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ROLE OF THE PROLIFERATION-RELATED MOLECULES IN THE PATHOGENESIS OF ALZHEIMER’S DISEASE By SHARON CHRISTINE YATES A thesis submitted to the University of Birmingham for the degree of Master of Philosophy Clinical and Experimental Medicine The Medical School University of Birmingham April 2012 University of Birmingham Research Archive e-theses repository This unpublished thesis/dissertation is copyright of the author and/or third parties. The intellectual property rights of the author or third parties in respect of this work are as defined by The Copyright Designs and Patents Act 1988 or as modified by any successor legislation. Any use made of information contained in this thesis/dissertation must be in accordance with that legislation and must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the permission of the copyright holder. ABSTRACT The cell cycle theory of Alzheimer’s Disease (AD) states that neurodegeneration is secondary to aberrant cell cycle activity in neurons. Previous studies suggest that this may be partly attributed to alterations in the mTOR pathway, which promotes cell growth and division, and partly to genetic variants on genes responsible for cell cycle control. In this study we perform a systematic analysis of the rapamycin-regulated genes that are differentially regulated in brain affected by AD compared to control. These genes may serve as novel therapeutic targets or biomarkers of AD. Secondly, we investigate the association of a cancer-associated variant of p21cip1, and a variant of p57kip2, with AD. These cyclin dependent kinase inhibitors are crucial cell cycle regulatory components that function downstream of mTOR. We confirm the association of the p21cip1 SNPs with AD, and inform on the mechanisms by which they cause loss of function. We also show a weak association between variant p57kip2 and AD. Furthermore, we demonstrate that p57kip2 is differentially imprinted in the frontal and occipital lobe; and suggest that AD may be associated with change in the imprinting status of p57kip2 in the brain. ACKNOWLEDGEMENTS I would like to express my gratitude to Zsuzsanna Nagy for her help and support during the course of this MPhil. Without her encouragement it is doubtful I would have started. Secondly, I would like to thank Roy Bicknell, my second supervisor, for his expert advice. I am grateful to Cytox Ltd for financing this study; and to the Oxford Project to Investigate Memory and Aging for providing the necessary resources. Without the contribution of the many patients, carers and staff involved, this study would not have been possible. I would also like to thank my co-workers- Erzsebet Rabai, Amen Zafar, Sheila Nagy, Sarah Durant, and Ghaniah Hassan-Smith- for technical help, encouragement, and friendship during the many months of hard work. The experience was made more enjoyable by your presence. And finally, I am grateful to my husband, Tom Yates, for marrying me at the start of this MPhil, and supporting me throughout; and my family and friends for hours of trying to understand its subject matter. TABLE OF CONTENTS 1. INTRODUCTION .................................................................................................. 1 1.1. Pathological hallmarks of AD ...................................................................................... 1 1.2. Diagnosis ...................................................................................................................... 2 1.3. Treatment and Biomarkers of disease .......................................................................... 3 1.4. AD pathogenesis .......................................................................................................... 3 1.5. Role of the cell cycle in AD ......................................................................................... 5 1.5.1 The cell cycle ........................................................................................................ 5 1.6. Cell cycle regulatory failure in AD .............................................................................. 7 1.7. mTOR pathway ............................................................................................................ 9 1.8. Cyclin dependent kinase inhibitors (CDKI)............................................................... 12 1.9. Aims ........................................................................................................................... 16 2. MATERIALS AND METHODS ................................................................ 18 2.1. Patients and Biomaterials ........................................................................................... 18 2.2. DNA, RNA and protein extraction ............................................................................ 18 2.3. Gene expression microarray ...................................................................................... 21 2.3.1 Two-colour microarray based gene expression analysis .................................... 21 2.3.1.1. Conversion of RNA to cDNA ......................................................................... 22 2.3.1.2. Conversion of cDNA to labelled cRNA ......................................................... 23 2.3.1.3. cRNA purification and quantification ............................................................. 24 2.3.1.4. Hybridisation ................................................................................................... 25 2.3.1.5. Data analysis: microarray................................................................................ 27 2.3.2 One-colour custom microarray based gene expression analysis (Agilent) ......... 27 2.3.2.1. Sample preparation ......................................................................................... 28 2.3.2.2. Conversion of RNA to labelled cRNA ........................................................... 28 2.3.2.3. Hybridisation ................................................................................................... 29 2.3.2.4. Data analysis: microarray................................................................................ 30 2.4. Q-PCR validation of Microarray results .................................................................... 32 2.4.1 Data analysis: Q-PCR ......................................................................................... 34 2.5. p21cip1 and p57kip2 genotyping ................................................................................... 35 2.5.1 p21cip1 genotyping: SNP A ................................................................................. 35 2.5.2 p21cip1 genotyping: SNP B .................................................................................. 37 2.5.3 p57kip2 genotyping............................................................................................... 39 2.5.4 p57kip2 imprinting status...................................................................................... 41 2.6. ELISA: Quantification of AD-related pathology ....................................................... 42 2.6.1 Method: ELISA .................................................................................................. 43 2.6.2 Data analysis: ELISA ......................................................................................... 45 2.7. SNP dependent Q-PCR .............................................................................................. 45 2.7.1 Data analysis: SNP dependent Q-PCR ............................................................... 47 2.8. p21cip1 and p57kip2 Q-PCR .......................................................................................... 48 2.9. Cell culture and transfection ...................................................................................... 50 2.9.1 p21cip1 Q-PCR ..................................................................................................... 50 2.9.2 Data analysis ....................................................................................................... 51 2.10. Statistical analysis ...................................................................................................... 51 3. RESULTS .................................................................................................................. 53 3.1. Altered Rapamycin response elements in the brain of Alzheimer’s disease patients ......................................................................................................................... 53 3.1.1 Rapamycin-regulated genes ................................................................................ 54 3.1.2 Altered rapamycin-response elements as a result of mild AD ........................... 55 3.1.2.1. Associated pathways, networks and functions ................................................ 56 3.1.3 Altered rapamycin-response elements as a result of advanced AD .................... 58 3.1.3.1. Associated pathways, networks and functions ................................................ 59 3.1.4 Altered rapamycin-response elements as a result of the ApoE 4 allele ............ 62 3.1.4.1. Associated pathways, networks and functions ................................................ 63 3.1.5 Altered rapamycin-response elements in AD irrespective of severity of AD .... 66 3.1.6 Microarray validation ......................................................................................... 67 3.1.7 Q-PCR validation of microarray ........................................................................
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  • Pancreatic Cancer Metabolism

    Pancreatic Cancer Metabolism

    Published OnlineFirst March 3, 2017; DOI: 10.1158/2159-8290.CD-RW2017-044 RESEARCH WATCH Pancreatic Cancer Major finding: PanNET mutations affect Concept: Comprehensive molecular anal- Impact: The comprehensive identifica- DNA damage repair, chromatin remodeling, ysis of 102 clinically sporadic PanNETs tion of PanNET genetic alterations may telomere maintenance, and mTOR signaling. uncovers essential PanNET pathways. aid risk stratification and treatment. WHOLE-GENOME SEQUENCING DEFINES THE MUTATIONAL LANDSCAPE OF PanNETS Pancreatic neuroendocrine tumors (PanNET) are exhibited increased telomere length. There were classifi ed into three groups: low grade (G1), inter- an average of 29 structural rearrangements per mediate grade (G2), and high grade (G3). G3 Pan- tumor, with rearrangements leading to inactiva- NETs have a universally poor prognosis, whereas tion of tumor suppressors such as MTAP, ARID2, G1 and G2 tumors have an unpredictable clinical SMARCA4, MLL3, CDKN2A, and SETD2, or creating course. A better understanding of the molecular oncogenic gene fusions. In total, 66 somatic in- underpinnings of the disease may enable better frame gene fusions were identifi ed, including three risk stratifi cation and the identifi cation of patients EWSR1 fusion events leading to EWSR1–BEND2 or who might benefi t from early aggressive therapy. Scarpa and EWSR1–FLI1. Although EWSR1–FLI1 is a characteristic Ewing colleagues performed comprehensive molecular analyses of sarcoma fusion gene, the morphologic and pathologic features 102 clinically sporadic PanNETs. Whole-genome sequencing were consistent with PanNETs. RNA sequencing of 30 Pan- of 98 PanNETs defi ned fi ve distinct mutational signatures: NET tumors found that common genetic alterations affected MUTYH, APOBEC, BRCA-defi ciency, age, and COSMIC signa- DNA damage and repair, chromatin remodeling, telomere ture 5.