Insights into Neuroblastoma Initiation and Disease Progression Through integrative Genomics and Epigenomics

In this dissertation, we use integrative genomics to shed new insights into the molecular lesions and mechanisms that drive neuroblastoma. In Part 1, we use imputation and epigenetic profiling in order to identify the causal germline SNP that drives differential susceptibility to neuroblastoma at the LMO1 oncogene locus. In Part 2, we use whole genome sequencing and Bayesian statistical modeling to understand the clonal evolution that occurs between diagnosis and relapse. Part 1: Neuroblastoma is a pediatric malignancy that typically arises in early childhood, and is derived from the developing sympathetic nervous system. A previous genome-wide association study identified common polymorphisms at the LMO1 gene locus that are highly associated with neuroblastoma susceptibility and oncogenic addiction to LMO1 in the tumor cells. Here we investigate the causal DNA variant at this locus. We show that SNP rs2168101 G\u3eT is the most highly associated variant and resides in a super-enhancer defined by extensive acetylation of histone H3 lysine 27 within the first intron of LMO1. The ancestral G allele that is associated with tumor formation resides in a conserved GATA transcription factor binding motif. We show that the newly evolved protective TATA allele ablates GATA3 binding and enhancer activity, and is associated with decreased total and allele-specific LMO1 expression in neuroblastoma primary tumors. These findings indicate that a recently evolved polymorphism within a super-enhancer element in the first intron of LMO1 influences neuroblastoma susceptibility through differential GATA transcription factor binding and direct modulation of LMO1 expression in cis. Part 2: The majority of high-risk neuroblastomas initially respond to chemotherapy, but over half of patients will experience therapy-resistant relapses which are nearly always fatal. The molecular defects driving relapse and drug resistance are unknown. We performed whole genome sequencing of 23 paired diagnostic and relapsed neuroblastomas, and corresponding normal lymphocyte DNAs, to define genetic alterations associated with relapse. Unbiased pathway analysis of the somatic mutations detected in the relapse tissues identified a strong enrichment in genes associated with RAS-MAPK signaling (18 of 23 patients). These RAS-MAPK mutations were clonally enriched at relapse and exist within clonal or major subclonal tumor populations. Similar MAPK pathway mutations were detected in 11 of 18 human neuroblastoma-derived cell lines, and these lesions are predicted to be sensitive to small molecule inhibition of MEK in vitro and in vivo. In this study of 23 neuroblastoma cases, MAPK pathway mutations were highly enriched in the relapsed genomes, providing a potential biomarker for new therapeutic approaches to chemotherapy refractory disease. Collectively, these studies provide important insights into the genetic and epigenetic factors driving neuroblastoma, and suggest new opportunities for pathway-targeted therapies

CODEX: A Normalization and Copy Number Variation Detection Method for Whole Exome Sequencing

High-throughput sequencing of DNA coding regions has become a common way of assaying genomic variation in the study of human diseases. Copy number variation (CNV) is an important type of genomic variation, but detecting and characterizing CNV from exome sequencing is challenging due to the high level of biases and artifacts. We propose CODEX, a normalization and CNV calling procedure for whole exome sequencing data. The Poisson latent factor model in CODEX includes terms that specifically remove biases due to GC content, exon capture and amplification efficiency, and latent systemic artifacts. CODEX also includes a Poisson likelihood-based recursive segmentation procedure that explicitly models the count-based exome sequencing data. CODEX is compared to existing methods on a population analysis of HapMap samples from the 1000 Genomes Project, and shown to be more accurate on three microarray-based validation data sets. We further evaluate performance on 222 neuroblastoma samples with matched normals and focus on a well-studied rare somatic CNV within the ATRX gene. We show that the cross-sample normalization procedure of CODEX removes more noise than normalizing the tumor against the matched normal and that the segmentation procedure performs well in detecting CNVs with nested structures

Optimizing copy number variation analysis using genome-wide short sequence oligonucleotide arrays

The detection of copy number variants (CNV) by array-based platforms provides valuable insight into understanding human diversity. However, suboptimal study design and data processing negatively affect CNV assessment. We quantitatively evaluate their impact when short-sequence oligonucleotide arrays are applied (Affymetrix Genome-Wide Human SNP Array 6.0) by evaluating 42 HapMap samples for CNV detection. Several processing and segmentation strategies are implemented, and results are compared to CNV assessment obtained using an oligonucleotide array CGH platform designed to query CNVs at high resolution (Agilent). We quantitatively demonstrate that different reference models (e.g. single versus pooled sample reference) used to detect CNVs are a major source of inter-platform discrepancy (up to 30%) and that CNVs residing within segmental duplication regions (higher reference copy number) are significantly harder to detect (P < 0.0001). After adjusting Affymetrix data to mimic the Agilent experimental design (reference sample effect), we applied several common segmentation approaches and evaluated differential sensitivity and specificity for CNV detection, ranging 39–77% and 86–100% for non-segmental duplication regions, respectively, and 18–55% and 39–77% for segmental duplications. Our results are relevant to any array-based CNV study and provide guidelines to optimize performance based on study-specific objectives

MIBG avidity correlates with clinical features, tumor biology, and outcomes in neuroblastoma: A report from the Children’s Oncology Group

BackgroundPrior studies suggest that neuroblastomas that do not accumulate metaiodobenzylguanidine (MIBG) on diagnostic imaging (MIBG non‐avid) may have more favorable features compared with MIBG avid tumors. We compared clinical features, biologic features, and clinical outcomes between patients with MIBG nonavid and MIBG avid neuroblastoma.ProcedurePatients had metastatic high‐ or intermediate‐risk neuroblastoma and were treated on Children’s Oncology Group protocols A3973 or A3961. Comparisons of clinical and biologic features according to MIBG avidity were made with chi‐squared or Fisher exact tests. Event‐free (EFS) and overall (OS) survival compared using log–rank tests and modeled using Cox models.ResultsThirty of 343 patients (8.7%) had MIBG nonavid disease. Patients with nonavid tumors were less likely to have adrenal primary tumors (34.5 vs. 57.2%; P = 0.019), bone metastases (36.7 vs. 61.7%; P = 0.008), or positive urine catecholamines (66.7 vs. 91.0%; P < 0.001) compared with patients with MIBG avid tumors. Nonavid tumors were more likely to be MYCN amplified (53.8 vs. 32.6%; P = 0.030) and had lower norepinephrine transporter expression. Patients with MIBG nonavid disease had a 5‐year EFS of 50.0% compared with 38.7% for patients with MIBG avid disease (P = 0.028). On multivariate testing in high‐risk patients, MIBG avidity was the sole adverse prognostic factor for EFS identified (hazard ratio 1.77; 95% confidence interval 1.04–2.99; P = 0.034).ConclusionsPatients with MIBG nonavid neuroblastoma have lower rates of adrenal primary tumors, bone metastasis, and catecholamine secretion. Despite being more likely to have MYCN‐amplified tumors, these patients have superior outcomes compared with patients with MIBG avid disease.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138438/1/pbc26545_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/138438/2/pbc26545.pd

A Computational Framework Discovers New Copy Number Variants with Functional Importance

Structural variants which cause changes in copy numbers constitute an important component of genomic variability. They account for 0.7% of genomic differences in two individual genomes, of which copy number variants (CNVs) are the largest component. A recent population-based CNV study revealed the need of better characterization of CNVs, especially the small ones (<500 bp).We propose a three step computational framework (Identification of germline Changes in Copy Number or IgC2N) to discover and genotype germline CNVs. First, we detect candidate CNV loci by combining information across multiple samples without imposing restrictions to the number of coverage markers or to the variant size. Secondly, we fine tune the detection of rare variants and infer the putative copy number classes for each locus. Last, for each variant we combine the relative distance between consecutive copy number classes with genetic information in a novel attempt to estimate the reference model bias. This computational approach is applied to genome-wide data from 1250 HapMap individuals. Novel variants were discovered and characterized in terms of size, minor allele frequency, type of polymorphism (gains, losses or both), and mechanism of formation. Using data generated for a subset of individuals by a 42 million marker platform, we validated the majority of the variants with the highest validation rate (66.7%) was for variants of size larger than 1 kb. Finally, we queried transcriptomic data from 129 individuals determined by RNA-sequencing as further validation and to assess the functional role of the new variants. We investigated the possible enrichment for variant's regulatory effect and found that smaller variants (<1 Kb) are more likely to regulate gene transcript than larger variants (p-value = 2.04e-08). Our results support the validity of the computational framework to detect novel variants relevant to disease susceptibility studies and provide evidence of the importance of genetic variants in regulatory network studies

The Global Regulator Ler Is Necessary for Enteropathogenic Escherichia coli Colonization of Caenorhabditis elegans

Enteropathogenic Escherichia coli (EPEC) is an important cause of infant diarrhea in developing countries and is useful for general investigations of the bacterial infection process. However, the study of the molecular pathogenesis of EPEC has been hampered by the lack of genetically tractable, convenient animal models. We have therefore developed the use of the nematode Caenorhabditis elegans as a small animal model of infection for this diarrheal pathogen. We found that nematodes died faster on nematode growth medium in the presence of EPEC pathogens than in the presence of the laboratory control strain MG1655. Increased numbers of pathogens in the gut, determined by standard plate count assays and fluorescence microscopy using green fluorescent protein-expressing bacteria, correlated with killing. Deletion of the gene encoding the global regulator Ler severely reduced the ability of EPEC to colonize the nematode gut and could be complemented by providing the ler gene on a multicopy plasmid in trans. Neither the type III secretion system nor the type IV bundle-forming pilus was required for colonization. Combined, the similarities and distinct differences between EPEC infection of nematodes and that of humans offer a unique opportunity to study several stages of the infection process, namely, attachment, colonization, and persistence, in a genetically tractable, inexpensive, and convenient in vivo system

Common variants upstream of MLF1 at 3q25 and within CPZ at 4p16 associated with neuroblastoma

Neuroblastoma is a cancer of the developing sympathetic nervous system that most commonly presents in young children and accounts for approximately 12% of pediatric oncology deaths. Here, we report on a genome-wide association study (GWAS) in a discovery cohort or 2,101 cases and 4,202 controls of European ancestry. We identify two new association signals at 3q25 and 4p16 that replicated robustly in multiple independent cohorts comprising 1,163 cases and 4,396 controls (3q25: rs6441201 combined P = 1.2x10-11, Odds Ratio 1.23, 95% CI:1.16-1.31; 4p16: rs3796727 combined P = 1.26x10-12, Odds Ratio 1.30, 95% CI: 1.21-1.40). The 4p16 signal maps within the carboxypeptidase Z (CPZ) gene. The 3q25 signal resides within the arginine/serine-rich coiled-coil 1 (RSRC1) gene and upstream of the myeloid leukemia factor 1 (MLF1) gene. Increased expression of MLF1 was observed in neuroblastoma cells homozygous for the rs6441201 risk allele (P = 0.02), and significant growth inhibition was observed upon depletion of MLF1 (P < 0.0001) in neuroblastoma cells. Taken together, we show that common DNA variants within CPZ at 4p16 and upstream of MLF1 at 3q25 influence neuroblastoma susceptibility and MLF1 likely plays an important role in neuroblastoma tumorigenesis