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Expression profiling by DNA microarrays [Elektronische Ressource] : development of amplification methods for the analysis of minimal tumor samples / presented by Jörg Schlingemann

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156 pages
Expression Profiling by DNA Microarrays: Development of Amplification Methods for the Analysis of Minimal Tumor Samples DISSERTATION submitted to the Combined Faculties for the Natural Sciences and Mathematics of the Ruperto-Carola-University of Heidelberg for the degree of Doctor of Natural Sciences presented by DIPL.-BIOL. JÖRG SCHLINGEMANN born in Hagen in 1975 2005 DISSERTATION submitted to the Combined Faculties for the Natural Sciences and Mathematics of the Ruperto-Carola-University of Heidelberg for the degree of Doctor of Natural Sciences presented by DIPL.-BIOL. JÖRG SCHLINGEMANN born in Hagen in 1975 thoral examination: September 30 , 2005 Expression Profiling by DNA Microarrays: Development of Amplification Methods for the Analysis of Minimal Tumor Samples Referees: PD Dr. Karsten Rippe Prof. Dr. Peter Lichter T ABLE OF CONTENTS V I. TABLE OF CONTENTS P AGE I. TABLE OF CONTENTS V II. PUBLICATIONS, PEER-REVIEWED IX III. P, NON PEER-REVIEWED IV. POSTERS X V. ACKNOWLEDGEMENTS XI VI. ABBREVIATIONS XII VII. ABSTRACT XV VIII. ZUSAMMENFASSUNG XVI 1 INTRODUCTION 1 1.1 Cancer Statistics 2 1.2 The Human Genome 5 1.3 Genetic Aberrations of Cancer Cells 7 1.3.1 Oncogenes 7 1.3.2 Tumor Suppressor Genes 9 ‘Mutator Genes’ 10 1.4 Multistage Carcinogenesis 11 1.
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Expression Profiling by DNA Microarrays:
Development of Amplification Methods
for the Analysis of Minimal Tumor Samples






DISSERTATION

submitted to the
Combined Faculties for the Natural Sciences and Mathematics
of the Ruperto-Carola-University of Heidelberg
for the degree of
Doctor of Natural Sciences


presented by
DIPL.-BIOL. JÖRG SCHLINGEMANN
born in Hagen in 1975


2005




DISSERTATION

submitted to the
Combined Faculties for the Natural Sciences and Mathematics
of the Ruperto-Carola-University of Heidelberg
for the degree of
Doctor of Natural Sciences









presented by
DIPL.-BIOL. JÖRG SCHLINGEMANN
born in Hagen in 1975



thoral examination: September 30 , 2005





Expression Profiling by DNA Microarrays:
Development of Amplification Methods
for the Analysis of Minimal Tumor Samples
















Referees:

PD Dr. Karsten Rippe
Prof. Dr. Peter Lichter


T ABLE OF CONTENTS V

I. TABLE OF CONTENTS P AGE

I. TABLE OF CONTENTS V
II. PUBLICATIONS, PEER-REVIEWED IX
III. P, NON PEER-REVIEWED
IV. POSTERS X
V. ACKNOWLEDGEMENTS XI
VI. ABBREVIATIONS XII
VII. ABSTRACT XV
VIII. ZUSAMMENFASSUNG XVI

1 INTRODUCTION 1
1.1 Cancer Statistics 2
1.2 The Human Genome 5
1.3 Genetic Aberrations of Cancer Cells 7
1.3.1 Oncogenes 7
1.3.2 Tumor Suppressor Genes 9 ‘Mutator Genes’ 10
1.4 Multistage Carcinogenesis 11
1.5 Microarray Technology in Cancer Research 12
1.6 RNA Amplification 16
1.7 Signal 21
1.7.1 Phage Ф29 22
1.7.2 Rolling Circle Replication 23
1.8 Objective 26


VI TABLE OF CONTENTS

2 MATERIALS AND METHODS 28
2.1 Materials 28
2.1.1 Chemicals and Biochemicals
2.1.2 Enzyme 29
2.1.3 Kits 30
2.1.4 Other Materials
2.1.5 Instruments 31
2.1.6 Software 32
2.1.7 Standard Solutions
2.1.8 Human Total RNA 33
2.2 Tumor Samples 34
2.2.1 Human HNSCC Tumor Samples
2.3 RNA Extraction 35
2.3.1 RNA Extraction from Tissue Samples 35
2.3.2 RNA Quantitation by Spectrophotometry 35
2.3.3 Assessment of RNA Integrity and Purity 36
2.4 Oligonucleotides 38
2.4.1 Probe Sequences for High-Density Oligonucleotide Microarrays
2.4.2 Primer Sequences for RQ-PCR Analysis 38
2.4.3 Padlock Probes and Associated Sequences for RCA on Microarrays 39
2.5 Oligonucleotide Microarrays 40
2.5.1 Preparation of Fluorescent Targets 2.5.1.1 Reverse Transcriptase (RT) Labeling 40
2.5.1.2 TAcKLE 40
2.5.1.3Sample Purification 41
2.5.2 Preparation and Post-Processing of Microarrays 42
2.5.2.1 Microarray Spotting 42
2.5.2.2 DNA Immobilization 42
2.5.3 Microarray Hybridization
2.5.4 Data Acquisition 43
2.5.5 Affymetrix GeneChip Arrays
2.5.6 Data Processing and Analysis 44
2.5.6.1 Data Normalization 44
2.5.6.2Filtering
2.5.6.3 Orthogonal Regression and Pearson Correlation 45
2.5.6.4 Linear Modeling 45
2.5.6.5Identification of Differentially Expressed Genes 46
2.5.6.6 Distance Weighted Discrimination 46
2.5.6.7GO Data Mining and EASE Overrepresentation Analysis 46
2.5.6.8 Matching of Oligonucleotide Probe Sequences 46
T ABLE OF CONTENTS VII

2.5.7 Accession Numbers 47
2.6 RQ-PCR Analysis 48
2.7 Rolling Circle Amplification 49
2.7.1 Padlock Probe Ligation 49
2.7.2 Purification of Circularized Padlock Probes 49
2.7.3 Reverse Transcription with Aminoallyl-dUTP 49
2.7.4 Psoralen Conjugation (Preparation of cDNA-Psoralen Conjugates) 50
2.7.5 Photoreactive Coupling 51
2.7.6 Rolling Circle Amplification on Oligonucleotide Microarrays 52

3 RESULTS 54
3.1 Target Amplification for Oligonucleotide Microarrays 54
3.1.1 Motivation 54
3.1.2 Protocol Variants 55
3.1.3 T7 Amplification and cDNA Klenow Labeling for Expression Analysis 59
3.1.4 Experimental Design 62
3.1.5 Reproducibility of Amplification 63
3.1.6 Reproducibility of Expression Ratios with and without Dye Swap 65
3.1.7 Comparison of Amplified and Unamplified Targets 68
3.1.8 Linear Modeling and Statistical Analysis 70
3.2 Signal Amplification by Rolling Circle Replication 74
3.2.1 Motivation 74
3.2.2 Preparatory Experiments 75
3.2.3 The Challenge Caused by Long Amplification Products 76
3.2.4 Two-Color Hybridizations 78
3.3 Cross-Platform Reproducibility of Expression Profiles 80
3.3.1 Motivation 80
3.3.2 Experimental Design 82
3.3.3 Probe Matching 83
3.3.4 Intra-Platform Reproducibility of Expression Ratios 84
3.3.5 Cross-Platform Reproducibility of Expression Ratios 84
3.3.6 Systematic Bias Correction by ‘Distance Weighted Discrimination’ 86
3.3.7 Significant Differences and Similarities 87
3.3.8 RQ-PCR Analysis 93
VIII TABLE OF CONTENTS

4 DISCUSSION 94
4.1 The TAcKLE Protocol 94
4.2 RCA for Microarray Expression Analyis 99
4.3 Comparison of Oligonucleotide Microarray Platforms 103
4.4 Conclusions and Perspectives 108

5 REFERENCES 111

6 APPENDIX 128
6.1 R Scripts for the Comparison of Microarray Platforms 128
6.1.1 Normalization of Affymetrix GeneChip Data (affynorm.R) 129
6.1.2 Matching of Oligonucleotide Probe Sequences (alignment.R) 131
6.1.3 Comparison of Operon and Affymatrix GeneChip Data (compare.R) 133