Libi Hertzberg

Down syndrome acute lymphoblastic leukemia, a highly heterogeneous disease in which aberrant expression of CRLF2 is associated with mutated JAK2: a report from the International BFM Study Group.

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.

Hsa-mir-125b-2 is highly expressed in childhood ETV6/RUNX1 (TEL/AML1) leukemias and confers survival advantage to growth inhibitory signals independent of p53

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 function of trisomy 21. The levels of chr 21 miRNAs were quantified by qRT–PCR in four types of childhood acute lymphoblastic leukemia (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 showed 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 after 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.

Automated long-term tracking and social behavioural phenotyping of animal colonies within a semi-natural environment

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.

Prediction of chromosomal aneuploidy from gene expression data

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.

STOP: searching for transcription factor motifs using gene expression

MOTIVATION Existing computational methods that identify transcription factor (TF) binding sites on a genes promoter are plagued by significant inaccuracies. Binding of a TF to a particular sequence is assessed by comparing its similarity score, obtained from the TFs known position weight matrix (PWM), to a threshold. If the similarity score is above the threshold, the sequence is considered a putative binding site. Determining this threshold is a central part of the problem, for which no satisfactory biologically based solution exists. RESULTS We present here a method that integrates gene expression data with sequence-based scoring of TF binding sites, for determining a global score threshold for each TF. We validate our method, STOP (Searching TFs Of Promoters), in several ways: (1) we calculate the average expression values of groups of human putative target genes of each TF, and compare them to similar averages derived for random gene groups. The groups of putative targets show significantly higher relative average expression. (2) We find high consistency between the induced lists of putative targets in human and in mouse. (3) The expression patterns associated with human and mouse genes (ordered by PWM scores for each TF) exhibit high similarity between human and mouse, indicating that our method has firm biological basis. (4) Comparison of results obtained by STOP and PRIMA (Elkon et al., 2003) suggests that determining the score threshold using gene expression, as is done in STOP, is more biologically tuned. AVAILABILITY Software package will be available for academic users upon request. SUPPLEMENTARY INFORMATION Supplementary data are available on Bioinformatics online.

Integration of gene expression and GWAS results supports involvement of calcium signaling in Schizophrenia

The number of Genome Wide Association Studies (GWAS) of schizophrenia is rapidly growing. However, the small effect of individual genes limits the number of reliably implicated genes, which are too few and too diverse to perform reliable pathway analysis; hence the biological roles of the genes implicated in schizophrenia are unclear. To overcome these limitations we combine GWAS with genome-wide expression data from human post-mortem brain samples of schizophrenia patients and controls, taking these steps: 1) Identify 36 GWAS-based genes which are expressed in our dataset. 2) Find a cluster of 19 genes with highly correlated expression. We show that this correlation pattern is robust and statistically significant. 3) GO-enrichment analysis of these 19 genes reveals significant enrichment of ion channels and calcium-related processes. This finding (based on analyzing a small number of coherently expressed genes) is validated and enhanced in two ways: First, the emergence of calcium channels and calcium signaling is corroborated by identifying proteins that interact with those encoded by the cluster of 19. Second, extend the 19 cluster genes into 1028 genes, whose expression is highly correlated with the clusters average profile. When GO-enrichment analysis is performed on this extended set, many schizophrenia related pathways appear, with calcium-related processes enriched with high statistical significance. Our results give further, expression-based validation to GWAS results, support a central role of calcium-signaling in the pathogenesis of schizophrenia, and point to additional pathways potentially related to the disease.