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Gene Expression and DNA Methylation in Acute Lymphoblastic

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Gene Expression and DNA Methylation in Acute Lymphoblastic In memory of Mimi Nordlund List of Papers This thesis is based on the following papers, which are referred to in the text by their Roman numerals. I Nordlund J, Kiialainen A, Karlberg O, Berglund EC, Göransson- Kultima H, Sønderkær M, Nielsen KL, Gustafsson MG, Behrendtz M, Forestier E, Perkkiö M, Söderhäll S, Lönnerholm G, Syvänen A- C. (2012) Digital gene expression profiling of primary acute lym- phoblastic leukemia cells. Leukemia, 6(26):1218-1227 II Milani L, Lundmark A, Nordlund J, Kiialainen A, Flaegstad T, Jonmundsson G, Kanerva J, Schmiegelow K, Gunderson KL, Lön- nerholm G, Syvänen A-C. (2009) Allele-specific gene expression patterns in primary leukemic cells reveal regulation of gene expres- sion by CpG site methylation. Genome Research, 19:1-11 III Nordlund J, Milani L, Lundmark A, Lönnerholm G, Syvänen A-C. (2012) DNA methylation analysis of bone marrow cells at diagnosis of acute lymphoblastic leukemia and at remission. PLoS ONE, 7(4) IV Nordlund J*, Bäcklin C*, Wahlberg P, Busche S, Berglund EC, El- oranta M-L, Flaegstad T, Forestier E, Frost B-M, Harila-Saari A, Heyman M, Jonsson O, Larsson R, Palle J, Rönnblom L, Schmie- gelow K, Sinnett D, Söderhäll S, Pastinen T, Gustafsson MG, Lön- nerholm G, Syvänen A-C. (2012) DNA hypermethylation signatures for genetic subtypes of pediatric ALL at diagnosis and relapse. Man- uscript. * Equally contributing authors Reprints were made with permission from the respective publishers. Related Paper Milani L*, Lundmark A*, Kiialainen A, Nordlund J, Flaegstad T, Forestier E, Heyman M, Jonmundsson G, Kanerva J, Schmiegelow K, Söderhäll S, Gustafsson MG, Lönnerholm G, Syvänen A-C (2010) DNA methylation for subtype classification and prediction of treatment outcome in patients with childhood acute lymphoblastic leukemia. Blood, 11;115(6) Contents Introduction ................................................................................................... 11 Acute Lymphoblastic Leukemia ............................................................... 11 Cytogenetic Classification of ALL ...................................................... 12 Clinical Implications ............................................................................ 15 Genetic Variation in the Human Genome ................................................ 16 Genetic Variation and Risk of ALL ..................................................... 17 Somatic Genetic Variation in ALL ...................................................... 18 The Human Epigenome ............................................................................ 19 Histone modifications .......................................................................... 19 DNA Methylation ................................................................................ 20 DNA Methylation and Cancer ............................................................. 21 Epigenetics in ALL .............................................................................. 22 Cooperation of Genetic and Epigenetic Mechanisms in Cancer .............. 23 Gene Expression ....................................................................................... 23 Allele-Specific Gene Expression ......................................................... 24 Gene Expression Profiling in ALL ...................................................... 25 Technologies for Genome-Scale Analysis ............................................... 25 Array-Based Technologies ................................................................... 25 Sequencing-Based Technologies ......................................................... 26 Present Investigations .................................................................................... 28 Thesis Aims .............................................................................................. 28 Materials and Methods ............................................................................. 28 Samples ................................................................................................ 28 Digital Gene Expression Profiling (Paper I) ........................................ 30 SNP Genotyping of DNA and RNA (Paper II) .................................... 30 DNA Methylation Analyses (Papers II, III & IV) ............................... 31 Bioinformatics and Statistical Analyses (Papers I-IV) ........................ 31 Results ...................................................................................................... 33 Genome-Wide Gene Expression in ALL Cells (Paper I) ..................... 33 Allele-Specific Gene Expression in ALL Cells (Paper II) ................... 33 DNA Methylation at Diagnosis of ALL and Remission (Paper III) ...... 34 Genome-Wide DNA methylation Analysis in a Large ALL Cohort (Paper IV) ............................................................................................. 34 Discussion ................................................................................................. 36 Concluding Remarks ................................................................................ 38 Acknowledgements ....................................................................................... 40 References ..................................................................................................... 43 Abbreviations 5mC 5-Methylcytosine ABL1 C-abl oncogene, non-receptor tyrosine kinase ALL Acute lymphoblastic leukemia APA Alternative polyadenylation ASE Allele-specific expression BCP-ALL B-cell precursor ALL BCR Breakpoint cluster region bp Base-pair cDNA Complementary DNA ChIP-seq Chromatin immunoprecipitation sequencing CML Chronic myeloid leukemia CNA Copy number alteration CNV Copy number variation CpG CG dinucleotide DGE Digital gene expression DNMT DNA methyltransferase E2A Transcription factor 3 (E2A immunoglobulin enhanc- er binding factors E12/E47) ENCODE Encyclopedia of DNA Elements ETV6 Ets variant 6 (TEL oncogene) EZH2 Histone-lysine N-methyltransferase FDR False discovery rate GWAS Genome-wide association study HeH High hyperdiploidy miRNA Micro RNA MLL Myeloid/lymphoid or mixed lineage leukemia MRD Minimum residual disease ncRNA Non-coding RNA NOPHO Nordic Society of Pediatric Hematology & Oncology NSC Nearest shrunken centroids nsSNP Non-synonymous SNP PBX1 Pre-B leukemia homobox 1 PCA Principal component analysis PcG Polycomb-group PCR Polymerase chain reaction RNA-seq Transcriptome (RNA) sequencing RT-PCR Reverse transcription PCR RUNX1 Runt-related transcription factor 1 SAGE Serial analysis of gene expression SNP Single nucleotide polymorphism SNV Single nucleotide variation SV Structural variation T-ALL T-cell acute lymphoblastic leukemia TPM Tags per million TPMT Thiopurine s-methylstransferase TSS Transcription start site UTR Untranslated region WGA Whole-genome amplification WGBS Whole-genome bisulfite sequencing WGS Whole-genome sequencing Introduction Over the last decade, the completed sequence of the ~3 billion nucleotides that comprise the human genome has provided the foundation for under- standing human genetic variation in health and disease [1]. New high- throughput methods made genome-wide discovery and analysis of such vari- ation a feasible endeavor [2-4]. In studying malignancies, we are interested in identifying and understanding the causal and associated molecular chang- es that contribute to malignant phenotypes. This thesis focuses on using new technologies for identifying such factors that may have a functional role in the regulation of gene expression, DNA methylation, and in the development of acute lymphoblastic leukemia in children. Acute Lymphoblastic Leukemia Acute lymphoblastic leukemia (ALL) is a malignant disease of the bone marrow that is characterized by the rapid clonal expansion of immature white blood cells. This expanded lymphoblast population is defective in their normal maturation and function and quickly crowd out the healthy function- ing blood cells [5]. Thus, immediate treatment is required to restore normal functional bone marrow. ALL is the most common form of cancer in chil- dren, with a peak incidence between two and five years of age [6]. Accord- ing to the Nordic Society of Pediatric Hematology and Oncology (NOPHO), approximately 200 children are newly diagnosed with ALL in the Nordic countries (Denmark, Finland, Iceland, Norway & Sweden) each year [7]. With contemporary combination chemotherapy protocols for ALL, approxi- mately 80% of patients achieve continuous complete remission (CR). De- spite these improvements, for unknown reasons approximately 20% of chil- dren do not respond to treatment, experience relapse, or suffer serious treat- ment related complications [8]. ALL is a clinically and genetically heterogeneous disease that can initially be divided into two immunophenotypic subgroups based on the cellular origin of lymphoblastic cells. The most frequent immunophenotype arises from pre-B cell precursor cells (BCP-ALL) and accounts for approximately 85% of cases. T-cell ALL (T-ALL) represents the remaining 15% of cases. ALL cells can be characterized at the molecular level by the presence of several recurrent structural and numerical chromosomal aberrations. Cyto- 11 genetic subtyping in BCP-ALL has a significant impact on the clinical man- agement of patients as some subtypes infer a better or worse prognosis [9]. Cytogenetic Classification of ALL Cytogenetic characterization provides the basis for subtype classification of BCP-ALL cases. The known recurrent structural and numerical chromoso-
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