expression underlying the modifications induced by AT-2-inactivated HIV-1 in MoDC, at early stages of antigen administration, may be extremely helpful for the identification of exclusive activation markers to trace the biological effects of modifications/optimizations of the MoDc vaccination strategy

O receptor ativado do peroxissomo γ (PPAR-γ) é regulador do metabolismo e diferenciação do tecido adiposo, sendo um alvo conhecido das tiazolidinedionas (TZD), utilizadas para o tratamento do diabetes tipo 2 (DM2). As TZD agem como um agente sensibilizador da ação da insulina nos tecidos periféricos e tem sido especulado que as TZDs podem ter um papel na função da célula , prevenindo perda de massa e melhorando a sua viabilidade a longo prazo. Este efeito seria supostamente mediado pela transcrição de genes que favoreceriam a lipólise, diminuindo o conteúdo intracelular de triglicérides e, portanto, diminuindo a lipotoxicidade. Entretanto, alguns estudos também mostraram efeito nulo ou mesmo deletério das TZDs sobre as ilhotas pancreáticas. Na realidade, o papel de genes-alvo para o PPAR- nas ilhotas pancreáticas é ainda pouco conhecido. Estudamos o perfil de expressão gênica induzido pelo tratamento com Pioglitazona (Pio), uma TZD aprovada e disponível para uso clínico no tratamento do DM2, em ilhotas pancreáticas murídeas em cultura primária, com concentrações normal e suprafisiológica de glicose no meio de cultura. As ilhotas foram obtidas de ratos wistar machos de dois meses de idade e isoladas pelo método do gradiente de Ficoll e então cultivadas em 5,6 mM ou 23 mM de glicose por 24h, sendo tratadas com Pio 10 M ou DMSO 0,1% (veículo). A Pioglitazona foi cedida pela Takeda Farmacêutica, Osaka, Japão. O RNA foi extraído com Trizol e purificado com o kit RNeasy (Qiagen). As amostras foram marcadas e hibridizadas no microarranjo de cDNA Mouse Panchip 13k, usando-se cinco replicatas biológicas diferentes para cada condição. A análise estatística dos dados do microarranjo foi feita com o uso do programa significance analysis of microarrays (SAM) com uso de taxa de descobrimento falso (FDR) de 20%. A análise das vias acometidas foi feita com o Ingenuity Pathway Analysis (www.ingenuity.com). Os resultados de expressão gênica foram confirmados por RT-qPCR. Em concentração de 5,6 mM de glicose no meio de cultura, 101 genes foram modulados pela Pio, sendo 49 regulados para cima, com aumento de sua expressão na presença da droga e 52 genes regulados para baixo. Em 23 mM de glicose, 1.235 genes foram afetados, sendo 621 para cima e 623 para baixo. A comparação entre as duas condições revelou 74 genes que foram modulados em ambas as concentrações de glicose. A análise das vias biológicas alteradas mostrou que genes relacionados ao metabolismo de lípides foram modulados em ambas as concentrações de glicose. Em 23 mM foi ainda significativo o grupo de genes relacionados a ciclo celular e morte celular que tiveram sua expressão modificada pela presença da droga na cultura. Este dado demonstrou que além de seus efeitos conhecidos nos adipócitos, o sensibilizador de insulina Pioglitazona modula a expressão de genes nas ilhotas pancreáticas, especialmente na presença de concentrações suprafisiológicas de glicose, afetando notadamente genes relacionados ao metabolismo lipídico, sendo vários deles ligados a lipogênese, como Srebf1, Scd2 e Fabp4 cujas expressões aumentaram em ambas as concentrações de glicose. Além disso foi observado aumento na expressão de genes com atividade pró-apoptótica como Tnf, Bad, Bax, Caspase4, Fadd e Myc. A Pioglitazona parece induzir um perfil gênico desfavorável em ilhotas pancreáticas mantidas em cultura em concentrações suprafisiológicas de glicose. / Peroxisome proliferator-activator receptor-γ (PPAR-γ) is a target for thiazolidinedione (TZD) antidiabetic drugs and a regulator of adipose tissue differentiation and metabolism. TZD act as an insulin sensitizing agent on peripheral tissues. It has been speculated that TZD could play a role on beta-cell function, preventing loss and improving viability in the long-term. This effect is supposed to be mediated through a potential benefit against lipotoxicity, favouring lypolisis and decreasing intracellular tryglicerides content. Nevertheless some studies also showed a lack or even a potential deleterious effect of TZD on islets. The role of PPAR-γ target genes in pancreatic islets is actually still largely unclear. We studied the gene expression profile induced by the treatment with Pioglitazone (Pio), an approved TZD for T2DM therapy, on rat pancreatic islets primary culture both at normal and supraphysiological glucose medium concentrations. Islets were obtained from 2 month-old, male, wistar rats and isolated through the Ficoll gradient method and then cultured with 5.6 mM or 23 mM of glucose concentration for 24h, being treated with Pio 10 µM or DMSO 0.1% (vehicle). Pioglitazone was provided by Takeda Pharmaceuticals, Osaka, Japan. RNA was extracted with Trizol (Sigma) and purified with RNeasy kit (Qiagen). Samples were labeled and then hybridized on the Mouse PanChip 13k cDNA microarray, using 5 different biological replicates for each test condition. Statistical Analysis of the microarray data was performed using significance analysis of microarrays (SAM) with a false discovery rate of 20%. Pathways assessment was performed through Ingenuity Pathway Analysis (www.ingenuity.com). Gene expression results were confirmed through RT-qPCR. At 5.6 mM glucose 101 genes were modulated by Pio, 49 upregulated and 52 downregulated. At 23 mM, 1,235 genes were affected, 612 upregulated and 623 downregulated. Comparison between both conditions revealed 74 genes that were similarly modulated at both glucose concentrations. Pathway analysis of perturbed genes revealed biologically relevant networks related to lipid metabolism at both glucose medium concentrations. At 23 mM, cell cycle and cell death pathways were significant modulated as well. These data demonstrates that in addition to known effect in adipocytes, the insulin sensitizing agent Pioglitazone modulates gene expression in pancreatic islets, especially in the presence of supraphysiological glucose concentrations, affecting especially lipid metabolism and mechanisms of cell death and cell cycle. Considering the ontology of modulated genes it seems to be a trend towards lypogenesis (increased Srebf1, Scd2 and Fabp4 RNA expressions) with Pio treatment also enhancing the abundance of some genes considered to be pro apoptotic like Tnf, Bad, Bax, Caspase4, Fadd and Myc. Pioglitazone seems to induce a negative gene expression profile in islets cultured at high glucose concentrations.