Prenatal origin of childhood AML occurs less frequently than in childhood ALL

Background While there is enough convincing evidence in childhood acute lymphoblastic leukemia (ALL), the data on the pre-natal origin in childhood acute myeloid leukemia (AML) are less comprehensive. Our study aimed to screen Guthrie cards (neonatal blood spots) of non-infant childhood AML and ALL patients for the presence of their respective leukemic markers. Methods We analysed Guthrie cards of 12 ALL patients aged 2–6 years using immunoglobulin (Ig) and T-cell receptor (TCR) gene rearrangements (n = 15) and/or intronic breakpoints of TEL/AML1 fusion gene (n = 3). In AML patients (n = 13, age 1–14 years) PML/RARalpha (n = 4), CBFbeta/MYH11 (n = 3), AML1/ETO (n = 2), MLL/AF6 (n = 1), MLL/AF9 (n = 1) and MLL/AF10 (n = 1) fusion genes and/or internal tandem duplication of FLT3 gene (FLT3/ITD) (n = 2) were used as clonotypic markers. Assay sensitivity determined using serial dilutions of patient DNA into the DNA of a healthy donor allowed us to detect the pre-leukemic clone in Guthrie card providing 1–3 positive cells were present in the neonatal blood spot. Results In 3 patients with ALL (25%) we reproducibly detected their leukemic markers (Ig/TCR n = 2; TEL/AML1 n = 1) in the Guthrie card. We did not find patient-specific molecular markers in any patient with AML. Conclusion In the largest cohort examined so far we used identical approach for the backtracking of non-infant childhood ALL and AML. Our data suggest that either the prenatal origin of AML is less frequent or the load of pre-leukemic cells is significantly lower at birth in AML compared to ALL cases

BCL11A deletions result in fetal hemoglobin persistence and neurodevelopmental alterations

A transition from fetal hemoglobin (HbF) to adult hemoglobin (HbA) normally occurs within a few months after birth. Increased production of HbF after this period of infancy ameliorates clinical symptoms of the major disorders of adult ß-hemoglobin: ß-thalassemia and sickle cell disease. The transcription factor BCL11A silences HbF and has been an attractive therapeutic target for increasing HbF levels; however, it is not clear to what extent BCL11A inhibits HbF production or mediates other developmental functions in humans. Here, we identified and characterized 3 patients with rare microdeletions of 2p15-p16.1 who presented with an autism spectrum disorder and developmental delay. Moreover, these patients all exhibited substantial persistence of HbF but otherwise retained apparently normal hematologic and immunologic function. Of the genes within 2p15-p16.1, only BCL11A was commonly deleted in all of the patients. Evaluation of gene expression data sets from developing and adult human brains revealed that BCL11A expression patterns are similar to other genes associated with neurodevelopmental disorders. Additionally, common SNPs within the second intron of BCL11A are strongly associated with schizophrenia. Together, the study of these rare patients and orthogonal genetic data demonstrates that BCL11A plays a central role in silencing HbF in humans and implicates BCL11A as an important factor for neurodevelopment

Homeobox gene expression in acute myeloid leukemia is linked to typical underlying molecular aberrations

__Background:__ Although distinct patterns of homeobox (HOX) gene expression have been described in defined cytogenetic and molecular subsets of patients with acute myeloid leukemia (AML), it is unknown whether these patterns are the direct result of transcriptional alterations or rather represent the differentiation stage of the leukemic cell. __Method:__ To address this question, we used qPCR to analyze mRNA expression of HOXA and HOXB genes in bone marrow (BM) samples of 46 patients with AML and sorted subpopulations of healthy BM cells. These various stages of myeloid differentiation represent matched counterparts of morphological subgroups of AML. To further study the transcriptional alterations of HOX genes in hematopoiesis, we also analyzed gene expression of epigenetic modifiers in the subpopluations of healthy BM and leukemic cells. __Results:__ Unsupervised hierarchical clustering divided the AMLs into five clusters characterized by the presence of prevalent molecular genetic aberrations. Notably, the impact of genotype on HOX gene expression was significantly more pronounced than that of the differentiation stage of the blasts. This driving role of molecular aberrations was best exemplified by the repressive effect of the PML-RARa fusion gene on HOX gene expression, regardless of the presence of the FLT3/ITD mutation. Furthermore, HOX gene expression was positively correlated with mRNA levels of histone demethylases (JMJD3 and UTX) and negatively correlated with gene expression of DNA methyltranferases. No such relationships were observed in subpopulations of healthy BM cells. __Conclusion:__ Our results demonstrate that specific molecular genetic aberrations, rather than differentiation per se, underlie the observed differences in HOX gene expression in AML. Moreover, the observed correlations between epigenetic modifiers and HOX ex pression that are specific to malignant hematopoiesis, suggest their potential causal relationships

MicroRNA-106b~25 cluster is upregulated in relapsed MLL-rearranged pediatric acute myeloid leukemia

The most important reason for therapy failure in pediatric acute myeloid leukemia (AML) is relapse. In order to identify miRNAs that contribute to the clonal evolution towards relapse in pediatric AML, miRNA expression profiling of 127 de novo pediatric AML cases were used. In the diagnostic phase, no miRNA signatures could be identified that were predictive for relapse occurrence, in a large pediatric cohort, nor in a nested mixed lineage leukemia (MLL)-rearranged pediatric cohort. AML with MLL- rearrangements are found in 15-20% of all pediatric AML samples, and reveal a relapse rate up to 50% for certain translocation partner subgroups. Therefore, microRNA expression profiling of six paired initial diagnosis-relapse MLL-rearranged pediatric AML samples (test cohort) and additional eight paired initial diagnosisrelapse samples with MLL-rearrangements (validation cohort) was performed. A list of 53 differentially expressed miRNAs was identified of which the miR-106b~25 cluster, located in intron 13 of MCM7, was the most prominent. These differentially expressed miRNAs however could not predict a relapse in de novo AML samples with MLLrearrangements at diagnosis. Furthermore, higher mRNA expression of both MCM7 and its upstream regulator E2F1 was found in relapse samples with MLL-rearrangements. In conclusion, we identified the miR-106b~25 cluster to be upregulated in relapse pediatric AML with MLL-rearrangements

CANCERTOOL: A Visualization and Representation Interface to Exploit Cancer Datasets

[EN] With the advent of OMICs technologies, both individual research groups and consortia have spear-headed the characterization of human samples of multiple pathophysiologic origins, resulting in thousands of archived genomes and transcriptomes. Although a variety of web tools are now available to extract information from OMICs data, their utility has been limited by the capacity of nonbioinformatician researchers to exploit the information. To address this problem, we have developed CANCERTOOL, a web-based interface that aims to overcome the major limitations of public transcriptomics dataset analysis for highly prevalent types of cancer (breast, prostate, lung, and colorectal). CANCERTOOL provides rapid and comprehensive visualization of gene expression data for the gene(s) of interest in well-annotated cancer datasets. This visualization is accompanied by generation of reports customized to the interest of the researcher (e.g., editable figures, detailed statistical analyses, and access to raw data for reanalysis). It also carries out gene-to-gene correlations in multiple datasets at the same time or using preset patient groups. Finally, this new tool solves the time-consuming task of performing functional enrichment analysis with gene sets of interest using up to 11 different databases at the same time. Collectively, CANCERTOOL represents a simple and freely accessible interface to interrogate well-annotated datasets and obtain publishable representations that can contribute to refinement and guidance of cancer-related investigations at all levels of hypotheses and design. Significance: In order to facilitate access of research groups without bioinformatics support to public transcriptomics data, we have developed a free online tool with an easy-to-use interface that allows researchers to obtain quality information in a readily publishable forma

Cancertool: A visualization and representation interface to exploit cancer datasets

With the advent of OMICs technologies, both individual research groups and consortia have spear-headed the characterization of human samples of multiple pathophysiologic origins, resulting in thousands of archived genomes and transcriptomes. Although a variety of web tools are now available to extract information from OMICs data, their utility has been limited by the capacity of nonbioinformatician researchers to exploit the information. To address this problem, we have developed CANCERTOOL, a web-based interface that aims to overcome the major limitations of public transcriptomics dataset analysis for highly prevalent types of cancer (breast, prostate, lung, and colorectal). CANCERTOOL provides rapid and comprehensive visualization of gene expression data for the gene(s) of interest in well-annotated cancer datasets. This visualization is accompanied by generation of reports customized to the interest of the researcher (e.g., editable figures, detailed statistical analyses, and access to raw data for reanalysis). It also carries out gene-to-gene correlations in multiple datasets at the same time or using preset patient groups. Finally, this new tool solves the time-consuming task of performing functional enrichment analysis with gene sets of interest using up to 11 different databases at the same time. Collectively, CANCERTOOL represents a simple and freely accessible interface to interrogate well-annotated datasets and obtain publishable representations that can contribute to refinement and guidance of cancer-related investigations at all levels of hypotheses and design.We are grateful to Iñaki Lazaro for the design of the tumor type logos, Evarist Planet and Antoni Berenguer for insightful discussions, and the Carracedo lab for valuable input. V. Torrano is funded by Fundación Vasca de Innovación e Investigación Sanitarias, BIOEF (BIO15/CA/052), the AECC J.P. Bizkaia and the Basque Department of Health (2016111109). The work of A. Carracedo is supported by the Basque Department of Industry, Tourism and Trade (Etortek) and the Department of Education (IKERTALDE IT1106-16, also participated by A. Gomez-Muñoz), the BBVA Foundation, the MINECO [SAF2016-79381-R (FEDER/EU)]; Severo Ochoa Excellence Accreditation SEV-2016-0644; Excellence Networks (SAF2016-81975-REDT), European Training Networks Project (H2020-MSCA-ITN-308 2016 721532), the AECC IDEAS16 (IDEAS175CARR), and the European Research Council (Starting Grant 336343, PoC 754627). CIBERONC was cofunded with FEDER funds. The work of A. Aransay is supported by the Basque Department of Industry, Tourism and Trade (Etortek and Elkartek Programs), the Innovation Technology Department of Bizkaia County, CIBERehd Network, and Spanish MINECO the Severo Ochoa Excellence Accreditation (SEV-2016-0644). I. Apaolaza is funded by a Basque Government predoctoral grant (PRE_2017_2_0028). X.R. Bustelo is supported by grants from the Castilla-León Government (BIO/SA01/15, CSI049U16), Spanish Ministry of Economy and Competitiveness (MINECO; SAF2015-64556-R), Worldwide Cancer Research (14-1248), Ramón Areces Foundation, and the Spanish Society against Cancer (GC16173472GARC). Funding from MINECO to X.R. Bustelo is partially contributed by the European Regional Development Fund. The work of F.J. Planes is supported by the MINECO (BIO2016-77998-R) and ELKARTEK Programme of the Basque Government (KK-2016/00026)

Hadron Energy Reconstruction for the ATLAS Calorimetry in the Framework of the Non-parametrical Method

This paper discusses hadron energy reconstruction for the ATLAS barrel prototype combined calorimeter (consisting of a lead-liquid argon electromagnetic part and an iron-scintillator hadronic part) in the framework of the non-parametrical method. The non-parametrical method utilizes only the known $e/h$ ratios and the electron calibration constants and does not require the determination of any parameters by a minimization technique. Thus, this technique lends itself to an easy use in a first level trigger. The reconstructed mean values of the hadron energies are within $\pm 1$ of the true values and the fractional energy resolution is $[(58\pm3)/\sqrt{E}+(2.5\pm0.3)$. The value of the $e/h$ ratio obtained for the electromagnetic compartment of the combined calorimeter is $1.74\pm0.04$ and agrees with the prediction that $e/h > 1.7$ for this electromagnetic calorimeter. Results of a study of the longitudinal hadronic shower development are also presented. The data have been taken in the H8 beam line of the CERN SPS using pions of energies from 10 to 300 GeV.Comment: 33 pages, 13 figures, Will be published in NIM