No abstract

Although children with acute lymphoblastic leukemia (ALL) generally have a good outcome, some patients do relapse and survival following relapse is poor. Altered DNA methylation is highly prevalent in ALL and raises the possibility that DNA methylation-based biomarkers could predict patient outcome. In this study, genome-wide methylation analysis, using the Illumina Infinium HumanMethylation450 BeadChip platform, was carried out on 52 diagnostic patient samples from 4 genetic subtypes [ETV6-RUNX1, high hyperdiploidy (HeH), TCF3-PBX1 and dic(9;20)(p11–13;q11)] in a 1:1 case-control design with patients who went on to relapse (as cases) and patients achieving long-term remission (as controls). Pyrosequencing assays for selected loci were used to confirm the array-generated data. Non-negative matrix factorization consensus clustering readily clustered samples according to genetic subgroups and gene enrichment pathway analysis suggested that this is in part driven by epigenetic disruption of subtype specific signaling pathways. Multiple bioinformatics approaches (including bump hunting and individual locus analysis) were used to identify CpG sites or regions associated with outcome. However, no associations with relapse were identified. Our data revealed that ETV6-RUNX1 and dic(9;20) subtypes were mostly associated with hypermethylation; conversely, TCF3-PBX1 and HeH were associated with hypomethylation. We observed significant enrichment of the neuroactive ligand-receptor interaction pathway in TCF3-PBX1 as well as an enrichment of genes involved in immunity and infection pathways in ETV6-RUNX1 subtype. Taken together, our results suggest that altered DNA methylation may have differential impacts in distinct ALL genetic subtypes.

Trisomy causes mental retardation, pregnancy loss, IVF failure, uniparental disomy and several other pathologies, and its accurate detection is thus clinically essential. Most trisomies arise at meiosis I and are associated with increasing maternal age and reduction or alteration in recombination patterns. Investigations into the relationship between trisomy and meiotic recombination have used short tandem repeat markers; however, this approach is limited by the resolution with which the position of crossovers can identified. As cytogenetics enters the post-genomic era, recent work has used array comparative genomic hybridisation (aCGH) to screen for trisomy of all 24 chromosomes, determining chromosome copy number by dosage analysis. However, aCGH has a fundamental drawback for studying the aetiology of trisomy since neither the parent and phase of origin nor uniparental disomy can be ascertained. The development of SNP microarrays has made it possible to analyse multiple loci for sequence variation, and the proprietary software provided can determine the presence of aneuploidy by algorithms based on fluorescence intensity. To the best of our knowledge, however, such software is not equipped to determine the phase of origin of the error or the position of any chiasmata. In this study, therefore, we present an algorithm to determine the parent of origin, the phase of origin and the location of chiasmata in a series of nine "trisomy triplets" (i.e. samples derived from father, mother and their trisomic foetus). Novel adaptations of well-established principles are applied along with a simple algorithm written in Microsoft Excel for visualisation of the results. Such analysis has a range of applications in preimplantation and prenatal diagnosis.

Purpose: Circulating tumor cells (CTCs) serve as noninvasive tumor biomarkers in many types of cancer. Our aim was to detect CTCs from patients with neuroblastoma for use as predictive and pharmacodynamic biomarkers. Experimental Design: We collected matched blood and bone marrow samples from 40 patients with neuroblastoma to detect GD 2 þ /CD45 À neuroblastoma CTCs from blood and disseminated tumor cells (DTCs) from bone marrow using the Imagestream Imaging flow cytometer (ISx). In six cases, circulating free DNA (cfDNA) extracted from plasma isolated from the CTC sample was analyzed by high-density single-nucleotide polymorphism (SNP) arrays. Results: CTCs were detected in 26 of 42 blood samples (1-264/ mL) and DTCs in 25 of 35 bone marrow samples (57-291,544/ mL). Higher numbers of CTCs in patients with newly diagnosed, high-risk neuroblastoma correlated with failure to obtain a complete bone marrow (BM) metastatic response after induction chemotherapy (P < 0.01). Ex vivo Nutlin-3 (MDM2 inhibitor) treatment of blood and BM increased p53 and p21 expression in CTCs and DTCs compared with DMSO controls. In five of six cases, cfDNA analyzed by SNP arrays revealed copy number abnormalities associated with neuroblastoma. Conclusions: This is the first study to show that CTCs and DTCs are detectable in neuroblastoma using the ISx, with concurrently extracted cfDNA used for copy number profiling, and may be useful as pharmacodynamic biomarkers in early-phase clinical trials. Further investigation is required to determine whether CTC numbers are predictive biomarkers of BM response to first-line induction chemotherapy.