Inferring a tumor progression model for neuroblastoma from genomic data

Chromosome instability in neuroblastoma: A pathway to aggressive disease

For over 100-years, genomic instability has been investigated as a central player in the pathogenesis of human cancer. Conceptually, genomic instability includes an array of alterations from small deletions/insertions to whole chromosome alterations, referred to as chromosome instability. Chromosome instability has a paradoxical impact in cancer. In most instances, the introduction of chromosome instability has a negative impact on cellular fitness whereas in cancer it is usually associated with a worse prognosis. One exception is the case of neuroblastoma, the most common solid tumor outside of the brain in children. Neuroblastoma tumors have two distinct patterns of genome instability: whole-chromosome aneuploidy, which is associated with a better prognosis, or segmental chromosomal alterations, which is a potent negative prognostic factor. Through a computational screen, we found that low levels of the de- ubiquitinating enzyme USP24 have a highly significant negative impact on survival in neuroblastoma. At the molecular level, USP24 loss leads to destabilization of the microtubule assembly factor CRMP2 - producing mitotic errors and leading to chromosome missegregation and whole-chromosome aneuploidy. This apparent paradox may be reconciled through a model in which whole chromosome aneuploidy leads to the subsequent development of segmental chromosome alterations. Here we review the mechanisms behind chromosome instability and the evidence for the progressive development of segmental alterations from existing numerical aneuploidy in support of a multi-step model of neuroblastoma progression.

Role of microRNAs in epigenetic silencing of the CHD5 tumor suppressor gene in neuroblastomas

Neuroblastoma (NB), a tumor of the sympathetic nervous system, is the most common extracranial solid tumor of childhood. We and others have identified distinct patterns of genomic change that underlie diverse clinical behaviors, from spontaneous regression to relentless progression. We first identified CHD5 as a tumor suppressor gene that is frequently deleted in NBs. Mutation of the remaining CHD5 allele is rare in these tumors, yet expression is very low or absent, so expression is likely regulated by epigenetic mechanisms. In order to understand the potential role of miRNA regulation of CHD5 protein expression in NBs, we examined all miRNAs that are predicted to target the 3′-UTR using miRanda, TargetScan and other algorithms. We identified 18 miRNAs that were predicted by 2 or more programs: miR-204, -211, -216b, -17, -19ab, -20ab, -93, -106ab, -130ab, -301ab, -454, -519d, -3666. We then performed transient transfections in two NB cell lines, NLF (MYCN amplified) and SY5Y (MYCN non-amplified), with the reporter plasmid and miRNA mimic, as well as appropriate controls. We found seven miRNAs that significantly downregulated CHD5 expression in NB: miR-211, 17, -93, -20b, -106b, -204, and -3666. Interestingly, MYCN upregulates several of the candidates we identified: miR-17, -93, -106b & -20b. This suggests that miRNAs driven by MYCN and other genes represent a potential epigenetic mechanism to regulate CHD5 expression.

Neuroblastoma cells undergo transcriptomic alterations upon dissemination into the bone marrow and subsequent tumor progression

Neuroblastoma is the most common extracranial solid tumor in childhood. The vast majority of metastatic (M) stage patients present with disseminated tumor cells (DTCs) in the bone marrow (BM) at diagnosis and relapse. Although these cells represent a major obstacle in the treatment of neuroblastoma patients, insights into their expression profile remained elusive. The present RNA‐Seq study of stage 4/M primary tumors, enriched BM‐derived diagnostic and relapse DTCs, as well as the corresponding BM‐derived mononuclear cells (MNCs) from 53 patients revealed 322 differentially expressed genes in DTCs as compared to the tumors (q < 0.001, |log₂FC|>2). Particularly, the levels of transcripts encoded by mitochondrial DNA were elevated in DTCs, whereas, for example, genes involved in angiogenesis were downregulated. Furthermore, 224 genes were highly expressed in DTCs and only slightly, if at all, in MNCs (q < 8 × 10⁻⁷⁵ log₂FC > 6). Interestingly, we found the transcriptome of relapse DTCs largely resembling those of diagnostic DTCs with only 113 differentially expressed genes under relaxed cut‐offs (q < 0.01, |log₂FC|>0.5). Notably, relapse DTCs showed a positional enrichment of 31 downregulated genes on chromosome 19, including five tumor suppressor genes: SIRT6, BBC3/PUMA, STK11, CADM4 and GLTSCR2. This first RNA‐Seq analysis of neuroblastoma DTCs revealed their unique expression profile in comparison to the tumors and MNCs, and less pronounced differences between diagnostic and relapse DTCs. The latter preferentially affected downregulation of genes encoded by chromosome 19. As these alterations might be associated with treatment failure and disease relapse, further functional studies on DTCs should be considered.

What's new?

More than 90% of patients diagnosed with stage 4 metastatic (4/M) neuroblastoma present with disseminated tumor cells (DTCs) in the bone marrow (BM). Despite treatment, a substantial fraction of these patients experience disease relapse. Here, sequencing analysis of tumor tissue, BM‐derived mononuclear cells (MNCs), and DTCs from stage 4/M neuroblastoma patients indicates that numerous genes are differentially expressed in DTCs but are not or are only slightly altered in tumors and MNCs. Moreover, DTCs exhibited significant downregulation of tumor suppressor genes specifically on chromosome 19. Further studies are needed to determine whether DTC transcriptomic alterations are associated with neuroblastoma relapse.

The evolution of tumour phylogenetics: principles and practice

Rapid advances in high-throughput sequencing and a growing realization of the importance of evolutionary theory to cancer genomics have led to a proliferation of phylogenetic studies of tumour progression. These studies have yielded not only new insights but also a plethora of experimental approaches, sometimes reaching conflicting or poorly supported conclusions. Here, we consider this body of work in light of the key computational principles underpinning phylogenetic inference, with the goal of providing practical guidance on the design and analysis of scientifically rigorous tumour phylogeny studies. We survey the range of methods and tools available to the researcher, their key applications, and the various unsolved problems, closing with a perspective on the prospects and broader implications of this field.

Spanning the genomics era: the vital role of a single institution biorepository for childhood cancer research over a decade

The 'genomics era' is considered to have begun with the commencement of the Human Genome Project. As translational genomic studies can only be established when human tissue samples are available for analysis, biospecimens are now proven to be an essential element for their success. During the genomics era the necessity for more extensive biobanking infrastructure has been highlighted. With the increased number of genomic studies into cancer, it is considered that the availability of biospecimens will become the rate limiting step. Despite the efforts in international biobanking, translational genomics is hampered when there low numbers of biospecimens for a particular rare diseases and is most apparent for paediatric cancer. As there is a call for biobanking practice to be responsive to the current experimental needs of the time and for more expansive systems of tissue procurement to be established we have asked the question what role does a single institution biorepository play in the current highly networked world of translational genomics. Here we describe such a case. The Tumour Bank at The Children's Hospital at Westmead (TB-CHW) in the western suburbs of Sydney was formally established in 1998 as a key resource for translational paediatric cancer research. During the genomics era, we show that the TB-CHW has developed into a key biospecimen repository for the cancer research community, during which time it has increasingly found itself having a vital role in the establishment of translational genomics for paediatric cancer. Here we detail metrics that demonstrate how as a single institution biorepository, the TB-CHW has been a strong participant in the advancement of translational genomics throughout the genomics era. This paper describes the significant contribution of a single institutional hospital embedded tumour biobank to the genomic research community. Despite the increased stringencies placed on biobanking practice, the TB-CHW has shown that a single institution biorespository can have a consistent and effective contribution to translational research into rare paediatric malignancy demonstrating its long term benefit throughout the genomics era.

Bone marrows from neuroblastoma patients: an excellent source for tumor genome analyses

Neuroblastoma is the most common extra‐cranial solid tumor in childhood. Presence of disseminated tumor cells (DTCs) in the bone marrow (BM) at diagnosis and at relapse is a common event in stage M neuroblastomas. Although the clinical heterogeneity of disseminated neuroblastomas is frequently associated with genomic diversity, so far, only little information exists about the genomic status of DTCs. This lack of knowledge is mainly due to the varying amount of BM infiltrating tumor cells, which is usually below 30% even at diagnosis thereby hampering systematic analyses. Thus, a valuable chance to analyze metastatic and relapse clones is, so far, completely unexploited. In this study, we show that the enrichment of tumor cells in fresh or DMSO frozen BM samples with a minimum of 0.05% or 0.1% infiltration rate, respectively, by applying magnetic bead‐based technique increased the DTC content to a sufficient level to allow SNP array analyses in 49 out of 69 samples. In addition, we successfully used non‐enriched BM samples with ≥30% DTCs including non‐stained and immunostained cytospin and BM smear slides for SNP array analyses in 44 cases. We analyzed the genomic profile of DTCs by an ultra‐high density SNP array technique with highest performance detecting all segmental chromosomal aberrations, amplified regions, acquired loss of heterozygosity events and minor aberrations affecting single genes or parts thereof.

Genomic analysis of bone marrow micrometastases by ultra‐high density SNP array.

Routinely processed bone marrow (BM) samples allow detailed genomic studies.

Enrichment of BM samples with >0.05% tumor cells allows detailed genomic analyses.

Neuroblastoma: molecular pathogenesis and therapy

Neuroblastoma is a developmental tumor of young children arising from the embryonic sympathoadrenal lineage of the neural crest. Neuroblastoma is the primary cause of death from pediatric cancer for children between the ages of one and five years and accounts for ∼13% of all pediatric cancer mortality. Its clinical impact and unique biology have made this aggressive malignancy the focus of a large concerted translational research effort. New insights into tumor biology are driving the development of new classification schemas. Novel targeted therapeutic approaches include small-molecule inhibitors as well as epigenetic, noncoding-RNA, and cell-based immunologic therapies. In this review, recent insights regarding the pathogenesis and biology of neuroblastoma are placed in context with the current understanding of tumor biology and tumor/host interactions. Systematic classification of patients coupled with therapeutic advances point to a future of improved clinical outcomes for this biologically distinct and highly aggressive pediatric malignancy.

Algorithms to model single gene, single chromosome, and whole genome copy number changes jointly in tumor phylogenetics

We present methods to construct phylogenetic models of tumor progression at the cellular level that include copy number changes at the scale of single genes, entire chromosomes, and the whole genome. The methods are designed for data collected by fluorescence in situ hybridization (FISH), an experimental technique especially well suited to characterizing intratumor heterogeneity using counts of probes to genetic regions frequently gained or lost in tumor development. Here, we develop new provably optimal methods for computing an edit distance between the copy number states of two cells given evolution by copy number changes of single probes, all probes on a chromosome, or all probes in the genome. We then apply this theory to develop a practical heuristic algorithm, implemented in publicly available software, for inferring tumor phylogenies on data from potentially hundreds of single cells by this evolutionary model. We demonstrate and validate the methods on simulated data and published FISH data from cervical cancers and breast cancers. Our computational experiments show that the new model and algorithm lead to more parsimonious trees than prior methods for single-tumor phylogenetics and to improved performance on various classification tasks, such as distinguishing primary tumors from metastases obtained from the same patient population.

Cancer is an evolutionary system whose growth and development is attributed to aberrations in well-known genes and to cancer-type specific genomic imbalances. Here, we present methods for reconstructing the evolution of individual tumors based on cell-to-cell variations between copy numbers of targeted regions of the genome. The methods are designed to work with fluorescence in situ hybridization (FISH), a technique that allows one to profile copy number changes in potentially thousands of single cells per study. Our work advances the prior art by developing theory and practical algorithms for building evolutionary trees of single tumors that can model gain or loss of genetic regions at the scale of single genes, whole chromosomes, or the entire genome, all common events in tumor evolution. We apply these methods on simulated and real tumor data to demonstrate substantial improvements in tree-building accuracy and in our ability to accurately classify tumors from their inferred evolutionary models. The newly developed algorithms have been released through our publicly available software, FISHtrees.

Recurrent pre-existing and acquired DNA copy number alterations, including focal TERT gains, in neuroblastoma central nervous system metastases

Stage 4 neuroblastomas have a high rate of local and metastatic relapse and associated disease mortality. The central nervous system (CNS) is currently one of the most common isolated relapse sites, yet the genomic alterations that contribute to these metastases are unknown. This study sought to identify recurrent DNA copy number alterations (CNAs) and target genes relating to neuroblastoma CNS metastases by studying 19 pre-CNS primary tumors and 27 CNS metastases, including 12 matched pairs. SNP microarray analyses revealed that MYCN amplified (MYCNA) tumors had recurrent CNAs different from non-MYCNA cohorts. Several CNAs known to be prevalent among primary neuroblastomas occurred more frequently in CNS metastases, including 4p-, 7q+, 12q+, and 19q- in non-MYCNA metastases, and 9p- and 14q- irrespective of MYCNA status. In addition, novel CNS metastases-related CNAs included 18q22.1 gains in non-MYCNA pre-CNS primaries and 5p15.33 gains and 15q26.1→tel losses in non-MYCNA CNS metastases. Based on minimal common regions, gene expression, and biological properties, TERT (5p), NR2F2 (15q), ALDH1A3 (15q), CDKN2A (9p), and possibly CDH7 and CDH19 (18q) were candidate genes associated with the CNS metastatic process. Notably, the 5p15 minimal common region contained only TERT, and non-MYCNA CNS metastases with focal 5p15 gains had increased TERT expression, similar to MYCNA tumors. These findings suggest that a specific genomic lesion (18q22.1 gain) predisposes to CNS metastases and that distinct lesions are recurrently acquired during metastatic progression. Among the acquired lesions, increased TERT copy number and expression appears likely to function in lieu of MYCNA to promote CNS metastasis.

Methods and challenges in timing chromosomal abnormalities within cancer samples

Motivation: Tumors acquire many chromosomal amplifications, and those acquired early in the lifespan of the tumor may be not only important for tumor growth but also can be used for diagnostic purposes. Many methods infer the order of the accumulation of abnormalities based on their occurrence in a large cohort of patients. Recently, Durinck et al. (2011) and Greenman et al. (2012) developed methods to order a single tumor’s chromosomal amplifications based on the patterns of mutations accumulated within those regions. This method offers an unprecedented opportunity to assess the etiology of a single tumor sample, but has not been widely evaluated.

Results: We show that the model for timing chromosomal amplifications is limited in scope, particularly for regions with high levels of amplification. We also show that the estimation of the order of events can be sensitive for events that occur early in the progression of the tumor and that the partial maximum likelihood method of Greenman et al. (2012) can give biased estimates, particularly for moderate read coverage or normal contamination. We propose a maximum-likelihood estimation procedure that fully accounts for sequencing variability and show that it outperforms the partial maximum-likelihood estimation method. We also propose a Bayesian estimation procedure that stabilizes the estimates in certain settings. We implement these methods on a small number of ovarian tumors, and the results suggest possible differences in how the tumors acquired amplifications.

Availability and implementation: We provide implementation of these methods in an R package cancerTiming, which is available from the Comprehensive R Archive Network (CRAN) at http://CRAN.R-project.org/.

Contact:epurdom@stat.Berkeley.edu

Supplementary information:Supplementary data are available at Bioinformatics online.

Mechanisms of CHD5 Inactivation in neuroblastomas

PURPOSE

Neuroblastomas (NBs) have genomic, biological, and clinical heterogeneity. High-risk NBs are characterized by several genomic changes, including MYCN amplification and 1p36 deletion. We identified the chromatin-remodeling gene CHD5 as a tumor suppressor gene that maps to 1p36.31. Low or absent CHD5 expression is associated with a 1p36 deletion and an unfavorable outcome, but the mechanisms of CHD5 inactivation in NBs are unknown.

EXPERIMENTAL DESIGN

We examined (i) the CHD5 sequence in 188 high-risk NBs investigated through the TARGET initiative, (ii) the methylation status of the CHD5 promoter in 108 NBs with or without 1p36 deletion and/or MYCN amplification, and (iii) mRNA expression of CHD5 and MYCN in 814 representative NBs using TaqMan low-density array microfluidic cards.

RESULTS

We found no examples of somatically acquired CHD5 mutations, even in cases with 1p36 deletion, indicating that homozygous genomic inactivation is rare. Methylation of the CHD5 promoter was common in the high-risk tumors, and it was generally associated with both 1p deletion and MYCN amplification. High CHD5 expression was a powerful predictor of favorable outcome, and it showed prognostic value even in multivariable analysis after adjusting for MYCN amplification, 1p36 deletion, and/or 11q deletion.

CONCLUSIONS

We conclude that (i) somatically acquired CHD5 mutations are rare in primary NBs, so inactivation probably occurs by deletion and epigenetic silencing; (ii) CHD5 expression and promoter methylation are associated with MYCN amplification, suggesting a possible interaction between these 2 genes; and (iii) high CHD5 expression is strongly correlated with favorable clinical/biological features and outcome.

Accurate reconstruction of the temporal order of mutations in neoplastic progression

The canonical route from normal tissue to cancer occurs through sequential acquisition of somatic mutations. Many studies have constructed a linear genetic model for tumorigenesis using the genetic alterations associated with samples at different stages of neoplastic progression from cross-sectional data. The common interpretation of these models is that they reflect the temporal order within any given tumor. Linear genetic methods implicitly neglect genetic heterogeneity within a neoplasm; each neoplasm is assumed to consist of one dominant clone. We modeled neoplastic progression of colorectal cancer using an agent-based model of a colon crypt and found clonal heterogeneity within our simulated neoplasms, as observed in vivo. Just 7.3% of cells within neoplasms acquired mutations in the same order as the linear model. In 41% of the simulated neoplasms, no cells acquired mutations in the same order as the linear model. We obtained similarly poor results when comparing the temporal order with oncogenetic tree models inferred from cross-sectional data. However, when we reconstructed the cell lineage of mutations within a neoplasm using several biopsies, we found that 99.7% cells within neoplasms acquired their mutations in an order consistent with the cell lineage mutational order. Thus, we find that using cross-sectional data to infer mutational order is misleading, whereas phylogenetic methods based on sampling intratumor heterogeneity accurately reconstructs the evolutionary history of tumors. In addition, we find evidence that disruption of differentiation is likely the first lesion in progression for most cancers and should be one of the few regularities of neoplastic progression across cancers.

Analysis of the copy number profiles of several tumor samples from the same patient reveals the successive steps in tumorigenesis

We present a computational method, TuMult, for reconstructing the sequence of copy number changes driving carcinogenesis, based on the analysis of several tumor samples from the same patient. We demonstrate the reliability of the method with simulated data, and describe applications to three different cancers, showing that TuMult is a valuable tool for the establishment of clonal relationships between tumor samples and the identification of chromosome aberrations occurring at crucial steps in cancer progression.

Systems biology and modeling in neuroblastoma: practicalities and perspectives

Neuroblastoma (NB) is a common pediatric malignancy characterized by clinical and biological heterogeneity. A host of prognostic markers are available, contributing to accurate risk stratification and appropriate treatment allocation. Unfortunately, outcome is still poor for many patients, indicating the need for a new approach with enhanced utilization of the available biological data. Systems biology is a holistic approach in which all components of a biological system carry equal importance. Systems biology uses mathematical modeling and simulation to investigate dynamic interactions between system components, as a means of explaining overall system behavior. Systems biology can benefit the biomedical sciences by providing a more complete understanding of human disease, enhancing the development of targeted therapeutics. Systems biology is largely contiguous with current approaches in NB, which already employ an integrative and pseudo-holistic approach to disease management. Systems modeling of NB offers an optimal method for continuing progression in this field, and conferring additional benefit to current risk stratification and management. Likewise, NB provides an opportunity for systems biology to prove its utility in the context of human disease, since the biology of NB is comprehensively characterized and, therefore, suited to modeling. The purpose of this review is to outline the benefits, challenges and fundamental workings of systems modeling in human disease, using a specific example of bottom-up modeling in NB. The intention is to demonstrate practical requirements to begin bridging the gap between biological research and applied mathematical approaches for the mutual gain of both fields, and with additional benefits for clinical management.

The role of complex genomic alterations in neuroblastoma risk estimation

Specific genomic alterations, such as loss of the chromosomal region 11q or amplification of the oncogene MYCN, are well established markers of poor outcome in neuroblastoma. The advent of microarray-based comparative genomic hybridization (array-CGH) has enabled the analysis of pangenomic alteration profiles in the cancer genome, offering the possibility of identifying new prognostic markers from complex aberration patterns. Results from recent studies examining large primary neuroblastoma cohorts by array-CGH show that global genomic profiles may add significant prognostic information. Here, we discuss potential implications for risk estimation of neuroblastoma patients in clinical practice as well as for the understanding of neuroblastoma pathogenesis.

Tracing the tumor lineage

Defining the pathways through which tumors progress is critical to our understanding and treatment of cancer. We do not routinely sample patients at multiple time points during the progression of their disease, and thus our research is limited to inferring progression a posteriori from the examination of a single tumor sample. Despite this limitation, inferring progression is possible because the tumor genome contains a natural history of the mutations that occur during the formation of the tumor mass. There are two approaches to reconstructing a lineage of progression: (1) inter-tumor comparisons, and (2) intra-tumor comparisons. The inter-tumor approach consists of taking single samples from large collections of tumors and comparing the complexity of the genomes to identify early and late mutations. The intra-tumor approach involves taking multiple samples from individual heterogeneous tumors to compare divergent clones and reconstruct a phylogenetic lineage. Here we discuss how these approaches can be used to interpret the current models for tumor progression. We also compare data from primary and metastatic copy number profiles to shed light on the final steps of breast cancer progression. Finally, we discuss how recent technical advances in single cell genomics will herald a new era in understanding the fundamental basis of tumor heterogeneity and progression.

Integrated genomic profiling identifies two distinct molecular subtypes with divergent outcome in neuroblastoma with loss of chromosome 11q

Imbalances in chromosome 11q occur in approximately 30% of primary neuroblastoma and are associated with poor outcome. It has been suggested that 11q loss constitutes a distinct clinico-genetic neuroblastoma subgroup by affecting expression levels of corresponding genes. This study analysed the relationship of 11q loss, clinical phenotype and global transcriptomic profiles in four clinico-genetic subgroups (11q alteration/favourable outcome, n=7; 11q alteration/unfavourable outcome, n=14; no 11q alteration/favourable outcome, n=81; no 11q alteration/unfavourable outcome, n=8; tumours with MYCN amplification and/or 1p loss were excluded). Unsupervised and supervised comparisons of gene expression profiles consistently showed significantly different mRNA patterns between favourable and unfavourable neuroblastomas, both in the subgroups with and without 11q loss. In contrast, favourable tumours with and without 11q loss showed highly similar transcriptomic profiles. Disproportionate downregulation of 11q genes was observed only in unfavourable tumours with 11q loss. The diverging molecular profiles were neither caused by considerable differences in the size of the deleted regions nor by differential methylation patterns of 11q genes. Together, this study shows that neuroblastoma with 11q loss comprises two biological subgroups that differ both in their clinical phenotype and gene expression patterns, indicating that 11q loss is not a primary determinant of neuroblastoma tumour behaviour.

Inferring progression models for CGH data

MOTIVATION

One of the mutational processes that has been monitored genome-wide is the occurrence of regional DNA copy number alterations (CNAs), which may lead to deletion or over-expression of tumor suppressors or oncogenes, respectively. Understanding the relationship between CNAs and different cancer types is a fundamental problem in cancer studies.

RESULTS

This article develops an efficient method that can accurately model the progression of the cancer markers and reconstruct evolutionary relationship between multiple types of cancers using comparative genomic hybridization (CGH) data. Such modeling can lead to better understanding of the commonalities and differences between multiple cancer types and potential therapies. We have developed an automatic method to infer a graph model for the markers of multiple cancers from a large population of CGH data. Our method identifies highly related markers across different cancer types. It then builds a directed acyclic graph that shows the evolutionary history of these markers based on how common each marker is in different cancer types. We demonstrated the use of this model in determining the importance of markers in cancer evolution. We have also developed a new method to measure the evolutionary distance between different cancers based on their markers. This method employs the graph model we developed for the individual markers to measure the distance between pairs of cancers. We used this measure to create an evolutionary tree for multiple cancers. Our experiments on Progenetix database show that our markers are largely consistent to the reported hot-spot imbalances and most frequent imbalances. The results show that our distance measure can accurately reconstruct the evolutionary relationship between multiple cancer types.

Molecular characterization and classification of neuroblastoma

For many decades, neuroblastoma has remained a challenging disease for both clinicians and researchers. Now, techniques that efficiently specify both comprehensive genetic and gene-expression alterations of neuroblastoma tumors have provided molecular markers that indicate tumor behavior and patient outcome with very high accuracy. Once the anticipated value of these markers has been confirmed in ongoing studies, patients may profit from more accurate risk assessment by integrating these markers into clinical routine. Moreover, disclosing further tumor-initiating events, such as the recently revealed oncogenic mutations of ALK, will further promote the elucidation of the genetic etiology of the disease. Together with recent information on altered signaling pathways in aggressively growing tumors, this knowledge will help to establish therapeutic strategies specifically targeting molecular key factors of neuroblastoma tumor progression.

Whole chromosome alterations predict survival in high-risk neuroblastoma without MYCN amplification

PURPOSE

Patients with stage IV neuroblastoma over the age of 500 days without MYCN amplification have a survival rate of <30% and there are currently no reliable means of predicting which of these patients will survive or succumb to the disease. The goal of this study is to develop a DNA copy number-based prognostic profile for these patients.

EXPERIMENTAL DESIGN

We have used comparative genomic hybridization to identify genome copy number changes that can predict outcome in patients with stage IV neuroblastoma without MYCN amplification.

RESULTS

A strong correlation of patient survival with the presence of whole chromosome changes (WCC >or=2) was observed, even in the group of patients older than 500 days at time of diagnosis. This novel prognostic marker showed a significant dependence on the date of diagnosis; patients with WCC >or=2 diagnosed after 1998 had a significantly higher probability of survival compared with those diagnosed earlier. At the same time, no such time dependence was found among the samples with WCC <2, suggesting that medical progress patients in recent years has particularly benefited those patients with a stage IV non-MYCN-amplified disease if WCC >or=2 were present.

CONCLUSIONS

In this pilot study, we present a novel prognostic marker for survival of high-risk neuroblastoma patients over the age of 500 days without MYCN amplification and diagnosed after 1998. Further validation study is required to establish this risk stratification for these patients.

GEAR: genomic enrichment analysis of regional DNA copy number changes

We developed an algorithm named GEAR (genomic enrichment analysis of regional DNA copy number changes) for functional interpretation of genome-wide DNA copy number changes identified by array-based comparative genomic hybridization. GEAR selects two types of chromosomal alterations with potential biological relevance, i.e. recurrent and phenotype-specific alterations. Then it performs functional enrichment analysis using a priori selected functional gene sets to identify primary and clinical genomic signatures. The genomic signatures identified by GEAR represent functionally coordinated genomic changes, which can provide clues on the underlying molecular mechanisms related to the phenotypes of interest. GEAR can help the identification of key molecular functions that are activated or repressed in the tumor genomes leading to the improved understanding on the tumor biology.

AVAILABILITY

GEAR software is available with online manual in the website, http://www.systemsbiology.co.kr/GEAR/.

Genome-wide genetic aberrations of thymoma using cDNA microarray based comparative genomic hybridization

Background

Thymoma is a heterogeneous group of tumors in biology and clinical behavior. Even though thymoma is divided into five subgroups following the World Health Organization classification, the nature of the disease is mixed within the subgroups.

Results

We investigated the molecular characteristics of genetic changes variation of thymoma using cDNA microarray based-comparative genomic hybridization (CGH) with a 17 K cDNA microarray in an indirect, sex-matched design. Genomic DNA from the paraffin embedded 39 thymoma tissues (A 6, AB 11, B1 7, B2 7, B3 8) labeled with Cy-3 was co-hybridized with the reference placenta gDNA labeled with Cy-5. Using the CAMVS software, we investigated the deletions on chromosomes 1, 2, 3, 4, 5, 6, 8, 12, 13 and 18 throughout the thymoma. Then, we evaluated the genetic variations of thymoma based on the subgroups and the clinical behavior. First, the 36 significant genes differentiating five subgroups were selected by Significance Analysis of Microarray. Based on these genes, type AB was suggested to be heterogeneous at the molecular level as well as histologically. Next, we observed that the thymoma was divided into A, B (1, 2) and B3 subgroups with 33 significant genes. In addition, we selected 70 genes differentiating types A and B3, which differ largely in clinical behaviors. Finally, the 11 heterogeneous AB subtypes were able to correctly assign into A and B (1, 2) types based on their genetic characteristics.

Conclusion

In our study, we observed the genome-wide chromosomal aberrations of thymoma and identified significant gene sets with genetic variations related to thymoma subgroups, which might provide useful information for thymoma pathobiology.

Chromosomal CGH identifies patients with a higher risk of relapse in neuroblastoma without MYCN amplification

Whereas neuroblastoma (NB) with MYCN amplification presents a poor prognosis, no single marker allows to reliably predict outcome in tumours without MYCN amplification. We report here an extensive analysis of 147 NB samples at diagnosis, without MYCN amplification, by chromosomal comparative genomic hybridisation (CGH), providing a comprehensive overview of their genomic imbalances. Comparative genomic hybridisation profiles showed gains or losses of entire chromosomes (type 1) in 71 cases, whereas partial chromosome gains or losses (type 2), including gain involving 17q were observed in 68 cases. Atypical profiles were present in eight cases. A type 1 profile was observed more frequently in localised disease (P<0.0001), and in patients of less than 12 months at diagnosis (P<0.0001). A type 2 genomic profile was associated with a higher risk of relapse in the overall population (log-rank test; P<0.0001), but also in the subgroup of patients with localised disease (log-rank test, P=0.007). In multivariate analysis, the genomic profile was the strongest independent prognostic factor. In conclusion, the genomic profile is of prognostic impact in patients without MYCN amplification, making it a help in the management of low-stage NB. Further studies using higher-resolution CGH are needed to better characterise atypical genomic alterations.

Analysis of comparative genomic hybridization data on cDNA microarrays

We present a detailed method to analyze DNA copy number data generated on cDNA microarrays. A web interface is made available for those steps in the workflow that are not typically used in gene expression analysis so that these steps can be carried out online. The end result of the analysis is a list of p-values for the presence of genomic gains or losses for each sample individually or an average p-value, which we show is useful to identify recurrent genomic imbalances.

Oligonucleotide array-based comparative genomic hybridization (aCGH) of 90 neuroblastomas reveals aberration patterns closely associated with relapse pattern and outcome

The study of genomic alterations in neuroblastoma is of particular importance since several cytogenetic markers proved to be closely associated with the clinical phenotype. To disclose patterns of gains and losses, we performed high-resolution oligonucleotide array-based comparative genomic hybridization (aCGH). A total cohort of 90 patients was classified into 6 subsets according to tumor stage and outcome: Stages 1-3+ (with event), Stage 1-3- (no event), Stage 4+/-, and Stage 4S+/-. The aberration patterns in Stages 1-3- and 4S- tumors differed from all other groups as they were predominantly characterized by losses (3, 4, 14, X) and gains (7, 17) of whole chromosomes. However, 59/65 (91%) tumors of Stages 1-3+ or Stage 4 revealed numerous structural copy number alterations (sCNA). While deletions in chromosomes 1, 3, and 11 discriminated outcome in Stage 4, there were no specific sCNA that distinguished tumor stage within the subgroup of unfavorable tumors. sCNA in 1p, 3p, 11q, 17q, or MYCN amplification (MNA) was seen among 22/24 patients who died, 10/12 with metastatic relapses, and 5/9 with local recurrences. Detailed breakpoint analyses on chromosomes 1, 3, 11, and 17 disclosed preferred breaking areas, although breakpoints were not identical. Amplifications were found in 18 patients and involved 2p24 (MYCN) and other segments of chromosome 2, as well as regions on chromosome arms 6q, 12q, and 17q. One single feature in 21q21.1 (BU678720, without known function yet) attracted particular attention since five patients showed a homozygous loss of this sequence.

Increased WSB1 copy number correlates with its over-expression which associates with increased survival in neuroblastoma

Gain of chromosome 17 is the most prevalent genetic abnormality identified in neuroblastoma (NB) and distal 17q gain has prognostic significance in NB. In this report, we have combined array-based comparative genomic hybridization (A-CGH) and gene expression analysis to investigate gene copy number changes and its impact on the gene expression level as well as their association with prognosis genes located on chromosome 17 in NB tumors. We observed differential gains of chromosome 17 between Stages 4- and 4S tumors. We found that WSB1, mapping to 17q11.1, which was frequently gained in 4S- tumors and not changed in 4- tumors, showed strong correlations between expression level and copy number. Furthermore, the increase of WSB1 gene expression is associated with good outcome in patients with NB of all stages. WSB1 also enhances the prognostic prediction when combined with other current prognostic factors in NB. Our results demonstrate that WSB1 copy number correlates with its expression level and that its high expression associates with good prognosis suggesting a possible role of this gene in the biology of favorable outcome NB. This article contains Supplementary Material available at http://www.interscience.wiley.com/jpages/1045-2257/suppmat.

Integrative genomics identifies distinct molecular classes of neuroblastoma and shows that multiple genes are targeted by regional alterations in DNA copy number

Neuroblastoma is remarkable for its clinical heterogeneity and is characterized by genomic alterations that are strongly correlated with tumor behavior. The specific genes that influence neuroblastoma biology and are targeted by genomic alterations remain largely unknown. We quantified mRNA expression in a highly annotated series of 101 prospectively collected diagnostic neuroblastoma primary tumors using an oligonucleotide-based microarray. Genomic copy number status at the prognostically relevant loci 1p36, 2p24 (MYCN), 11q23, and 17q23 was determined by PCR and was aberrant in 26, 20, 40, and 38 cases, respectively. In addition, 72 diagnostic neuroblastoma primary tumors assayed in a different laboratory were used as an independent validation set. Unsupervised hierarchical clustering showed that gene expression was highly correlated with genomic alterations and clinical markers of tumor behavior. The vast majority of samples with MYCN amplification and 1p36 loss of heterozygosity (LOH) clustered together on a terminal node of the sample dendrogram, whereas the majority of samples with 11q deletion clustered separately and both of these were largely distinct from the copy number neutral group of tumors. Genes involved in neurodevelopment were broadly overrepresented in the more benign tumors, whereas genes involved in RNA processing and cellular proliferation were highly represented in the most malignant cases. By combining transcriptomic and genomic data, we showed that LOH at 1p and 11q was associated with significantly decreased expression of 122 (61%) and 88 (27%) of the genes mapping to 1p35-36 and all of 11q, respectively, suggesting that multiple genes may be targeted by LOH events. A total of 71 of the 1p35-36 genes were also differentially expressed in the independent validation data set, providing a prioritized list of candidate neuroblastoma suppressor genes. Taken together, these data are consistent with the hypotheses that the neuroblastoma transcriptome is a sensitive marker of underlying tumor biology and that chromosomal deletion events in this cancer likely target multiple genes through alteration in mRNA dosage. Lead positional candidates for neuroblastoma suppressor genes can be inferred from these data, but the potential multiplicity of transcripts involved has significant implications for ongoing gene discovery strategies.

Sialyltransferase STX (ST8SiaII): A novel molecular marker of metastatic neuroblastoma

Polysialic acid (PSA) is highly expressed in many human cancers, including neuroblastoma (NB), and is critical for cellular adhesion, neuronal migration and tumor metastasis. The key enzyme responsible for PSA synthesis is sialyltransferase STX (ST8SiaII). Using quantitative RT-PCR we (i) studied STX expression in 39 NB tumors and 8 cell lines and (ii) examined its potential clinical utility as an early response marker in the bone marrows of the entire cohort of 136 high-risk NB patients treated with an immunotherapy protocol utilizing anti-GD2 antibody 3F8 and GM-CSF. Based on the quantitation of 24 normal marrow and peripheral blood samples, a normalized STX transcript value below the mean + 2SD was defined as negative. Sensitivity of this assay was 1 NB cell in 10(6) normal mononuclear cells. STX expression was high among NB tumors of all stages, as well as NB cell lines of different phenotypes. Evaluation for early (2.5 months from protocol entry) marrow response by univariate Cox model indicated that STX marker status (positive versus negative) was strongly associated with both progression-free and overall survival (p < 0.0005 for both). Similarly, the STX transcript level of posttreatment marrows was also highly prognostic of outcome (PFS, p = 0.001; OS, p < 0.0005). We conclude that STX mRNA has potential clinical utility as a molecular marker of metastatic NB.