We report gene expression and other analyses to elucidate the molecular characteristics of acute lymphoblastic leukemia (ALL) in children with Down syndrome (DS). We find that by gene expression DS-ALL is a highly heterogeneous disease not definable as a unique entity. Nevertheless, 62% (33/53) of the DS-ALL samples analyzed were characterized by high expression of the type I cytokine receptor CRLF2 caused by either immunoglobulin heavy locus (IgH@) translocations or by interstitial deletions creating chimeric transcripts P2RY8-CRLF2. In 3 of these 33 patients, a novel activating somatic mutation, F232C in CRLF2, was identified. Consistent with our previous research, mutations in R683 of JAK2 were identified in 10 specimens (19% of the patients) and, interestingly, all 10 had high CRLF2 expression. Cytokine receptor-like factor 2 (CRLF2) and mutated Janus kinase 2 (Jak2) cooperated in conferring cytokine-independent growth to BaF3 pro-B cells. Intriguingly, the gene expression signature of DS-ALL is enriched with DNA damage and BCL6 responsive genes, suggesting the possibility of B-cell lymphocytic genomic instability. Thus, DS confers increased risk for genetically highly diverse ALLs with frequent overexpression of CRLF2, associated with activating mutations in the receptor itself or in JAK2. Our data also suggest that the majority of DS children with ALL may benefit from therapy blocking the CRLF2/JAK2 pathways. (Blood.

Social behaviour has a key role in animal survival across species, ranging from insects to primates and humans. However, the biological mechanisms driving natural interactions between multiple animals, over long-term periods, are poorly studied and remain elusive. Rigorous and objective quantification of behavioural parameters within a group poses a major challenge as it requires simultaneous monitoring of the positions of several individuals and comprehensive consideration of many complex factors. Automatic tracking and phenotyping of interacting animals could thus overcome the limitations of manual tracking methods. Here we report a broadly applicable system that automatically tracks the locations of multiple, uniquely identified animals, such as mice, within a semi-natural setting. The system combines video and radio frequency identified tracking data to obtain detailed behavioural profiles of both individuals and groups. We demonstrate the usefulness of these data in characterizing individual phenotypes, interactions between pairs and the collective social organization of groups.

MicroRNAs (miRNAs) regulate the expression of multiple proteins in a dose dependent manner. We hypothesized that increased expression of miRNAs encoded on chromosome 21 (chr 21) contribute to the leukemogenic role of trisomy 21. The levels of chr 21 miRNAs were quantified by qRT-PCR in four types of childhood ALL characterized by either numerical (trisomy or tetrasomy) or structural abnormalities of chr 21. Suprisingly high expression of the hsa-mir-125b-2 cluster, consisting of three miRNAs, was identified in leukemias with the structural ETV6/RUNX1 abnormality and not in ALLs with trisomy 21. Manipulation of ETV6/RUNX1 expression and chromatin immunoprecipitation studies demonstrated that the high expression of the miRNA cluster is an event independent of the ETV6/RUNX1 fusion protein. Overexpression of hsa-mir-125b-2 conferred a survival advantage to Ba/F3 cells following IL-3 withdrawal or a broad spectrum of apoptotic stimuli through inhibition of caspase 3 activation. Conversely, knockdown of the endogenous miR-125b in the ETV6/RUNX1 leukemia cell line REH increased apoptosis after Doxorubicin and Staurosporine treatments. P53 protein levels were not altered by miR-125b. Together these results suggest that the expression of hsa-mir-125b-2 in ETV6/RUNX1 ALL provides survival advantage to growth inhibitory signals in a p53 independent manner.

Extra copies of chromosome 21 are often found in sporadic leukemias. Constitutional trisomy 21 of Down syndrome (DS) is associated with markedly increased risk for childhood leukemia. Thus the oncogenic role of trisomy 21 in the more common sporadic childhood leukemias may be revealed through the investigations of the relatively rare leukemias of DS. Recent studies of the megakaryoblastic leukemias of Down syndrome have uncovered a developmental leukemogenic mechanism characterized by a unique pre-natal collaboration between overexpressed genes from chromosome 21 and an acquired mutation in the transcription factor GATA1. The base of the markedly enhanced risk for acute lymphoblastic leukemia conferred by trisomy 21 is still unclear. Studies of the leukemias of DS are likely to contribute to the general understanding of the oncogenic mechanisms of chromosomal aneuploidies, the most common abnormalities in cancer.

Chromosomal aneuploidy is commonly observed in neoplastic diseases and is an important prognostic marker. Here we examine how gene expression profiles reflect aneuploidy and whether these profiles can be used to detect changes in chromosome copy number. We developed two methods for detecting such changes in the gene expression profile of a single sample. The first method, fold-change analysis, relies on the availability of gene expression data from a large cohort of patients with the same disease. The expression profile of the sample is compared with that of the dataset. The second method, chromosomal relative expression analysis, is more general and requires the expression data from the tested sample only. We found that the relative expression values are stable among different chromosomes and exhibit little variation between different normal tissues. We exploited this novel finding to establish the set of reference values needed to detect changes in the copy number of chromosomes in a single sample on the basis of gene expression levels. We measured the accuracy of the performance of each method by applying them to two independent leukemia datasets. The second method was also applied to two solid tumor datasets. We conclude that chromosomal aneuploidy can be detected and predicted by analysis of gene expression profiles. This article contains Supplementary Material available at http://www.interscience.wiley.com/jpages/1045-2257/suppmat.

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A central issue in molecular biology is understanding the regulatory mechanisms that control gene expression. The availability of whole genome sequences opens the way for computational methods to search for the key elements in transcription regulation. These include methods for discovering the binding sites of DNA-binding proteins, such as transcription factors. A common representation of transcription factor binding sites is a position specific score matrix (PSSM). We developed a probabilistic approach for searching for putative binding sites. Given a promoter sequence and a PSSM, we scan the promoter and find the position with the maximal score. Then we calculate the probability to get such a maximal score or higher on a random promoter. This is the p-value of the putative binding site. In this way, we searched for putative binding sites in the upstream sequences of Saccharomyces cerevisiae, where some binding sites are known (according to the Saccharomyces cerevisiae Promoters Database, SCPD). Our method produces either exact p-values, or a better estimate for them than other methods, and this improves the results of the search. For each gene we found its statistically significant putative binding sites. We measured the rates of true positives, by a comparison to the known binding sites, and also compared our results to these of MatInspector, a commercially available software that looks for putative binding sites in DNA sequences according to PSSMs. Our results were significantly better. In contrast with us, MatInspector doesn't calculate the exact statistical significance of its results.

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